Eastern CFRAM Study HA09 Hydrology Report
IBE0600Rp0016
rpsgroup.com/ireland
Eastern CFRAM Study
HA09 Hydrology Report
DOCUMENT CONTROL SHEET
Client OPW
Project Title Eastern CFRAM Study
Document Title IBE0600Rp0016_HA09_Hydrology Report_F03
Document No. IBE0600Rp0016
DCS TOC Text List of Tables List of Figures No. of This Document Appendices Comprises 1 1 1 1 1 5
Rev. Status Author(s) Reviewed By Approved By Office of Origin Issue Date
B. Quigley D01 Draft M. Brian G. Glasgow Belfast 10/04/2013 U. Mandal B. Quigley D02 Draft M. Brian G. Glasgow Belfast 29/04/2013 U. Mandal B. Quigley F01 Draft Final M. Brian G. Glasgow Belfast 03/09/2013 U. Mandal B. Quigley F02 Draft Final M. Brian G. Glasgow Belfast 14/08/2015 U. Mandal B. Quigley F03 Final B. Quigley G. Glasgow Belfast 29/04/2016 U. Mandal
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This report is subject to the limitations and warranties contained in the contract between the commissioning party (Office of Public Works) and RPS Group Ireland
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Eastern CFRAM Study HA09 Hydrology Report – FINAL
TABLE OF CONTENTS
LIST OF FIGURES ...... IV LIST OF TABLES ...... VI ABBREVIATIONS ...... IX 1 INTRODUCTION ...... 1 1.1 OBJECTIVE OF THIS HYDROLOGY REPORT ...... 3 1.2 SUMMARY OF THE AVAILABLE DATA ...... 4 1.2.1 Summary of Available Hydrometric Data ...... 4 1.2.2 Additional Simulated Flow Data ...... 5 1.2.3 Summary of Available Meteorological Data ...... 7 1.2.4 Rainfall Radar ...... 9 1.2.5 Historic Flood Frequency Analysis ...... 10 2 METHODOLOGY REVIEW ...... 11 2.1 HYDROLOGICAL ANALYSIS ...... 11 2.2 METEOROLOGICAL ANALYSIS ...... 12 2.3 DESIGN FLOW ESTIMATION ...... 12 2.3.1 Index Flood Flow Estimation ...... 12 2.3.2 Growth Curve / Factor Development ...... 14 2.3.3 Design Flow Hydrographs ...... 14 2.4 HYDROLOGY PROCESS REVIEW ...... 15 2.5 ALTERNATIVE APPROACHES REQUIRED WITHIN HA09 ...... 18 2.5.1 Integrated Drainage Network / Watercourse Model and Direct Application of Design Rainfall Events ...... 19 2.6 CATCHMENT BOUNDARY REVIEW ...... 20 3 HYDROMETRIC GAUGE STATION RATING REVIEWS ...... 21 3.1 METHODOLOGY ...... 21 3.2 RATING REVIEW RESULTS ...... 22 3.3 IMPACT OF RATING REVIEWS ON HYDROLOGICAL ANALYSIS ...... 23 4 INDEX FLOOD FLOW ESTIMATION ...... 27 4.1 MODEL 1 – SANTRY ...... 29 4.2 MODEL 2A – BALDONNEL ...... 31 4.3 MODEL 2B – LUCAN TO CHAPELIZOD ...... 34 4.4 MODEL 2C – LOWER LIFFEY ...... 37 4.5 MODEL 2D – CAMAC ...... 39 4.6 MODEL 2E – PODDLE ...... 43 4.7 MODEL 3A – LEIXLIP ...... 45 4.8 MODEL 3B – HAZELHATCH / CELBRIDGE ...... 48 4.9 MODEL 4 – MAYNOOTH ...... 53 4.10 MODEL 5 – KILCOCK ...... 56
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4.11 MODEL 6A – CLANE ...... 58 4.12 MODEL 6B – NAAS ...... 60 4.13 MODEL 7 – TURNINGS / KILLEENMORE (MORELL) ...... 64 4.14 MODEL 8 – NEWBRIDGE ...... 67 4.15 MODEL 9 – BLESSINGTON ...... 70 4.16 INDEX FLOOD FLOW CONFIDENCE LIMITS ...... 72
4.16.1 Gauged Qmed ...... 72
4.16.2 Ungauged Qmed ...... 74 5 FLOOD FREQUENCY ANALYSIS AND GROWTH CURVE DEVELOPMENT ...... 75 5.1 OBJECTIVE AND SCOPE ...... 75 5.2 METHODOLOGY ...... 75 5.2.1 Selection of Statistical Distribution ...... 75 5.2.2 Forming a Pooling Region and Groups ...... 75 5.2.3 Growth Curve Development ...... 75 5.2.4 Limitations in the FEH and FSU Studies ...... 76 5.3 DATA AND STATISTICAL PROPERTIES ...... 76 5.3.1 Flood Data ...... 76 5.3.2 Pooling Region Catchment Physiographic and Climatic Characteristic Data ...... 81 5.3.3 Statistical Properties of the AMAX series ...... 83 5.4 STATISTICAL DISTRIBUTION ...... 84 5.5 GROWTH CURVE ESTIMATION POINTS ...... 85 5.6 POOLING REGION AND GROUP FOR GROWTH CURVE ESTIMATION ...... 88 5.6.1 Pooling Region ...... 88 5.6.2 Pooling Group ...... 88 5.7 GROWTH CURVE ESTIMATION ...... 89 5.7.1 Choice of Growth Curve Distributions ...... 89 5.7.2 Estimation of Growth Curves ...... 89 5.7.3 Examination of Growth Curve Shape ...... 91 5.7.4 Recommended Growth Curve Distribution for the River Liffey and Santry River Catchments ...... 95 5.8 RATIONALISATION OF GROWTH CURVES ...... 97 5.8.1 Relationship of Growth Factors with Catchment Characteristics ...... 97 5.8.2 Generalised Growth Curves ...... 98 5.8.3 Comparison of the at-site growth curves with the pooled growth curves ...... 104 5.8.4 Growth factors for all HEPs within HA09 ...... 108 5.9 COMPARISON WITH FSR GROWTH FACTORS ...... 117 5.10 GROWTH CURVE DEVELOPMENT SUMMARY ...... 118 6 DESIGN FLOWS AT POLLAPHUCA / GOLDEN FALLS ...... 120
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6.1 AVAILABLE DATA ...... 121 6.2 EXTREME VALUE ANALYSIS ...... 122 6.3 DESIGN PEAK FLOWS ...... 125 7 DESIGN FLOWS ...... 126 7.1 DESIGN FLOW HYDROGRAPHS ...... 126 7.1.1 Rainfall Run-off (NAM) Modelling and HWA ...... 126 7.1.2 FSU Hydrograph Shape Generator ...... 129 7.1.3 FSSR 16 Unit Hydrograph Method ...... 129 7.2 COASTAL HYDROLOGY ...... 131 7.2.1 ICPSS Levels ...... 131 7.2.2 ICWWS Levels ...... 133 7.2.3 Consideration of ICPSS and ICWWS Outputs ...... 134 7.3 JOINT PROBABILITY ...... 136 7.3.1 Fluvial – Fluvial ...... 136 7.3.2 Fluvial – Coastal ...... 136 8 FUTURE ENVIRONMENTAL AND CATCHMENT CHANGES ...... 140 8.1 CLIMATE CHANGE ...... 140 8.1.1 HA09 Context ...... 140 8.1.2 Sea Level Rise ...... 142 8.2 AFFORESTATION ...... 143 8.2.1 Afforestation in HA09 ...... 143 8.2.2 Impact on Hydrology ...... 145 8.3 LAND USE AND URBANISATION ...... 147 8.3.1 Impact of Urbanisation on Hydrology ...... 150 8.4 ARTERIAL DRAINAGE ...... 153 8.4.1 The Impact of Arterial Drainage Scheme on HA09 Hydrology ...... 154 8.5 HYDROGEOMORPHOLOGY ...... 156 8.5.1 Channel Typology ...... 156 8.5.2 Land Use and Morphological Pressures ...... 161 8.5.3 River Continuity ...... 165 8.6 FUTURE SCENARIOS FOR FLOOD RISK MANAGEMENT ...... 167 8.7 POLICY TO AID FLOOD REDUCTION ...... 168 9 SENSITIVITY AND UNCERTAINTY ...... 169 9.1 UNCERTAINTY / SENSITIVITY ASSESSMENT MODEL BY MODEL ...... 170 9.2 CONCLUSIONS OF SENSITIVITY ANALYSIS ...... 173 10 CONCLUSIONS ...... 174 10.1 SUMMARY OF THE RESULTS AND GENERAL PATTERNS ...... 175 10.2 RISKS IDENTIFIED ...... 176 10.3 OPPORTUNITIES / RECOMMENDATIONS ...... 176 11 REFERENCES: ...... 178
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LIST OF FIGURES
Figure 1.1: HA09 AFA Locations and Extents ...... 2 Figure 1.2: Hydrometric Data Availability ...... 4 Figure 1.3: Water mass balance between observed and simulated catchment at Morell Bridge (09024) ...... 6 Figure 1.4: Observed and simulated flow trace for catchment at Morell Bridge (09024) ...... 6 Figure 1.5: Meteorological Data Availability ...... 8 Figure 2.1: Hydrology Process Flow Chart...... 17 Figure 4.1: HA09 Watercourses to be Modelled ...... 28 Figure 4.2: Model 1 HEPs and Catchment Boundaries ...... 29 Figure 4.3: Model 2A HEPs and Catchment Boundaries ...... 32 Figure 4.4: Model 2B HEPs and Catchment Boundaries ...... 34 Figure 4.5: Model 2C (Lower Liffey) ...... 37 Figure 4.6: Model 2D HEPs and Catchment Boundaries ...... 39 Figure 4.7: Model 2E HEPs and Catchment Boundaries ...... 43 Figure 4.8: Model 3A Catchment Boundaries and HEPs ...... 45 Figure 4.9: Model 3B Catchment Boundaries and HEPs ...... 50 Figure 4.10: Model 4 Catchment Boundaries and HEPs ...... 53 Figure 4.11: Model 5 Catchment Boundaries and HEPs ...... 56 Figure 4.12: Model 6A Catchment Boundaries and HEPs ...... 58 Figure 4.13: Model 6B Catchment Boundaries and HEPs ...... 61 Figure 4.14: Model 7 Catchment Boundaries and HEPs ...... 64 Figure 4.15: Model 8 Catchment Boundaries and HEPs ...... 69 Figure 4.16: Model 9 Catchment Boundaries and HEPs ...... 70 Figure 5.1: Locations of 92 Gauging Stations ...... 80 Figure 5.2: Relative frequencies of catchments sizes (AREA) within the selected 92 stations ...... 81 Figure 5.3: Relative frequencies of the SAAR values within the selected 92 stations ...... 82 Figure 5.4: Relative frequencies of the BFI values within the selected 92 stations ...... 82 Figure 5.5: L-Moment Ratio Diagram (L-CV versus L-Skewness) for 92 AMAX series ...... 83 Figure 5.6: Spatial distribution of the HEPs on the modelled watercourses in HA09 ...... 87 Figure 5.7: L-moment ratio diagram (L-skewness versus L-kurtosis) ...... 89 Figure 5.8: Pooled Growth Curve 83 - (a) EV1 and GEV distributions; (b) GLO distributions ...... 93
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Figure 5.9: Comparison of EV1, GEV and GLO growth curves on the EV1-y probability plot (Growth Curve No. 83) ...... 96 Figure 5.10: GLO growth curves for 95 HEPs within HA09 ...... 96 Figure 5.11: Relationship of growth factors with catchment areas for 95 HEPs ...... 97 Figure 5.12: Relationship of growth factors with SAAR for 95 HEPs ...... 97 Figure 5.13: Relationship of growth factors with BFI for 95 HEPs ...... 98 Figure 5.14: Relationship of growth factors with catchment areas (for 292 growth curve estimation points) ...... 99 Figure 5.15: GLO growth curves for all Growth Curve Groups (6 No.) ...... 103 Figure 5.16: Growth Curve for GC Group No. 4 with 95% confidence limits ...... 104 Figure 5.17: The at-site and pooled frequency curves along with the 95% confidence intervals ...... 106 Figure 6.1: Plotted Flow Data at Golden Falls ...... 121 Figure 6.2: 2 parameter distributions fitted to Golden Falls (09007) dam flow data ...... 124 Figure 6.3: L-Moment diagram of 2 parameter distributions ...... 124 Figure 7.1: NAM Conceptual Model ...... 126 Figure 7.2: Median Semi-dimensionless Hydrograph with Fitted Gamma Curve ...... 128 Figure 7.3: Design Flow Hydrographs for Morell Upstream Limit Node 09_540_6_RPS .....128 Figure 7.4: 1% AEP Hydrographs for the Camac (Model 2D) ...... 130 Figure 7.5: Location of ICPSS Nodes in Relation to Coastal AFAs ...... 132 Figure 7.6: Draft ICWWS potential areas of vulnerable coastline ...... 133 Figure 7.7: Regression Analysis of Tidal Height versus River Flow on the Liffey ...... 138 Figure 8.1: CORINE 2006 Forest Coverage in HA09 Compared to the rest of Ireland ...... 143 Figure 8.2: Forest Coverage Changes in HA09 ...... 144 Figure 8.3: HA09 CORINE Artificial Surfaces (2000 / 2006) ...... 149 Figure 8.4: Watercourses affected by arterial drainage in HA09 ...... 153 Figure 8.5: WFD Channel Typology HA09 ...... 158 Figure 8.6: HA09 Modelled Watercourses – Channel Type ...... 159 Figure 8.7: Changes in Channel Slope HA09 ...... 160 Figure 8.8: HA09 Land Use (CORINE 2006) ...... 162 Figure 8.9: HPWs/MPWs flowing through Arable Land in HA09...... 164
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LIST OF TABLES Table 1.1: Fluvial and Coastal Flood Risk at each AFA ...... 2 Table 2.1: FSU 1% AEP Design Flows ...... 18 Table 2.2: Summary of Catchment Boundary Review ...... 20 Table 3.1: Existing Rating Quality Classification for Rating Review Stations in HA09 ...... 22 Table 3.2: AMAX Series Data Before and After Rating Review ...... 23 Table 3.3: Summary of Rating Review Effects and Mitigation ...... 25
Table 4.1: Qmed Values for Model 1 ...... 30
Table 4.2: Qmed Values for Model 2A ...... 33
Table 4.3: Qmed Values for Model 2B ...... 36
Table 4.4: Qmed Values for Model 2C ...... 38
Table 4.5: Qmed Values for Model 2D ...... 41 Table 4.6: FSU DDF Derived Design Rainfall Sums ...... 44
Table 4.7: Qmed Values for Model 3A ...... 47
Table 4.8: Qmed Values for Model 3B ...... 51
Table 4.9: Qmed Values for Model 4 ...... 55
Table 4.10: Qmed Values for Model 5 ...... 57
Table 4.11: Qmed Values for Model 6A ...... 59
Table 4.12: Qmed Values for Model 6B ...... 62 Table 4.13: Summary of hydrometric gauge data within Model 7 Extents ...... 65
Table 4.14: Qmed Values for Model 7 ...... 65
Table 4.15: Qmed Values for Model 8 ...... 67
Table 4.16: Qmed Values for Model 9 ...... 71 Table 4.17: Calibrated NAM Model Qmed Accuracy ...... 72 Table 5.1: Hydrometric Station Summary ...... 76 Table 5.2: Summary of Catchment physiographic and climatic characteristics of Pooling Region ...... 81 Table 5.3: Statistical properties of 92 AMAX Series ...... 83 Table 5.4: Summary results of probability plots assessments (EV1, GEV & GLO distributions) for all 92 AMAX series ...... 85 Table 5.5: Summary of the catchment characteristics associated with the 133 HEPs ...... 86 Table 5.6: Growth curves shape summary ...... 91 Table 5.7: Catchment descriptors for all pooled sites for growth curve No. 83 ...... 91 Table 5.8: Frequency curve shapes of the individual site’s AMAX series associated with the pooled group No. 83 ...... 93
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Table 5.9: Estimated growth factors for Growth Curve No. 83 ...... 94 Table 5.10: Growth curve estimation summary ...... 100 Table 5.11: Growth Curve (GC) Groups ...... 102 Table 5.12: Growth factors for range of AEPs ...... 102 Table 5.13: Estimated percentage standard errors for growth factors (XT) for a range of AEPs ...... 103 Table 5.14: Hydrometric gauging stations located on the modelled watercourses in HA09 hydrometric area ...... 105 Table 5.15: Growth factors for all 220 HEPs for a range of AEPs for the subject watercourses with HA09 (River Liffey and Santry River catchments) ...... 108 Table 5.16: Adjusted growth factors for a number of selected HEPs (77 Nos.) ...... 115 Table 5.17: Study growth factors compared with FSR, GDSDS and FEM-FRAM growth factors ...... 117 Table 6.1: AMAX Series from Flow Records at Golden Falls ...... 123 Table 6.2: Growth Factors and Design Flows at Golden Falls ...... 125 Table 7.1: ICPSS Level in Close Proximity to HA09 AFAs ...... 132 Table 7.2: Initial Screening for Relevance of Joint Probability ...... 137 Table 8.1: Afforestation from 2000 to 2006 ...... 145 Table 8.2: Allowances for Effects of Forestation / Afforestation (100 year time horizon) ....146 Table 8.3: Population Growth in the Council Areas of HA09 (Source: CSO) ...... 147 Table 8.4: Historic Urbanisation Growth Indicators ...... 150
Table 8.5: Potential Effect of Urbanisation on Qmed Flow in HA09 ...... 151 Table 8.6: Qmed at Leixlip gauging station on Rye Water (09001 – OPW) ...... 154 Table 8.7: Channel Types and Associated Descriptors ...... 156 Table 8.8: HA09 Allowances for Future Scenarios (100 year time horizon) ...... 167 Table 9.1: Assessment of contributing factors and cumulative effect of uncertainty / sensitivity in the hydrological analysis ...... 170
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APPENDICES
APPENDIX A HA09 Hydrometric Data Status Table 1 Page
APPENDIX B Analysis of the Dublin Airport Radar Data 83 Pages
APPENDIX C Rating Reviews 16Pages
APPENDIX D Design Flows for Modelling Input 50 Pages
APPENDIX E NAM Outputs 18 Pages
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ABBREVIATIONS
AEP Annual Exceedance Probability
AFA Area for Further Assessment
AFF At-site Flood Frequency
AMAX Annual Maximum flood series
AREA Catchment Area
BFI Base Flow Index
CFRAM Catchment Flood Risk Assessment and Management
C4i Community Climate Change Consortium for Ireland
DTM Digital Terrain Model
ERBD Eastern River Basin District
EV1 Extreme Value Type 1 (distribution) (=Gumbel distribution)
EPA Environmental Protection Agency
ESBI Electricity Supply Board International
FARL Flood Attenuation for Rivers and Lakes
FEH Flood Estimation Handbook
FEM-FRAMS Fingal East Meath Catchment Flood Risk Assessment and Management Study
FRA Flood Risk Assessment
FRMP Flood Risk Management Plan
FSE Factorial Standard Error
FSR Flood Studies Report
FSSR 16 Flood Studies Supplementary Report No. 16
FSU Flood Studies Update
GC Growth Curve
GDSDS Greater Dublin Strategic Drainage Study
GEV Generalised Extreme Value (distribution)
GLO General Logistic (distribution)
GSI Geological Survey of Ireland
HA Hydrometric Area
HEFS High End Future Scenario (Climate Change)
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HEP Hydrological Estimation Point
HPW High Priority Watercourse
HWA Hydrograph Width Analysis
IH124 Institute of Hydrology Report No. 124
IPCC Intergovernmental Panel on Climate Change
LA Local Authority
LN2 2 Parameter Log Normal (distribution)
L-CV Coefficient of L variation
MPW Medium Priority Watercourse
MRFS Mid Range Future Scenario (Climate Change)
NAM Catchment hydrological model using MIKE NAM (by DHI) modelling software. NAM is an acronym for Nedbor-Afrstrømnings-Model
NDTM National Digital Terrain Model
OD Ordnance Datum
OPW Office of Public Works
PFRA Preliminary Flood Risk Assessment
Qmed median of AMAX flood series
Qbar / QBAR mean average of AMAX flood series
RBD River Basin District
RFF Regional Flood Frequency
ROI Region of Influence
SAAR Standard Average Annual Rainfall (mm)
SERBD South Eastern River Basin District
SuDS Sustainable Urban Drainage
UAF Urban Adjustment Factor
UoM Unit of Management
WP Work Package (FSU)
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1 INTRODUCTION
The Office of Public Works (OPW) commissioned RPS to undertake the Eastern Catchment Flood Risk Assessment and Management Study (Eastern CFRAM Study) in June 2011. The Eastern CFRAM Study was the second catchment flood risk management study to be commissioned in Ireland under the EC Directive on the Assessment and Management of Flood Risks 2007 as implemented in Ireland by SI 122 of 2010 European Communities (Assessment and Management of Flood Risks) Regulations 2010.
The Eastern CFRAM Study covers an area of approximately 6,250 km2 and includes four Units of Management / Hydrometric Areas (Unit of Management Boundaries match the Hydrometric Area boundaries within the ECFRAM Study area). These are HA/UoM 07 (Boyne), HA/UoM 08 (Nanny – Delvin), HA/UoM 09 (Liffey-Dublin Bay) and HA/UoM 10 (Avoca-Vartry). There is a high level of flood risk within the Eastern CFRAM Study area with significant coastal and fluvial flooding events having occurred in the past.
HA09 is a relatively urbanised catchment in an Irish context, containing Greater Dublin and its surrounding commuter belt. There are significant towns and developments along the N4 and N7 national road corridors, including Naas, Celbridge and Maynooth. However the upland portions of the catchment are rural in nature hosting agricultural, forestry and power generation land uses and the Wicklow Mountains National Park. The hydrology of the main channel of the Liffey is greatly influenced by the dams and reservoirs operated by ESBI at Pollaphuca, Golden Falls and Leixlip. In particular the reservoir at Pollaphuca is capable of storing up to 50% of the average annual inflow and as such during typical daily operations the flow is dominated by electricity generation requirements. The dams at Golden Falls, a balancing reservoir just below Pollaphuca, and at Leixlip are much smaller and have a much lesser ability to store flood flows but they still have some attenuating effect on the middle and lower catchments. The location of the dams and reservoirs is shown in Figure 1.1.
Within HA09 there are 19 Areas for Further Assessment (AFA) as shown in Table 1.1 & Figure 1.1. The principal source of flood risk within HA09 is fluvial flooding with this source of flooding identified as requiring further analysis at 17 of the 19 AFAs. Six AFAs have been identified as requiring further analysis for coastal flooding. Clontarf and Sutton and Howth North have been identified as only requiring analysis of the coastal flood risk.
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AFA Fluvial Coastal AFA Fluvial Coastal AFA Fluvial Coastal
Baldonnel - Kilcock - Raheny
Blessington - Leixlip - Sandymount Lucan to Celbridge - - Santry - Chapelizod Sutton & Clane - Maynooth - Baldoyle Sutton & Clontarf - Naas - - Howth North
Dublin City Newbridge - Turnings -
Hazelhatch - Total 19 17 6
Table 1.1: Fluvial and Coastal Flood Risk at each AFA
Figure 1.1: HA09 AFA Locations and Extents
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For HA09, the CFRAM brief requirements include the need to review and ultimately incorporate the outputs from three previous smaller scale CFRAM studies for the Dodder and Tolka River catchments and the Fingal East-Meath area (FEM FRAMS). Three AFAs listed above have previously been considered to varying degrees under these studies. These are Sutton and Baldoyle (FEM FRAMS), Sandymount (Dodder) and parts of the Dublin City AFA (Dodder). The inclusion of these AFAs within the Eastern CFRAM Study is such that the coastal source of flooding can be fully analysed in conjunction with the fluvial analysis previously undertaken.
Each section of this report initially relates to the HA09 Study Area excluding the Dodder CFRAM Study, Tolka Flood Study and FEM FRAMS areas. The previously undertaken hydrological analysis for the three other study areas is reviewed in a separate report IBE0600Rp0017 ‘Hydrology Review: Fingal East Meath FRAM Study, Dodder FRAM Study and Tolka Flood Study (RPS, 2013). The purpose of that Hydrology Review is to ensure that the outputs from the hydrological analysis and design flow estimation are broadly consistent with the outputs which are derived using the latest techniques and catchment information. Where these are not consistent this is identified and recommendations (where applicable) given to update the relevant hydrology element such that it is consistent with the Eastern CFRAM Study.
1.1 OBJECTIVE OF THIS HYDROLOGY REPORT
The principal objective of this Hydrology Report is to provide detail on the outputs from the processes of hydrological analysis and design flow estimation. The details of the methodologies used and the preliminary hydrological analysis are provided in the Inception Report ‘IBE0600Rp0008_HA09 Inception Report_F02’ (RPS, 2012). This report provides a review and summary of the methodologies used as well as details of any amendments to the methodologies since completion of the Inception Report. The report will provide details of the results of the hydrological analysis and design flow estimation and summarise the outputs from the analysis which will be taken forward as inputs for the hydraulic modelling. Discussion will be provided within this report on the outputs in terms of the degree of confidence which can be attached to the outputs and the opportunities for providing greater certainty for future studies, including opportunities for improving the observed data used to inform the study.
This report does not include details of the data collection process, flood history within the AFAs or methodology and results from the historic flood analysis (except where this is used to inform the design flow estimation) as this is contained within the Inception Report for HA09.
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1.2 SUMMARY OF THE AVAILABLE DATA
1.2.1 Summary of Available Hydrometric Data
Hydrometric data is available at 32 hydrometric gauge station locations within HA09 as shown in Figure 1.2 below.
Figure 1.2: Hydrometric Data Availability
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15 stations which are located on watercourses to be modelled have data available within HA09 but only three of these stations were rated under FSU as having a rating classification of A1 (confidence in the rating up to 2 times Qmed), A2 (confidence in the rating up to 1.3 times Qmed) or B (confidence in the rating up to Qmed). Only four stations on the main channel of the River Liffey have flow data available for use in this study:
Celbridge (09006 – EPA / ESB) has continuous water level and flow data available for 1967 – 1986 and 1995 – 1997. The conventional water level – flow gauging station is now redundant.
Golden Falls (09007 – EPA / ESB) has continuous water level and flow data available from 1975 – 1981. The conventional water level – flow gauging station is now redundant and only continuous flow measurements through the dam structures are available from 2005 – 2012.
Leixlip (09022 – EPA / ESB. The conventional water level – flow gauging station is now redundant and only continuous flow measurements through the dam structures are available from 2005 – 2012.
Pollaphuca (09032 – ESB). . The conventional water level – flow gauging station is now redundant and only continuous flow measurements through the dam structures are available from 2005 – 2012.
There are some limitations on the usefulness of this data for design flow estimation due to the record length. Furthermore the upstream data cannot be easily analysed using standard flood hydrology techniques as the flows are largely dominated by non-standard, in catchment hydrology terms, considerations such as power generation, water abstraction and dam safety. Four stations within HA09 were recommended for CFRAM Study rating review which is discussed further in chapter 3.
In general HA09 can be considered to be a moderately well gauged catchment with most of the watercourse models having at least one hydrometric gauge station with flow data available. However only four out of a total of 15 models have gauging stations which have either:
1. An FSU rating classification indicating confidence in the rating at Qmed or;
2. Are subject to rating review such that confidence in the rating at Qmed is achieved.
Further details on the data availability at hydrometric gauge stations within HA09 can be found in Appendix A.
1.2.2 Additional Simulated Flow Data
As discussed in the Inception Report and in various sections of this report additional flow data has been simulated at various HEPs through the application of rainfall data in catchment scale run-off models. This additional, simulated layer of flow data has been used to aid design flow estimation. This flow data will also be used during the hydraulic modelling calibration phase in order to provide simulated historic flood hydrographs where no flow data currently exists which can be matched against recorded levels and / or mapped flood extents. Each model has been considered on an individual
IBE0600Rp00016 5 Rev F03 Eastern CFRAM Study HA09 Hydrology Report – FINAL basis against the available flow data and calibration has been achieved based on a range of goodness of fit measures and on visual inspection of the mass balance and flow trace graphs, examples of which are shown in Figure 1.3 and Figure 1.4 for the modelled catchment to the Morell Bridge (09024 – EPA) hydrometric gauging station.
Figure 1.3: Water mass balance between observed and simulated catchment at Morell Bridge (09024)
Figure 1.4: Observed and simulated flow trace for catchment at Morell Bridge (09024)
Gaps in the observed record as is evident in the above flow trace in late 2005 / early 2006 and issues with the rating curve can lead to erroneous goodness of fit measures. It is therefore not possible to make a meaningful summary of the calibration of this simulated data against available flow data from
IBE0600Rp00016 6 Rev F03 Eastern CFRAM Study HA09 Hydrology Report – FINAL hydrometric gauging stations and each model must be considered on an individual basis. Results of the calibration process and a summary of the output flow data are contained within Appendix E.
1.2.3 Summary of Available Meteorological Data
Meteorological data is available from a number of Met Éireann daily and hourly rain gauges within the Eastern RBD and beyond which has the potential to be used within the hydrological analysis. In particular, within the RPS methodology the historical time series data can be used as an input to catchment scale hydrological rainfall run-off models to simulate a continuous flow record within a catchment. High resolution temporal data is required to achieve the required accuracy within the hydrological models and as such hourly time series data is required. There are three Met Éireann hourly rain gauges within HA09 itself, at Casement, Phoenix Park and Dublin Airport. Combinations of data from these stations can be used as inputs to hydrological modelling by using the area weighted thiessen polygons method to interpolate data at geographical locations between the stations. Some sub-daily historical data is also available from Local Authority rain gauges in the Dublin area also. Daily rainfall data is not considered to be of a high enough temporal resolution to be used as direct input for hydrological modelling on its own but can be used along with the hourly data to inform the spatial distribution of hourly rainfall data within the catchments.
In addition to the observed historical rainfall data available at the aforementioned rain gauge locations, further meteorological information is required as input to hydrological models namely observed evaporation, soil moisture deficits and potential evapotranspiration data. Historical time series data is available for these parameters at Met Éireann synoptic weather stations. The locations at which historical data is available is generally the same as for hourly rainfall data and is available at Casement, Phoenix Park and Dublin Airport. This additional meteorological data was found to be of sufficient availability to be used as input to the hydrological models. Figure 1.5 shows the locations of all of the rain gauges available and the availability of historic information at the hourly rainfall gauges.
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Figure 1.5: Meteorological Data Availability
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1.2.4 Rainfall Radar
A data collection meeting held at the beginning of the Eastern CFRAM Study (between RPS, HydroLogic, OPW and Met Éireann) identified an opportunity for exploring the use and benefits of rainfall radar data in hydrological analysis. A radar trial was undertaken on the Dodder catchment and is reported in ‘IBE0600Rp0007 Eastern CFRAM Study, Dublin Radar Data Analysis for the Dodder Catchment, Stage 1’ (RPS / Hydrologic, 2012) whereby data from the Dublin radar was adjusted against the available rain gauge data to produce an adjusted hourly gridded time series of rainfall data. When compared to the area-weighted derived rainfall series from the gauge data alone, the use of the radar data was shown to bring significant improvements to the rainfall data for rainfall run-off modelling input in terms of spatial distribution of the rainfall, the peak discharges and the timing of the peak discharges. Simulated hydrograph shapes and the overall water balance error margins were also shown to be significantly improved. A further analysis is also being undertaken remote from the Dublin radar in order to quantify the benefits at a location further away from the radar. The Athboy River within HA07 has been chosen as a suitable location for the trial and the results of the analysis are presented in the forthcoming report ‘IBE0600Rp0013 Athboy Radar Analysis’ (RPS).
Following approval from OPW to process historical data from the Met Éireann radar located at Dublin Airport for the entire Eastern CFRAM Study area information was received covering the time period from January 1998 to July 2012. Following initial screening of both the radar information and the available rain gauge information which is required for adjustment of the radar observed rainfall sums the following dataset was processed for use in the ECFRAM Study:
Hourly PCR (Pulse Compression Radar) data on a 1 x 1 km grid (480km x 480km total grid) covering the entire calendar years 1998 – 2010
Following processing of this radar dataset rainfall sums are available for every hour, for every 1km² grid square of the Eastern CFRAM Study area for the calendar years 1998 - 2010. During the processing the rainfall sums have been adjusted spatially and temporally so as to match the daily and hourly sums at the rain gauges and as such RPS considers this processed dataset to be of high accuracy and high resolution.
Concurrent radar and rain gauge data covering the entire years of 2011 and 2012 was not available at the time of commencement of the radar processing. This data (including the flood event of 24th October 2011) may be used to validate the models subject to approval from OPW for processing further concurrent datasets which have since become available.
Full details of the methodology, datasets used and outcomes of the Dublin radar and rain gauge data processing for the ECFRAM Study area can be found in the report Analysis of the Dublin Radar Data for the Eastern CFRAM Study Area in Appendix B.
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1.2.5 Historic Flood Frequency Analysis
Flood frequency analysis has been undertaken as part of the Eastern CFRAM Study in relation to the available hydrometric and rainfall gauge data in order to assess the probability / rarity of past flood events. In relation to HA09 this analysis can be found in the HA09 Inception Report (IBE0600Rp0008, RPS, 2012) and also in relation to the flood event of October 2011 in HA09 through the subsequent Overarching Report on the October 2011 Flood Event (IBE0600Rp0014, RPS, 2013).
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2 METHODOLOGY REVIEW
The methodologies for hydrological analysis and design flow estimation were developed based on the current best practice and detailed in the HA09 Inception Report. In the intervening period there have been a number of developments both in best practice, and the hydrological analysis tools which are available such that it is prudent that the overall methodology is reviewed and discussed. As well as a review of the methodology this chapter seeks to identify changes to the catchment, such as diversions through drainage networks and amendments / updates to the FSU catchment data, which have become apparent and must be considered in the hydrological analysis.
2.1 HYDROLOGICAL ANALYSIS
The main tasks of hydrological analysis of existing gauge data have been undertaken based on the best practice guidance for Irish catchments contained within the Flood Studies Update. The analysis of the data available from the hydrometric gauge stations shown in Figure 1.2 has been carried out based on the guidance contained within FSU Work Packages 2.1 ‘Hydrological Data Preparation’ and 2.2 ‘Flood Frequency Analysis’ and is detailed in Chapter 4. This analysis was undertaken prior to the receipt of survey information which would have allowed the progression of the Eastern CFRAM Study gauge station rating reviews identified within the HA09 Inception Report. The rating reviews, the new rating relationships and the consequences of the rating reviews for hydrological analysis are discussed in detail in chapter 3 of this report. The following elements of hydrological analysis have been assessed against the potential impact of uncertainty in the rating and mitigation measures and / or re- analysis undertaken to ensure the robustness of the hydrological analysis:
Gauged Index Flood Flow (Qmed) – Where there has been shown to be uncertainty in the
rating within the range of flows up to and around Qmed, the Annual Maxima (AMAX) flow series
has been re-processed using the revised rating. The use of the gauged Qmed in design flow estimation is further discussed in 2.2.1.
Single site (historic) flood frequency analysis – As the estimated frequency of a flood event is a function of the ranking of the event within the AMAX series, and this will not change following re-processing of the AMAX series, this will have little impact on the outputs of this study.
Growth Curve Development – The inclusion of gauge years within pooled flood frequency analysis that have a high degree of uncertainty could have a skewing effect within the frequency analysis but the effect will be diluted within a group (where it is assumed other gauge years have a high degree of confidence). The cumulative effect of uncertainty in both directions at multiple gauges may also have a cancelling out effect within a pooling group and as such it is not necessary to re-analyse the pooling groups. However where growth curves are based on a single site analysis where it has been shown that there is uncertainty in the
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rating, the single site analysis has been re-analysed with the re-processed AMAX data based on the revised rating relationship.
2.2 METEOROLOGICAL ANALYSIS
Chapters 1.2.2, 1.2.3 and 1.2.4 discuss how a wide range of meteorological data, both rain gauge and radar based, has been brought together to cover the entire Eastern CFRAM Study area such that all areas are covered by high resolution spatial and temporal historical rainfall data. The methodology does not seek to analyse the raw rainfall sums which have been produced from the processing of the data but rather seeks to interpret this data through rainfall run-off modelling and build simulations of the resulting flows in the catchments and sub-catchments and in some areas which are otherwise ungauged (hydrometrically). The modelling techniques used result in a wealth of additional (simulated) historical flow data within the catchments which is directly relevant to fluvial modelling and which therefore adds statistical robustness to the traditional analysis techniques.
2.3 DESIGN FLOW ESTIMATION
The estimation of design flows is based on a methodology combining the available best practice guidance for Irish catchments and hydrological catchment rainfall run-off modelling to supplement the available gauged data with simulated flow data. The methodologies for estimation of the various elements which make up the design flow estimates to be used for modelling are detailed below.
2.3.1 Index Flood Flow Estimation
Estimation of the Index Flood Flow is required for all catchments and sub-catchments to be analysed under the CFRAM Study with each sub-catchment defined by a Hydrological Estimation Point (HEP). The preferred methodologies for estimation of design flow vary depending on the size, whether or not the catchment is gauged and also based on how the run-off from the catchments impacts upon the AFA. However a comprehensive, hierarchical approach is being taken to index flood flow estimation whereby all the specified methodologies available at each HEP are employed to estimate the index flood flow and to provide robustness to the estimates. For example, in the first instance, the FSU 7- variable ungauged catchment descriptor equation (Work Package 2.3) is used to calculate an estimate of the Index Flood Flow at all HEPs and where available, gauge records, catchment run-off models and other applicable methodologies are used to adjust / improve the estimate as the design flow estimation is developed. The hierarchy of preferred methodologies is discussed below.
2.3.1.1 Gauged Index Flood Flow (Qmed)
HEPs have been located at all hydrometric gauging stations where flow data is available and these HEPs are all subject to hydrological catchment scale rainfall run-off modelling, the methodology for which is described in detail within the HA09 Inception Report. Two hydrometric gauging stations within
HA09 have been shown to have significant uncertainty (affected the Qmed by 15% or more) in the
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existing rating at flood flows following CFRAM Study rating review. The gauged Qmed to be used for design flow estimation is improved using simulated data from the AMAX series from the rainfall run-off model constructed for the catchment at the gauge station. This has a number of advantages:
An AMAX series is simulated for the duration of the meteorological records which are
generally between 50 – 70 years in length giving greater statistical confidence in the Qmed value.
The modelled catchment characteristics reflect present day (derived from the current CORINE 2006 land use and GSI data sets) conditions and as such are not subject to changes in flood flow behaviour over time due to changing catchment conditions (as may be the case within historic gauge records).
It must be noted however that the run-off models are calibrated against the gauge records so in theory there is the potential for any error in the gauge records to be carried over into the rainfall run-off models. As such the following mitigation measure has been taken to ensure that the effect of uncertainty at the hydrometric gauging station is not replicated in the rainfall run-off model:
Catchment scale rainfall run-off (NAM) models are calibrated only to the range of the flow trace at gauging stations where there is certainty in the rating. For example where there is an FSU A2 classification of the rating the rainfall run-off model will be calibrated on the flow
values up 1.3 times Qmed only. Where there is no FSU classification the calibration will be carried out on the range of flows for which spot gaugings are available (i.e. not on flows based on an extrapolated rating curve).
Conversely to this potential for error in the rainfall run-off model, if the calibration is carried out against a period for which there is certainty in the gauged flows then it is possible that the model will replicate historic event flood flows which are beyond the confidence of the gauging station rating (i.e. based on an extrapolated relationship between water level and flow) more accurately than the gauge station has recorded (where there is uncertainty in the rating).
The simulated AMAX series and subsequent Qmed will be considered alongside the existing AMAX series and Qmed to achieve the most robust estimate of the gauged Qmed . Where for example there is confidence in the rating at Qmed (FSU A1, A2 & B classification or post rating review) and the gauge record is sufficiently long such that the statistical standard error as detailed in FSU WP 2.3, Table 2 is lower than that of the rainfall run-off models within the catchment (Appendix E) then the Qmed at the gauge is preferred.
2.3.1.2 Ungauged Index Flood Flow (Qmed)
At all catchments the relevant ungauged catchment descriptor based methods have been used to derive estimates of Qmed. Estimates based on both methodologies listed below (FSU and IH124) are
IBE0600Rp00016 13 Rev F03 Eastern CFRAM Study HA09 Hydrology Report – FINAL carried out for all catchments for comparative purposes but the preferred methodology is dependent on catchment size and based on current best practice guidance:
1. FSU WP 2.3 ‘Flood Estimation in Ungauged Catchments’ has been used for all catchments with an area more than 25km².
2. Institute of Hydrology Report No. 124 (Marshall & Bayliss) ‘Flood Estimation for Small Catchments’ has been used for all catchments with an area less than 25km² although the FSU method above has also been retained for comparative purposes.
The FSU methodology outlined in WP 2.3 recommends that all estimates based on the seven parameter catchment descriptor equation are adjusted based on the most hydrologically similar gauged site. The adjustment factor is applied to the regression equation estimate at the subject catchment and can be described in simple terms as the gauged Qmed divided by the regression equation estimated Qmed at the most hydrologically similar gauged site. Hydrological analysis tools developed by OPW as part of the FSU identify 216 gauge locations which are described as ‘Pivotal Sites’ following analysis of the data available as part of FSU WP 2.1 ‘Hydrological Data Preparation’. Rather than be restricted to the list of Pivotal Sites RPS has used the results of the rainfall run-off modelling at gauging stations (both FSU pivotal sites and other gauged locations) to build a higher density of gauge sites for which data is available upon which to base adjustment. As such the adjustment of ungauged estimates of Qmed considers a number of sources of gauged data upon which to base adjustments:
1. Rainfall run-off (NAM) model results discussed in 2.3.1.1 where these are available upstream or downstream of the subject site. 2. FSU pivotal sites database
3. Other gauge sites where due to rating review there is confidence in the observed Qmed (Cadburys gauge station 09102 in the case of HA09).
2.3.2 Growth Curve / Factor Development
Growth curves have been developed based on single site and pooled analysis of gauged hydrometric data based on the FSU methodology set out in Work Packages 2.1 and 2.2. Due to CFRAM Study programme constraints it was not possible to include the simulated AMAX series years at gauging stations within the analysis and as such all analysis is based on the recorded data only. Full details and discussion of the results can be found in Chapter 4.
2.3.3 Design Flow Hydrographs
The design flow hydrograph methodology for the Eastern CFRAM Study centres around FSU Work Package 3.1 ‘Hydrograph Width Analysis’ and uses the tools developed by OPW for analysing flood hydrographs at gauged sites supplemented with the additional simulated continuous flow data derived
IBE0600Rp00016 14 Rev F03 Eastern CFRAM Study HA09 Hydrology Report – FINAL from the catchment rainfall run-off (NAM) models. Since the completion of the Inception Report the methodology for deriving design flow hydrographs has been developed further following the release of the FSU Hydrograph Shape Generator version 5 and further development of the rainfall run-off (NAM) methodology. As such the hydrograph shapes are generated based on the following methods:
1. At all rainfall run-off modelled HEPs simulated continuous flow records are now available such that a range of past flood events can be analysed. The method utilises the Hydrograph Width Analysis (HWA) software developed as part of FSU WP 3.1 to analyse these simulated flow records to produce median width, semi-dimensionless hydrographs for design events. The methodology requires the conversion of the continuous flow trace data into the required HWA specific format (.tsf file) before historic events are isolated and analysed. This methodology will provide the larger inflow hydrographs which will drive the hydraulic models.
2. At most other HEPs within HA09 hydrographs will be generated using the recently released Hydrograph Shape generator version 5 developed by OPW. This tool increases the list of Pivotal Sites from which median hydrograph shape parameters can be borrowed based on the hydrological similarity of the Pivotal Site when compared to the subject site. The release of version 5 of this tool has increased the pool of Pivotal Sites to over 150. RPS trialling of this version of the FSU Hydrograph Shape Generator in the CFRAM Studies has found that the generated hydrograph shapes provide a reasonably good fit when compared to the observed and simulated (NAM) hydrographs within the catchment.
3. At a few locations it may not be possible to find a suitable Pivotal Site from which a comparable hydrograph shape can be borrowed, particularly for the very small sub- catchments which have been delineated within the watercourses in South Dublin. In this instance hydrograph shapes have been generated using the Flood Studies Supplementary Report (FSSR) 16 Unit Hydrograph method.
Design hydrographs have been developed at all HEPs. It was originally intended that at the smallest inflow / tributary HEPs continuous point flows could be input. However analysis of this method found that the hydrograph was critical in some of the smallest watercourses which are restricted by culverts / bridges where flood volume as opposed to flood flow becomes the critical characteristic of a flood. One example of this is at the upstream limits of the Camac watercourse in south Dublin where during the October 2011 event the volumes of flood water which built up upstream of culvert inlet structures was critical. Application of continuous point flows on the upstream reaches of the hydraulic models could lead to an unrealistic build-up of water behind culvert structures where this is the critical flood mechanism.
2.4 HYDROLOGY PROCESS REVIEW
Following developments in best practice and guidance documents and the refinement of RPS methodology through its application on the Eastern CFRAM Study the hydrology process has been
IBE0600Rp00016 15 Rev F03 Eastern CFRAM Study HA09 Hydrology Report – FINAL amended slightly from that which has been presented in the HA09 Inception Report (summarised previously in Figure 5.2 of report IBE0600Rp0008_HA09 Inception Report_F02). The revised process flow chart which has been applied in carrying out the hydrological analysis and design flow estimation for HA09 is presented in Figure 2.1.
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Figure 2.1: Hydrology Process Flow Chart
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2.5 ALTERNATIVE APPROACHES REQUIRED WITHIN HA09
In addition to the approaches outlined in the HA09 Inception Report and further developed in the previous sections of this report, RPS have been required to adopt alternative approaches to design flow estimation within the hydraulic models following on from discussions with the hydraulic modeller, following initial calibration attempts. This relates specifically to the small, heavily urbanised, ungauged Poddle watercourse in south Dublin. For the higher return periods, statistical catchment descriptor based estimates and rainfall run-off modelling derived design flows along the main channel of the watercourse were found to be much higher than the physical capacity of the urbanised channel and culvert sections. Initial design flow estimates were derived based on the FSU and IH 124 ungauged catchment estimation methods and supplemented with a rainfall run-off (MIKE 11 NAM / Urban) model using gauge adjusted rainfall data from the Dublin radar (Appendix B - report IBE0600Rp0015 Stage 2 – Analysis of Dublin Radar Data for the Eastern CFRAM area). IH 124 estimates were quickly ruled out because of the extreme effect of urbanisation within such a heavily urbanised catchment which resulted in very high design flows. The catchment run-off model suggested a higher Qmed value than the FSU derived estimates but the run-off model could not be calibrated to hydrometric data as the Poddle is an ungauged catchment. For that reason the FSU estimates were preferred for initial design flow estimation. A summary of the initial design flows is given in Table 2.1 below.
Table 2.1: FSU 1% AEP Design Flows
CFRAMS Location Area FSU1 NAM / CFRAMS 1% AEP Design HEP Node Urban Urban Peak Flow (km2) 1% AEP ID 3 Qmed Qmed Growth (m /s) (m3/s) (m3/s) Factor
09_1029_U Tallaght / 0.77 0.38 1.26 Tymon North
09_1874_5_ Whitehall 5.44 1.87 2.922 6.21 Close / RPS Park 3.323 09_1874_10 Mount 8.11 3.04 10.10 _RPS Argus Close
09_1874_17 DS 12.17 4.51 15.00 _RPS Boundary at Liffey
1 IH124 methodology returned higher values than FSU and as such was deemed less suitable for use
2 Adjustment based on the NAM simulated Qmed was not deemed suitable for this catchment due to the NAM simulation having no calibration reference site (hydrometric gauge station) within the catchment. Simulated value provided for reference only here.
Initial attempts at model calibration suggested that the 1% AEP design flows as outlined above (reflective of the flows which are generated by the catchment) when input directly into the constricted
IBE0600Rp00016 18 Rev F03 Eastern CFRAM Study HA09 Hydrology Report – FINAL channels and piped sections of the Poddle could not be conveyed hydraulically by the channel and immediate floodplain (where relevant), particularly at the downstream reaches. Although no flow data is available for the October 2011 flood event in the Poddle, based on data from surrounding catchments and rainfall data it is estimated that the October 2011 event was up to a 1% AEP event (see Overarching Report on the October 2011 Flood Event IBE0600RP0014). It is not considered that flow rates as estimated in Table 2.1 can be conveyed by the Poddle or were replicated during the October 2011 event.
The total catchment is approximately 90% urbanised and therefore the Poddle watercourse is dependent on urban drainage systems to deliver run-off to the Poddle watercourse. Design standards have traditionally stipulated that underground piped elements of drainage networks are designed to convey between 1 in 2 year (50% AEP) and 1 in 5 year (20% AEP) flows before the individual element may surcharge. Higher return period events such as 1 in 10 year (10% AEP) to 1 in 100 year (1% AEP) are unlikely to be conveyed to the watercourse effectively. Therefore it can be considered that although the catchment run-off methods may accurately estimate the run-off flows generated by the urban catchment, these flows cannot be conveyed within the channel and adjacent floodplain due to constrictions in what is essentially an urban drainage network. For this reason it was felt necessary that the effect of the urban drainage network in conveying the run-off to the Poddle must be considered in order to simulate flooding in the Poddle catchment accurately.
2.5.1 Integrated Drainage Network / Watercourse Model and Direct Application of Design Rainfall Events
In order to fully capture the effect of the drainage network and the complexity of the culverted sections of the Poddle an integrated drainage network and watercourse model is being utilised using InfoWorks ICM (integrated Catchment Modelling) 2.0 from Innovyze. This allows direct application of design rainfall events onto the modelled urban fabric of the Poddle catchment and allows simulation of the performance of the drainage network in conveying the run-off into the Poddle. Design rainfall events are therefore used as inputs to the model rather than design flows at HEPs. The rainfall events have been derived from FSU Work Package 1.2 ‘Estimation of Point Rainfall Frequencies’ and the accompanying Depth, Duration, Frequency (DDF) 2km x 2km gridded rainfall sum data for a range of return periods (or AEPs) and storm durations. For each AEP design event a range of storm durations are converted to rainfall hydrograph profiles using the FSR 50% summer and 75% winter hydrograph profiles. For further details of the design rainfall which has been applied to the models see Section 4.6. The result of using this approach is that the model now models the performance (captures the restrictions) of the integrated Poddle catchment / drainage system network in delivering rainfall into the watercourse and flows are generated which can be validated against the capacity, flood extents and event flow data (recorded as part of the GDSDS).
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2.6 CATCHMENT BOUNDARY REVIEW
In line with the CFRAM Study Stage 1 Project Brief (ref. 2149/RP/002/F, May 2010) section 6.3 RPS have delineated the catchment boundaries at HEPs using the FSU derived ungauged and gauged catchment boundaries as a starting point. For details of the full methodology for undertaking this review see HA09 Inception Report section 5.3.2. Following the completion of this process a number of the catchment boundaries were amended and in a number of catchments the boundaries were amended significantly. Table 2.2 gives a summary of the changes in the catchment area at CFRAM Study HEP points when compared to the equivalent FSU catchment from which they were derived.
Table 2.2: Summary of Catchment Boundary Review
Change in Catchment Area Number of HEPs
New Catchment Delineated 80
No change 98
0 – 10% 41
Greater than 10% 22
Total 241
Not all the catchments related to HEPs that are required to be considered within HA09 were previously delineated. Some of the catchments relate to small streams and land drains which were too small to be considered under FSU and as such RPS delineated these previously undelineated HEP catchments using a combination of mapping, aerial photography and the National Digital Height Model (NDHM). The review concluded that most catchments were already accurately delineated or were newly delineated but 39% of the catchments delineated under FSU were found not to be representative of the NDHM, the mapping or draft survey information. The most common reasons for amendment in HA09 were due to diversions of the natural catchment through urban drainage networks or due to urban topography or built environment changes. 22 of the catchments (9%) were found to have margins of error of over 10%. These catchments ranged from 0.29 to 49.57 km² in catchment area.
IBE0600Rp00016 20 Rev F03 Eastern CFRAM Study HA09 Hydrology Report – FINAL 3 HYDROMETRIC GAUGE STATION RATING REVIEWS
As a follow on from the recommendations of Work Package 2.1 of the FSU, a task was included in the Eastern CFRAM Study brief to undertake further rating review of a subset of hydrometric stations. Following the completion of the risk review stage and finalisation of the AFA locations four hydrometric stations were specified for rating review. These stations were chosen for rating review by OPW as they had available continuous flow data, were located on (or just upstream or downstream of) watercourses to be modelled and were deemed under FSU Work Package 2.1 as currently having a rating quality classification that could be improved upon (i.e. there may be some uncertainty in the rating at extreme flood flows).
3.1 METHODOLOGY
The methodology for carrying out rating reviews entails the following general steps:
1. Gauge station reach of watercourse is surveyed in detail (site visit, cross sections and LiDAR survey). Rating review survey is prioritised ahead of survey required for hydraulic modelling.
2. A hydraulic model is constructed of the reach of the watercourse from sufficient distance upstream to a sufficient distance downstream of the gauge station.
3. Spot gauged flows are replicated within the model and the model calibrated in order to achieve the observed measured water levels at the gauge station location.
4. When calibration is achieved flows are increased from zero to above the highest design flow (>0.1% AEP event) and the corresponding modelled water levels at the gauge location are recorded.
5. The stage (water level minus gauge station staff zero level) versus discharge results are plotted to determine the modelled stage discharge (Q-h) relationship.
6. The existing Q-h relationship is reviewed in light of the modelled relationship and the existing reliable limit of the Q-h relationship is extended up to the limit of the modelled flows. In some cases where the existing Q-h relationship has been extrapolated beyond the highest gauged flow (for practical reasons) the modelled Q-h relationship may vary significantly and as such the reliability of the existing gauged flood flows is called into question.
Four hydrometric stations have been specified for this analysis within HA09 and are shown in Table 3.1.
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3.2 RATING REVIEW RESULTS
The current rating quality classification assigned under the FSU for each station (if available) and whether the rating review indicated that there is significant uncertainty in the existing rating, defined as a difference in Qmed of more than 10%, is stated in Table 3.1.
Table 3.1: Existing Rating Quality Classification for Rating Review Stations in HA09
Significant Uncertainty Station Final Station Rating Quality Station Name Identified in current Number Classification rating
A1 09001 Leixlip No (1980 – 2004) A1 09002 Lucan Yes (1977 -2004) B 09035 Killeen Road Yes (1996 – 2004) 09102 Cadburys NOT REVIEWED UNDER FSU No
A1 sites – Confirmed ratings good for flood flows well above Qmed with the highest gauged flow greater than 1.3 x Qmed and/or with a good confidence of extrapolation up to 2 times Qmed, bank full or, using suitable survey data, including flows across the flood plain.
A2 sites – ratings confirmed to measure Qmed and up to around 1.3 times the flow above Qmed. Would have at least one gauging to confirm and have a good confidence in the extrapolation.
B sites – Flows can be determined up to Qmed with confidence. Some high flow gaugings must be around the Qmed value. Suitable for flows up to Qmed. These were sites where the flows and the rating was well defined up to Qmed i.e. the highest gauged flow was at least equal to or very close to Qmed, say at least 0.95 Qmed and no significant change in channel geometry was known to occur at or about the corresponding stage.
C sites – possible for extrapolation up to Qmed. These are sites where there was a well defined rating up to say at least 0.8 x Qmed. Not useable for the FSU.
U sites – sites where the data is totally unusable for determining high flows. These are sites that did not possess 10 years of data or more, had water level only records or sites where it is not possible to record flows and develop stage discharge relationships. Not useable for FSU.
As well as the uncertainty in the existing ratings some gauging station ratings are limited such that they do not cover the range of flood flows other than through extrapolation of the stage discharge relationship. As a result of this all of the AMAX series level data has been re-processed into AMAX flow data using the revised rating derived from the rating review models and the revised AMAX series
IBE0600Rp00016 22 Rev F03 Eastern CFRAM Study HA09 Hydrology Report – FINAL flow data presented in Table 3.2 below. Full details of the individual rating reviews can be found in Appendix C.
Leixlip Lucan Killeen Road Cadburys 09001 09002 09035 09102 Exist RR Exist RR Exist RR Exist RR (m3/s) (m3/s) (m3/s) (m3/s) (m3/s) (m3/s) (m3/s) (m3/s) 1977 2.86 1978 6.47 1979 8.86 1980 32.02 2.21 1981 22.37 3.64 1982 38.04 8.68 1983 40.71 3.84 1984 38.57 4.62 1985 48.10 16.60 1986 35.46 11.00 1987 26.10 5.56 1988 9.39 1.26 1989 43.48 3.27 1990 29.66 4.28 1991 27.85 2.37 1992 60.74 22.50 1993 29.66 9.50 1994 48.10 4.95 1995 25.24 1.83 1996 16.14 5.25 14.72 10.79 1997 21.58 6.18 8.86 9.20 1998 30.13 5.55 5.55 24.10 12.91 1999 24.40 ------6.73 6.73 2000 81.82 23.70 23.70 14.31 10.68 2001 42.36 8.66 8.66 7.13 7.13 3.38 3.228 2002 91.50 ------47.27 16.70 5.78 6.125 2003 27.85 ------4.75 4.75 3.03 2.847 2004 58.09 3.83 3.55 18.15 11.63 3.32 3.168 2005 22.40 4.60 4.28 2.59 2.59 3.51 3.380 2006 38.60 12.79 13.04 12.78 10.32 3.30 3.138 2007 65.50 13.20 13.45 20.08 12.07 3.88 3.803 2008 25.70 6.18 6.03 6.03 6.03 7.97 9.221 2009 51.10 43.09 11.02 11.24 15.98 11.11 3.33 3.174 2010 28.30 27.84 4.63 4.32 5.39 5.39 3.22 3.049 2011 37.52 34.48 19.56 17.54 16.64 11.28 7.20 8.081 2012 25.19 12.10
Qmed 33.74 31.16 5.56 7.42 13.55 10.50 3.38 3.23 % Diff. -7.6% +33.5% -22.5% -4.4% Table 3.2: AMAX Series Data Before and After Rating Review
IBE0600Rp00016 23 Rev F03 Eastern CFRAM Study HA09 Hydrology Report – FINAL
Not all of the record length of existing AMAX series data has been re-assessed given the new rating. The revised ratings have only been applied to the period of record with a relevant staff gauge zero level and where there is no evidence of a significant shift in the rating. As can be seen from Table 3.2, at two of the stations given ratings under FSU, indicating that there is confidence in the Qmed values, there is significant uncertainty in the existing ratings provided by the relevant rating authority (OPW / EPA).
The Leixlip gauging station (09001 – OPW) was classified as an A1 station under FSU suggesting confidence in the rating at over 1.3 times the Qmed. However the rating review hydraulic modelling indicated that the current Q-h curve is significantly different from the OPW rating. The review found that there have been significant changes to the channel in the last few years including the construction of a by-pass channel in around 2008. This means that the OPW rating is unlikely to still be applicable but the rating may have been applicable and accurate up to the works in question and as such the
Qmed value up to that point may be also be accurate. The new rating which has been derived from modelling results in a similar Qmed however the amount of data since the works is not enough to give statistical confidence to the new derived value. Given that the existing rating was classified as A1 it is appropriate that this is taken forward as the basis for design flow estimation.
The Lucan gauging station (09002 – EPA) was also classified as an A1 station under FSU suggesting confidence in the rating at over 1.3 times the Qmed. The rating review hydraulic modelling did not indicate that there was a significant difference in the EPA and modelled rating curves. However the modelled rating curve could only be applied from 2004 onwards due to a weir having been constructed. Consideration of the AMAX values from 2004 onwards did however indicate that there has been a big upwards shift in the Qmed value. The new rating derived from the rating review hydraulic model could only be applied with certainty to the period from 2004 onwards but the Qmed for this period is more than double the previous, FSU Qmed. It is considered that this may be due to a combination of:
1. Rapid urbanisation – a review of the Corine land use dataset and aerial photography suggests that the catchment has undergone rapid urbanisation between 2006 and 2012.
2. The short period of record (9 years) on which the new rating is applied may represent a period rich in significant flood events. A record period of less than ten years can be shown to have a
significant standard error of approximately 0.12 times Qmed (FSU Work Package 2.3, Chapter 1.4).
In light of the uncertainty in the FSU Qmed value despite the rating review not contradicting the existing rating, it is considered that the Qmed based on the entire record period cannot be taken forward with confidence. There are also issues of statistical confidence in taking the post 2004 rating review based value forward. As such it is considered prudent that the last 14 years of AMAX values are used as the basis for the design flood Qmed. For Qmed based on a record period of this length and greater the approximate standard error drops below 0.1 (or the equivalent of 10%).
The Killeen Road gauging station (09035 – EPA) on the Camac River was classified as a B station under FSU suggesting the rating is suitable for deriving a Qmed value with confidence. At the time it
IBE0600Rp00016 24 Rev F03 Eastern CFRAM Study HA09 Hydrology Report – FINAL was classified under FSU there were only 9 years of data and it is worth noting that the current EPA rating differs from that used to derive the FSU value which was 11.7 m3/s. The rating review indicated that there is significant uncertainty in the current EPA rating at Qmed. The rating review Qmed is significantly lower than the value based on the current rating (22.5%) but is closer to the FSU derived value (10.3% lower than the FSU value).
The Cadbury’s gauging station (09102 – EPA) on the Santry River was not given a classification under FSU owing to the fact it only became operational in 2001 and at the time of the FSU review there would only have been three years of data collected. The rating review however did not indicate that there is significant uncertainty in the existing EPA rating at Qmed.
3.3 IMPACT OF RATING REVIEWS ON HYDROLOGICAL ANALYSIS
As discussed in Chapter 2, Methodology Review much of the hydrological analysis was undertaken prior to survey information at the relevant gauging stations being available such that the rating reviews can be carried out. As such it is necessary to quantify the potential impact on the hydrological analysis and identify where re-analysis or mitigation to minimise the potential impact is required. The various elements of the hydrological analysis and design flow estimation are listed below and a summary of the potential impact and the proposed mitigation measures is detailed.
Table 3.3: Summary of Rating Review Effects and Mitigation
Hydrological Potential Effects of Uncertainty in the Potential Mitigation Analysis Rating Impact
Most uncertainty with poor rating likely at flood flows and as such there could be uncertainty in AMAX series. Will affect Re-assess Qmed for FSU Q at sites with a classification lower classified sites of C or U Gauged Q med Medium med than B. Not critical under RPS for verification of NAM methodology as NAM model Qmed will be Qmed taken forward. Gauged Qmed used for verification purposes. An issue where an ungauged catchment is adjusted based on a pivotal site with Ungauged high uncertainty. As Pivotal Sites are Low None required Q med taken from A1, A2 & B classification they are unlikely to be affected.
Flood frequency is a function of the Frequency re-analysis not ranking of events within the AMAX series, required. Historic flood the position in the ranking is unlikely to be frequency affected by adjusting all the values of the Medium Where event flows are analysis series (i.e. unless just adjusting a specific used for calibration historic gauge period) but the flood flow figure flows must be re- must be revised used for calibration. calculated
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Hydrological Potential Effects of Uncertainty in the Potential Mitigation Analysis Rating Impact
The inclusion of gauge years within pooled flood frequency analysis that have a high degree of uncertainty could skew At gauges where there has the pooled frequency analysis but the been shown to be effect will be diluted within a group (where uncertainty, re-assess Growth curve Medium / it is assumed other gauge years have a single site analysis to development Low high degree of confidence). The check that it is within 95th cumulative effect of uncertainty in both percentile confidence limits directions at multiple gauges may also of the pooled analysis. have a cancelling out effect within a pooling group. Catchment scale rainfall run-off or NAM At gauges where there has models are calibrated to the flow trace at Rainfall run- been shown to be gauging stations. If there is uncertainty in off / NAM uncertainty, calibration of the flow trace (most likely at higher flood Medium model the rainfall run-off (NAM) flows) then this could lead to poor calibration model limited to below calibration and the error carried over to threshold values. the run-off model. Calibration of hydraulic models is undertaken at extreme flood flows where Hydraulic highest degree of uncertainty could be Reassess calibration event model High present. Model calibration therefore flows where necessary calibration dependant on upper limits of gauge rating.
Methodology utilises hydrographs in hierarchical order from FSU pivotal sites, Hydrograph NAM models, FSR catchment descriptor Shape Low None required based methods and as such corruption of Generation the design flow hydrographs is considered minimised.
Following the rating reviews carried out for HA09 there was found to be a high degree of uncertainty
(>10% at Qmed) at the Killeen Road gauging station. The rating review found that the existing EPA rating is overestimating flows at Qmed by 15% when compared to the modelled rating curve. In addition to the EPA rating at this station the FSU derived AMAX series is generated using a separate equation derived as a result of FSU WP 2.1. The rating equation was not provided as part of this study but the derived values appear to also indicate that the EPA rating is overestimating flood flows. The Qmed derived as part of FSU WP 2.1 is 11.70 m3/s which compares to 13.56 m3/s from the EPA rating and 10.50m3/s from the rating review. It is worth noting that the FSU derived rating was given a B classification indicating confidence at Qmed.
There was also found to be a high degree of uncertainty (>10% at Qmed) at the Lucan gauging station.
The rating review found that the existing rating is underestimating flows at Qmed by 33% when compared to the modelled rating curve. The rating review AMAX series has only been applied to the last 14 years of record for statistical confidence. The catchment has become substantially urbanised during this time which is the likely cause of the existing rating underestimating flood flows.
IBE0600Rp00016 26 Rev F03 Eastern CFRAM Study HA09 Hydrology Report – FINAL 4 INDEX FLOOD FLOW ESTIMATION
The first component in producing fluvial design flows within the majority of best practice methods widely used in the UK and Ireland is to derive the Index Flood Flow which within the FSU guidance is defined as the median value of the annual maximum flood flow series or Qmed. The methodologies being used in this study are detailed in the HA09 Inception Report and are reviewed in chapter 2 of his report. As discussed the methods combine best practice statistical methods with rainfall run-off (NAM) modelling techniques. This chapter details the Index Flood Flow estimation at each of the HEPs within HA09 on a model by model basis, including a discussion on the confidence and comparison of the outputs from the considered methodologies. HEPs have been specified at the upstream extents of all of the modelled watercourses but it is worth noting that some of these represent the very upstream limits of the catchments and as such there is either little or no contributing catchment. Flood flow at these HEPs may be negligible or zero however these HEPs have been retained to avoid confusion.
For the purposes of design flows derived from catchment descriptor based methods this chapter considers only the catchment downstream of Pollaphuca / Golden Falls dams. Although control of flooding downstream is one of the considerations in the operating regime of the dams, the flows at this point are largely dictated by non-hydrological concerns such as dam safety, reservoir levels and power generation. As such the flows at the upstream end (i.e. released at Golden Falls) are dealt with separately in Chapter 6 and their effect is considered through application at the upstream end of hydraulic model 8 and then sequentially through the Liffey main channel models 6A, 3B, 3A, 2B and 2C.
HA09 had originally been divided into nine fluvial hydrodynamic models, primarily based on the requirement within the modelling software to have only one continuous modelled floodplain per model. Following a subsequent review of the complexity of the individual hydrodynamic models it was decided to further split the models to reduce the complexity of some of the models. Therefore the lower and middle reaches of the Liffey and its tributaries have been split further, over and above the models which were identified in the HA09 Inception Report (IBE0600Rp0008) The 15 models included in HA09 are shown in Figure 4.1.
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Figure 4.1: HA09 Watercourses to be Modelled
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4.1 MODEL 1 – SANTRY
Raheny located at the downstream extents of the Santry River and The Santry River itself are designated as Areas for Further Assessment (AFAs). The Santry model is isolated from the rest of the Liffey system and flows directly into Dublin Bay at Raheny to the west of North Bull Island. The watercourse originates from the southern edge of Dublin Airport and drainage drawings supplied by Dublin Airport Authority indicate that the drainage system for the western edge of the southern runway and some car park hardstanding both discharge to the head of the Santry through conventional piped drainage systems. The Santry is a narrow catchment and has no significant tributaries. The catchment is heavily urbanised (62%) and also includes an attenuating structure and online storage pond at Santry Demesne to the south of Northwood Avenue.
The model can be considered to represent a gauged catchment with the Cadburys hydrometric gauging station (09102 – EPA) located approximately two thirds of the length of the river from Dublin Airport. The gauging station was not given a classification under FSU and the rating curve does not extend up to the range of the observed corresponding water level at Qmed. As such the gauging station 3 cannot be considered to have a high degree of certainty at flood flows. The observed Qmed of 3.37m /s is derived from only 11 complete hydrological years of data and as such does not have the highest degree of statistical certainty. The total catchment area of the model at the downstream extents (at Raheny) is 13.96km². The HEPs and associated sub-catchments of the Santry model are shown in Figure 4.2.
Figure 4.2: Model 1 HEPs and Catchment Boundaries
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A rainfall run-off model has been developed of the contributing catchment to the Cadburys gauging station in order to simulate a longer AMAX series and increase confidence in the Cadburys gauged
Qmed. The model was calibrated against the existing continuous flow record of the gauging station from 2001 to 2011 and utilises rainfall data from the hourly gauge at Dublin Airport as input data. The hourly rainfall gauge was used at Dublin Airport due to its location at the edge of the Santry catchment which is small and therefore has little spatial variation in meteorological conditions which would be captured by the rainfall radar also located at Dublin Airport. The rainfall run-off (NAM) model was calibrated to the period for which there is corresponding flow data and rainfall gauge data (2001 – 2010) and good calibration was achieved. Hourly rainfall information is available for the period of 1941 – 2010 and was input to the rainfall run-off model. The simulated and observed continuous flow trace calibration plots and simulated AMAX series are located in Appendix E. Analysis of the simulated flow trace shows 3 that the simulated Qmed from this period is 3.25 m /s. This compares to values derived from catchment descriptor based methods at the gauge of 4.55 m3/s and 2.53m3/s using IH124 and FSU methods respectively. Due to the catchment sizes the IH124 values have been retained and adjusted downwards based on the relationship between the NAM simulated and IH124 derived index flood flow values at the Cadburys gauging station. The estimated Qmed values for the various HEPs within Model 1 are shown in Table 4.1.
Table 4.1: Qmed Values for Model 1
2 3 Preferred Estimation Node ID_CFRAMS AREA (km ) Qmed (m /s) Methodology
09_1502_1_RPS 1.65 0.39 IH124
09_1507_6_RPS 8.93 2.48 IH124
09102_RPS
G.S. (no FSU 10.90 3.25 NAM classification)
09_1507_17_RPS 13.96 5.24 IH124
Note: Flow highlighted in yellow represent total flows at that point in the model rather than input flows
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4.2 MODEL 2A – BALDONNEL
The Baldonnel model represents the upper and middle reaches of the Griffeen River, a tributary of the River Liffey, including all the smaller tributaries of the Griffeen which affect the Baldonnel AFA including the Carrigeen and the Baldonnel watercourses which neighbour the Camac catchment to the east. The Griffeen joins the Liffey approximately 8km to the north of Baldonnel. The catchment of the model is relatively small (30 km2) and is partially urbanised (16%).
Although there are no gauging stations directly on the Baldonnel model (2A) the Lucan gauging station (09002 – OPW) is just downstream on the lower reaches (model 2B) of the Griffeen at a location just upstream of the confluence with the main Liffey channel. This gauging station represents a contributing catchment area of approximately 36 km2. The station was given a classification of A1 under FSU and as such there can be considered to be a high degree of confidence in the flow at Qmed. The gauging station also has over 20 years of continuous flow data. The Baldonnel model is shown in Figure 4.3.
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Figure 4.3: Model 2A HEPs and Catchment Boundaries
A catchment rainfall run-off model was also constructed representing the catchment to the gauging station at Lucan (09002) and calibrated using the processed rainfall radar data against the continuous flow record at the gauging station. The simulated and observed continuous flow trace calibration plots and simulated AMAX series can be found in Appendix E. Analysis of the simulated flow trace shows 3 that the simulated Qmed from this period is 5.83 m /s which compares well to the gauged value of 5.56 m3/s. Following the rating review it was found that there was significant uncertainty in the existing observed Qmed value covering the entire length of record. This was not due to inaccuracy in the rating, which was given a classification of A1 under FSU, but due to a significant increase in the Qmed when the most recent (since 2004) values are considered (see Section 3 and Appendix C). Following the rating review it was considered prudent that the observed Qmed value was updated to reflect the most recent AMAX values but also that the Qmed considered a sufficient record period such that there was statistical confidence in the value taken forward. As such a Qmed value based on the last 14 years of
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3 record of 7.42 m /s was considered (1996 – 2012) appropriate to take forward as the Qmed value at the gauging station.
Values were derived from catchment descriptor based methods at the gauge of 7.93 m3/s and 5.88 m3/s using IH124 and FSU methods respectively. Flows on the main channel of the Griffeen have been derived based on estimates using the FSU ungauged catchment descriptor equation and the Lucan gauge as a pivotal site. The rating review based observed value has been used as the basis for the design flows as opposed to using the NAM simulated value. The NAM value is calibrated to the older FSU period of record and is not reflective of the most recent, higher values which may be resulting from rapid urbanisation of the catchment. FSU values have been adjusted slightly downwards based on this site. The majority of the smaller input HEPs at the top of the modelled catchment represent small catchments and initially the Qmed values at these HEPs were based on IH124 derived values. However following initial hydraulic modelling of the Baldonnel area it was found that the sum of the IH124 values was too small to reach the rating review based values at the downstream end of the model. As such all of the Qmed estimated values entered into the model were based on FSU based ungauged estimates which were then adjusted based on the rating review Qmed value at Lucan.
Furthermore, in light of the shift in the Qmed values observed at the gauging station, it was considered appropriate that urban extent values were re-calculated (from the FSU ungauged physical catchment descriptor values) based on aerial photography and the latest land use datasets. The estimated Qmed values for the various HEPs within Model 2A are shown in Table 4.2.
2 3 Preferred Estimation Node ID_CFRAMS AREA (km ) Qmed (m /s) Methodology
09_990_U 1.19 0.29 FSU
09_1156_1 1.06 0.61 FSU
09_1165_5 3.53 1.55 FSU
UN_Trib_Griffn_U 0.00 0.00 FSU
UN_Trib_Griffn_1 0.04 0.01 FSU
UN_Trib_Griff_U 1.71 0.59 FSU
UN_Trib_Griff_1 4.81 1.65 FSU
09_452_U 0.01 0.00 FSU
09_452_2_RPS 0.52 0.16 FSU
09_1120_3_RPS 30.03 6.21 FSU
09002_RPS G.S. (A1) 34.58 7.42 Observed Qmed Note: Flow highlighted in yellow represent total flows at that point in the model rather than input
Table 4.2: Qmed Values for Model 2A
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4.3 MODEL 2B – LUCAN TO CHAPELIZOD
The Lucan to Chapelizod model represents the portion of the lower Liffey affecting the Lucan to Chapelizod AFA including the lower reaches of the Griffeen River. The model is downstream of a number of other significant models and is affected by the ESB electricity generation dams upstream on the River Liffey (although their attenuating effect on the flows on the lower reaches is minimal).
Figure 4.4: Model 2B HEPs and Catchment Boundaries
The model is characterised by two different types of watercourses which are hydrologically quite different; the lower reaches of the River Liffey itself (excluding upper catchment area is 730 km2) and the much smaller tributaries which flow into this portion of the Liffey including the Griffeen River and the smaller Milltown, Hermitage and Woodville and Quarryvale watercourses (catchment areas ranging from 0.2 to 35 km2). The Griffeen is gauged at Lucan (EPA – 09002) with an A1 rating classification under FSU. A catchment rainfall run-off model of the Griffeen has been simulated and good agreement was found with the observed Qmed value. However as discussed in Section 3.3 following the rating review it was found that there was significant uncertainty in the existing observed
Qmed value covering the entire length of record due to a significant increase in the Qmed when the most recent (since 2004) values are considered (see Section 3 and Appendix C). Following the rating 3 review a Qmed value based on the last 14 years of record of 7.42 m /s was considered (1996 – 2012) appropriate to take forward as the Qmed value at the Lucan gauging station on the Griffeen.
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Index flow estimates on the Griffeen have been based on the FSU method with adjustment based on the gauging station as the pivotal site. The other smaller watercourses are ungauged and as such the
Qmed is derived from estimates based on catchment descriptors using the IH124 method although it is worth noting that the derived values are in good agreement with FSU catchment descriptor based estimates. These smaller HEPs have not been adjusted downwards based on the relationship between the gauged and IH124 Qmed values at the gauging station (09002_RPS). Due to the uncertainty in these small catchment estimates the Qmed values may be subject to further adjustment at the hydraulic modelling stage. The Qmed estimates for these catchments can be considered to have a lower degree of confidence.
The portion of the Liffey within this model is not directly gauged although there is a gauge station approximately 2 km upstream of the model extents at the Leixlip hydro-electric power generation station owned and operated by ESB (09022). This station was not given a classification under FSU and is not a standard water level recorder station as operated by OPW and EPA. The flow data received has been derived from continuous recordings of flows and water levels through the various structures of the plant and converted into combined flow rates on request to ESB. The continuous flow records can be considered to have a high degree of confidence since they are derived from a combination of measured flows and fully defined water level flow relationships (through the turbines, sluices and spillways) rather than based on an extrapolated relationship between water level and flow as is common at conventional gauging stations. However continuous recordings are only available for seven years from 2005 to 2011 inclusive and such the Qmed derived from the AMAX series of 61.64 m3/s can be considered to have a low degree of statistical confidence. This AMAX series has also been combined with flow values observed at the bottom of the Rye Water from the Leixlip gauging station (09001 – OPW) to create an observed Qmed value at the confluence point of the Rye Water and the Liffey. Five complete hydrological years of combined data are available (2005 – 2009) but the combined Qmed value is derived from two gauging stations which can be considered to have 3 confidence in their ratings at Qmed. This combined observed Qmed value of 76.68 m /s (combined catchment area of 719 km2) can be considered to have a low degree of statistical confidence due to the short record length. In light of this a further analysis of the data using the Peaks Over Threshold (POT) method as detailed in the Flood Estimation Handbook, Volume 3 was undertaken. Using this method the 24 flood peak values over a threshold value of 57 m3/s were considered and an equivalent 3 Qmed was extracted of 94.1 m /s. This figure is significantly higher than the value extracted from the AMAX series but can be considered to have a higher statistical confidence with a factorial standard error (FSE) of 1.18 compared to 1.22 from the five years of the AMAX series. As such the Qmed value from the extracted POT series can be considered the most appropriate estimate of Qmed on this reach of the Liffey. The FSU derived estimates on the main channel have been adjusted upwards based on the adjustment factor at this point. The estimated Qmed values for the various HEPs within Model 2B are shown in Table 4.3.
.
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Table 4.3: Qmed Values for Model 2B
Preferred Estimation Node ID_CFRAMS AREA (km2) Q (m3/s) med Methodology
09_1239_6_RPS 730.00 94.98 FSU
09_1131_U 0.01 0.005 IH124
09_475_U 0.00 0.00 IH124
09_475_3_RPS 1.74 0.24 IH124
09_1237_4_RPS 6.43 0.94 IH124
09_1120_3_RPS 30.03 6.209 FSU
09_613_U 0.08 0.02 IH124
09_613_3_RPS 1.31 0.50 IH124
09002_RPS 34.58 7.418 Observed Qmed G.S. (A1)
09_242_3_RPS 34.66 7.469 FSU
09_1136_U 0.20 0.068 IH124
09_1136_1 0.54 0.10 IH124
09_221_3 11.38 1.43 IH124
09_1128_U 0.02 0.01 IH124
09_1128_1 0.21 0.046 IH124
09_1142_U 0.28 0.12 IH124
09_1142_1 0.73 0.23 IH124
09_1870_7_RPS 807.10 106.34 FSU
09_1870_8_RPS 807.58 106.40 FSU
09_1870_13_RPS 815.14 107.45 FSU
Note: Flow highlighted in yellow represent total flows at that point in the model rather than input flows
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4.4 MODEL 2C – LOWER LIFFEY
The Lower Liffey model stretches from Islandbridge to Dublin Bay and represents the portion of the Lower Liffey in Dublin City which is significantly affected by tidal influence (see Section 7.2 for further details on coastal hydrology). In relation to the fluvial flows the total contributing catchment of the model from Pollaphuca dam to Dublin Bay is 1020 km2 with a number of tributary catchments entering the Liffey within the model extents including the Camac, Poddle and Dodder Rivers. The Dodder is the largest of these rivers and represents a contributing catchment of 113 km2 flowing into the Liffey at Ringsend. The Camac is the second largest representing a contributing catchment of 58 km2 and flows into the Liffey via a large culvert at Heuston Station. The Poddle is the smallest of the three representing a catchment of 12 km2 and flows into the Liffey via a culvert at Wellington Quay. In addition to the main river inputs the run-off from Dublin City through the storm drainage network, combined storm overflows, other minor watercourses and direct from surface run-off is estimated to account for up to 21 km2 of urban catchment in total. The flow from this additional area will be added to the model as a lateral inflow along the length of the Liffey main channel in the model.
Figure 4.5: Model 2C (Lower Liffey)
As discussed in Section 4.3 an AMAX series has been derived by combining flow values observed at Leixlip through the ESB dam structures and at the bottom of the Rye Water from the Leixlip gauging station (09001 – OPW) to create an observed Qmed value at the confluence point of the Rye Water and the Liffey. Despite only six years of combined data available (2006 – 2011) the combined Qmed value is
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derived from two gauging stations which can be considered to have confidence in their ratings at Qmed. 3 2 This combined observed Qmed value of 78.03 m /s (combined catchment area of 719 km ) is considered the most appropriate estimate of Qmed on this reach of the Liffey and as such the FSU derived estimates on the main channel have been adjusted slightly upwards based on the adjustment factor at this point. Estimates of the index flow in the Poddle and the Camac have been derived using the FSU derived estimates of Qmed based on catchment descriptors and adjusted based on the pivotal sites Killeen Road (09035 - EPA) and Waldrons Bridge (09010 – EPA). Inputs from the Poddle are derived solely from the outputs from model 2E. An estimate of the index flow from the urban area has been derived using the FSU catchment descriptor equation with the URBEXT catchment descriptor estimated from the Corine 2006 database. The estimated Qmed values for the various HEPs within Model 2C are shown in Table 4.4.
Table 4.4: Qmed Values for Model 2C
2 3 Preferred Estimation Node ID_CFRAMS AREA (km ) Qmed (m /s) Methodology
09_1870_13_RPS 815.145 107.45 FSU
09_1870_14_RPS 816.377 107.60 FSU
09_1872_9_RPS 57.907 19.53 FSU
Integrated Catchment 09_1874_17_RPS 12.172 1.64 Model Output (50% AEP Flow at outfall to Liffey)
09_587_11 112.821 52.15 FSU
Lateral Inflow from 21.03 4.89 FSU City Urban Area
09_631_D 1020.307 132.61 FSU
Note: Flow highlighted in yellow represent total flows at that point in the model rather than input flows
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4.5 MODEL 2D – CAMAC
Model 2D represents the Camac system, a significant tributary of the River Liffey which emanates in the foothills of the Wicklow Mountains to the south of Dublin City. The catchment area is 58 km2 and is highly urbanised in the lower reaches (50% total of the total catchment). The catchment is also characterised by many sub-catchments or branches many of which represent urban drainage networks. The Camac catchment is shown in Figure 4.6 below.
Figure 4.6: Model 2D HEPs and Catchment Boundaries
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The catchment has two gauging stations located within close proximity to one another in the middle reaches of the main river channel. The Clondalkin gauging station (09005 – EPA) was active from
1976 to 1984 and the rating curve indicates that flows recorded at Qmed are based on a large extrapolation of the rating curve, which appears only suitable for low flows. As the gauging station is obsolete there is no opportunity for reviewing the rating through hydraulic modelling. This gauging station also represents a catchment which has undergone a fair degree of urbanisation since the period of record (particularly in the Clondalkin and Fortunestown areas) and as such there is further uncertainty in the applicability of the gauging station flow record to represent the hydrological conditions of the current catchment. In light of these factors and as the Killeen Road gauging station represents the same catchment yet has a much higher quality record, the Clondalkin gauging station has not been considered for the purposes of index flood flow (Qmed) estimation in this catchment. The Clondalkin gauging station may be useful for the calibration and validation of the hydraulic model as it may provide some estimate of flows for events that took place between 1976 – 1984 although it is not thought that the staff gauge is still in place and therefore direct water level – flow calibration will not be possible. The Killeen Road gauging station (09035 – EPA) has been active since 1996. The rating curve is extrapolated at Qmed and the gauging station is subject to a rating review as part of the study.
The rating review found that there is significant uncertainty in the existing rating at Qmed. The rating 3 review resulted in a Qmed value of 10.5m /s which is significantly lower than the value based on the existing rating of 13.5 m3/s. The FSU derived value was based on a different rating and considered values up to 2004 only. The FSU based value of 11.7m3/s is closer to the rating review based value but there are no spot gaugings at the gauging station for flows as high as this which could be used to calibrate / validate the modelled rating at Qmed.
A catchment rainfall run-off model was developed to represent the catchment at the Killeen Road gauging station in order to achieve calibration at the gauging station and create an extended simulated AMAX series at the gauging station. The rainfall run-off (NAM) model was calibrated using high resolution rainfall data from the adjusted sums from the rainfall radar at Dublin Airport (as reported in Appendix B of this report) and the nearby hourly rainfall gauging station at Casement aerodrome and good calibration was achieved. An extended AMAX series was simulated from 1964 – 2009 (2009 being the last full hydrological year that adjusted radar data was available for) which has a median flood flow value of 12.2 m3/s. The IH124 and FSU catchment descriptor based estimates at the Killeen Road gauging station are 18.72 m3/s and 9.80 m3/s respectively. The rating review of the Killeen Road 3 gauging station resulted in a modelled rating curve producing a Qmed of 10.50 m /s suggesting that the
EPA rating curve is overestimating at Qmed. Considering that the FSU (WP 2.1) observed figure to 2004 (11.7m3/s) and the NAM simulated figure are in good agreement it would seem prudent to use the value derived from the NAM model rather than the lower rating reviewed value or the higher EPA derived value.
Qmed estimates at the various HEPs were derived based on catchment descriptor based estimates and adjusted based on the gauge at Killeen Road for HEPs located on the main channel of the Camac. Following initial hydraulic model calibration runs it was found that the accumulated median flows at the Killeen Road gauging station were exceeding the observed median flow and the modelled
IBE0600Rp00016 40 Rev F03 Eastern CFRAM Study HA09 Hydrology Report – FINAL flood extents, particularly in the smaller upper tributaries for the 1% and 2% design events exceeded those recorded for the October 2011 flood event. Considering that most of these smaller inputs were derived based on the IH124 method and that the IH124 derived value at the gauge is approximately 50% greater than the observed values it was decided to adjust all of the IH124 derived flows on the upper reaches downwards in line with the ratio of the Qmed at the gauging station to the Qmed derived through the IH124 method at the gauging station (i.e. 09035 used as pivotal site at all HEPs within the model). However estimates of Qmed based on the FSU methodologies were preferred for the upstream reaches of the Camac as there is a significant lake / reservoir at Glenaraneen. It was considered that the effect of this on flood flows would be much more accurately captured using the FSU estimation methods through the FARL (Flood Attenuation due to Reservoirs and Lakes) physical catchment descriptor applied within the FSU equation but which is not considered under the IH124 method.
The approaches discussed resulted in flows which were in agreement with the gauging station and the observed flood extents in the upper reaches. The estimated Qmed values for the various HEPs within Model 2D are shown in Table 4.5.
Table 4.5: Qmed Values for Model 2D
2 3 Preferred Estimation Node ID_CFRAMS AREA (km ) Qmed (m /s) Methodology
09_481_U 3.870 0.85 FSU
09_472_4_RPS 8.507 1.33 FSU
09_472_8_RPS 10.104 1.95 FSU
09_435_U 0.037 0.03 IH124
09_435_1_RPS 1.218 0.62 IH124
09_37_U 0.265 0.18 IH124
09_37_1 0.408 0.22 IH124
09_36_2 1.812 0.76 IH124
UN_Inter_Camac_1 0.099 0.03 IH124
UN_Trib_Camac_10 0.144 0.04 IH124
UN_Trib_Camac_20 0.233 0.07 IH124
09_464_1 1.014 0.68 IH124
09_396_U 0.250 0.14 IH124
09_396_1 0.857 0.25 IH124
09_586_3 4.066 1.44 IH124
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2 3 Preferred Estimation Node ID_CFRAMS AREA (km ) Qmed (m /s) Methodology
09_1308_U 0.020 0.01 IH124
09_606_1 0.052 0.02 IH124
09_39_U 0.000 0.00 IH124
09_39_1 1.986 1.02 IH124
09_360_4_RPS 3.241 1.51 IH124
09_499_1_RPS 24.070 7.85 IH124
09_499_3_RPS 25.244 8.00 IH124
09_UN_T03_U 0.020 0.01 IH124
09_UN_T02_U 0.000 0.00 IH124
09_UN_T03_1 0.197 0.06 IH124
09_UN_T02_1 0.265 0.08 IH124
09_448_U 0.123 0.04 IH124
09_448_1 0.371 0.11 IH124
09005_RPS 36.758 10.89 FSU
09035_RPS NAM 38.644 12.20 G.S. (B) (Simulated Qmed)
09_1252_U 0.806 0.15 IH124
UN_Trib_Camac_U 1.475 0.69 IH124
09_1243_U 0.016 0.01 IH124
UN_Trib_Camac_1 2.575 1.13 IH124
09_1243_1 2.742 1.76 IH124
09_1242_2_RPS 7.805 3.03 IH124
09_832_U 1.625 0.75 IH124
09_832_1 2.654 1.16 IH124
09_1872_9_RPS 57.907 19.54 FSU Note: Flow highlighted in yellow represent total flows at that point in the model rather than input flows
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4.6 MODEL 2E – PODDLE
The model of the Poddle watercourse stretches from its source at the Institute of Technology at Tallaght to the outfall to the River Liffey at Wellington Quay. As discussed in Section 2.5 the Poddle is heavily urbanised with much of the lower reaches culverted / channelised and following initial attempts to calibrate the hydraulic model it became clear that the flows derived from catchment descriptor based methods were not achievable within the channel and immediate floodplain. The Poddle catchment and HEPs are shown in Figure 4.7.
Figure 4.7: Model 2E HEPs and Catchment Boundaries
In order to accurately capture the performance of the Poddle system during a flood event it is necessary to also consider the drainage network and topography which deliver run-off to the main channel of the watercourse through an integrated modelling approach. The modelled approach requires that rainfall events are applied directly to the model. The rainfall events have been derived from FSU Work Package 1.2 ‘Estimation of Point Rainfall Frequencies’ and the accompanying Depth, Duration, Frequency (DDF) 2km x 2km gridded rainfall sum data for a range of return periods (or AEPs) and storm durations. For each AEP design event a range of storm durations are converted to rainfall hydrograph profiles using storm profiles developed through the FSR and subsequent Flood Studies Supplementary Report No. 16. The recommended profiles are the 50% summer, a more peaked shape representing the 50th percentile average of an analysed set of summer storm profiles, and the 75% winter, a less peaked shape representing the 75th percentile (in terms of peaked shape) of an analysed set of recorded winter storm profiles. Following initial calibration attempts whereby IBE0600Rp00016 43 Rev F03 Eastern CFRAM Study HA09 Hydrology Report – FINAL design rainfall sums were aggregated into both profiles the FSR 50% summer profile was found to produce the most onerous flood flow conditions within the Poddle model and as such was used as the design storm profile to all design rainfall AEP events. The design rainfall sums which are to be applied within the integrated model are shown in Table 4.6.
Table 4.6: FSU DDF Derived Design Rainfall Sums
Annual Exceedance Probability (AEP) % Storm Duration 50% 20% 10% 5% 3.30% 2% 1% 0.67% 0.50% 0.10% Rainfall Sums in mm 15 mins 7.1 10.8 13.7 17.2 19.5 22.8 28.1 31.8 34.7 51.0 30 mins 9.2 13.8 17.4 21.6 24.4 28.4 34.8 39.2 42.6 64.0 1 hour 11.9 17.6 22.0 27.1 30.5 35.3 43.0 48.2 52.3 77.0 2 hour 15.5 22.5 27.9 34.1 38.2 44.0 53.2 59.3 64.1 91.0 3 hour 18.0 25.9 32.1 39.0 43.6 50.1 60.2 67.0 72.3 103.0 4 hour 20.1 28.7 35.4 42.9 47.9 54.8 65.7 73.1 78.7 112.0 6 hour 23.4 33.2 40.7 49.1 54.6 62.3 74.4 82.5 88.7 125.0 9 hour 27.2 38.3 46.7 56.1 62.3 70.9 84.3 93.2 100.1 139.0 12 hour 30.3 42.4 51.6 61.7 68.4 77.6 92.0 101.6 108.9 150.0 18 hour 35.3 48.9 59.2 70.6 78.0 88.3 104.2 114.7 122.8 168.0 1 day 38.8 53.3 64.2 76.2 83.9 94.6 111.2 122.1 130.5 179.0 2 days 46.7 62.8 74.6 87.4 95.6 106.9 124.2 135.5 144.1 194.0 3 days 53.1 70.4 83.0 96.6 105.3 117.1 135.1 146.8 155.7 207.0 4 days 58.7 77.1 90.4 104.6 113.7 126.0 144.7 156.7 165.9 218.0 6 days 68.4 88.6 103.1 118.5 128.2 141.4 161.3 174.0 183.7 249.0 8 days 76.9 98.7 114.1 130.6 140.9 154.8 175.7 189.1 199.2 257.0 10 days 84.6 107.8 124.2 141.5 152.3 166.9 188.7 202.7 213.2 272.0 12 days 91.8 116.2 133.4 151.5 162.8 178.1 200.7 215.2 226.0 288.0 16 days 105.0 131.7 150.4 169.9 182.1 198.4 222.5 237.9 249.4 314.0 20 days 117.1 145.8 165.8 186.6 199.5 216.7 242.2 258.4 270.5 349.0 25 days 131.2 162.2 183.6 205.8 219.5 237.9 264.9 282.0 294.7 368.0
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4.7 MODEL 3A – LEIXLIP
The Leixlip model encompasses the middle and lower reaches of the Liffey catchment separated by the ESB dam at Leixlip. The total contributing catchment area of the model to the downstream extents is 730 km2 (excluding the upper catchment, upstream of Golden Falls dam). Included within this area is the Rye Water (or River Rye) catchment which joins the River Liffey at Leixlip and accounts for 209 km2. The Leixlip AFA is affected by a number of small tributaries to the Rye Water and Liffey including the Sion, Moor of Meath and Ballymadeer watercourses. The modelled extents and HEPs are shown in Figure 4.8 below.
Figure 4.8: Model 3A Catchment Boundaries and HEPs
There are two hydrometric gauging stations within the modelled reaches, one on the Rye Water approximately 1 km upstream of its confluence with the River Liffey and also one on the River Liffey at the Leixlip power generation plant. The Rye Water station is named Leixlip (09001 – OPW) and was given an A1 classification under FSU and a long record period with data received covering the complete hydrological years of 1956 – 2010 (A1 applies to 1980 onwards). Therefore the Qmed flow of 33.7 m3/s derived from the AMAX series at the Leixlip gauging station representing the Rye Water catchment can be considered to have a high degree of confidence. This was confirmed through the
IBE0600Rp00016 45 Rev F03 Eastern CFRAM Study HA09 Hydrology Report – FINAL rating review at this station which found that, although there have been significant changes to the channel resulting in a change to the rating, the long term Qmed does not carry a significant degree of uncertainty.
As discussed in 0 the gauging station located at the Leixlip hydro-electric power generation station on the Liffey main channel is owned and operated by ESB (09022). As previously discussed the Qmed derived from the AMAX series of 61.64 m3/s (catchment area of 510km2) can be considered to have a low degree of statistical confidence. There is a further historic gauging station located on the main channel of the Liffey just upstream of the model extents called Celbridge (09006 – ESB) representing a catchment area of 479 km2 which has continuous flow data available for the periods of 1967 – 1986 and from 1995 - 1997. This gauging station was not given a classification under FSU but data provided by ESB indicates that there is confidence in the rating at the Qmed value from the extracted AMAX 3 series of 56.5m /s. Although there is some uncertainty in the Qmed value (discussed in greater detail in 0) this figure is in good agreement with observed value at the dam at Leixlip from the later, shorter period.
As discussed in Section 4.3 an AMAX series has been derived by combining flow values observed at Leixlip through the ESB dam structures and at the bottom of the Rye Water from the Leixlip gauging station (09001 – OPW) to create an observed Qmed value at the confluence point of the Rye Water and the Liffey. Five complete hydrological years of combined data are available (2005 – 2009) and as such an analysis of the data using the Peaks Over Threshold (POT) method as detailed in the Flood Estimation Handbook, Volume 3 was preferred. Using this method the 24 flood peak values over a 3 3 threshold value of 57 m /s were considered and an equivalent Qmed was extracted of 94.1 m /s. This figure is significantly higher than the value extracted from the AMAX series but can be considered to have a higher statistical confidence with a factorial standard error (FSE) of 1.18 compared to 1.22 from the five years of the AMAX series. As such the Qmed value from the extracted POT series can be considered the most appropriate estimate of Qmed on this reach of the Liffey. The FSU derived estimates on the main channel have been adjusted upwards based on the adjustment factor at this point.
Despite only five years of combined data available the combined Qmed value is derived from two gauging stations which can be considered to have confidence in their ratings at Qmed. This combined 3 2 observed Qmed value of 94.1 m /s (combined catchment area of 719 km ) is considered the most appropriate estimate of Qmed on this reach of the Liffey and as such the FSU derived estimates on the main channel have been adjusted upwards based on the adjustment factor at this point.
Flows on the main channel of the Liffey upstream of the dam at Leixlip have been adjusted based on the observed Qmed at Celbridge. Minor tributaries entering this length of the Liffey have not been adjusted as they are not considered hydrologically similar to any of the nearby gauging stations and a review of hydrologically similar FSU pivotal sites did not support a clear adjustment either way.
Downstream of Leixlip main channel flows have been adjusted based on the combined observed Qmed value downstream of the confluence point at Leixlip.
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The Leixlip (09001) gauging station has been used for adjustment of the Qmed flows derived from catchment descriptor based methods on all of the Rye Water portions of the model. Although some of the tributaries are very small and as such are not hydrologically similar to any of the pivotal sites, all of the gauging stations on the Rye Water (09001, 09048 – see 4.10, 09049 – see 4.9) suggest the FSU, and to a lesser extent IH124 catchment descriptor estimates are under predicting Qmed estimates on the Rye Water system. The estimated Qmed values for the various HEPs are shown in Table 4.7.
Table 4.7: Qmed Values for Model 3A
2 3 Preferred Estimation Node ID_CFRAMS AREA (km ) Qmed (m /s) Methodology
09_284_2_RPS 502.06 62.82 FSU
09_994_U 0.00 0.00 IH124
09_994_1 1.52 0.24 IH124
09_1260_4_RPS 194.96 33.39 FSU
09_1137_1 3.62 0.59 IH124
09_1137_5 4.86 0.76 IH124
09_1246_U 0.02 0.00 IH124
09_1246_1 0.56 0.11 IH124
09001_RPS 208.53 33.7 Observed Qmed G.S. (A1)
09_246_4_RPS 209.13 34.52 FSU
09022_RPS Observed Qmed (D.S. of Rye Water 718.68 94.01 (POT analysis of combined confluence) 09001 & 09022 records)
09_1050_U 0.00 0.00 FSU
09_346_3 2.37 0.40 IH124
09_1050_1 0.87 0.16 IH124
09_584_4_RPS 5.34 1.00 FSU
09_1239_6_RPS 730.00 94.98 FSU Note: Flow highlighted in yellow represent total flows at that point in the model rather than input flows
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4.8 MODEL 3B – HAZELHATCH / CELBRIDGE
The Hazelhatch / Celbridge model represents the watercourses, including a portion of the middle Liffey, affecting the town of Celbridge and the Hazelhatch area to the east of the town. A number of minor watercourses affect the AFAs including the Crippaun, Coolfitch, Hazelhatch, Kilwoghan and Shinkeen.
No recorded flow data records were provided for the upstream gauging station called Straffan U/S (09034 – ESB) on the main channel of the Liffey. Continuous flow data is however available further downstream at the Celbridge gauging station (09006 – ESB) for the periods of 1967 – 1986 and from 1995 - 1997. This gauging station was not given a classification under FSU but data provided by ESB indicates that there is confidence in the rating at the Qmed value from the extracted AMAX series of 56.5m3/s. Visual inspection of the records indicates that there may be some gaps in the data although these do not seem to be consistent with any known flood events, although the long gap in the gauge record from 1986 to 1995 does coincide with the occurrence of Hurricane Charlie in late August 1986. This suggests the gauge may have malfunctioned during this particular flood event but the 19 years of data prior to this are considered complete. The gauged Qmed value is similar in magnitude to catchment descriptor based estimates for the middle catchment; although it must be pointed out that the gauged Qmed is derived from a record which allows for the releases from the upper catchment through the dams at Golden Falls and Pollaphuca. Nevertheless it is prudent that the gauged Qmed figure of 56.5m3/s is used as the basis for design flows at the gauging station. The additional flows as a result of release from the dam must be considered through the output from the upstream models and additional allowance made following modelling.
No catchment rainfall run-off models have been developed for the Hazelhatch / Celbridge model as the available gauge data on the main channel of the Liffey includes the intermittent releases from the dams upstream and as such calibration of the models could not be achieved. Tributaries which enter the model laterally represent small catchments which are ungauged and as such calibration of catchment models could not be achieved.
All index flows derived for the main channel HEPs have been adjusted downwards slightly based on the relationship between the FSU catchment descriptor based estimate at the Celbridge gauging station (09006 – ESB) and the observed value. Flow estimates for the Morrell River entering the model at 09_1627_6_RPS have been adjusted upwards based on the simulated Qmed value at the Morrell Bridge gauging station just upstream (09024 – EPA). Estimates of flow on the minor tributaries were initially estimated using the IH124 catchment descriptor based method and were not adjusted. Following initial attempts at model calibration however this was revisited as observed flooding on the Crippaun, Shinkeen and Hazelhatch watercourses could not be replicated within the model using the flows based on the IH124 method. For each of these watercourses a review of the nearest hydrologically similar pivotal sites was undertaken and an adjustment factor applied to the FSU catchment descriptor based estimates of flood flow. These reviews resulted in upwards adjustments to the estimates for all three watercourses ranging between 1.12 and 1.27 based on the most
IBE0600Rp00016 48 Rev F03 Eastern CFRAM Study HA09 Hydrology Report – FINAL hydrologically similar pivotal sites. Further to this it was also established that there are two significant additional sources of flood flow to the Shinkeen Stream:
1. The Baldonnel hydraulic model established that there is a flow diversion out of the Griffeen catchment and into the Shinkeen catchment. This flow was extracted from the Baldonnel model and added to the estimated design flow entered into the model at the HEP 09_501_U.
2. Discussions with Waterways Ireland ascertained that there is a significant overflow from the Grand Canal at Hazelhatch. The flow out of the canal was estimated based on the hydraulic capacity of the overflow structure. The location of this overflow is approximately 400m downstream of HEP 09_501_U.
The model catchment and HEPs are shown in Figure 4.9 with the estimated index flood flow values
(Qmed) shown in Table 4.8.
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Figure 4.9: Model 3B Catchment Boundaries and HEPs
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Table 4.8: Qmed Values for Model 3B
2 3 Preferred Estimation Node ID_CFRAMS AREA (km ) Qmed (m /s) Methodology
09034_RPS 337.31 43.17 FSU
09_1627_6_RPS 98.49 20.52 FSU
09_426_5_RPS 12.60 1.42 IH124
09_1579_U 2.00 0.27 IH124
09_727_U 0.06 0.02 IH124
09_727_2_RPS 0.37 0.07 IH124
09_1069_2_RPS 6.52 0.78 IH124
09_294_1_RPS 472.81 55.73 FSU
09_1126_U 0.26 0.04 IH124
09_1126_1 1.09 0.19 IH124
09_1668_2_RPS 474.37 55.90 FSU
09_292_1_RPS 475.13 55.94 FSU
09_1245_U 0.76 0.14 FSU
09_1245_6_RPS 2.98 1.04 FSU
09006_RPS
G.S. (FSU 478.58 56.49 Observed Qmed Unclassified)
UN_Trib_Liffey_U 2.12 0.36 FSU
UN_Liffey_Inter 4.04 0.65 FSU
UN_Trib_Liffey_1 5.21 1.04 FSU
09_299_3_RPS 484.93 56.55 FSU
09_467_U 1.33 0.21 IH124
09_467_8 3.43 0.54 IH124
09_300_1_RPS 488.26 56.86 FSU
09_501_U 1.39 0.22 FSU
Overflow from n/a 1.28 Extracted from Model 2A Griffeen catchment
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2 3 Preferred Estimation Node ID_CFRAMS AREA (km ) Qmed (m /s) Methodology
Estimated from hydraulic Canal Overflow n/a 2.32 capacity of canal overflow structure.
09_501_Trib 0.00 0.02 FSU
09_501_Inter 10.31 1.44 FSU
09_501_Inter_1 11.49 1.59 FSU
09_501_7_RPS 12.76 1.78 FSU
09_284_2_RPS 502.06 62.82 FSU Note: Flow highlighted in yellow represent total flows at that point in the model rather than input flows
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4.9 MODEL 4 – MAYNOOTH
The Maynooth model represents the portion of the Rye Water, a large tributary of the Liffey, where it passes through the Maynooth AFA. The model also represents the main tributary of the Rye Water, the Lyreen River and also a number of tributaries that flow into the Lyreen through Maynooth. The total catchment represented by the model is 195 km2 with 88 km2 of the catchment area made up by the Lyreen which joins the Rye Water just north of the town. The contributing catchments and HEPs are shown in Figure 4.10.
Figure 4.10: Model 4 Catchment Boundaries and HEPs
Both the Rye Water and the Lyreen are gauged within the model extents. The data available for flood flow estimation at both gauges is of a similar quality and duration with both gauges having been installed in 2001 and operated by the EPA since. The Annes Bridge gauging station (09048 – EPA) is located at the upstream extents of the model on the Rye Water. The gauging station stage discharge rating relationship is heavily extrapolated at the FSU estimated Qmed value based on catchment descriptors of 8.2 m3/s. Due to the high uncertainty in the rating at flood flows and the short record length (10 complete years AMAX data with some gaps) there is low confidence in the Qmed value of 22.9 m3/s derived from the gauging station record. A catchment run-off (NAM) model has been developed of the gauged catchment and calibrated against the low to mid range continuous flow trace at the Annes Bridge gauging station using gauge adjusted radar based hourly rainfall sums for the catchment from 2001 to 2010. Using the adjusted radar based rainfall sums and observed rainfall
IBE0600Rp00016 53 Rev F03 Eastern CFRAM Study HA09 Hydrology Report – FINAL sums from surrounding rain gauges a continuous flow trace was simulated for the period 1950 to
2010. An AMAX series was extracted from the continuous flow trace and the simulated Qmed calculated to be 17.0 m3/s.
The Lyreen is gauged at its downstream reach, approximately 0.5km upstream of its confluence with the Rye Water at Maynooth (09049 – EPA). Similar to the Annes Bridge gauging station the stage discharge rating relationship is heavily extrapolated at the FSU estimated Qmed value based on catchment descriptors of 10.0 m3/s. Due to the high uncertainty in the rating at flood flows and the short record length (10 complete years AMAX data with some gaps) there is low confidence in the 3 Qmed value of 25.8 m /s derived from the gauging station record. A catchment run-off (NAM) model has been developed of the gauged catchment and calibrated against the low to mid range continuous flow trace at the Maynooth gauging station using gauge adjusted radar based hourly rainfall sums for the catchment from 2001 to 2010. Using the adjusted radar based rainfall sums and observed rainfall sums from surrounding rain gauges a continuous flow trace was simulated for the period 1964 to
2010. An AMAX series was extracted from the continuous flow trace and the simulated Qmed calculated to be 12.4 m3/s.
Although both simulated Qmed values are affected by any uncertainty in the observed flow record at the gauging station (through calibration of the NAM model) they are considered improved estimates of
Qmed at the gauging stations due to the longer record length, the quality of the rainfall and catchment data and the availability of the flow records for calibration. There still remains however a striking difference between the simulated values and those derived from the catchment descriptor based FSU approach, ranging between 20% and 110%, and it still remains a possibility that the poor record (and potentially grossly overestimating rating curves) has skewed the simulation despite the best efforts to focus the calibration on low to mid range flows. It is worth noting though that at the gauging station on the Rye Water downstream at Leixlip (09001 – OPW) the difference between the observed Qmed and the Qmed derived from catchment descriptors is approximately 35%. Considering the quality of the data at this station it can be considered that there is definitely an underestimation using the FSU catchment descriptor based equation when considering the Rye Water catchment and it is possible that the error is most pronounced upstream of the Annes Bridge gauging station (09048). No gauging station rating reviews are proposed for these stations and as such it is considered prudent that both of these simulated Qmed values are reviewed at hydraulic model calibration stage to ensure the mapped flood extents produced by these flows are validated against historic evidence. The estimated Qmed values for the various HEPs within Model 4 are shown in Table 4.9 with FSU estimates adjusted based on the most appropriate of the NAM simulated models to the HEP.
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Table 4.9: Qmed Values for Model 4
2 3 Preferred Estimation Node ID_CFRAMS AREA (km ) Qmed (m /s) Methodology
09048_RPS 59.55 16.96 NAM
09_468_1 9.23 2.35 IH124
09_468_3 9.57 2.51 IH124
09_1060_1 17.40 4.22 FSU
09_1060_3 18.00 4.31 FSU
09_1450_U 0.00 0.00 IH124
09_1452_2_RPS 49.07 7.77 FSU
09_1464_1_RPS 13.64 2.49 IH124
09_1464_2_RPS 65.23 10.49 FSU
09_1464_5_RPS 66.95 10.92 FSU
09_1839_7 11.29 1.49 IH124
09_1839_12_RPS 17.91 2.83 FSU
09_1444_U 0.00 0.00 IH124
09_1444_4 1.60 0.58 IH124
09049_RPS 87.50 12.40 NAM
09_611_3_RPS 87.63 12.29 FSU
09_600_2 12.02 2.38 IH124
09_1260_4_RPS 194.96 29.78 FSU Note: Flow highlighted in yellow represent total flows at that point in the model rather than input flows
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4.10 MODEL 5 – KILCOCK
The Kilcock model encompasses the upper reaches of the Rye Water including the tributaries which affect the Kilcock AFA including the smaller tributary watercourses the Culcor, Balfeaghan and Dolanstown. The total contributing catchment area is approximately 60 km2. The model is gauged at the downstream boundary at Annes Bridge (09048 – EPA) as discussed in the previous section.
Figure 4.11: Model 5 Catchment Boundaries and HEPs
A catchment run-off (NAM) model has been developed of the gauged catchment and calibrated against the low to mid range continuous flow trace at the Annes Bridge gauging station using gauge adjusted radar based hourly rainfall sums for the catchment from 2001 to 2010. Using the adjusted radar based rainfall sums and observed rainfall sums from surrounding rain gauges a continuous flow trace was simulated for the period 1950 to 2010. An AMAX series was extracted from the continuous 3 flow trace and the simulated Qmed observed to be 17.0 m /s. Although the simulated Qmed value may be affected by any uncertainty in the observed flow record at the gauging station (through calibration of the NAM model) they are considered improved estimates of Qmed at the gauging stations due to the longer record length, the quality of the rainfall and catchment data and the availability of the flow records for calibration. The estimated Qmed values for the various HEPs within Model 5 are shown in Table 4.10.
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Table 4.10: Qmed Values for Model 5
2 3 Preferred Estimation Node ID_CFRAMS AREA (km ) Qmed (m /s) Methodology
09_181_1_RPS 19.59 6.19 FSU
09_1251_1_RPS 0.29 0.16 IH124
09_1251_4 1.76 0.82 IH124
09_566_U 5.55 2.47 IH124
09_566_1 5.98 2.51 IH124
09_1535_1_RPS 12.16 4.87 IH124
09_1535_7_RPS 14.87 5.14 IH124
09048_RPS 59.55 16.96 NAM Note: Flow highlighted in yellow represent total flows at that point in the model rather than input flows
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4.11 MODEL 6A – CLANE
The Clane model represents the portion of the middle Liffey affecting the Clane AFA and a number of tributaries including the Gollymochy River and the Cott watercourse. The contributing catchment of the middle Liffey at the downstream boundary of the model is 337 km2 (excludes the upper catchment the effect of which is considered in Chapter 6). The model catchment and HEPs are shown in Figure 4.12.
Figure 4.12: Model 6A Catchment Boundaries and HEPs
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There are no gauging stations located directly on the modelled reaches of the Clane model with the nearest gauging station location approximately 10km downstream at Celbridge (09006 – ESB). As discussed in Section 0 there are some issues with the quality of data at this gauging station however ESB provided rating and spot gauge information indicates that there is confidence in the rating up to and above Qmed. In the absence of any other gauging stations on the main channel of the middle reaches of the Liffey it is considered prudent that this station is considered in the adjustment of the catchment descriptor based estimates of the index flood flow (Qmed).
No catchment rainfall run-off models have been developed for the Clane model as the available gauge data on the main channel of the Liffey includes the intermittent releases from the dams upstream and as such calibration of the models could not be achieved. Tributaries which enter the model laterally are both small and ungauged and as such calibration of catchment models could not be achieved.
The model catchment and HEPs are shown in Figure 4.12 with the estimated index flood flow values
(Qmed) shown in Table 4.11.
Table 4.11: Qmed Values for Model 6A
2 3 Preferred Estimation Node ID_CFRAMS AREA (km ) Qmed (m /s) Methodology
09_1519_13_RPS 169.65 20.28 FSU
09_1519_14_RPS 170.47 20.37 FSU
09_1519_16_RPS 179.54 21.55 FSU
09_1650_9_RPS 3.57 0.61 IH124
09_1211_2_RPS 18.94 2.16 FSU
09_529_2_RPS 4.02 0.71. IH124
09_1210_2_RPS 1.30 0.20 IH124
09_1853_7_RPS 5.69 0.75 IH124
09_1649_1_RPS 2.47 0.36 IH124
09_1649_9_RPS 5.94 0.92 IH124
09_429_1 5.39 0.88 IH124
09_200_2_RPS 15.40 2.07 IH124
09_782_3_RPS 5.43 0.77 IH124
09_1601_3_RPS 336.88 43.17 FSU Note: Flow highlighted in yellow represent total flows at that point in the model rather than input flows
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4.12 MODEL 6B – NAAS
The Naas model represents a network of tributaries affecting the Naas AFA which flow into the middle Liffey including the Naas Stream, Monread, Bluebell, Broadfield, Oldtown, and Ploopluck watercourses amongst others. The catchments are complex and are connected to and traverse the Grand Canal (Naas and Corbally Branch) at various locations. In discharging to the Liffey all of the watercourse must also pass under the M7 and as such these watercourses serve as outfall points for the drainage system of the motorway although these outfall points are downstream of the AFA extents. Many of the catchments were either incorrectly delineated or not delineated at all under FSU and due to the flat topography, limits of the survey data and interactions with the canal a site walkover survey and discussions with the NRA, EPA, Kildare County Council and Waterways Ireland were required to determine the nature of the catchments / source of hydrological inputs.
The Naas stream (25 km2) is largest of the model catchments and emanates in the foothills of the Wicklow Mountains to the south of the town. The Broadfield watercourse is the main contributing sub- catchment which flows from the south through the lakes adjacent to the Ballymore Road in the south of the town before joining the Naas stream near the centre of the town. The Naas Stream then flows to the north past the Octagon Pond system which it feeds via a system of sluice gates and weirs before discharging to the canal (Naas Corbally Branch) to the west of Oldtown Demesne. A number of watercourses / ditches adjacent to the canal are fed from overflows which transfer flow between canal sections, bypassing the lock gates. The final section of the watercourse located between the canal and the Liffey does not seem to be fed from the canal and is thought to be a drainage link under the canal for the partly urbanised catchment to the east. The Naas Stream catchment is relatively flat (S1085 = 5m/km) and is urbanised in its lower reaches. The upper reaches are almost entirely pasture. A second outfall point from the lakes adjacent to the Ballymore Road also serves as the source of the watercourse known locally as the Monread Stream. This watercourse flows in a north-easterly direction through the town in a culvert until it eventually discharges into an open watercourse adjacent to Monread Avenue. After passing under the M7 the watercourse turns in a north-westerly direction and passes under the railway line before discharging to the Grand Canal at Sallins. This watercourse is essentially an overspill from the lakes and as such the Broadfield catchment but it also acts as the spine of the main drainage for the eastern, urban portions of Naas (1.9 km2) as well as farmland within the Monread area to the east of the town (2.7 km2).
The Ploopluck and Oldtown watercourses drain the area (4km2) of flat pastures to the north of the town centre bounded by the canal and Caragh Road to the south and east. The area is drained by a network of field drains with minimal gradient. The area is in parts recently urbanised.
The Bluebell Watercourse catchment can be considered to be split with the upper part of the catchment emanating from the pastures to the south west of the town. The watercourse flows in a north easterly direction where it turns right as part of a system to feed the canal. This system flows into the canal quay via a culverted section in the centre of Naas. Although there is a ditch linking the upper portion of the Bluebell watercourse through the Jigginstown Commercial Centre to the rest of the
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Bluebell stream it is considered that the flow under normal conditions all goes to feed the canal, although there may be an overflow route at times of flood via the ditch. The Bluebell watercourse from the Newbridge Road onwards is fed from two sources:
1. Drainage network of the Jigginstown area in the west of Naas
2. A watercourse emanating from the canal embankment which acts as a canal overflow and drains the rural area of Jigginstown to the south of the Newbridge Road.
The modelled watercourses are shown in Figure 4.13.
Figure 4.13: Model 6B Catchment Boundaries and HEPs
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There is one gauging station located on the modelled reaches located on the Ploopluck / Oldtown watercourse called Osberstown House (09042 – EPA). Only two years of continuous flow records are available at this gauging station from 2009 – 2011 and such the record is not suitable for the derivation of Qmed. A catchment rainfall run-off model was developed for this gauging station using the delineated catchment based on the surveyed watercourse information, the EPA blue line network, orthophotography and the national digital height model (NDHM). Attempts were made to calibrate the model to the limited gauge record at Osbesrtown House in order to simulate a longer flow trace but acceptable calibration could not be achieved with flow peaks much lower within the catchment rainfall run-off model than were recorded at the gauging station.
In the absence of a suitably long gauged record of high certainty or a rainfall run-off model estimates must be based on catchment descriptor based methods. For the smaller catchments (less than 25km2) estimates of Qmed have been based on the IH124 cathcment descriptor equation with many of the catchment descriptors from the undelineated and incorrectly delineated catchments having been derived from aerial photography, the Corine land use database, the national digital height model and nearby hydrologically similar FSU catchments. The total catchment of the Naas stream is just over 2 25km and as such an estimate of the total Qmed was derived using the FSU 7 variable equation (FSU WP 2.3). This estimate was found to be slightly lower than the IH124 derived estimate. A review of the nearest hydrologically similar and geographically closest pivotal sites was undertaken in order to review the performance of the FSU PCD equation for similar catchments. The Killeen Road and Griffeen gauging stations both within HA09 were found to be geographically close and the 2nd and 3rd most hydrologically similar nationally. Both pivotal sites suggest adjustment of the FSU PCD estimate upwards and as such a cumulative adjustment factor of 1.16 was applied to the total estimate of flow in the Naas catchment. Following adjustment the estimate was found to be a very close match to the IH124 derived estimate for the Naas Stream catchment and as such provides some confidence that the IH124 method is accurately estimating the Qmed in the smaller sub-catchments around Naas.
Table 4.12: Qmed Values for Model 6B
2 3 Preferred Estimation Node ID_CFRAMS AREA (km ) Qmed (m /s) Methodology
09_1533_U 0.02 0.005 IH124
09_322_U 0.01 0.004 IH124
09_322_1 0.24 0.06 IH124
09_356_U 11.96 1.57 IH124
09_321_1_RPS 18.63 2.41 IH124
09_454_Inter 18.88 2.48 IH124
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2 3 Preferred Estimation Node ID_CFRAMS AREA (km ) Qmed (m /s) Methodology
09_454_Trib 19.17 2.54 IH124
09_1490_1_RPS 25.32 3.50 FSU
09_1490_Inter 0.37 0.20 IH124
09_1490_DSL 1.09 0.39 IH124
09_1490_7_RPS 1.49 0.50 IH124
09_Monread_U 1.86 1.08 IH124
09_Monread_1 4.51 1.40 IH124
09_1534_U 0.00 0.005 IH124
09_353_U 1.16 0.22 IH124
09_529_1_RPS 2.31 0.44 IH124
09042_RPS 3.79 0.68 IH124
09_529_2_RPS 4.02 0.71 IH124
09_1650_U 0.27 0.05 IH124
09_1650_2 1.22 0.23 IH124
09_DSL_01 2.30 0.68 IH124
09_USL_01 0.36 0.16 IH124
09_USL_02 0.95 0.16 IH124 + Canal Overflow
09_1650_9_RPS 3.57 0.61 IH124
Note: Flow highlighted in yellow represent total flows at that point in the model rather than input flows
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4.13 MODEL 7 – TURNINGS / KILLEENMORE (MORELL)
The Turnings / Killeenmore model represents the Morell River system, a substantial tributary of the River Liffey with a total catchment area of nearly 100km2. The upper extents of the catchment represent the foothills of the Wicklow Mountains and a number of small tributary catchments including the Haynestown, Hartwell, Kill, and Slane Rivers (the Slane and Kill Rivers then combine to form the Painestown River). The Turnings and Killeenmore rural area defines the affected AFA although the upstream limits of the model also affect the Naas AFA to the west. The catchment and HEPs are shown in Figure 4.14.
Figure 4.14: Model 7 Catchment Boundaries and HEPs
The model is very well gauged with four gauging stations along the modelled extents that have flow data available. The data is of varying quality but none of the stations were taken forward for use in the
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Flood Studies Update (FSU), i.e. having a rating classification of B or more. A summary of the available continuous flow data and the confidence in the rating at Qmed is given in Table 4.13.
Table 4.13: Summary of hydrometric gauge data within Model 7 Extents
Station No. Station Name Flow Data Confidence in Availability rating at Qmed
09024 (EPA) Morell Bridge 2001 - 2012 No
09027 (EPA) Broguestown 2001 - 2011 No
09044 (EPA) Kerdiffstown House 2009 - 2012 No
09047 (EPA) Baronrath 2009 - 2011 No
None of the gauging stations within the modelled extents that have flow data available could be used to derive the index flood flow (Qmed) with a high level of confidence, due to uncertainty in the rating and the short record lengths available. Four catchment rainfall run-off (NAM) models have been developed for the catchment using rainfall data applied to the model from the nearby hourly rainfall gauge at Casement and the gauge adjusted hourly sums which have been processed from the rainfall radar at Dublin Airport. These models are calibrated against the aforementioned gauging stations whereby the short amount of hydrometric data available is used for calibration. The result of this is that continuous flow data has been simulated for the period of 1964 – 2009 and an AMAX series extracted. Following initial modelling it was found that calibration of the Morell reaches upstream of the Kerdiffstown House gauging station (09044 – EPA) could not be achieved. A review of the survey data and the NAM model found that the hydrologically modelled catchment did not take into account the catchment of the Hartwell River despite survey data showing that the gauging station is located downstream of the confluence point. In light of this the results from the NAM model for this catchment (09044_RPS) were discarded from the analysis. Two further NAM models have been developed at the upstream extents of the models whereby a continuous flow trace and AMAX flow series has been developed based on the catchment parameters derived at the gauge sites within the catchment. At all other HEPs within the catchment Qmed values have been derived based on catchment descriptor based methods (IH124 and FSU) and adjusted where appropriate based on the simulated Qmed value at the nearest hydrologically / geographically similar gauge location. The Qmed values are shown in Table 4.14.
Table 4.14: Qmed Values for Model 7
2 3 Preferred Estimation Node ID_CFRAMS AREA (km ) Qmed (m /s) Methodology
09_540_6_RPS 7.19 2.96 IH124
09_371_U 0.05 0.01 IH124
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2 3 Preferred Estimation Node ID_CFRAMS AREA (km ) Qmed (m /s) Methodology
09_371_1 1.26 0.11 IH124
UN_Morrell_U 0.54 0.14 IH124
UN_Morrell_1 2.19 0.48 IH124
09_1597_1 0.19 0.05 IH124
09_1612_1_RPS 9.55 3.15 IH124
09_1557_3_RPS 14.87 4.15 IH124
09044_RPS 45.78 10.21 FSU
09_1306_1 11.92 3.40 IH124
09027 12.40 3.42 NAM
09_707_U 0.18 0.06 IH124
09_706_1 0.35 0.11 IH124
09_1602_1_RPS 17.00 3.51 FSU
09036_RPS 47.17 10.50 FSU
09045_RPS 47.22 10.51 FSU
09_411_5_RPS 4.63 0.78 IH124
09_1305_2_RPS 5.93 2.47 IH124
09_1305_8_RPS 7.78 3.06 IH124
09_421_1 10.50 4.80 IH124
09_1118_6 20.78 8.12 FSU
09047_RPS 41.90 13.11 NAM
09_1055_3_RPS 41.96 12.98 FSU
09024_RPS 98.40 20.55 NAM
09_1627_6_RPS 98.49 20.52 FSU Note: Flow highlighted in yellow represent total flows at that point in the model rather than input flows
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4.14 MODEL 8 – NEWBRIDGE
The Newbridge model represents the most upstream stretch of the River Liffey middle catchment and the small tributaries of the Liffey which run through the Newbridge AFA. The small tributaries, the Riccardstown Common (1km2), Doorfield (5km2) and Walshtown (2km2) watercourses, could all be considered part of the urban drainage network. Aside from these tributaries this portion of the middle catchment (177 km2) can be considered to be predominantly rural with approximately 5% urban cover (Newbridge). The only gauging station which is located on the model is at the upstream extent at the Golden Falls power generation station (09007 – ESB). For the purposes of the estimation of design flows the index flood flow from the upper catchment is not considered here as the flow released from the dams is dominated by considerations which are largely non-hydrological. Dam safety, flood management, power generation, water abstraction are among the factors considered by ESB when releasing water from the dams with a resulting continuous flow record at Golden Falls which is dominated by the cyclical pattern of discharges through the electricity generation turbines in normal operating conditions. This is considered further in Chapter 6 while the design flows here represent those generated by the catchment downstream of the dams only. It will be necessary for the hydraulic modeller to therefore consider the additional flows as discussed in Section 6.3 on top of the flows from the middle and lower catchment with the effect of flows from the dam considered sequentially, from model to model, down through the middle catchment.
No catchment run-off models have been constructed for this stretch of the Liffey as no calibration data is available. Therefore the estimates of index flood flow are derived solely from catchment descriptor based estimates. Although the gauging station at Celbridge (09006 – ESB) is located on the main channel of the Liffey it represents combined flows from both dam releases and catchment run-off and as such would not be considered appropriate as a pivotal site for the flows derived on this portion of the Liffey main channel which are dominated by the dam releases (see Chapter 6). A review of the most hydrologically similar FSU pivotal sites was also considered but no clear pattern of under or over estimation of the Qmed value based on physical catchment descriptors was obvious. The HEPs and catchment boundaries for Model 8 are shown in Figure 4.15 and the estimated Qmed values and estimation methodology outlines in Table 4.15.
Table 4.15: Qmed Values for Model 8
2 3 Preferred Estimation Node ID_CFRAMS AREA (km ) Qmed (m /s) Methodology
09007_RPS 328.19 See Chapter 6
09_1119_5_RPS 30.62 5.96 FSU
09_1011_7 15.21 2.48 IH124
09_1281_2_RPS 31.32 3.35 FSU
09_1154_U 0.34 0.25 IH124
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2 3 Preferred Estimation Node ID_CFRAMS AREA (km ) Qmed (m /s) Methodology
09_588_2_RPS 2.62 0.91 IH124
09_1518_4_RPS 140.07 18.53 FSU
09_1517_U 0.54 0.11 IH124
09_1517_1 0.93 0.18 IH124
09_1519_2_RPS 151.19 19.11 FSU
09_1519_8_RPS 155.92 19.71 FSU
09_1519_13_RPS 176.68 20.28 FSU
09_363_U 0.13 0.04 IH124
09_363_2_RPS 2.00 0.59 IH124 Note: Flow highlighted in yellow represent total flows at that point in the model rather than input flows
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Figure 4.15: Model 8 Catchment Boundaries and HEPs
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4.15 MODEL 9 – BLESSINGTON
The Blessington model represents a number of minor watercourses in the upper Liffey catchment that affect the Blessington AFA and which discharge directly to Pollaphuca Reservoir namely the Newtown Park, Little Newtown and Deerpark watercourses. The total catchment area is just over 8 km2 and is shown in Figure 4.16 below.
Figure 4.16: Model 9 Catchment Boundaries and HEPs
There are no gauging stations available within the modelled catchment and no NAM models have been developed for the catchment due to its size and as there is no gauged data upon which to calibrate the model. Index flood flows for the inflows to the model have been estimated using the IH124 catchment descriptor based estimation method due to the small size of the catchments under consideration. The IH124 method results in flows which are significantly higher than the FSU catchment descriptor based estimates. A review of hydrologically similar pivotal sites considered against the total modelled catchment found that the Rochfort gauging station in the Shannon
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Table 4.16: Qmed Values for Model 9
2 3 Preferred Estimation Node ID_CFRAMS AREA (km ) Qmed (m /s) Methodology
09_581_U 0.80 0.50 IH124
09_605_2_RPS 2.69 1.27 IH124
09_625_U 0.34 0.35 IH124
09_591_U 0.22 0.15 IH124
09_591_1 0.69 0.43 IH124
09_1876_5_RPS 8.14 2.76 FSU Note: Flow highlighted in yellow represent total flows at that point in the model rather than input flows
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4.16 INDEX FLOOD FLOW CONFIDENCE LIMITS
4.16.1 Gauged Qmed
As has been shown previously HA09 is a moderately well gauged catchment with most models having some gauge data available upon which estimates of flood flow can be based. However there are not many stations which have a high confidence in Qmed such that they were classified as useable within the FSU and have confidence in the rating at Qmed. The problem is particularly pronounced on the main channel of the Liffey where there are no FSU classified stations. The use of rainfall run-off modelling techniques can bring additional confidence at stations where the station rating is questionable at Qmed, the length of AMAX series is short such that statistical confidence in the Qmed value is diminished or where the behaviour of the catchment may have changed over time. However rainfall run-off modelling using the NAM catchment model within MIKE 11 is of limited use on the main channel of the Liffey as calibration cannot be achieved due to the flow records being affected by non- catchment run-off factors (e.g. the cyclical flow releases from the upstream dams).
Rainfall run off models which have been completed to date for the Eastern CFRAM Study area have been considered by RPS in order to measure the accuracy of the models in predicting Qmed. Models representing catchments at hydrometric gauging stations which were considered useable for FSU (see
FSU WP 2.1) had the rainfall run-off model simulated Qmed values compared against the station observed Qmed values to see if the calibrated NAM models were replicating the gauged Qmed values. Twelve Pivotal Site stations have calibrated rainfall run-off models within the Eastern CFRAM Study area. The results of the comparable simulated and observed Qmed values are shown in Table 4.17 below.
Table 4.17: Calibrated NAM Model Qmed Accuracy
Station Station Name FSU AMAX Observed Simulated % Error Number Years Qmed Value Qmed Value
07001 Tremblestown No calibration data for FSU period (pre 1970)
07003 Castlerickard 1975 - 2004 21.87 22.24 1.7
07005 Trim 1975 - 2004 104.42 103.31 1.1
07007 Boyne Aqueduct 1979 - 2004 35.70 34.63 2.8
07009 Navan Weir 1976 - 2004 134.82 130.46 3.2
07010 Liscartan 1986 - 2004 68.36 72.15 5.5
07012 Slane 1941 - 2004 191.40 192.73 0.7
07041 Ballinter Bridge 1998 - 2004 161.00 189.00 17.4
09002 Lucan 1977 - 2004 5.25 5.91 12.5
09035 Killeen Road 1996 - 2004 11.70 12.19 4.2
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Station Station Name FSU AMAX Observed Simulated % Error Number Years Qmed Value Qmed Value
10021 Shanganagh 1980 - 2004 7.36 8.03 9.1
1984 - 1997 10022 Cabinteely 3.85 3.52 8.6 2001 - 2003
Conc. years: 1986 - 1991, 10028 Aughrim 43.60 45.47 4.3 1999 - 2000, 2004
Average Error 5.9
It can be shown that the rainfall run-off models appear to be replicating to a high degree of accuracy the FSU Qmed values for the FSU period of record for nearly all of the stations considered. The one exception is at Ballinter Bridge where the error on the Qmed for the concurrent period of observed and simulated record is over 17%. It is worth noting that this is based on a short comparison period and that the Qmed for the entire simulation period of the NAM model (1941 – 2009) is 157 m3/s. Lucan also has an error above 10% but it must be noted that this is quite a small flow and it would be expected that calibration in percentage terms would be more difficult to achieve on these smaller catchments. The difference in flow terms is less than 0.7 m3/s. In relation to the accuracy it should also be noted these models are calibrated against the gauge records themselves and as such we would expect them to replicate the results. The ability to replicate the reliable record does however give us some degree of confidence in the models ability to extend the AMAX series and fill in record gaps.
Where gauging station flow records are derived from very poor ratings there is potential for the record to influence the calibration and as such over or under estimation in the record may get, to some degree, carried over into the simulation. The methodology seeks to minimise this risk by limiting the calibration at such gauges to the portion of the record where there is confidence in the rating, generally below the highest gauged flow. The Anne’s Bridge station on the Rye Water (09048 – EPA) is one such station where the results of the simulated flow trace, although not as stark as the actual observed flow record, diverge significantly in terms of Qmed from the FSU catchment descriptor model. It is known however that the FSU catchment descriptor model under estimates on the Rye Water and it may be the case that the NAM model has moderated the record somewhat towards reality. In the absence of this additional catchment run-off modelling technique we would potentially be forced to abandon consideration of this gauge record, and the similar Maynooth (09049 – EPA) record, altogether. Notwithstanding this the NAM model has not been validated and it is considered worthwhile that a dialogue regarding the performance of this gauging station at high flows is continued to see if validation, through higher spot gauged flows and possibly a rating review leading to improved observed data, can be achieved.
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4.16.2 Ungauged Qmed
A variety of methods are considered in the estimation of Qmed for the ungauged catchments within this study from statistical based methods where regression equations are used based on catchment descriptors to rainfall run-off modelling techniques which are an extension of the technique analysed previously, but without the availability of direct calibration data.
The FSU method for Flood Estimation in ungauged Catchments (WP 2.3) includes only eight out of a total of 190 hydrometric gauge stations from across Ireland for catchments less than 25km² from which data was used to derive the equation. The IH124 method utilised data from a total of 87 UK catchments (three of which were in Northern Ireland) but all of these catchments were less than 25km² in area. The factorial standard error (FSE) associated with Qmed estimation using FSU (WP 2.3) is 1.37 and for IH124 the FSE is given as 1.651. This is substantially higher for IH124 but this method is generally preferred for smaller catchments less than 25km² in area as the data upon which the regression equation was derived is much more weighted towards smaller catchments. In some instances the FSU equation has been preferred for sites smaller than 25km2 where a good pivotal site gauge is located nearby or where it was felt the IH124 method (and the derived catchment descriptors) did not particularly represent the catchment accurately.
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5 FLOOD FREQUENCY ANALYSIS AND GROWTH CURVE DEVELOPMENT
5.1 OBJECTIVE AND SCOPE
This chapter deals with the estimation of flood growth curves for the River Liffey and Santry River catchments (Hydrometric Area HA09). The estimated growth curves will be used in determining the peak design flood flows for all Hydrological Estimation Points (HEP) located on the modelled tributary and main river channels within the Hydrometric Area HA09.
The scope of this chapter includes:
(i) Selection of a statistical distribution suitable for regional flood frequency analysis, (ii) Selection of pooling region and groups, and (iii) Growth curve estimation,
5.2 METHODOLOGY
5.2.1 Selection of Statistical Distribution
The suitable distributions for the Annual Maximum (AMAX) series for all hydrometric gauging sites located within HA09 were determined based on the statistical distribution fitting technique described in the Flood Studies Update (FSU) Programme Work Package 2.2 “Frequency Analysis” (OPW, 2009), UK Flood Estimation Handbook (FEH) (Institute of Hydrology, 1999) and 1975 Flood Studies Report (NERC, 1975).
5.2.2 Forming a Pooling Region and Groups
The pooling group associated with each of the growth curves was formed based on the Region-of- Influence (ROI) approach (Burn, 1990) recommended in FSU (2009). The region from which the AMAX series were pooled to form a pooling group for each of the growth curves was selected based on the similarity in catchment characteristics (both in terms of climatic and physiographic) in the neighbouring geographical region.
5.2.3 Growth Curve Development
Growth curves for each of the HEP locations were developed / estimated in accordance with the methodologies set out in the FSU, FSR and FEH studies. The Hosking and Wallis (1997) proposed L-Moment theories were used in estimating the parameters of the statistical distributions. The growth curve estimation process was automated through development of a FORTRAN 90 language based computational program.
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5.2.4 Limitations in the FEH and FSU Studies
There is no explicit guidance provided in FEH or FSU for dealing with the issues surrounding production of a large number of growth factors within a river system and the associated problems with consistency and transition from growth curve to growth curve. For the River Liffey and Santry River (HA09) catchments, a catchment characteristic based generalised growth curve estimation method, as discussed later in Sections 5.7.4 and 5.8, was used to deal with this real world problem.
5.3 DATA AND STATISTICAL PROPERTIES
5.3.1 Flood Data
The AMAX series for all hydrometric gauging sites located within the River Liffey and Santry River catchments were obtained from the OPW and the EPA. In addition to these, flow records from neighbouring catchments were also collected to form a pooling region for growth curve analysis. The AMAX series and continuous flood records for 92 gauging sites were obtained for up to year 2011. Table 5.1 presents the locations details, record lengths and some of the catchment characteristics of these hydrometric stations, while Figure 5.1 illustrates their spatial distributions in the region. The majority of the 92 stations have A1 & A2 rating quality classification (refer to Section 3.2 of HA09 Inception Report for the definition of the rating quality classifications of the hydrometric gauges) but other stations were also included within the pooling group as it was considered beneficial to include these additional station years, many of which capture recent flood events since FSU WP 2.1 was undertaken, despite the uncertainty in the ratings. The record lengths in these gauging stations vary from 9 to 70 years with a total of 3,336 station-years of AMAX series. HA09 has 199 station-years of AMAX series from 8 hydrometric gauging sites.
There are climatic differences between the eastern and other parts of the country and restricting the choice of pooling stations to the eastern and south-eastern regions along including HA06 should ensure an additional degree of homogeneity. In particular it was felt that the catchments of the Shannon hydrometric areas (HA), many of which are large and flat, would not necessarily be homogeneous with the eastern and south-eastern region HAs and therefore would not make any additional useful contribution to the development of growth curves for the east and south-eastern HAs. In the light of the large number of AMAX values (3,336 station-years) available in the eastern and south-eastern HAs, it is not considered necessary to extend the pooling region to the entire country.
Table 5.1: Hydrometric Station Summary
Record Gauge Rating Area SAAR Stations Waterbody Location Length BFI FARL Classification (Km2) (Mm) (Years)
6011 Fane Moyles Mill 51 229.19 1028.98 0.708 0.874 A1 6012 Annalong Subsidiary Intake 53 162.80 1046.24 0.680 0.831 A1
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Record Gauge Rating Area SAAR Stations Waterbody Location Length BFI FARL Classification (Km2) (Mm) (Years)
6013 Dee Charleville 35 309.15 873.08 0.617 0.971 A1 6014 Glyde Tallanstown 35 270.38 927.45 0.634 0.927 A1 6025 Dee Burley 36 175.98 908.31 0.615 0.956 A1 7001 Tremblestown Tremblestown 42 151.31 913.24 0.700 0.996 A2 Deel 7002 A2 [Raharney] Killyon 51 284.97 920.53 0.780 0.929 Blackwater 7003 Castlerickard 51 181.51 809.22 0.649 1.000 A1 & B (Enfield) Blackwater 7004 A2 (Kells) Stramatt 53 245.74 1007.88 0.619 0.772 7005 Boyne Trim 52 1332.17 879.71 0.721 0.983 A1 7006 Moynalty Fyanstown 49 177.45 936.67 0.552 0.990 A2 7007 Boyne Boyne Aqueduct 50 441.18 870.98 0.663 1.000 A1 & B 7009 Boyne Navan Weir 34 1658.19 868.55 0.713 0.911 A1 Blackwater 7010 A1 & A2 (Kells) Liscartan 51 699.75 948.29 0.658 0.798 Blackwater 7011 A2 & B (Kells) O'Daly's Br. 49 281.74 1003.32 0.678 0.965 7012 Boyne Slane Castle 70 2460.27 890.06 0.678 0.893 A1 7017 Moynalty Rosehill 11 70.64 991.74 0.516 0.993 n.a. 7023 Athboy Athboy 9 100.10 950.81 0.717 0.995 n.a. Blackwater 7033 A2 (Kells) Virginia Hatchery 30 124.94 1032.22 0.439 0.893 8002 Delvin Naul 24 33.43 791.12 0.597 1.000 A1 8003 Broadmeadow Fieldstown 18 83.59 826.00 0.466 0.880 B 8005 Sluice Kinsaley Hall 23 9.17 710.76 0.523 1.000 A2 8007 Broadmeadow Ashbourne 21 37.94 845.02 0.399 1.000 B 8008 Broadmeadow Broadmeadow 28 107.92 810.61 0.487 0.999 A2 8009 Ward Balheary 15 61.64 767.09 0.545 0.999 A1 8010 Garristown St. Garristown S.W. 13 1.13 818.92 0.682 1.000 n.a. 8011 Nanny Duleek D/S 28 181.77 819.49 0.520 0.999 B 8012 Stream Ballyboghill 17 25.95 798.70 0.524 0.999 B 9001 Ryewater Leixlip 54 209.63 783.26 0.507 1.000 A1 9002 Griffeen Lucan 25 34.95 754.75 0.674 0.958 A1 9010 Dodder Waldron's Bridge 57 94.26 955.04 0.561 0.993 A1 9011 Slang Frankfort 19 5.46 772.95 0.563 0.986 B 9024 Morell Morell Bridge 9 98.75 851.99 0.705 0.987 n.a. 9035 Camac Killeen Road 15 37.14 794.21 0.673 0.932 B 9048 Ryewater Anne's Bridge 10 59.35 805.54 0.474 1.000 n.a. 9049 Lyreen Maynooth 10 87.52 768.17 0.473 1.000 n.a.
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Record Gauge Rating Area SAAR Stations Waterbody Location Length BFI FARL Classification (Km2) (Mm) (Years)
10002 Avonmore Rathdrum 52 230.89 1530.19 0.538 0.986 B 10004 Glenmacnass Laragh 14 30.57 1700.39 0.436 0.997 B 10021 Shanganagh Common's Road 30 32.51 799.07 0.654 0.997 A1 10022 Cabinteely Carrickmines 17 12.94 821.92 0.600 1.000 A1 10028 Aughrim Knocknamohill 22 202.92 1396.92 0.788 0.999 B 10038 Stream Druids Glen 10 16.14 914.40 0.618 1.000 n.a. 11001 Owenavorragh Boleany 38 155.11 931.07 0.489 0.999 A1 12001 Slaney Scarawalsh 55 1030.75 1167.31 0.716 0.999 A2 12002 Slaney Enniscorthy 31 1319.92 1129.33 0.714 1.000 C/U 12013 Slaney Rathvilly 35 204.39 1383.48 0.743 0.999 B 13002 Corock Foulk's Mill 25 62.96 1043.79 0.733 1.000 B 14003 Barrow Borness 27 206.73 1160.51 0.532 1.000 B 14004 Figile Clonbulloge 53 268.85 838.67 0.537 1.000 A1 14005 Barrow Portarlington 53 405.48 1014.90 0.501 1.000 A2 14006 Barrow Pass Br 56 1063.59 899.07 0.571 1.000 A1 14007 Stradbally Derrybrock 30 118.59 814.07 0.642 1.000 A1 14009 Cushina Cushina 30 68.35 831.24 0.667 1.000 A2 14011 Slate Rathangan 31 162.30 806.97 0.600 0.999 A1 14013 Burren Ballinacarrig 55 154.40 887.98 0.701 0.999 A2 14018 Barrow Royal Oak 67 2419.40 857.46 0.665 1.000 A1 14019 Barrow Levitstown 57 1697.28 861.46 0.624 0.999 A1 Barrow New 14022 A2 Barrow Bridge 12 2069.53 855.63 0.652 0.999 Graiguenamanagh 14029 A2 Barrow U/S 52 2778.15 876.50 0.688 0.999 14031 Tully Japanese Gdns 10 13.00 826.06 0.650 1.000 n.a. 14033 Owenass Mountmellick 10 78.89 1145.22 0.454 0.999 B 14034 Barrow Bestfield Lock 17 2057.36 856.05 0.652 0.999 A2 14101 Boghlone Kyleclonhobert 9 9.60 929.15 0.554 1.000 n.a. 15001 Kings Annamult 48 444.35 935.24 0.514 0.997 A2 15002 Nore John's Br. 53 1644.07 945.44 0.625 0.730 A2 15003 Dinin Dinin Br. 56 299.17 933.86 0.381 0.998 A2 15004 Nore Mcmahons Br. 56 491.38 1067.46 0.594 0.999 A2 15005 Erkina Durrow Ft. Br. 55 379.37 884.96 0.712 0.999 B 15006 Nore Brownsbarn 54 2418.27 941.92 0.633 0.997 A2 15007 Nore Kilbricken 35 339.76 1123.04 0.594 1.000 A2 15008 Nore Borris In Ossory 35 116.22 943.75 0.533 0.993 n.a. 15009 Kings Callan 54 203.14 940.19 0.540 1.000 B 15010 Goul Ballyboodin 31 159.06 886.97 0.657 0.997 n.a.
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Record Gauge Rating Area SAAR Stations Waterbody Location Length BFI FARL Classification (Km2) (Mm) (Years)
15011 Nore Mount Juliet 57 2225.79 938.02 0.618 0.999 C 15012 Nore Ballyragget 16 1056.80 974.00 0.682 0.999 B 15021 Delour Annagh 11 67.05 1358.56 0.651 1.000 C 15041 Goul Ballinfrase 9 135.39 889.60 0.634 0.996 n.a. 16001 Drish Athlummon 38 135.06 916.42 0.606 1.000 A2 16002 Suir Beakstown 56 485.70 932.15 0.634 0.999 A2 16003 Clodiagh Rathkennan 56 243.20 1192.01 0.550 1.000 A2 16004 Suir Thurles 55 228.74 941.36 0.579 1.000 A2 16005 Multeen Aughnagross 35 84.00 1153.57 0.560 0.994 A2 16006 Multeen Ballinaclogh 38 75.80 1115.82 0.587 0.999 B 16007 Aherlow Killardry 56 273.26 1330.55 0.578 0.999 B 16008 Suir New Bridge 56 1090.25 1029.63 0.635 0.998 A2 16009 Suir Caher Park 57 1582.69 1078.57 0.631 0.998 A2 16010 Anner Anner 38 437.10 985.24 0.624 0.999 C 16011 Suir Clonmel 71 2143.67 1124.95 0.670 0.993 A1 16012 Tar Tar Br. 46 229.63 1320.79 0.628 0.999 B 16013 Nire Fourmilewater 45 93.58 1471.29 0.539 0.993 B 16051 Rossestown Clobanna 13 34.19 895.27 0.676 1.000 B 17002 Tay River Fox Castle 10 33.50 1554.00 n.a. n.a. n.a.
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Figure 5.1: Locations of 92 Gauging Stations
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5.3.2 Pooling Region Catchment Physiographic and Climatic Characteristic Data
In addition to the AMAX series, some catchment physiographic and climatic characteristics information including the catchment sizes (AREA), Standard Average Annual Rainfall (SAAR), catchment Base Flow Index (BFI) and the Flood Attenuation by Reservoirs and Lakes (FARL) Index for all 92 stations were also obtained from OPW. Table 5.2 presents a summary of these catchment characteristics. Catchment sizes range from 1.13 to 2778.15 km2 with a median value of 182 km2, SAAR values range from 711 to 1700 mm with a median value of 927 mm. The BFI values vary from 0.381 to 0.788, while the FARL values range from 0.730 to 1.0.
Table 5.2: Summary of Catchment physiographic and climatic characteristics of Pooling Region
HA09 Characteristics Minimum Maximum Average Median Median
AREA (km2) 1.13 2778.15 489.17 181.77 283.19
SAAR (mm) 710.76 1700.39 967.15 927.45 916.89
BFI 0.381 0.788 0.608 0.624 0.671
FARL 0.730 1.000 0.979 0.999 0.974
Furthermore the relative frequencies of the AREA, SAAR and BFI values within the 92 stations are also presented in Figure 5.2, Figure 5.3 and Figure 5.4 respectively. It can be seen from Figure 5.2 that the majority of the catchment areas in the selected sites fall in the range of 100 to 500 km2. Figure 5.3 shows that the SAAR values in majority of the stations range from 800 to 1000 mm and very few stations have SAAR values more than 1400 mm. Similarly, Figure 5.4 shows the relative frequency of the BFI values within the 92 catchments. It can be seen from this figure that the BFI values in the majority of the 92 catchment areas range from 0.5 to 0.75.
AREA
0.14
0.12
0.10
0.08
0.06
0.04 Relative frequency Relative 0.02
0.00 0 100 200 300 400 500 600 700 800 900 1000 1100 1200 1300 1400 1500 1600 1700 1800 1900 2000 2100 2200 2300 2400 2500 2600 2700 2800 Area (km 2)
Figure 5.2: Relative frequencies of catchments sizes (AREA) within the selected 92 stations
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SAAR
0.35
0.30
0.25
0.20
0.15
Relative frequency Relative 0.10
0.05
0.00 700 900 1100 1300 1500 1700 SAAR (mm)
Figure 5.3: Relative frequencies of the SAAR values within the selected 92 stations
BFI
0.250
0.200
0.150
0.100 Relative frequency 0.050
0.000 0.35 0.40 0.45 0.50 0.55 0.60 0.65 0.70 0.75 0.80 BFI
Figure 5.4: Relative frequencies of the BFI values within the selected 92 stations
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5.3.3 Statistical Properties of the AMAX series
Table 5.3 provides a summary of the statistical properties of the AMAX series for all 92 gauging sites. 3 The median annual maximum flows (Qmed) range from 0.47 to 299.32 m /s with an average value of 53.83 m3/s. The L-CV values range from 0.052 to 0.415 with an average value of 0.198, while the L- Skewness values range from -0.181 to 0.488 with an average value of 0.166 which is approximately equal to the theoretical L-Skewness of EV1 distribution. Figure 5.5 shows the L-CV versus L- Skewness diagram for the 92 AMAX series with the values associated with HA09 shown in red colour.
Table 5.3: Statistical properties of 92 AMAX Series
Maximu Averag Parameters Minimum Median m e
Record Lengths 9 71 37 35 (years)
Mean Flow (m3/s) 0.49 303.45 56.56 27.16
Median Flow (m3/s) 0.47 299.32 53.83 25.42
L-CV 0.052 0.415 0.198 0.182
L-skewness -0.181 0.488 0.166 0.163
L-kurtosis -0.127 0.426 0.155 0.139
HA09 Stations
Figure 5.5: L-Moment Ratio Diagram (L-CV versus L-Skewness) for 92 AMAX series
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5.4 STATISTICAL DISTRIBUTION
The individual gauging site’s AMAX series were fitted to four flood like distributions, namely EV1, GEV, GLO and LN2 distributions. The EV1 and LN2 distributions are two-parameter distributions while the GLO and GEV distributions each have three-parameters.
The choice of distributions used for this study was guided by the findings in FSU Report (September, 2009). In the case of 2-parameter distributions, the FSU Work Package 2.2 report states (Section 4.2, page 40) “It can be deduced from the linear patterns that Irish flood data are more likely to be distributed as EV1 or LN2 rather than Logistic distribution (LO) among 2-parameter distributions”. Therefore the elimination of LO as a 2-parameter distribution is robustly based on a study of all relevant Irish data. Also, FSU concentrated on GEV and GLO from among the available 3-parameter distributions. The lack of emphasis on LN3 by FSU was possibly based on the L-kurtosis vs. L- skewness moment ratio diagram (FSU WP 2.2 Report, Figure 3.10, page 30) and that one could be used as a surrogate for the other. Then, because of the overwhelmingly central role, traditionally played by GEV in flood frequency analysis, the FSU decided to base its analysis using the GEV rather than LN3. The same reasoning was adopted for the present study.
Based on the visual inspections of the probability plots of all 92 AMAX series, it was found that the three-parameter distributions provide better fits to the majority of the 92 AMAX series. Between the GEV and GLO distributions, the GLO distribution was found to be the better. In GLO distribution, out of 92 frequency curves, 80 showed concave upward shape, 5 concave downward and 7 straight lines. In GEV distribution, 35 showed concave upward shape, 41 showed concave downward and 16 are of straight line type. In HA09, the GLO distribution was found to be the best suited to 6 AMAX series out of 8 series (all concave upward). In the case of GEV distribution, 6 concave upward shape, one concave downward and one straight line. Table 5.4 presents the summary results of the visual assessments of the probability plots for all 92 AMAX series. It should be noted here that one reason for the change of concavity (upward and downward) shapes seen in GEV and GLO is due to the difference in abscissa used in the probability plots i.e. EV1y = -ln{-ln(1-1/T)} for GEV distribution and GLOy = -ln{1/(T-1)} for GLO distribution.
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Table 5.4: Summary results of probability plots assessments (EV1, GEV & GLO distributions) for all 92 AMAX series
No. distribution in each quality ranks (1, 2 & 3) Distribu Fitted line type tion Rank 1 Rank 2 Rank 3 (very (good) (fair) good)
EV1 18 12 62 All straight line
LN2 18 33 41 All concave upward (At Log n scale)
16 – straight line (GEV type I) GEV 20 56 16 35 – concave upward (GEV Type II) 41 – concave downward (GEV Type III) 7 – straight line, GLO 54 24 14 80 – concave upward & 5 – concave downward
A study carried out in University College Dublin (UCD) by S. Ahilan et al. (2012) on 143 stations countrywide in Ireland found that the AMAX series of the majority of hydrometric stations located in the Eastern and South Eastern regions follow the GEV type III distribution.
5.5 GROWTH CURVE ESTIMATION POINTS
In order to estimate the peak design flows for each of the 220 HEPs located on the modelled watercourses in HA09 using the ‘index-flood’ method (FEH, 1999; FSU, 2009), growth curves for each of the HEPs are required. The selection of the HEPs was based on the hydraulic model conceptualisation of the modelled watercourses within each of the Areas for Further Assessment (AFA) in HA09. For the integration of hydrological input to the hydraulic model and also for the calibration and verification of the hydraulic models the HEPs were identified at the following locations on the modelled watercourses:
- HEPs at the upstream limit of model, - HEPs where tributaries enter the modelled channels, - HEPs at gauged stations on modelled channels, - HEPs at intermediate points on the modelled channels (to ensure maximum 5km spacing), and - HEPs at downstream limit of model.
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The details of the selection process for the HEPs are discussed in the HA09 Inception Report (section 5.3). Table 5.5 presents a summary of the catchment characteristics associated with the 220 HEPs in HA09. The catchment areas vary from close to 0 (at the top of modelled tributaries) to 1055 km2. The SAAR values range from 715 to 1342 mm while the BFI values vary from 0.438 to 0.711.
Table 5.5: Summary of the catchment characteristics associated with the 133 HEPs
Catchment Maximu Minimum Average Median descriptors m
AREA (km2) 0.10 1055 52.40 2.61
SAAR (mm) 715 1342 863 828
BFI 0.438 0.711 0.590 0.619
Based on the similarity of the catchment characteristics of these HEPs with the selected gauging sites located within the pooling region, growth curves for all HEPs with areas greater than 5 km2 were estimated. Almost 95% of the selected gauging sites in the pooled region have catchment areas more than 5 km2. Therefore, the pooling groups for the HEPs with catchment areas less than 5 km2 would not be the homogeneous groups and therefore the errors in the estimated growth curves would be larger. All HEPs with catchment areas less than 10 km2 are considered to have the same growth curve. Based on these considerations, 95 HEPs (out of 220) were initially selected as points for the estimation of growth curves within HA09 but as will be discussed in section 5.8.2 this was extended with the addition of a further 205 Growth Curve Estimation Points (GC_EPs) in order to aid rationalisation of the growth factors. Figure 5.6 shows the spatial distribution of these HEPs on the modelled watercourses in HA09.
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Figure 5.6: Spatial distribution of the HEPs on the modelled watercourses in HA09
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5.6 POOLING REGION AND GROUP FOR GROWTH CURVE ESTIMATION
5.6.1 Pooling Region
Based on the similarity of climatic characteristics, it has been decided that the AMAX series from both the Eastern and South-eastern CFRAM study areas and also from the neighbouring hydrometric area 06 (HA06 – Newry, Fane, Glyde and Dee) will be pooled to form a pooling group for growth curve estimation for HA09. The pooling region for this study therefore covers the eastern and south-eastern parts of Ireland. Figure 5.1 illustrates the extent of the pooling region. A summary of the statistical properties of all AMAX series and their associated catchment characteristics is presented in Table 5.2 & Table 5.3 respectively. The values of AREA, SAAR and BFI encountered in the 133 HEPs are summarised by their minimum, maximum, average and median values in Table 5.5. Comparison of these with the histograms of AREA, SAAR and BFI for the 92 stations selected for pooling purposes (Figure 5.2 to Figure 5.4) show a good overlap, which indicates that the 92 stations provide good coverage for the range of catchments encountered in the HEPs in HA09.
5.6.2 Pooling Group
Pooling groups can be formed on the basis of geographical proximity to the subject site. However in the UK FEH study (1999) it was found that such pooling groups were less homogeneous than those formed by the Region of Influence (ROI) approach of the type proposed by Burn (1990). The ROI approach selects stations, which are nearest to the subject site in catchment descriptor space, to form the pooling group for that subject site. In the FSU studies a distance measure in terms of three catchment descriptors of AREA, SAAR and BFI was used in forming a pooling group. The recommended distance measure in the FSU studies is:
2 2 2 ln AREAi ln AREAj ln SAARi ln SAAR j i BFIBFI j (5.1) dij 7.1 2.0 ln AREA ln SAAR BFI
Where i is the subject site and j=1,2,….M are the donor sites.
In this study, the pooling group was formed based on the above distance measure. The size of the pooling groups was determined based on the FEH recommended 5T rules (i.e. the total number of station-years of data to be included when estimating the T-year flood should be at least 5T). The donor sites associated with this pooling group size are selected based on the lowest distance measures among the available gauging sites in the pooling region. Individual pooling groups have been developed and growth curve have been estimated for every HEP. However, the estimated pooled growth factors/curves have been generalised further based on a range of catchment sizes as discussed later in Section 5.8.2.
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5.7 GROWTH CURVE ESTIMATION
5.7.1 Choice of Growth Curve Distributions
In the ‘index-flood’ method one of the major assumptions is that the frequency distributions at different sites in the pooled group are identical apart from a scale factor, which is the median flow (Qmed).
As discussed in Section 5.4, the three-parameter GEV and GLO distributions were found to be the better suited distribution for most of the 92 AMAX series than the two-parameter distributions. Furthermore, it can be seen from the L-moment ratio diagram for these 92 AMAX series as shown in Figure 5.7 that the GEV distribution is providing better fits than the GLO distribution, since the theoretical values of the GEV distribution’s L-Skewness and L-Kurtosis pass centrally through the observed L-moments ratios of the 92 AMAX series.
Figure 5.7: L-moment ratio diagram (L-skewness versus L-kurtosis)
Based on the above, the GEV distribution can be adopted as the best candidate distribution for the regional growth curve for the River Liffey and Santry River catchments. However, since the probability plots show that the GLO distribution is also suitable, this distribution is also considered as a candidate distribution for the regional growth curve estimation. Although the two-parameter distributions exhibit more bias in the regional flood frequency estimates as compared to the three-parameter distributions, the two-parameter EV1 distribution is also used in the growth curve estimation process for comparison purposes and to replace the GEV or GLO growth curve when the shape displayed by either of these two distributions is concave downwardin order to avoid potential underestimation of extreme event growth factors.
5.7.2 Estimation of Growth Curves
The algebraic equations of the EV1, GEV and GLO growth curves and associated parameters are given below:
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EV1 distribution:
Growth Curve: xT /11lnln2lnln1 T (5.2)
t Parameter: 2 (5.3) t 2 2lnln2ln
where, t2 is the L-coefficient of variation (L-CV) and is Euler’s constant = 0.5772.
GEV distribution:
k k T Growth Curve: x ln2ln1 , k 0 (5.4) T k T 1
The parameters k and are estimated from sample t2=L-CV and sample t3=L-skewness as follows: [Hosking & Wallis (1997, p.196)]
2 2ln k 9554.28590.7 cc 2 where c (5.5) 3 t3 3ln
kt 3 (5.6) k k 2 kt k 2112ln1
GLO distribution:
k Growth Curve: xT T 111 , k 0 (5.7) k
The parameters k and are estimated from sample t2=L-CV and sample t3=L-skewness as follows [Hosking & Wallis (1997, p.197)]:
2 sinkkt tk 3 and (5.8) 22 sin kttkk
The pooled regional values of the t2 (L-CV) and t3 (L-skewness) have been estimated as the weighted average values of corresponding at-site sample values weighted by the at-site record lengths. These values were equated to the expressions for these quantities written in terms of the distribution’s unknown parameters as given above and the resulting equations are solved for the unknown parameters.
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5.7.3 Examination of Growth Curve Shape
Growth curves for all of the selected 95 HEPs for a range of Annual Exceedance Probabilities (AEPs) were estimated in accordance with the above methodologies. An examination of the derived shapes of the growth curves showed that, because of the fixed shape distribution, the EV1 growth curves are of straight-line type for all 95 HEPs, while in the GEV and GLO distribution cases growth curves take either the concave upwards (upward bend) or concave downwards (downward bend) shapes based on the skewness of the pooled group. In the GEV distribution case, out of 95 curves, 22 showed concave downward shape, 70 showed concave upward shape and 3 showed almost a straight line; while in the GLO distribution case, all 95 curves showed the concave upward shape (Table 5.6).
Table 5.6: Growth curves shape summary
Distribution Growth Curve Shape
EV1 All straight lines
22 - concave downward GEV 70 – concave upward 3 – straight line
GLO All concave upward
An assessment of the suitability of the above three growth curve distributions was carried out by examining the suitability of these distributions in fitting the AMAX series in the pooling groups associated with all 95 HEPs. In other words, for a particular HEP, the pooled growth curves, based on EV1, GEV and GLO, were superimposed on the standardised probability plots of the AMAX series which form the pooling group (typically 10 to 12 such series). A visual comparison of the suitability of the growth curves was made and recorded, as done in Figure 5.8 for example for HEP No. 83 of the 95 HEPs selected for the growth curve analysis in HA09. The HEP No. 83 was selected to illustrate the composition of one pooling group.
In estimating the pooled growth curve for HEP No.83, 514 station-years of records from 11 sites were pooled. Figure 5.6 shows the location of this HEP. Table 5.7 shows the catchment characteristics, statistical properties and estimated distance measures for each of the sites from the subject HEP.
Table 5.7: Catchment descriptors for all pooled sites for growth curve No. 83
Record Specific Hydrometric AREA SAAR Qmean length BFI Qmean L-CV L-skew L-kur dij stations (km2) (mm) (m3/s) 2 (years) (m3/s/km )
15004 56 491.38 1067.46 0.594 37.13 0.076 0.158 0.118 0.150 0.335
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Record Specific Hydrometric AREA SAAR Qmean length BFI Qmean L-CV L-skew L-kur dij stations (km2) (mm) (m3/s) 2 (years) (m3/s/km )
16010 38 437.10 985.24 0.624 44.76 0.102 0.117 0.061 0.105 0.348
7011 49 281.74 1003.32 0.678 26.71 0.095 0.245 0.175 0.096 0.533
7010 51 699.75 948.29 0.658 54.68 0.078 0.265 0.099 0.123 0.609
15007 35 339.76 1123.04 0.594 46.53 0.137 0.098 -0.112 0.180 0.628
16002 56 485.70 932.15 0.634 55.7 0.115 0.161 0.145 0.165 0.634
7004 53 245.74 1007.88 0.619 19.82 0.081 0.149 0.159 0.151 0.634
16008 56 1090.25 1029.63 0.635 91.75 0.084 0.075 -0.047 0.049 0.683
6011 51 229.19 1028.98 0.708 15.91 0.069 0.110 0.075 0.080 0.716
15012 16 1056.80 974.00 0.682 77.16 0.073 0.173 0.082 0.214 0.768
14005 53 405.48 1014.90 0.501 50.8 0.125 0.137 0.200 0.253 0.805
Subject site (Growth - 491.32 1038.08 0.650 - - 0.154* 0.094* - - Curve EP- 83)
*Pooled regional values
It can be seen from the above table that the subject site’s catchment characteristics are well placed within the pooled sites’ catchment descriptor space. The subject site has an upstream catchment area of 491.32 km2, SAAR and BFI values of 1038.08 mm and 0.650 respectively which are located approximately at the median locations of the pooled sites’ corresponding values.
The estimated pooled average L-CV and L-Skewness are 0.154 and 0.094 respectively. This suggests that the pooled growth curve would follow a distribution which has L-Skewness less than that of the EV1 distribution (0.167). Figure 5.8 shows the estimated EV1, GEV and GLO growth curves for the growth curve No. 83. The GEV growth curve is a concave downward shaped curve while the GLO one is a concave upward shaped curve.
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Figure 5.8: Pooled Growth Curve 83 - (a) EV1 and GEV distributions; (b) GLO distributions
An assessment of the at-site GEV and GLO growth curves were carried out through a visual inspection of their individual probability plots. A summary of this assessment is provided in Table 5.8.
Table 5.8: Frequency curve shapes of the individual site’s AMAX series associated with the pooled group No. 83
Individual at-site growth curves Hydrometric stations Comparison of performances GEV (EV1y Plot) GLO (Loy Plot) (visual)
Mild concave Both fit equally well to the observed Mild concave upward 15004 downward records
Mild concave Both fit equally well to the observed Mild concave upward 16010 downward records
Moderate concave GLO fits slightly better Straight line 07011 upward
Moderate concave Moderate concave GLO fits slightly better 07010 downward upward
Moderate concave Mild concave GLO fits slightly better 15007 downward downward
16002 Mild concave upward Mild concave upward GLO fits better
07004 Straight line Mild concave upward GLO fits slightly better
Mild concave Mild concave GEV fits better 16008 downward downward
06011 Straight line Mild concave upward GLO flits slightly better
Mild concave GLO fits slightly better Mild concave upward 15012 downward
14005 Straight line Mild concave upward GLO fits slightly better
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The above assessment shows that both the GEV and GLO distributions fit the observed at-site records quite well at all eleven sites with a slightly better performance by the GLO distribution. In the case of GEV distribution six sites showed concave downward shaped curves (mild to moderate), one concave upward and four sites showed straight lines. While in the GLO distribution case, nine showed concave upward and the two remaining sites showed concave downward shaped curves. This suggests that, the shape of the pooled growth curves in the case of GEV distribution can be expected as concave downward while for the GLO distribution case it would be concave upward.
Table 5.9 shows the estimated growth factors for a range of AEPs for Growth Curve No. 83. The estimated 1% AEP growth factors for the EV1, GEV and GLO distributions are 1.985, 1.797 and 1.892 respectively.
Table 5.9: Estimated growth factors for Growth Curve No. 83
AEP (%) EV1 GEV GLO
50 1.000 1.000 1.000
20 1.264 1.255 1.230
10 1.438 1.406 1.379
5 1.606 1.538 1.526
2 1.823 1.692 1.729
1 1.985 1.797 1.892
0.5 2.147 1.893 2.064
0.1 2.522 2.086 2.509
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5.7.4 Recommended Growth Curve Distribution for the River Liffey and Santry River Catchments
The following factors were considered to select an appropriate growth curve distribution for the River Liffey and Santry River catchments area:
(i) Suitability of a distribution in fitting the individual at-site records, (ii) No. of distribution parameters, and (iii) Shape of the pooled growth curve
A visual examination of the at-site frequency curves for all 92 gauging sites showed that the AMAX series for most of these sites can be described slightly better by the GLO distribution than by the EV1 and GEV distributions. This is in line with the approach recommended in FSU WP 2.2 but it is acknowledged that this moves away from traditional FSR based approaches where the EV1 Distribution was preferred.
The number of distribution parameters also plays an important role in deriving an appropriate growth curve. The fixed skewness two-parameter distributions generally suffer from large biases, particularly at the upper tail of the distribution. The three-parameter distributions, in contrast, suffer from larger standard error though they are less biased. However this standard error is generally reduced by the pooled estimation process. The use of two-parameter distributions such as the Gumbel distribution is not therefore recommended in regional frequency analysis (Hosking and Wallis, 1996). The use of a two-parameter distribution is beneficial only if the investigator has complete confidence that the at site distribution’s L-Skewness and L-kurtosis are close to those of the frequency distributions. As discussed in Section 5.7.1, the L-CV and L-Skewness of most of the sites in the Pooling Region differ from those of the theoretical values of the EV1 distribution. This suggests that a three-parameter distribution would be more appropriate to describe the growth curves for the subject watercourses within HA09 (River Liffey and Santry River catchments.)
The shape of the growth curve also plays an important role in the design and operation of the flood management scheme for a river catchment. It is generally not considered appropriate to have a growth curve with the concave downward shape. A significant number of the GEV growth curves showed concave downward shape (22 out 95). In contrast, all 95 GLO growth curves are of concave upward shape.
The estimated 1%-AEP GLO growth factor is slightly greater than the GEV growth factor, for almost all 95 growth curves by an amount of 0.1 to 5% (see Table 5.9 for growth curve No. 83). This is largely due to the concavity noted above. Figure 5.9 shows a comparison of the GEV, GLO and EV1 growth curves for growth curve No. 83, all plotted in the EV1 probability plot.
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Figure 5.9: Comparison of EV1, GEV and GLO growth curves on the EV1-y probability plot (Growth Curve No. 83)
Based on the above, it is recommended to adopt the GLO distribution derived concave upward shape growth curve for the River Liffey and Santry River catchments. Figure 5.10 shows the estimated 95 GLO growth curves for the River Liffey and Santry River catchments.
Figure 5.10: GLO growth curves for 95 HEPs within HA09
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5.8 RATIONALISATION OF GROWTH CURVES
5.8.1 Relationship of Growth Factors with Catchment Characteristics
In order to reduce the number of growth curves to a practicable number, the relationship between the estimated growth factors for a range of AEPs and the relevant catchment descriptors was examined. The catchment descriptors used were the AREA, SAAR and BFI. Figure 5.11, Figure 5.12 and Figure 5.13 show the variations of growth factors with AREA, SAAR and BFI respectively for all 95 HEPs.
Figure 5.11: Relationship of growth factors with catchment areas for 95 HEPs
Figure 5.12: Relationship of growth factors with SAAR for 95 HEPs
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Figure 5.13: Relationship of growth factors with BFI for 95 HEPs
It can be seen from the above figures that the growth factors generally increase with a decrease in catchment sizes. However this rate of increase is larger for the catchment areas less than 400 km2 and also for the larger AEPs growth factors. This can be attributed to the smaller upland catchment areas where catchment response time is shorter and where no flow attenuation is available. For the larger catchments flow attenuation is generally provided by lakes and wider downstream channels. For catchment areas larger than 850 km2 the growth factors remained unchanged with the further increase in catchment area. No particular patterns in the relationships of the growth factors with the SAAR and BFI values were found.
5.8.2 Generalised Growth Curves
Based on the findings as discussed in Section 5.8.1, growth curves for the subject river catchments within HA09 were further generalised based on catchment size. To examine further the relationship of the catchment size with the growth factors and also to generalise the growth factor estimates, an additional 197 growth curve estimation points with various catchment sizes were selected on the modelled watercourses. Figure 5.6 shows the spatial distribution of these points. The catchment physiographic and climatic characteristics data associated with these additional growth curve estimation points were obtained from OPW.
Figure 5.14 shows the variation of the estimated growth factors for a range of AEPs and catchment sizes for all 292 HEPs (95 HEPs plus 197 additional points). Similar catchment size-growth factor relationships were found in this case as were found in the 95 HEPs case. It can be seen from this figure that the growth factors for catchment areas greater than 450 km2 do not change appreciably with the increase in catchment sizes. However, the variations in growth factors for the smaller catchment sizes are very significant.
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Figure 5.14: Relationship of growth factors with catchment areas (for 292 growth curve estimation points)
As a result of the above growth curves are generalised based on ranges of catchment size as shown below:
1. AREA < 10 km2 2. 10 < AREA <= 25 km2 3. 25 < AREA < = 50 km2 4. 50 < AREA < = 100 km2 5. 100 < AREA < = 150 km2 6. 150 < AREA < = 200 km2 7. 200 < AREA < = 400 km2 8. 400 < AREA < = 600 km2 9. 600 < AREA < = 800 km2 10. 800 < AREA < = 1200 km2
Table 5.10 shows the estimated average and median growth factors for the above 10 categories of growth curves along with their associated group standard deviations for a range of AEPs. The number of HEPs used for the standard deviation calculation in each of the catchment size categories is presented in column 2 of Table 5.10. It can be seen from this that the standard deviations in the 1% AEP growth factors in these catchment size categories range from 0% to 21% for the 1% AEP case. The highest variations were found in the catchment size categories of 2, 3, 4 and 6. Hence, it is recommended that the growth factors for all HEPs with catchment sizes falling in these catchment area categories (i.e. from 10 to 200 km2) be estimated from the separate growth curve estimation process. In other words, separate growth curves should be estimated for all HEPs with the catchment areas falling in range of 10 to 200 km2. For the remaining categories the median growth curves will be used.
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Table 5.10: Growth curve estimation summary
Growth factors
No of AEP (%) 50% 20% 10% 5% 2% 1% 0.50% 0.20% 0.10% Catchment size HEPs range in size Return range Period 2 5 10 20 50 100 200 500 1000 (years)
Average 1.000 1.447 1.788 2.168 2.763 3.303 3.939 4.962 5.903 1. AREA < 10 2 km 54 Median 1.000 1.452 1.797 2.180 2.780 3.323 3.961 4.985 5.925
St. dev 0.000 0.011 0.022 0.035 0.058 0.082 0.112 0.166 0.220
Average 1.000 1.442 1.776 2.146 2.722 3.241 3.850 4.824 5.714 2. 10 < AREA 2 <= 25 km 62 Median 1.000 1.443 1.781 2.158 2.746 3.278 3.902 4.900 5.815
St. dev 0.000 0.012 0.025 0.041 0.072 0.103 0.144 0.216 0.290
Average 1.000 1.408 1.709 2.037 2.534 2.974 3.482 4.276 4.989 3. 25 < AREA 2 <= 50 km 37 Median 1.000 1.408 1.708 2.034 2.526 2.960 3.459 4.238 4.933
St. dev 0.000 0.024 0.046 0.075 0.124 0.173 0.235 0.341 0.445
Average 1.000 1.377 1.651 1.946 2.388 2.775 3.216 3.900 4.506 4. 50 < AREA 2 <= 100 km 20 Median 1.000 1.394 1.680 1.987 2.446 2.848 3.307 4.018 4.648
St. dev 0.000 0.033 0.061 0.096 0.154 0.210 0.278 0.394 0.505
Average N/A N/A N/A N/A N/A N/A N/A N/A N/A 5. 100 < AREA 2 < = 150 km N/A Median N/A N/A N/A N/A N/A N/A N/A N/A N/A
St. dev N/A N/A N/A N/A N/A N/A N/A N/A N/A
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Growth factors
No of AEP (%) 50% 20% 10% 5% 2% 1% 0.50% 0.20% 0.10% Catchment size HEPs range in size Return range Period 2 5 10 20 50 100 200 500 1000 (years)
Average 1.000 1.273 1.460 1.652 1.927 2.157 2.409 2.782 3.099 6. 150 < AREA 2 < = 200 km 10 Median 1.000 1.268 1.450 1.637 1.903 2.123 2.364 2.718 3.017
St. dev 0.000 0.045 0.077 0.112 0.164 0.209 0.260 0.339 0.409
Average 1.000 1.273 1.465 1.665 1.956 2.204 2.480 2.896 3.253 7. 200 < AREA 2 < = 400 km 28 Median 1.000 1.271 1.463 1.664 1.960 2.214 2.497 2.927 3.284
St. dev 0.000 0.013 0.020 0.026 0.032 0.036 0.040 0.049 0.059
Average 1.000 1.232 1.387 1.544 1.767 1.949 2.147 2.436 2.677 8. 400 < AREA 2 < = 600 km 31 Median 1.000 1.230 1.381 1.536 1.754 1.934 2.129 2.412 2.649
St. dev 0.000 0.006 0.012 0.019 0.033 0.047 0.064 0.093 0.120
Average 1.000 1.253 1.421 1.588 1.823 2.014 2.219 2.513 2.758 9. 600 < AREA 2 < = 800 km 21 Median 1.000 1.255 1.425 1.596 1.837 2.033 2.243 2.541 2.786
St. dev 0.000 0.006 0.010 0.015 0.021 0.026 0.033 0.043 0.054
Average 1.000 1.233 1.386 1.538 1.747 1.915 2.095 2.350 2.560 10. 800 < AREA 2 < = 1200 km 29 Median 1.000 1.230 1.381 1.531 1.739 1.906 2.085 2.340 2.549
St. dev 0.000 0.010 0.018 0.027 0.042 0.055 0.071 0.096 0.118
Thus for the River Liffey and Santry River catchments the above mentioned 10 categories of catchment size have been reduced to 6 categories (hereafter called Growth Curve Groups) as
IBE0600Rp00016 101 Rev F03 Eastern CFRAM Study HA09 Hydrology Report – FINAL presented in Table 5.11. The estimated growth curve types in each category are also presented in Table 5.11.
Table 5.11: Growth Curve (GC) Groups
Growth Curve Growth curves type / Catchment size range Group No. estimation process
1 AREA < 10 km2 Use median growth curve
2 10 < AREA <= 200 km2 Use individual growth curve
3 200 < AREA < = 400 km2 Use median growth curve
4 400 < AREA < = 600 km2 Use median growth curve
5 600 < AREA < = 800 km2 Use median growth curve
6 800 < AREA <= 1200 km2 Use median growth curve
Table 5.12 presents the estimated growth factors for a range of AEPs for each of the above growth curve groups. Figure 5.15 shows the estimated growth curves (GLO) for all growth curve groups except for the GC group No. 2 (10 < AREA <= 200 km2).
Table 5.12: Growth factors for range of AEPs
GLO - Growth factors GC
Group Catchment size range AEP AEP AEP AEP AEP AEP AEP AEP AEP AEP No. 50% 20% 10% 5% 4% 2% 1% 0.5% 0.2% 0.1%
1 AREA<=10km2 1.000 1.452 1.7965 2.18 2.3145 2.78 3.323 3.961 4.985 5.925
1.229 1.384 1.542 1.595 1.767 1.954 2.157 2.455 2 10 < AREA <= 200 km2 to to to to to to to to 2.705 to 1.000 1.456 1.807 2.200 2.339 2.818 3.383 4.051 5.132 6.132
3 200 < AREA < = 400 km2 1.000 1.271 1.463 1.664 1.733 1.960 2.214 2.497 2.927 3.284
4 400 < AREA < = 600 km2 1.000 1.230 1.381 1.536 1.587 1.754 1.934 2.129 2.412 2.649
5 600 < AREA < = 800 km2 1.000 1.232 1.390 1.550 1.604 1.778 1.967 2.172 2.473 2.726
6 800 < AREA <= 1200 km2 1.000 1.230 1.381 1.531 1.581 1.739 1.906 2.085 2.340 2.549
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Figure 5.15: GLO growth curves for all Growth Curve Groups (6 No.)
The uncertainties associated with the above growth curve estimates are expressed in terms of 95% confidence interval of these estimates and were estimated from the following relationship:
X T (95 ile X T .1)% 96 se X T )( (5.8)
The standard error (se) of the growth curves is estimated in accordance with the FSU recommended methodology.
Table 5.13 presents the estimated standard errors in terms of percentage of the estimated growth factor for a range of AEPs. The upper and lower limits of the confidence interval were estimated using the above mentioned Eq. 5.8. For example, for the GC Group No. 4, the estimated 1%-AEP growth factor is 1.934 and the associated 95% upper and lower confidence limits are 2.124 and 1.744 respectively. Figure 5.16 shows the estimated growth curve along with the 95% upper and lower confidence limits for GC Group No. 4.
Table 5.13: Estimated percentage standard errors for growth factors (XT) for a range of AEPs
(source FSU Work- Package 2.2 “Frequency Analysis” Final Report – Section 13.3)
Return periods Annual Exceedance Se (X ) % (years) probabilities (%) T
2 50% 0.60 5 20% 1.00 10 10% 1.80 20 5% 2.77 25 4% 3.00 50 2% 3.90 100 1% 5.00
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Return periods Annual Exceedance Se (X ) % (years) probabilities (%) T
200 0.5% 5.94 500 0.2% 7.30 1000 0.1% 8.30
Figure 5.16: Growth Curve for GC Group No. 4 with 95% confidence limits
5.8.3 Comparison of the at-site growth curves with the pooled growth curves
The FSU programme recommended that “in the event that the at-site estimate of Q-T relation is steeper than the pooled one then consideration will have to be given to using a combination of the at-site estimate and the pooled estimate for design flow estimation”. In light of this, the at-site frequency curves (Q-T) for each of the gauging sites located only on the modelled watercourses (8 No. gauging sites) in HA09 were examined and compared with the relevant pooled frequency curves. In the case where the pooled frequency curve is flatter than the at-site curve, the design growth curves/factors should be estimated from the at-site records. If the pooled growth curve is concave downwards upwards then a two parameter distribution should be fitted to the pooled growth curve so as to avoid the upper bound.
Further the FSU study recommended that “If a very large flood is observed during the period of records the question arises as to whether it should over-ride any more modest estimate of QT obtained by a pooling group approach or whether a weighted combination of the pooling group estimate and the at-site estimate should be adopted. If a combination is used the weights to be given to the two components of the combination cannot be specified by any rule based on scientific evidence but must be chosen in an arbitrary, however one would hope a reasonable way.”
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Table 5.14 shows the hydrometric gauges (7 gauging sites) located on the HA09 modelled watercourses. The estimated pooled growth curves associated with these gauges are also included therein.
Table 5.14: Hydrometric gauging stations located on the modelled watercourses in HA09 hydrometric area
Catchment Growth Curve Stations WATERBODY LOCATION Area (km2) Group No.
09001 Ryewater Leixlip 208.66 GC03
09002 Griffeen Lucan 34.56 GC02
09024 Morell Morell Bridge 98.40 GC02
09035 Camac Killeen Road 37.14 GC02
09048 Ryewater Anne's Bridge 59.67 GC02
09049 Lyreen Maynooth 87.51 GC02
09102 Santry Cadbury’s 10.90 GC02
Figure 5.17 shows the comparisons of the At-site and Regional Flood Frequency (AFF & RFF) curves for the above mentioned hydrometric gauging sites. The EV1 distribution was used for these comparisons. In addition to the frequency curves, the 95%ile confidence intervals associated with the regional estimates were also included in these plots. The EV1 straight line was used as an indicative descriptor of the at-site distribution, rather than a GEV or GLO curve, because the latter when fitted at- site, is liable to be misleading because of the large standard error involved in the shape parameter particularly. This was used for those stations where the individual AMAX series standardised growth curves were different considerably, in some cases, from the pooling growth curve. In such cases, EV1 regional growth curves were used instead of GLO curves; because the nature of the adjustment implies that an appropriate curved shape could not be determined with more accuracy than that of a straight line i.e. preserving with a curved growth curve in such cases would be an “illusion of accuracy”.
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Figure 5.17: The at-site and pooled frequency curves along with the 95% confidence intervals
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It can be seen from the above frequency curves that at 5 sites (out of 7), the AFF curves are steeper than the RFF curves, suggesting that the regional curves severely underestimate when compared with a considerable number of observed floods at these stations.
If an AFF curve lies below the confidence limits of the RFF curve then we consider it prudent to adopt the RFF curve as the design curve, on the basis that the observed flood record has, by chance, fallen below the regional average and that there is a chance or possibility that the record of the next 20 or 30 years will revert to resembling the RFF curve rather than reproduce a re-occurrence of the recent past. It has to be acknowledged that this type of decision may lead to a degree of over-design but it is recommended that this be knowingly accepted.
On the other hand if an AFF curve lies above the RFF curve, then we consider it prudent to take account of both when deciding on the design curve/flood. This could be done by calculating a weighted average of the two curves. The relative weights should be decided, on a case by case basis, following examination of the degree of difference between the two curves, including consideration of the confidence limits of the RFF curve, shape of the at-site probability plot and the number of observed large outliers in the data series.
At hydrometric station 09001 (Ryewater River at Leixlip) more than 50% of the observed flood values plot above the RFF curve (Figure 5.17). The at-site curve has a strong case for defining the design growth curve for this station; or, this at-site growth curve might be combined with the RFF growth curve with a large weight for the at-site curve (say 0.80 for at-site + 0.2 for regional curve). Also Stations 09002, 09035, 09048 and 09049 follow the same behaviour (Figure 5.17); weights for calculating the design growth curve could be (0.9 for at-site value + 0.1 for regional value). However some of these stations were either not classified under FSU or were given classifications that would suggest high uncertainty in their ratings above Qmed. At these stations, namely 09035, 09048 and 09049, there may be significant uncertainty in the ratings and hence the flood flow values which could result in a skewed AFF curve. Furthermore, from the rating reviews it can be shown that even at stations which have a rating with high certainty at flood flows there may have been changes within the catchment which have resulted in a skew to the AFF curve. An example of this would be at the Lucan gauging station where urbanisation has resulted in increasing magnitudes of peak flood flows which when considered within a record representing years where the catchment was rural will lead to an unrealistic steepness in the AFF growth curve.
It was considered prudent to include these stations within the pooling groups to maximise the quantity of geographically close data while any skew in the data would likely be balanced out by the quantity of other stations. However allowing these potentially skewed series to dictate the growth curve is not considered prudent. In light of this no adjustments were applied to the HA09 growth curves to favour at-site behaviour.
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5.8.4 Growth factors for all HEPs within HA09
Based on the catchment sizes associated with each of the 220 HEPs, the relevant estimated growth factors for a range of AEPs are presented in Table 5.15 below.
Table 5.15: Growth factors for all 220 HEPs for a range of AEPs for the subject watercourses within HA09 (River Liffey and Santry River catchments)
Growth factors (XT)
Node AREA 1% AEP 0.2% AEP 0.1% AEP No. Node ID_CFRAMS (km2) Lower Upper Lower Upper Lower Upper XT XT XT 95%ile 95%ile 95%ile 95%ile 95%ile 95%ile
1 09_1507_6_RPS 8.93 2.997 3.323 3.649 4.272 4.985 5.698 4.961 5.925 6.889
2 09_1502_1_RPS 1.65 2.997 3.323 3.649 4.272 4.985 5.698 4.961 5.925 6.889
3 09102_RPS 10.90 2.997 3.323 3.649 4.272 4.985 5.698 4.961 5.925 6.889
4 09_1156_1 1.06 2.997 3.323 3.649 4.272 4.985 5.698 4.961 5.925 6.889
5 09_475_3_RPS 1.74 2.997 3.323 3.649 4.272 4.985 5.698 4.961 5.925 6.889
6 09_613_3_RPS 1.31 2.997 3.323 3.649 4.272 4.985 5.698 4.961 5.925 6.889
7 09_452_2_RPS 0.52 2.997 3.323 3.649 4.272 4.985 5.698 4.961 5.925 6.889
8 09_36_2 1.81 2.997 3.323 3.649 4.272 4.985 5.698 4.961 5.925 6.889
9 09_221_3 11.38 3.005 3.331 3.657 4.292 5.009 5.726 4.990 5.960 6.930
10 09_242_3_RPS 34.66 2.628 2.913 3.198 3.537 4.127 4.717 4.003 4.781 5.559
11 UN_Trib_Camac_10 0.14 2.997 3.323 3.649 4.272 4.985 5.698 4.961 5.925 6.889
12 09_1165_5 3.53 2.997 3.323 3.649 4.272 4.985 5.698 4.961 5.925 6.889
13 09_1237_4_RPS 6.43 2.997 3.323 3.649 4.272 4.985 5.698 4.961 5.925 6.889 09_1870_13_RPS_R 14 ev01 829.43 1.719 1.906 2.093 2.005 2.340 2.675 2.134 2.549 2.964
15 09_1872_9_RPS 60.79 2.570 2.849 3.128 3.456 4.033 4.610 3.913 4.673 5.433
16 09_1874_17_RPS 12.17 2.997 3.323 3.649 4.272 4.985 5.698 4.961 5.925 6.889
17 09_1136_U 0.20 2.997 3.323 3.649 4.272 4.985 5.698 4.961 5.925 6.889
18 09_1128_U 0.02 2.997 3.323 3.649 4.272 4.985 5.698 4.961 5.925 6.889
19 09_1142_U 0.28 2.997 3.323 3.649 4.272 4.985 5.698 4.961 5.925 6.889
20 09_1029_U 0.77 2.997 3.323 3.649 4.272 4.985 5.698 4.961 5.925 6.889
21 09_1252_U 0.81 2.997 3.323 3.649 4.272 4.985 5.698 4.961 5.925 6.889
22 09_832_U 1.63 2.997 3.323 3.649 4.272 4.985 5.698 4.961 5.925 6.889
23 09_1243_U 0.02 2.997 3.323 3.649 4.272 4.985 5.698 4.961 5.925 6.889
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Growth factors (XT)
Node AREA 1% AEP 0.2% AEP 0.1% AEP No. Node ID_CFRAMS (km2) Lower Upper Lower Upper Lower Upper XT XT XT 95%ile 95%ile 95%ile 95%ile 95%ile 95%ile
24 09_627_U 0.80 2.997 3.323 3.649 4.272 4.985 5.698 4.961 5.925 6.889
25 09_628_U 0.03 2.997 3.323 3.649 4.272 4.985 5.698 4.961 5.925 6.889
26 09_396_U 0.25 2.997 3.323 3.649 4.272 4.985 5.698 4.961 5.925 6.889
27 09_435_U 0.04 2.997 3.323 3.649 4.272 4.985 5.698 4.961 5.925 6.889
28 09_481_U 3.99 2.997 3.323 3.649 4.272 4.985 5.698 4.961 5.925 6.889
29 09_1131_U 0.01 2.997 3.323 3.649 4.272 4.985 5.698 4.961 5.925 6.889
30 09_613_U 0.08 2.997 3.323 3.649 4.272 4.985 5.698 4.961 5.925 6.889
31 09_475_U 0.00 2.997 3.323 3.649 4.272 4.985 5.698 4.961 5.925 6.889
32 09_UN_T03_U 0.02 2.997 3.323 3.649 4.272 4.985 5.698 4.961 5.925 6.889
33 09_39_U 0.00 2.997 3.323 3.649 4.272 4.985 5.698 4.961 5.925 6.889
34 09_1308_U 0.02 2.997 3.323 3.649 4.272 4.985 5.698 4.961 5.925 6.889
35 09_452_U 0.01 2.997 3.323 3.649 4.272 4.985 5.698 4.961 5.925 6.889
36 TBC 0.00 2.997 3.323 3.649 4.272 4.985 5.698 4.961 5.925 6.889
37 09_990_U 1.19 2.997 3.323 3.649 4.272 4.985 5.698 4.961 5.925 6.889
38 09_606_U 0.00 2.997 3.323 3.649 4.272 4.985 5.698 4.961 5.925 6.889
39 09_448_U 0.12 2.997 3.323 3.649 4.272 4.985 5.698 4.961 5.925 6.889
40 UN_Trib_Griffn_U 0.00 2.997 3.323 3.649 4.272 4.985 5.698 4.961 5.925 6.889
41 09_37_U 0.27 2.997 3.323 3.649 4.272 4.985 5.698 4.961 5.925 6.889
42 09_UN_T01_U 0.25 2.997 3.323 3.649 4.272 4.985 5.698 4.961 5.925 6.889
43 UN_Inter_Camac_1 0.10 2.997 3.323 3.649 4.272 4.985 5.698 4.961 5.925 6.889
44 TBC 0.00 2.997 3.323 3.649 4.272 4.985 5.698 4.961 5.925 6.889
45 UN_Trib_Camac_20 0.23 2.997 3.323 3.649 4.272 4.985 5.698 4.961 5.925 6.889
46 TBC 0.00 2.997 3.323 3.649 4.272 4.985 5.698 4.961 5.925 6.889
47 UN_Trib_Griffn_1 0.04 2.997 3.323 3.649 4.272 4.985 5.698 4.961 5.925 6.889
48 09_832_1 2.65 2.997 3.323 3.649 4.272 4.985 5.698 4.961 5.925 6.889
49 09_1308_1 0.18 2.997 3.323 3.649 4.272 4.985 5.698 4.961 5.925 6.889
50 TBC 0.00 2.997 3.323 3.649 4.272 4.985 5.698 4.961 5.925 6.889
51 09002_RPS 34.56 2.628 2.913 3.198 3.537 4.127 4.717 4.003 4.781 5.559
52 09_1874_10_RPS 8.11 2.997 3.323 3.649 4.272 4.985 5.698 4.961 5.925 6.889
53 09_1874_5_RPS 5.44 2.997 3.323 3.649 4.272 4.985 5.698 4.961 5.925 6.889
IBE0600Rp00016 109 Rev F03 Eastern CFRAM Study HA09 Hydrology Report – FINAL
Growth factors (XT)
Node AREA 1% AEP 0.2% AEP 0.1% AEP No. Node ID_CFRAMS (km2) Lower Upper Lower Upper Lower Upper XT XT XT 95%ile 95%ile 95%ile 95%ile 95%ile 95%ile
54 09_1242_2_RPS 7.81 2.997 3.323 3.649 4.272 4.985 5.698 4.961 5.925 6.889
55 09_1243_1 2.74 2.997 3.323 3.649 4.272 4.985 5.698 4.961 5.925 6.889
56 UN_Trib_Camac_U 1.48 2.997 3.323 3.649 4.272 4.985 5.698 4.961 5.925 6.889
57 09_448_1 0.37 2.997 3.323 3.649 4.272 4.985 5.698 4.961 5.925 6.889
58 09_UN_T02_1 0.27 2.997 3.323 3.649 4.272 4.985 5.698 4.961 5.925 6.889
59 09_UN_T02_U 0.00 2.997 3.323 3.649 4.272 4.985 5.698 4.961 5.925 6.889
60 09_UN_T03_1 0.20 2.997 3.323 3.649 4.272 4.985 5.698 4.961 5.925 6.889
61 09_499_1_RPS 27.72 2.744 3.042 3.340 3.774 4.404 5.034 4.315 5.153 5.991
62 09_360_4_RPS 6.89 2.997 3.323 3.649 4.272 4.985 5.698 4.961 5.925 6.889
63 09_499_3_RPS 28.89 2.744 3.042 3.340 3.774 4.404 5.034 4.315 5.153 5.991
64 09_39_1 1.49 2.997 3.323 3.649 4.272 4.985 5.698 4.961 5.925 6.889
65 09_606_1 0.05 2.997 3.323 3.649 4.272 4.985 5.698 4.961 5.925 6.889
66 09_UN_T01_1 0.30 2.997 3.323 3.649 4.272 4.985 5.698 4.961 5.925 6.889
67 09_618_5 1.98 2.997 3.323 3.649 4.272 4.985 5.698 4.961 5.925 6.889
68 09_586_3 4.07 2.997 3.323 3.649 4.272 4.985 5.698 4.961 5.925 6.889
69 09_464_1 1.01 2.997 3.323 3.649 4.272 4.985 5.698 4.961 5.925 6.889
70 09_472_4_RPS 8.51 2.997 3.323 3.649 4.272 4.985 5.698 4.961 5.925 6.889
71 09_472_8_RPS 10.10 2.997 3.323 3.649 4.272 4.985 5.698 4.961 5.925 6.889
72 09_37_1 0.41 2.997 3.323 3.649 4.272 4.985 5.698 4.961 5.925 6.889
73 09_435_1_RPS 1.22 2.997 3.323 3.649 4.272 4.985 5.698 4.961 5.925 6.889
74 09_1870_14_Rev01 830.66 1.719 1.906 2.093 2.005 2.340 2.675 2.134 2.549 2.964
09_1870_7_RPS_Re 75 v01 821.25 1.719 1.906 2.093 2.005 2.340 2.675 2.134 2.549 2.964
09_1870_8_RPS_Re 76 v01 821.73 1.719 1.906 2.093 2.005 2.340 2.675 2.134 2.549 2.964
77 09_1142_1 0.73 2.997 3.323 3.649 4.272 4.985 5.698 4.961 5.925 6.889
78 09_1128_1 0.21 2.997 3.323 3.649 4.272 4.985 5.698 4.961 5.925 6.889
79 09_1136_1 0.54 2.997 3.323 3.649 4.272 4.985 5.698 4.961 5.925 6.889
80 UN_Trib_Griff_U 1.71 2.997 3.323 3.649 4.272 4.985 5.698 4.961 5.925 6.889
81 UN_Trib_Griff_1 4.81 2.997 3.323 3.649 4.272 4.985 5.698 4.961 5.925 6.889
82 UN_Trib_Camac_1 2.58 2.997 3.323 3.649 4.272 4.985 5.698 4.961 5.925 6.889
IBE0600Rp00016 110 Rev F03 Eastern CFRAM Study HA09 Hydrology Report – FINAL
Growth factors (XT)
Node AREA 1% AEP 0.2% AEP 0.1% AEP No. Node ID_CFRAMS (km2) Lower Upper Lower Upper Lower Upper XT XT XT 95%ile 95%ile 95%ile 95%ile 95%ile 95%ile
83 09_396_1 0.86 2.997 3.323 3.649 4.272 4.985 5.698 4.961 5.925 6.889
84 09005_RPS_Rev01 40.56 2.762 3.062 3.362 3.806 4.441 5.076 4.354 5.200 6.046
85 09035_RPS_Rev01 42.44 2.670 2.960 3.250 3.632 4.238 4.844 4.130 4.933 5.736
86 09_1655_5 1.81 2.997 3.323 3.649 4.272 4.985 5.698 4.961 5.925 6.889 09_1870_13_RPS_R 87 ev01 829.43 1.719 1.906 2.093 2.005 2.340 2.675 2.134 2.549 2.964
88 09_346_3 2.37 2.997 3.323 3.649 4.272 4.985 5.698 4.961 5.925 6.889
89 09_1245_6_RPS 2.98 2.997 3.323 3.649 4.272 4.985 5.698 4.961 5.925 6.889
90 09_727_2_RPS 0.37 2.997 3.323 3.649 4.272 4.985 5.698 4.961 5.925 6.889
91 09_467_8 3.43 2.997 3.323 3.649 4.272 4.985 5.698 4.961 5.925 6.889
92 09_426_5_RPS 12.60 2.946 3.266 3.586 4.189 4.888 5.587 4.860 5.804 6.748
93 09_1069_2_RPS 6.52 2.997 3.323 3.649 4.272 4.985 5.698 4.961 5.925 6.889
94 09_1137_5 4.86 2.997 3.323 3.649 4.272 4.985 5.698 4.961 5.925 6.889
95 09_501_7_RPS 12.76 2.663 2.952 3.241 3.607 4.209 4.811 4.094 4.890 5.686
96 09_292_1_RPS 494.10 1.744 1.934 2.124 2.067 2.412 2.757 2.218 2.649 3.080
97 09_1246_U 0.02 2.997 3.323 3.649 4.272 4.985 5.698 4.961 5.925 6.889
98 09_1050_U 0.00 2.997 3.323 3.649 4.272 4.985 5.698 4.961 5.925 6.889
99 09_1579_U 2.00 2.997 3.323 3.649 4.272 4.985 5.698 4.961 5.925 6.889
100 09_994_U 0.00 2.997 3.323 3.649 4.272 4.985 5.698 4.961 5.925 6.889
101 09_1245_U 0.76 2.997 3.323 3.649 4.272 4.985 5.698 4.961 5.925 6.889
102 09_467_U 1.33 2.997 3.323 3.649 4.272 4.985 5.698 4.961 5.925 6.889
103 09_1126_U 0.26 2.997 3.323 3.649 4.272 4.985 5.698 4.961 5.925 6.889
104 09_727_U 0.06 2.997 3.323 3.649 4.272 4.985 5.698 4.961 5.925 6.889
105 09_994_1 1.52 2.997 3.323 3.649 4.272 4.985 5.698 4.961 5.925 6.889
106 09001_RPS 208.66 1.997 2.214 2.431 2.508 2.927 3.346 2.750 3.284 3.818
107 09_1137_2 3.86 2.997 3.323 3.649 4.272 4.985 5.698 4.961 5.925 6.889
108 09_1246_1 0.56 2.997 3.323 3.649 4.272 4.985 5.698 4.961 5.925 6.889
109 09_1050_1 0.87 2.997 3.323 3.649 4.272 4.985 5.698 4.961 5.925 6.889
110 09_584_4_RPS 5.34 2.997 3.323 3.649 4.272 4.985 5.698 4.961 5.925 6.889
111 09_501_U 1.39 2.997 3.323 3.649 4.272 4.985 5.698 4.961 5.925 6.889
112 UN_Trib_Liffey_U 2.12 2.997 3.323 3.649 4.272 4.985 5.698 4.961 5.925 6.889
IBE0600Rp00016 111 Rev F03 Eastern CFRAM Study HA09 Hydrology Report – FINAL
Growth factors (XT)
Node AREA 1% AEP 0.2% AEP 0.1% AEP No. Node ID_CFRAMS (km2) Lower Upper Lower Upper Lower Upper XT XT XT 95%ile 95%ile 95%ile 95%ile 95%ile 95%ile
113 UN_Trib_Liffey_Inter 4.04 2.997 3.323 3.649 4.272 4.985 5.698 4.961 5.925 6.889
114 09_501_Trib 0.00 2.997 3.323 3.649 4.272 4.985 5.698 4.961 5.925 6.889
115 09_501_Inter 10.31 3.028 3.357 3.686 4.348 5.074 5.800 5.067 6.051 7.035
116 09_501_Inter_1 11.49 3.028 3.357 3.686 4.348 5.074 5.800 5.067 6.051 7.035
117 UN_Trib_Liffey_1 5.21 2.997 3.323 3.649 4.272 4.985 5.698 4.961 5.925 6.889
118 09_1126_1 1.09 2.997 3.323 3.649 4.272 4.985 5.698 4.961 5.925 6.889
119 09_300_1_RPS 502.27 1.744 1.934 2.124 2.067 2.412 2.757 2.218 2.649 3.080
120 09_299_3_RPS 498.57 1.744 1.934 2.124 2.067 2.412 2.757 2.218 2.649 3.080
121 09_294_1_RPS 491.32 1.744 1.934 2.124 2.067 2.412 2.757 2.218 2.649 3.080
122 09_1668_2_RPS 492.41 1.744 1.934 2.124 2.067 2.412 2.757 2.218 2.649 3.080
123 09_1668_2_RPS 492.41 1.744 1.934 2.124 2.067 2.412 2.757 2.218 2.649 3.080
124 09_246_4_RPS 209.26 1.997 2.214 2.431 2.508 2.927 3.346 2.750 3.284 3.818
125 09006_RPS_Rev02 497.03 1.744 1.934 2.124 2.067 2.412 2.757 2.218 2.649 3.080
126 09022_RPS_Rev02 732.55 1.774 1.967 2.160 2.119 2.473 2.827 2.283 2.726 3.169
127 09_600_2 12.02 2.946 3.266 3.586 4.189 4.888 5.587 4.860 5.804 6.748
128 09_1444_4 1.60 2.997 3.323 3.649 4.272 4.985 5.698 4.961 5.925 6.889
129 09_1839_12_RPS 17.91 2.990 3.315 3.640 4.254 4.964 5.674 4.936 5.895 6.854
130 09_468_3 9.57 2.997 3.323 3.649 4.272 4.985 5.698 4.961 5.925 6.889
131 09_611_3 87.64 2.392 2.652 2.912 3.151 3.677 4.203 3.537 4.224 4.911
132 09_1060_3 18.00 3.015 3.343 3.671 4.309 5.028 5.747 5.008 5.981 6.954
133 09_1450_U 0.00 2.997 3.323 3.649 4.272 4.985 5.698 4.961 5.925 6.889
134 09_1464_5 66.96 2.609 2.892 3.175 3.530 4.119 4.708 4.007 4.785 5.563
135 09_1464_2 65.24 2.609 2.892 3.175 3.530 4.119 4.708 4.007 4.785 5.563
136 09_1464_1_RPS 13.64 2.990 3.315 3.640 4.256 4.967 5.678 4.940 5.900 6.860
137 09_1444_U 1.05 2.997 3.323 3.649 4.272 4.985 5.698 4.961 5.925 6.889
138 9048 59.67 2.743 3.041 3.339 3.790 4.423 5.056 4.343 5.187 6.031
139 9049 87.51 2.392 2.652 2.912 3.151 3.677 4.203 3.537 4.224 4.911
140 09_1839_7 11.29 2.997 3.323 3.649 4.272 4.985 5.698 4.961 5.925 6.889
141 09_1452_2_RPS 49.10 2.783 3.085 3.387 3.848 4.491 5.134 4.410 5.267 6.124
142 09_1251_4 1.76 2.997 3.323 3.649 4.272 4.985 5.698 4.961 5.925 6.889
IBE0600Rp00016 112 Rev F03 Eastern CFRAM Study HA09 Hydrology Report – FINAL
Growth factors (XT)
Node AREA 1% AEP 0.2% AEP 0.1% AEP No. Node ID_CFRAMS (km2) Lower Upper Lower Upper Lower Upper XT XT XT 95%ile 95%ile 95%ile 95%ile 95%ile 95%ile
143 09_1535_7_RPS 14.87 2.972 3.295 3.618 4.258 4.969 5.680 4.959 5.923 6.887
144 09_566_U 5.55 2.997 3.323 3.649 4.272 4.985 5.698 4.961 5.925 6.889
145 09_1251_1 1.05 2.997 3.323 3.649 4.272 4.985 5.698 4.961 5.925 6.889
146 09_566_1 5.98 2.997 3.323 3.649 4.272 4.985 5.698 4.961 5.925 6.889
147 09_181_1 19.71 2.901 3.216 3.531 4.092 4.775 5.458 4.731 5.650 6.569
148 09_1535_1 12.16 2.898 3.213 3.528 4.087 4.769 5.451 4.724 5.642 6.560
149 09_1853_7_RPS 5.69 2.997 3.323 3.649 4.272 4.985 5.698 4.961 5.925 6.889
150 TBC 29.09 2.663 2.952 3.241 3.631 4.237 4.843 4.136 4.940 5.744
151 09_782_3_RPS 5.43 2.997 3.323 3.649 4.272 4.985 5.698 4.961 5.925 6.889
152 09_1210_2_RPS 1.30 2.997 3.323 3.649 4.272 4.985 5.698 4.961 5.925 6.889
153 09_1490_7 8.20 2.997 3.323 3.649 4.272 4.985 5.698 4.961 5.925 6.889
154 09_200_2_RPS 13.46 2.997 3.323 3.649 4.274 4.988 5.702 4.964 5.929 6.894
155 09_1533_U 0.02 2.997 3.323 3.649 4.272 4.985 5.698 4.961 5.925 6.889
156 09_356_U 11.96 3.051 3.383 3.715 4.398 5.132 5.866 5.134 6.132 7.130
157 09_322_U 0.01 2.997 3.323 3.649 4.272 4.985 5.698 4.961 5.925 6.889
158 09_454_Trib 19.17 2.884 3.197 3.510 4.055 4.732 5.409 4.682 5.592 6.502
159 09_429_3 5.01 2.997 3.323 3.649 4.272 4.985 5.698 4.961 5.925 6.889
160 09_1649_2_RPS 2.49 2.997 3.323 3.649 4.272 4.985 5.698 4.961 5.925 6.889
161 09_322_1 0.24 2.997 3.323 3.649 4.272 4.985 5.698 4.961 5.925 6.889
162 09_454_Inter 18.74 2.884 3.197 3.510 4.055 4.732 5.409 4.682 5.592 6.502
163 09_321_1_RPS 18.63 2.884 3.197 3.510 4.055 4.732 5.409 4.682 5.592 6.502
164 09_1649_9_RPS 5.93 2.997 3.323 3.649 4.272 4.985 5.698 4.961 5.925 6.889
165 TBC 0.00 2.997 3.323 3.649 4.272 4.985 5.698 4.961 5.925 6.889
166 09_1534_U 0.00 2.997 3.323 3.649 4.272 4.985 5.698 4.961 5.925 6.889
167 TBC 0.00 2.997 3.323 3.649 4.272 4.985 5.698 4.961 5.925 6.889
168 TBC 27.40 2.563 2.842 3.121 3.425 3.997 4.569 3.865 4.616 5.367
169 09_1490_DSL 0.00 2.997 3.323 3.649 4.272 4.985 5.698 4.961 5.925 6.889
170 09_411_5_RPS 4.63 2.997 3.323 3.649 4.272 4.985 5.698 4.961 5.925 6.889
171 09_1055_3_RPS 41.96 2.670 2.96 3.250 3.632 4.238 4.844 4.130 4.933 5.736
172 09_371_U 0.05 2.997 3.323 3.649 4.272 4.985 5.698 4.961 5.925 6.889
IBE0600Rp00016 113 Rev F03 Eastern CFRAM Study HA09 Hydrology Report – FINAL
Growth factors (XT)
Node AREA 1% AEP 0.2% AEP 0.1% AEP No. Node ID_CFRAMS (km2) Lower Upper Lower Upper Lower Upper XT XT XT 95%ile 95%ile 95%ile 95%ile 95%ile 95%ile
173 09_707_U 0.18 2.997 3.323 3.649 4.272 4.985 5.698 4.961 5.925 6.889
174 09024_RPS 98.40 2.192 2.430 2.668 2.794 3.260 3.726 3.091 3.692 4.293
175 09036_RPS 47.16 2.621 2.906 3.191 3.557 4.151 4.745 4.044 4.830 5.616
176 09_1557_3_RPS 0.40 2.997 3.323 3.649 4.272 4.985 5.698 4.961 5.925 6.889
177 09_1305_2_RPS 5.93 2.997 3.323 3.649 4.272 4.985 5.698 4.961 5.925 6.889
178 UN_Morrell_U 0.54 2.997 3.323 3.649 4.272 4.985 5.698 4.961 5.925 6.889
179 09_1597_1 0.19 2.997 3.323 3.649 4.272 4.985 5.698 4.961 5.925 6.889
180 09_371_1 1.26 2.997 3.323 3.649 4.272 4.985 5.698 4.961 5.925 6.889
181 09_540_6_RPS 7.19 2.997 3.323 3.649 4.272 4.985 5.698 4.961 5.925 6.889
182 09_1602_1_RPS 17.00 2.796 3.100 3.404 3.891 4.541 5.191 4.473 5.342 6.211
183 09_706_1 0.35 2.997 3.323 3.649 4.272 4.985 5.698 4.961 5.925 6.889
184 UN_Morrell_1 2.19 2.997 3.323 3.649 4.272 4.985 5.698 4.961 5.925 6.889
185 9027 12.40 2.833 3.141 3.449 3.969 4.632 5.295 4.577 5.466 6.355
186 09045_RPS 47.21 2.621 2.906 3.191 3.557 4.151 4.745 4.044 4.830 5.616
187 09044_RPS 28.77 2.675 2.966 3.257 3.658 4.269 4.880 4.172 4.983 5.794
188 09_1627_6_RPS 98.49 2.192 2.430 2.668 2.794 3.260 3.726 3.091 3.692 4.293
189 09_1306_1 11.92 2.833 3.141 3.449 3.969 4.632 5.295 4.577 5.466 6.355
190 09_542_3_RPS 11.07 3.001 3.327 3.653 4.301 5.019 5.737 5.009 5.982 6.955
191 09_1118_6 20.78 2.960 3.282 3.604 4.216 4.920 5.624 4.897 5.848 6.799
192 09_542_Inter 13.93 2.953 3.274 3.595 4.198 4.899 5.600 4.871 5.817 6.763
193 09047_RPS 41.90 2.670 2.960 3.250 3.632 4.238 4.844 4.130 4.933 5.736
194 09_1650_9 4.18 2.997 3.323 3.649 4.272 4.985 5.698 4.961 5.925 6.889
195 09_1211_2_RPS 22.37 2.980 3.304 3.628 4.238 4.946 5.654 4.917 5.872 6.827
196 09_1650_U 0.27 2.997 3.323 3.649 4.272 4.985 5.698 4.961 5.925 6.889
197 09_363_U 0.13 2.997 3.323 3.649 4.272 4.985 5.698 4.961 5.925 6.889
198 09_1154_U 0.34 2.997 3.323 3.649 4.272 4.985 5.698 4.961 5.925 6.889
199 09_1517_U 0.54 2.997 3.323 3.649 4.272 4.985 5.698 4.961 5.925 6.889
200 09_588_2_RPS 4.61 2.997 3.323 3.649 4.272 4.985 5.698 4.961 5.925 6.889
201 09_1517_1 0.93 2.997 3.323 3.649 4.272 4.985 5.698 4.961 5.925 6.889
202 09_1519_2_RPS 161.15 1.763 1.954 2.145 2.104 2.455 2.806 2.265 2.705 3.145
IBE0600Rp00016 114 Rev F03 Eastern CFRAM Study HA09 Hydrology Report – FINAL
Growth factors (XT)
Node AREA 1% AEP 0.2% AEP 0.1% AEP No. Node ID_CFRAMS (km2) Lower Upper Lower Upper Lower Upper XT XT XT 95%ile 95%ile 95%ile 95%ile 95%ile 95%ile
203 09_1518_4_RPS 157.07 1.763 1.954 2.145 2.104 2.455 2.806 2.265 2.705 3.145
204 09_1154_1 0.51 2.997 3.323 3.649 4.272 4.985 5.698 4.961 5.925 6.889
205 09_1281_2 38.41 2.509 2.782 3.055 3.340 3.898 4.456 3.764 4.495 5.226
206 09_1011_7 15.21 2.796 3.100 3.404 3.891 4.541 5.191 4.473 5.342 6.211
207 09_1119_5 33.49 2.162 2.397 2.632 2.732 3.188 3.644 3.011 3.596 4.181
208 09007_RPS 7.03 2.997 3.323 3.649 4.272 4.985 5.698 4.961 5.925 6.889
209 09_1296_U 0.00 2.997 3.323 3.649 4.272 4.985 5.698 4.961 5.925 6.889
210 09_1519_14_RPS 187.75 1.778 1.971 2.164 2.124 2.479 2.834 2.288 2.733 3.178
211 09_1519_16_RPS 196.82 1.778 1.971 2.164 2.124 2.479 2.834 2.288 2.733 3.178
212 09_1519_8_RPS 165.88 1.763 1.954 2.145 2.104 2.455 2.806 2.265 2.705 3.145
213 09_1650_2 1.22 2.997 3.323 3.649 4.272 4.985 5.698 4.961 5.925 6.889
214 09_DSL_01 0.00 2.997 3.323 3.649 4.272 4.985 5.698 4.961 5.925 6.889
215 09_625_U 0.34 2.997 3.323 3.649 4.272 4.985 5.698 4.961 5.925 6.889
216 09_581_U 0.80 2.997 3.323 3.649 4.272 4.985 5.698 4.961 5.925 6.889
217 09_591_U 0.22 2.997 3.323 3.649 4.272 4.985 5.698 4.961 5.925 6.889
218 09_591_1 0.69 2.997 3.323 3.649 4.272 4.985 5.698 4.961 5.925 6.889
219 09_605_2_RPS 2.69 2.997 3.323 3.649 4.272 4.985 5.698 4.961 5.925 6.889
220 09_1876_5_RPS 8.14 2.997 3.323 3.649 4.272 4.985 5.698 4.961 5.925 6.889
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The design flood flows for any required AEP will be calculated by multiplying the Index Flood, Qmed of each HEP by the above estimated relevant growth factors. The Qmed at gauged sites will be estimated from the observed AMAX series supplemented with additional simulated gauge years through rainfall run-off modelling (MIKE NAM). For the ungauged sites Qmed will be estimated from the FSU and IH 124 recommended catchment descriptors based methodologies and through the use of rainfall run-off (MIKE NAM) modelling to simulate flow records and hence produce a simulated AMAX record at the ungauged site.
It should be noted here that any uncertainties in the design flood estimates obtained from the index- flood method generally result from the uncertainties associated with both the index-flood (Qmed) and growth factor estimates. The uncertainties in the growth factor estimates can result both from the sampling variability and misspecification of the growth curve distribution. The sampling error is considered to be small due to the larger record lengths (pooled records) used in the estimation process.
Furthermore, it should also be noted here that, any allowances for future climate change in the design flood flow estimate should be applied to the median flow estimates. Any effects of the climate change on the growth curves are expected to be minimal.
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5.9 COMPARISON WITH FSR GROWTH FACTORS
A comparison of the estimated growth factors for HA09 was carried out with the FSR and Greater Dublin Strategic Drainage Study (GDSDS) and Fingal East Meath Flood Risk Assessment and Management Study (FEM-FRAM) growth factors for a range of AEPs as can be seen in Table 5.16. All growth curves were indexed to the median annual maximum flows (Qmed).
Table 5.16: Study growth factors compared with FSR, GDSDS and FEM-FRAM growth factors
AEP (%) 50% 20% 10% 4% 2% 1% 0.5% 0.2% 0.1%
Eastern 1.224 1.370 1.561 1.710 1.865 2.028 2.257 2.442 CFRAM Study 1.000 to to to to to to to to HA09 1.457 1.808 2.339 2.818 3.383 4.051 5.132 6.132
Average of HA09 1.000 1.356 1.615 1.992 2.319 2.693 3.123 3.797 4.401
FSR 1.000 1.260 1.450 1.630 1.870 2.060 2.620 2.530 2.750
FEM-FRAMS 1.000 1.520 1.890 2.380 2.760 3.160 3.570 - 4.600
GDSDS 1.000 1.470 1.850 2.230 2.530 2.830 3.150 - -
It can be noticed from Table 5.16 that the study area growth factors (average values) are slightly higher than the FSR growth factors. In contrast, the GDSDS and HA08 (FEM-FRAMS Study area) growth factors are slightly higher for some AEPs than the average HA09 growth factors. These higher values of growth factors for the FEM-FRAMS study can be attributed to the steeper nature of the smaller river catchments and the pooling region from which the AMAX records were pooled. It should be noted here that in the FEMFRAM study only one pooling group and/or regional growth curve was developed for all HEPs.
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5.10 GROWTH CURVE DEVELOPMENT SUMMARY
Growth curves for all HEPs were estimated from the regional flood frequency analysis technique as recommended in the FEH, FSU and FSR studies (Region of Influence Approach).
Annual Maximum Flow Records (AMAX) from the 92 hydrometric stations located in the Eastern and South Eastern Region of Ireland were pooled for estimating the pooled growth curves for 220 HEPs. The selection of this pooling region was based on the similarity of catchment characteristics both in terms of climatic and physiographic characteristics. The size of a pooling group associated with each of the HEPs was determined based on the FEH recommended 5T rule (with a minimum of 500 station- years AMAX series for each pooled growth curve). The pooling process was based on the FSU recommended catchment characteristics based (AREA, SAAR and BFI) distance measures between the subject and donor sites.
The statistical distribution suitable for a pooled growth curve was determined based on a number of factors such as - the suitability of this distribution for fitting the contributory stations’ at-site AMAX series, the number of distribution parameters and shape of the growth curves (concave upward or concave downward). Four flood like distributions namely, the EV1, LN2, GEV and GLO distributions were considered. The three-parameter GLO distribution was found to be the best suited distribution in all respects and therefore was chosen as the growth curve distribution for all HEPs in HA09.
Initially, growth curves for each of the 220 HEPs in HA09 were estimated separately. Subsequently, the number of growth curves was reduced based on their relationship with the catchment areas. It was found that the growth factors generally increase with the decrease in catchment sizes. This increase rate is larger for the catchment areas less than 450 km2 and also for the larger AEP growth factors. For any catchment areas larger than 800 km2 the growth factors remained unchanged with the further increase in catchment areas. Based on this the following 6 generalised growth curve groups were recommended for the HA09:
1. GC group No. 1: AREA < 10 km2
2. GC group No. 2: 10 < AREA <= 200 km2
3. GC group No. 3: 200 < AREA < = 400 km2
4. GC group No. 4: 400 < AREA < = 600 km2
5. GC group No. 5: 600 < AREA < = 800 km2
6. GC group No. 6: 800 < AREA < 1200 km2
It was decided that the growth factors for all HEPs with catchment sizes ranging from 10 to 200 km2 (Growth Curve Group No. 2) be estimated from the separate growth curve estimation process. For the remaining growth curve groups the median growth curves will be used. HEPs with catchment areas larger than 800 km2 have almost the same growth factors.
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The estimated 1% AEP growth factors for the HA09 vary from 1.865 to 3.383 depending on the catchment sizes. Growth factors for the smaller catchments are larger than those of the larger catchments.
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6 DESIGN FLOWS AT POLLAPHUCA / GOLDEN FALLS
As has been discussed in previous sections of this report an approach has been taken whereby the design flow estimates of flood flow from the upper catchment (upstream of Pollaphuca Reservoir) are considered separately from middle and lower catchment as they are dictated by factors which are very different and some of which are mutually exclusive of the factors which affect natural catchment run- off. The operation of the dams at Golden Falls / Pollaphuca including the regulations for the discharge of water from the dam are summarised in the separate Eastern CFRAM Study report titled ‘Liffey Flood Controls and Flood Forecasting System Option’ (IBE0600Rp0010). The main considerations for the operation of the dams are:
Dam safety (designed to safely store a 1 in 10,000 year or 0.01% AEP rainfall event)
Efficiency of electric power generation
Flood management
There are other legal, environmental and economic considerations such as water abstraction requirements of local authorities (3.5m3/s from Pollaphuca reservoir and 2.5m3/s upstream of Leixlip) and scouring of sediment build up behind the dams but these are largely secondary. During times of Flood Period Operation (when reservoir levels rise above a certain level) the overriding consideration is dam safety whereby the ESB will prioritise the release of water through the spillways of the dam until such times as normal operating levels in the reservoir are reached. It is without doubt that the dams attenuate flood flows via the dams at Pollaphuca and Golden Falls due to the large amount of storage in Pollaphuca Reservoir. Data provided by ESB indicates that the peak flows of potential flood events in November 2000 and November 2009 were reduced to approximately one eighth and one fifth respectively at Pollaphuca and to one third at Leixlip compared to what the peak flows would have been if the dams and reservoir had not attenuated the flow. The attenuation is most pronounced for shorter duration intense rainfall events such as the October 2011 event as the relatively small volume of water is easily absorbed by the vast scale of Pollaphuca Reservoir. Examination of the flow data from the dam at Golden Falls shows that far from having to release the run-off generated by the rainfall on the 23rd and 24th October 2011 the daily sums of which were estimated to have an Annual Exceedance Probability (AEP) of 20% in the upper catchment (see Eastern CFRAM Study report ‘Overarching Report on the October 2011 Flood Event’ IBE0600Rp0014), the run-off from the upper catchment did not force ESB to release anything other than base flow of less than 2 m3/s until nearly one week later when normal power generation activities were resumed.
In order to estimate the frequency and magnitude of the design flows at Pollaphuca we must first analyse the available historic flow data from the dam at Golden Falls. This can be considered a gauging station at the upstream limit of the most upstream model on the middle Liffey catchment (Model 8 – Newbridge), albeit one with quite an unnatural continuous flow record.
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6.1 AVAILABLE DATA
Two blocks of flow data are available which reflect the flows just downstream of the dam at Golden Falls. Firstly instantaneous (at varied time steps) flow records were provided by the EPA for the historic gauging station at Golden Falls (09007) originally operated by ESB. Data was provided for the entire calendar years 1975 – 1981 although data was missing for the year 1976 (complete year missing). The ESB report River Liffey Rating Curves (January 1995) indicates that spot gaugings are available up to and beyond the Qmed flow and as such there is good confidence in the rating and hence flow data. The second block of data was provided by ESB from June 2006 to October 2012 and is in the form of 15 minute flow data. This has been calculated from observations taken at the dam structure itself including measurement of water levels at the spillways and through the turbines. Assuming all the potential significant flow routes through the dam have been considered, the data can be considered to be of a high degree of confidence as the values are calculated based on observations through hard engineered structures (as opposed to based on a rating curve). The plotted flow trace from each of the record periods / information sources is shown in Figure 6.1.
Figure 6.1: Plotted Flow Data at Golden Falls
The main portion of the flow trace (excluding the larger peaks) reflects the cyclical (approximately twice daily) switching on and off of the turbines for electricity generation purposes. The flows fluctuate between less than 2 m3/s (ESB are required by statute to release 1.5m3/s at all times) and approximately 28 – 36 m3/s reflecting the on / off daily cycle of flow through the turbines for the vast majority of the record period. The gaps in between indicate periods where the power generation was
IBE0600Rp00016 121 Rev F03 Eastern CFRAM Study HA09 Hydrology Report – FINAL not occurring, possibly due to water levels in the reservoir being too low or perhaps reflecting maintenance periods. The spike above the normal daily range indicate larger releases of water through the spillways reflecting a need to lower the reservoir levels, possibly due to prolonged elevated inflows to the reservoir.
It is evident from Figure 6.1 that over time there appear to be some changes in the discharge pattern from the reservoir system above Golden Falls. In the earlier record period there are more peaks above the normal electricity generation cycle flows indicating there was previously a more frequent need to lower the reservoir levels by moving outside of ESB defined ‘Routine Operations’ and into the ‘Flood Period Operations’. Also in the more recent record period there are a greater number of gaps in normal power generation cycle indicating that the volume of water passing through the dam structure has decreased in recent years. There are a number of potential reasons for the change in flow discharge patterns from the dams:
Increasing water abstractions to supply the growing population in the greater Dublin area
Refinement of the water management regulations such that Flood Period Operations are less frequent1
Differences in uncertainty and how the flows were recorded in the two record periods (river gauge versus observed through dam structures.
6.2 EXTREME VALUE ANALYSIS
Due to the limited length of the data available in the recent data period and in line with a pre- cautionary approach it is prudent to analyse the data for both record periods within an Extreme Value Analysis (EVA) in order to predict the design flows. The data set has also been screened to remove events which are as a result of controlled releases during the summer months as these are not considered to be related to hydrologically driven flood conditions in the catchment and are of such a short duration that they are not considered to pose a flood risk during the drier summer months. Annual Maxima (AMAX) flood flow series have been extracted from both sets of data and are given in Table 6.1.
1 As operational experience grows ESB have regularly updated the Liffey Control Regulations, the latest version being ‘Regulations and Guidelines for the control of the River Liffey, Water Management Document’, February 2006, ESBI’
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Table 6.1: AMAX Series from Flow Records at Golden Falls
Hydrometric Date & Time Max Flow Qmed Year m3/s m3/s
1975 03/11/1975 20:12 89.06
1976 04/01/1977 19:09 82.23
1978 10/10/1978 11:57 93.33
1979 31/03/1980 21:14 58.44 90.79 m3/s 1980 19/08/1981 12:46 92.52 (1975 - 1980)
2005 02/11/2005 22:30 38.74
2006 24/11/2006 20:30 33.69
2007 20/01/2008 20:00 34.02 2008 07/10/2008 23:15 34.84
2009 09/12/2009 07:30 58.75
2010 16/04/2011 08:15 44.68 38.74 m3/s
2011 10/07/2012 02:00 87.11 (2005 – 2011)
Complete 58.75 m3/s
As can be seen from the AMAX series the index flood flow when considered as the median for the AMAX series is over double for the first record period what it is for the latter period. This is again due to the higher frequency of large releases from the dam over and above the normal electricity generation flows in the earlier record period. The combined series has been considered in a single site flood frequency analysis, again in line with a precautionary approach whereby the older more onerous flows are considered along with the flows from the latter period. In line with the derivation of growth curves detailed in Chapter 5 a number of two and three parameters distributions were considered to fit the AMAX data. Following this analysis it was found that the 2 parameter distributions provided a better visual fit to the AMAX series from the dam flows, with the 3 parameter distributions exhibiting steepness at the top end which is not representative of the data. A review of the visual fit and L moments of the 2 parameter distributions is shown in Figure 6.2 and Figure 6.3. A visual inspection shows that the LO distribution is the best fit in terms of visual inspection and L-moments.
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Figure 6.2: 2 parameter distributions fitted to Golden Falls (09007) dam flow data
Figure 6.3: L-Moment diagram of 2 parameter distributions
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6.3 DESIGN PEAK FLOWS
In light of the unique qualities of the flow data it is considered that it would be inappropriate to pool the AMAX years with data from FSU gauging stations as the hydrological and hydraulic properties of the catchment run-off, being totally controlled at the dam, are unique. As such the single site growth curve based on the LO distribution has been used to derive the growth factors and Annual Exceedance Probability (AEP) design flows from the dam at Golden Falls which will be input into the upstream boundary of model 8. The design flows are summarised in Table 6.2.
Table 6.2: Growth Factors and Design Flows at Golden Falls
AEP LO Growth Factors LO Calculated Flows (%) (m3/s) 50 1.00 58.75
20 1.44 77.34
10 1.74 88.21
5 2.04 98.23
2 2.44 110.93
1 2.75 120.36
0.5 3.06 129.72
0.2 3.49 142.05
0.1 3.83 151.36
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7 DESIGN FLOWS
7.1 DESIGN FLOW HYDROGRAPHS
Following estimation of the Index Flood Flow (Qmed) and growth factors for each HEP it is possible to estimate the peak design flows for a range of Annual Exceedance Probabilities (AEPs). All of the design flows which will be used for hydraulic modelling input are detailed in Appendix D. The final component of estimating the fluvial design flows is to ascertain the profile of the design flow hydrograph for each HEP, i.e. the profile of the flow over time as a flood event rises from its base flow to achieve the peak design flow (rising limb) and then as the flood flow rate decreases and the watercourse returns to more normal flows (recession limb). As discussed in Chapter 2 of this report the methodology for this study has been developed further since production of the Inception Report and as such three methodologies have been used within HA09 to derive the design flow hydrograph shapes (widths) such that these can be applied to a range of design events:
1. Analysis of simulated historic hydrograph width at all rainfall run-off modelling points based on guidance within FSU WP 3.1 ‘Hydrograph Width Analysis’.
2. FSU Hydrograph Shape generation tool (developed from FSU WP 3.1) for all other HEPs with the exception of 3 (below)
3. FSSR 16 Unit Hydrograph method for small (catchment less than 5 km2) where no suitable pivotal site is available
7.1.1 Rainfall Run-off (NAM) Modelling and HWA
There are two processes involved in the first method which combines the outputs of the catchment based rainfall run-off modelling with the Hydrograph Width Analysis software developed as part of FSU WP 3.1. The catchment rainfall run-off modelling has been carried out using the NAM (Nedbør- Afrstrømnings-Model) component of the MIKE 11 software developed by the Danish Institute of Hydrology (DHI).
Figure 7.1: NAM Conceptual Model
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With the correct catchment parameters and meteorological inputs the NAM replicates the simulated run-off from the catchment at desired time intervals. This continuous flow trace is comparable to the flow record that can be derived from level recordings at a hydrometric gauging station and as such can be analysed in a similar way.
The HWA software has been researched and developed by NUI Galway as part of FSU WP 3.1 (Hydrograph Width Analysis). It is a user friendly windows based software program which was designed to facilitate data-processing, information-extraction and design flood hydrograph production for the wealth of flow data available from hydrometric gauging stations. The first step in the processing of the information is to convert the file into a formatted text file in a file format derived as part of the HWA software development. Once a continuous flow text file in the correct format has been produced from the NAM outputs the software can then accept the full flow simulated record for analysis. The following general steps are then followed:
1. Input data and identify the events for hydrograph analysis, in this case we identify the annual maxima (AMAX) events
2. Isolated hydrographs are de-coupled from complex flood events, i.e. a number of peaks can be present in a flood hydrograph and as such we seek to isolate the largest of the peaks for analysis.
3. The selected hydrographs are analysed to determine the median width at each 5%ile step of their peak flow
4. Irregular parts of the hydrograph shape are discarded
5. A smoothed gamma curve is fitted to the median width hydrograph
Following these steps a parametric semi-dimensionless hydrograph is created (i.e. the hydrograph does not have a flow value on the y axis but rather is defined in height terms by the percentage of the peak flow). The result of these steps applied to the continuous flow trace from the NAM model for the ungauged upstream inflow HEP node (09_540_6_RPS) for the Turnings / Killeenmore (Morell) model (model no. 7) is shown in Figure 7.2.
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Figure 7.2: Median Semi-dimensionless Hydrograph with Fitted Gamma Curve
As is demonstrated in Figure 7.2 the hydrograph width is defined in time (hours) around a zero value which represents the peak. The peak itself represents 100% of the peak flood flow and as such can be applied to all of the design flood flow peak values. There is one further element, the base flow, which must be combined with the hydrograph peak flow and shape to arrive at the final design hydrograph.
Figure 7.3: Design Flow Hydrographs for Morell Upstream Limit Node 09_540_6_RPS
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The baseflow is calculated as per the recommendations of WP 3.1 and is a function of the catchment descriptors Standardised Average Annual Rainfall (SAAR), Catchment Wetness Index (CWI) and Area. The semi dimensionless hydrographs can then be scaled to fit a range of design flows as shown in Figure 7.3. Median hydrographs at each of the NAM modelled HEPs within HA09 are contained within Appendix E.
One further benefit of the rainfall runoff models is that a further layer of simulated hydrometric data is available for calibration of the hydraulic models. Events which may be outside the continuous flow record period of the gauge are now available through the simulated time series flow data at NAM modelling points. No continuous level information is available as the models are spatially dimensionless (i.e. they are not hydraulic models with inputted topographical survey information) but the simulated flow information can be used to replicate the recorded flood extents for historic events not previously captured.
7.1.2 FSU Hydrograph Shape Generator
For all of the HEPs which have not been subject to rainfall run-off modelling and which are not directly upstream or downstream of a NAM modelled HEP node such that the median hydrograph from the neighbouring HEP can be applied, the Hydrograph Shape Generator tool developed as an output from FSU WP 3.1 is used to derive the design hydrograph. The Hydrograph Shape Generator Tool is an excel spreadsheet containing a library of parametric, semi-dimensionless hydrograph shapes derived from gauge records of pivotal sites using the HWA software previously discussed. Based on hydrological similarity, a pivotal site hydrograph is ‘borrowed’ and applied at the subject site (in this case the CFRAM Study HEP) based on catchment descriptors. One potential issue with the use of the Hydrograph Shape Generator tool is the lack of small catchments from which suitably short hydrographs are available. This, along with overly long receding limbs on hydrographs, was particularly noticeable in earlier versions of the software but is much improved with the addition of further pivotal sites to bring the number within the library up to 145. Within HA09 the latest version of the software (version 5) was found to provide suitable hydrograph shapes for all of the HEPs.
7.1.3 FSSR 16 Unit Hydrograph Method
In a few instances it was found that Pivotal Sites could not be found which were sufficiently hydrologically similar to the subject catchment such that hydrograph shape parameters could be borrowed and hydrograph generated as per Section 7.1.2. This was particularly the case for some of the very small sub-catchments at the headwaters of the smaller watercourses such as the Camac in south Dublin. In these particular instances an alternative but tried and tested methodology was used to derive the hydrograph. The FSSR 16 Unit Hydrograph method was used for these catchments whereby semi dimensionless hydrographs where derived with the same timestep as used for the other hydrographs within the model using the ISIS FSSR 16 UH tool. The methodology followed to derive the FSSR 16 semi dimensionless hydrograph for a subject catchment is summarised below:
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1. Time to Peak of the 1 hour unit hydrograph estimated from FSU PCDs (area, MSL, S1085, SAAR & URBEXT) and adjusted for time step
2. The design storm duration is estimated as a function of SAAR and the estimated time to peak
3. An areal reduction factor is calculated as a function of design storm duration and catchment area.
4. Catchment Wetness Index is calculated as a function of SAAR.
5. A soil index is calculated using on FSR Winter Rain Acceptance Potential soil mapping
6. The Standard Percentage Runoff (SPR) is calculated as a function of the soil types within the subject catchment
7. Rainfall characteristics for the subject catchment are derived from FSU DDF gridded outputs (M5- 2D & M5-25D) and FSR maps (Jenkinson’s Ratio r)
The outputs from steps 2 to 7 are input to the ISIS FSSR 16 boundary unit module to produce a semi dimensionless hydrograph (fitted to a peak of 1) based on Unit Hydrograph principles which can then be scaled to the various design peak flows
Following the application of these methodologies hydrographs are then available for application within the hydraulic model. Using the Camac catchment (model 2D) as an example, the input / check hydrographs at each HEP are shown for the 1% AEP event in Figure 7.4.
Camac 1% AEP Hydrographs
40.0 09_481_U 09_472_4_RPS 09_472_8_RPS 09_435_U 09_435_1_RPS 09_37_U 35.0 09_37_1 09_36_2 UN_Inter_Camac_1 UN_Trib_Camac_10 UN_Trib_Camac_20 09_464_1 09_396_U 09_396_1 09_586_3 30.0 09_1308_U 09_618_5 09_606_1 09_39_1 09_360_4_RPS 09_499_1_RPS 25.0 09_499_3_RPS 09_UN_T03_U 09_UN_T03_1 09_UN_T02_1 09_448_U 09_448_1 09005_RPS 09035_RPS 09_1252_U 20.0 UN_Trib_Camac_U UN_Trib_Camac_1 09_1243_1 09_1242_2_RPS 09_832_U 09_832_1 Flow (m^3/s) Flow 15.0
10.0
5.0
0.0 0 5 10 15 20 25 Time (hours) Figure 7.4: 1% AEP Hydrographs for the Camac (Model 2D)
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7.2 COASTAL HYDROLOGY
Analysis of the hydrological elements which contribute to coastal flood risk has been undertaken at a national level through the Irish Coastal Protection Strategy Study (ICPSS) and the Irish Coastal Wave and Water level Study (ICWWS). It has also previously been carried out at a HA09 level through the Dublin Coastal Flooding Protection Project (2005). This study does not seek to re-analyse these elements of coastal flood risk but rather seeks to combine them, along with the fluvial elements where applicable, such that the total combined fluvial and coastal flood risk is assessed on an AFA by AFA basis. In the case of the Sutton and Howth North and Clontarf AFAs the coastal elements (wave, tide and storm surge) only are being considered. In the case of the Liffey Estuary it is also worth noting that the ICPSS modelling included for seiche effects and as such an allowance is included for this in the extreme levels.
7.2.1 ICPSS Levels
Outputs from the Irish Coastal Protection Strategy Study have resulted in extreme tidal and storm surge water levels being made available around the Irish Coast for a range of Annual Exceedance Probabilities (AEPs). The location of ICPSS nodes are shown in Figure 7.5. In relation to the Dublin City AFA on the Lower Liffey there is one node (NE22) at the downstream extents of the models at which coastal flood levels are available for a range of AEPs. Node NE21 is adjacent to the Clontarf AFA and likewise node NE23 is adjacent to the Sandymount AFA. The nearest ICPSS nodes to the Raheny AFA are located just to the north and south of the North Bull Island (node NE19 and NE21 respectively) however the outfall of the Santry River is cut off from Dublin Bay to the south by the causeway and hence node NE19 represents the most appropriate node for coastal flood levels. The Sutton and Baldoyle and Sutton and Howth North AFAs are both located along the narrow neck of the Howth Head peninsula and as such nodes to the north (NE17) and to the south (NE19) are the most applicable nodes for extreme tidal water levels within the coastal hydraulic models.
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Figure 7.5: Location of ICPSS Nodes in Relation to Coastal AFAs
Levels for a range of AEPs have been extracted from the ICPSS and are shown in Table 7.1.
Table 7.1: ICPSS Level in Close Proximity to HA09 AFAs
Height to OD Malin for different AEP AEP (%) NE_17 NE_19 NE_20 NE_21 NE_22 NE_23
50 2.52 2.44 2.41 2.41 2.41 2.43
20 2.65 2.57 2.54 2.53 2.53 2.55
10 2.75 2.67 2.63 2.62 2.62 2.64
5 2.85 2.77 2.72 2.71 2.71 2.74
2 2.98 2.90 2.85 2.83 2.83 2.86
1 3.08 3.00 2.94 2.92 2.93 2.95
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Height to OD Malin for different AEP AEP (%) NE_17 NE_19 NE_20 NE_21 NE_22 NE_23
0.5 3.18 3.10 3.03 3.01 3.02 3.04
0.1 3.41 3.33 3.25 3.22 3.23 3.25 (Extract from: Irish Coastal Protection Strategy Study, Phase 3 – North East Coast, Work Packages 2, 3 & 4A – Technical Report ref: IBE0071/June2010)
7.2.2 ICWWS Levels
The Irish Coastal Wave and Water level Study (ICWWS) is being progressed by OPW in order to consider the potential risk associated with wave overtopping at exposed coastal locations. The study is currently ongoing but preliminary analysis has been made available for the Eastern CFRAM Study to identify the areas within HA09 which have been identified as potentially vulnerable to this flood mechanism. The length of vulnerable coastline and the affected AFAs are shown in Figure 7.6.
Figure 7.6: Draft ICWWS potential areas of vulnerable coastline
As shown in Figure 7.6 three AFAs are potentially vulnerable to flooding due to wave overtopping. These are Sutton and Baldoyle, Sutton and Howth North and Sandymount. The study outputs will be in the form of a range of combinations of water level and wave characteristics (wave height, period,
IBE0600Rp00016 133 Rev F03 Eastern CFRAM Study HA09 Hydrology Report – FINAL frequency and the joint probability assessed extreme water level) for each annual exceedance probability (AEP %).
7.2.3 Consideration of ICPSS and ICWWS Outputs
It is important to note that the outputs from both the ICPSS and the ICWWS are to be considered separately. The AFAs which have been identified as only to be analysed for coastal flooding will be assessed through 2D modelling of Dublin Bay. Tidal boundaries will be applied within the 2D models at a scale and distance necessary to capture the complete effects of a dynamic tide and the propagation effects within Dublin Bay and the watercourse channels to be modelled which have a coastal outfall. At AFAs where fluvial flooding has also been identified as a consideration within the model the ICPSS levels will be applied considering a range of joint probability scenarios (as detailed in 7.3.2) in order to determine the most onerous flood outline for any AEP. The levels which have been derived from the ICPSS will be applied within the 2D portion of the hydraulic (hydrodynamic) models. All ICPSS levels will be applied as the maximum level on the oscillating average tidal cycle observed at the tidal gauge at Dublin Port with the surge applied over 48 hours. A typical 1% AEP surge on top of the tidal cycle to staff gauge zero is shown in Figure 7.7 below. A full bathymetric survey of Dublin Bay has been undertaken in order to accurately capture the effects of tidal propagation within Dublin Bay and into the tidal reaches of the HA09 watercourses. Full details on the application of the ICPSS levels at the coastal boundaries will be contained within the subsequent Hydraulic Modelling report.
Figure 7.7: Typical 1% AEP Coastal Boundary Makeup (to Staff Gauge Zero)
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It is important to note that the outputs from the ICWWS are not directly applicable through the standard 2D hydraulic modelling packages used for coastal flood modelling. The assessment of the volume of flood water from wave overtopping is a function of the outputs from the ICWWS (wave height, period, frequency and the joint probability assessed extreme water level), the duration of the event and the dimensions and hydraulic performance of the sea defence and foreshore. At each of the three AFAs that have been identified as vulnerable to wave overtopping, preliminary analysis will identify the location and length of sea defence / frontage which is vulnerable to wave overtopping. This section will then be assessed against the range of wave / extreme water level combinations for each annual exceedance probability (AEP %) to determine the most onerous scenario. The total overtopping volume from the most onerous scenario for each AEP will then be assessed against the digital terrain model (LiDAR based) to ascertain the mapped flood extents, depth and hazard behind the sea defence / frontage within the AFA. Further details of the methodology for assessment and modelling of the wave overtopping flood risk will be contained within the Hydraulic modelling report.
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7.3 JOINT PROBABILITY
Joint probability is a consideration within HA09 in relation to the occurrence of fluvial – fluvial events (where extreme flood events on tributaries and the main channel of rivers coincide) and also at the downstream tidal reaches of HA09 where tidal – fluvial events become a consideration in the Lower Liffey and at the downstream boundary of the Santry (model 1) where it flows into Dublin Bay.
7.3.1 Fluvial – Fluvial
With the exception of model 1 (Santry), there are modelled watercourse confluence points within every model in HA09. At these confluence points consideration must be given to the probability of coincidence of flood flows within the model. In order to minimise the need for joint probability analysis within the models RPS has split up the Liffey system into fourteen models (plus the separate Santry system) such that the hydrological conditions which cause the flood event have a low degree of variance across the model extents. In addition RPS has specified a high number of HEPs such that as we move down the model, i.e. past confluence points, the hydraulic modeller has to hand the design flows downstream of the confluence point such that they can check that the sum of the inflows within the tributary and the main channel are creating the correct frequency conditions downstream of the confluence point. Where these conditions are not being achieved the modeller will adjust the flows depending on the relationship between catchment descriptors of the main channel and tributary such that the joint probability relationship can be determined to create the correct frequency conditions downstream of the confluence point. This is a modelling consideration and may require an iterative approach. These adjustments will be carried out in line with the guidance provided in FSU WP 3.4 ‘Guidance for River Basin Modelling’ and detailed in the Hydraulic Modelling report.
7.3.2 Fluvial – Coastal
In terms of the CFRAM Study and HA09 this category of joint probability is most relevant to the Lower Liffey model (no. 2C) which is tidally influenced along its entire reach but is also relevant to the lower reach of the Santry (no. 1), the Camac to Bow Bridge (2D) and the final culverted portion of the Poddle (2E) model. In the cases of the models which have the Lower Liffey model at their downstream boundary (models 2D and 2E) the tidal effect at the downstream boundary must be considered through the output flood levels from the Lower Liffey model (2C). The RPS methodology for assessing joint probability for coastal and fluvial flooding is outlined in the CFRAM Study technical note ‘NTCG GN20 Joint Probability Guidance (RPS, June 2013)’. It advocates a stepped approach to the consideration of fluvial coastal joint probability whereby the relevance is assessed to ascertain at which sites dependence may exist and further analysis is needed:
The first stage in any Joint Probability analysis should be to ascertain whether the flooding mechanisms in any particular area, either AFA or MPW, actually warrant the consideration of the joint probability of occurrence. This screening stage should involve a review of all existing information on flooding within the area of interest, such as records of historic events or previous studies including the
IBE0600Rp00016 136 Rev F03 Eastern CFRAM Study HA09 Hydrology Report – FINAL output from the CFRAM PFRA and the complementary ICPSS data. Where this review identifies either a significant overlap in the areas of fluvial and tidal flood risk or a proven history of significant flooding from both sources, joint probability should be considered. Where the flooding mechanism is heavily dominated by one particular source it is questionable whether joint probability analysis is justified.
An initial screening process has been undertaken on the 4 models in HA09 (excluding previous studies) which have been identified as potentially at risk from fluvial and coastal flooding. The results of this screening are shown in Table 7.2 below:
Table 7.2: Initial Screening for Relevance of Joint Probability
Evidence / Model Further JP AFA Name History of Joint Comments No. Analysis Occurrence
1 Santry / No Lower reaches of Santry River relatively No Raheny steep. Very small overlap between fluvial and coastal flood outlines at mouth of Santry
2C Lower Liffey Yes Area downstream of Christchurch on Yes - Check Liffey highly susceptible to coastal for dependence flooding. Serious risk if this was to coincide with high flows.
2D Camac No Tidal influence to Bow Bridge in channel No but bank levels to this point above ICPSS 0.1% AEP event. No overlap of flood extents.
2E Poddle No No overlap of flood outlines. Last section No of watercourse in relatively steep culvert before discharging into Liffey.
Following initial screening three of the models were removed from the consideration of joint probability of fluvial and coastal flood events. This is not to say there is no evidence of a tidal influence at these locations but rather that there is no known evidence of joint fluvial and coastal flood occurrence and that there are no low lying areas on the lower reaches that would be particularly sensitive to such a joint occurrence, over and above a fluvially or tidally dominant event in isolation. For each of these models suitable conservative tidal downstream boundary conditions will be applied which are relatively conservative such as the highest astronomical tide, oscillating such that there is coincidence between peak tide and hydrograph peak or where there is no direct coastal boundary, the 50% AEP water level in the Lower Liffey. It is not thought this will lead to unrealistic downstream flood extents as the overlap
IBE0600Rp00016 137 Rev F03 Eastern CFRAM Study HA09 Hydrology Report – FINAL of the most extreme 0.1% AEP events, when considering the PFRA and ICPSS outlines, is minimal. Nevertheless this will be reviewed following initial model runs to check that this assumption is valid.
The Lower Liffey model however must consider the occurrence of joint probability further. The result of a joint occurrence of both fluvial and coastal flood conditions would have a massive impact on the lower parts of Dublin City. There is no documentary evidence of particularly high flows in the Liffey corresponding with coastal flood events but there is evidence of heavy rainfall, generally a condition of extreme fluvial events, jointly occurring at times of high coastal water levels.
The next stage in assessing the joint probability is to review the available data to ascertain if there is a dependence relationship between extreme coastal and fluvial events. A regression analysis was undertaken whereby 22 years of high tide values at the Dublin Port tidal gauge were considered along with mean daily flow values recorded at the ESB dam at Leixlip (09022). The results are plotted in Figure 7.8.
Figure 7.8: Regression Analysis of Tidal Height versus River Flow on the Liffey
The scatter diagram shown in Figure 7.8 does not indicate any correlation between high tidal levels and fluvial flows in the Liffey main channel. Regression analysis determined the r-squared value to be 0.0006 confirming that there is no correlation between the two variables in the data.
It is typical for both variables to be fairly independent on the east coast of Ireland. This is explained by the fact that extreme tidal events are directly linked to the occurrence of the Spring tides, which are influenced by astronomical factors (which do not affect river flows). Meteorological conditions (which dictate river flow) can also affect the tidal level through storm surge events. In the case of Dublin Bay the extreme storm surge events which occur along the eastern Irish coastline, are generated from a southerly direction and as such the meteorological conditions which affect tidal levels on the east
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As correlation between total water levels and fluvial flood flow within HA09 can be considered to be negligible it is proposed to follow a simplified conservative approach whereby the 50% AEP design event is maintained for one mechanism while the whole range of design AEP events for the other mechanism are tested and vice versa. This may be subject to sensitivity testing where necessary to ensure the approach does not yield results which could lead to unrealistic flood extents or over design of measures.
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8 FUTURE ENVIRONMENTAL AND CATCHMENT CHANGES
There are a number of future potential changes which may affect the outputs of this study and as such it is prudent that they are identified and their potential impact quantified such that the outputs can accommodate as much as practically possible these changes. This chapter outlines potential environmental changes such as climate change and changes to the catchment such as afforestation and changing land uses. HA09 is already a heavily urbanised catchment in the lower reaches of the Liffey and around the urban rivers in the greater Dublin area yet the catchment is still likely to experience further urbanisation which could put further pressure on some of the partly urbanised watercourses in and around Dublin which have flooded frequently in recent years. This issue, along with potential management and policy changes is considered in this chapter.
8.1 CLIMATE CHANGE
According to the United Nations Intergovernmental Panel on Climate Change (2007) there is “unequivocal” evidence of climate change and furthermore:
"most of the observed increase in global average temperatures since the mid-20th century is very likely due to the observed increase in anthropogenic greenhouse gas concentrations."
(Climate Change 2007, IPCC, Fourth Assessment Report AR4)
Further to this carbon dioxide levels in the atmosphere were observed at over 400 parts per million in Hawaii. This is considered a milestone threshold and is at a level last thought to have occurred several million years ago when the arctic was ice free and sea levels were up to 40m higher2.
The effects of climate change on flood risk management are obvious but in terms of fluvial flooding they are not straightforward to quantify. Changes in sea level have direct impact on coastal flooding and a range of predictions on projected rises are available. A number of meteorological projections are also available for changes in rainfall but these have a wide degree of variance particularly from season to season and are difficult to translate into river flow.
8.1.1 HA09 Context
Research into climate change in Ireland is coordinated by Met Éireann through the Community Climate Change Consortium for Ireland (www.c4i.ie). Research summarised in the report ‘Ireland in a Warmer World – Scientific Predictions of the Irish Climate in the 21st Century’ (Mc Grath et al, 2008) seeks to quantify the impact of climate change on Irish hydrology and considers the impacts of nine Irish catchments all of which were outside HA09 but including two adjacent catchments in the Barrow
2 http://www.theguardian.com/environment/2013/may/10/carbon-dioxide-highest-level-greenhouse-gas
IBE0600Rp00016 140 Rev F03 Eastern CFRAM Study HA09 Hydrology Report – FINAL and the Boyne. The ensemble scenario modelling from the regional climate change model predicts that between the two periods of 1961 – 2000 and 2021 – 2060 that Ireland is likely to experience more precipitation in autumn and winter (5 – 10%) and less precipitation in summer (5 – 10%). Between the periods of 1961 – 2000 and 2060 – 2099 this trend is likely to continue with increases of 15 – 20% generally, but up to 25% in the northern half of the country in autumn and drier summers of up to 10 – 18%.
The report seeks to further quantify the impact on hydrology in Ireland through the use of a HBV-Light conceptual rainfall run-off model (provided by Prof. Jan Seibert of Stockholm University) to simulate the effects of climate change on stream flow within the nine Irish catchments. The HBV-Light conceptual rainfall run-off model of the Boyne catchment (HA07) was calibrated using historical meteorological data against the hydrometric gauge record at the Slane Castle gauging station (07012). Validation of the model found that the Boyne model was relatively well calibrated when it came to simulating the annual maximum daily mean flow for historical flows. The HBV-Light conceptual rainfall run-off model of the Barrow catchment (HA14) was calibrated using historical meteorological data against the hydrometric gauge record at the Royal Oak gauging station (14018). Validation of the model found that the Barrow model was not quite as well calibrated when it came to simulating the mean winter and summer flows. The flows were overestimated when compared against the observed historic data from the gauging station at Royal Oak and as such the risk outputs from the model can be considered to be overestimated. Following simulation of the meteorological climate change ensembles within the run-off models the following observations were made in both catchments for the changes between the periods (1961 – 2000) and (2021 – 2060):
Reductions in mean daily summer flow of up to 60% and increases in mean winter flow of up to 20% within both catchments
The risk of extremely high winter flows will increase in both catchments
No definite increase in annual maximum daily mean flow is apparent in the Boyne catchment for all return periods but for events with past return periods less than 20 years an increase in risk is expected
Moderate increases in annual maximum daily mean flow are apparent in the Barrow catchment for all return periods although this must be tempered by the knowledge that the Barrow model may be overestimating the risk
In addition to the research undertaken by C4i the paper titled ‘Quantifying the cascade of uncertainty in climate change impacts for the water sector’ (Dept. of Geography, National University of Ireland, Maynooth, 2011) seeks to quantify the cumulative effect of uncertainties on catchment scale climate change run-off models from uncertainties in emissions scenarios, climate model selection, catchment model structure and parameters. This paper concludes that uncertainties are greatest for low exceedance probability scenarios and that there is considerable residual risk associated with
IBE0600Rp00016 141 Rev F03 Eastern CFRAM Study HA09 Hydrology Report – FINAL allowances of +20% on fluvial flows for climate change, as recommended in ‘Assessment of Potential Future Scenarios for Flood Risk Management’ (OPW, 2009) for the mid range future scenario. In light of this conclusion there is an even greater weight to be placed on higher end future predictions for climate change. The use of the OPW high end future scenario for fluvial flows of +30% is even more relevant in this context.
8.1.2 Sea Level Rise
Research from c4i summarised in the aforementioned report states that sea levels around Ireland have been rising at an annual rate of 3.5mm per year for the period 1993 – 2003 which is higher than the longer term rate of 1.8mm per year for the period 1963 – 2003. This trend is likely to be more modest in the Irish Sea with a ‘net trend’ (allowing for isostatic adjustment of the earth’s crust) of 2.3 – 2.7mm per year. On top of this the report notes that storm surges are likely to increase in frequency.
The latest UK Climate Projections are covered in UKCP09 and put the central estimate of relative sea level rise at Belfast (to the north of HA09), based on a medium emissions scenario for the year 2095 at 31.6cm. The central estimate of a high emissions scenario for 2095 is 40.3cm but the predictions range from approximately 10cm to 70cm. The relative sea level rise detailed in UKCP09 allows for vertical land movement (isostatic adjustment) based on estimates taken from Bradley et al (2009). Storm surge models using the operational Storm Tide Forecasting Service (STFS) also show some increase in extreme storm surge although these rises are much less than was predicted in UKCIP02. It is not projected that the surge which could be expected to be exceeded for the 2, 10, 20 or 50 year return periods will increase by any more than 9cm by 2100 anywhere along the UK coast. It is noted however that other international climate models predict the rises to be much greater and these cannot be completely ruled out. In particular one high end surge scenario H++ combined with sea level rise infers increases in the 50 year return period extreme water level of as much as 3m by 2100 in some places around the UK.
Guidance for the application of climate change in terms of sea level rise is provided in ‘Assessment of Potential Future Scenarios for Flood Risk Management’ (OPW, 2009). It is recommended that a mid range future scenario of a 500mm rise in sea levels is considered and a 1000mm increase in sea levels is considered for the high end future scenario. These allowances would seem appropriate and consistent with the higher end estimates from the regional climate change predictions when both sea level rise and an increase in storm surge are considered.
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8.2 AFFORESTATION
8.2.1 Afforestation in HA09
There is much legislation governing forestry practices in Ireland but it is implemented through the document ‘Growing for the Future – A Strategic Plan for the Development of the Forestry Sector in Ireland’ (Department for Agriculture, Food & Forestry, 1996). The plan points out that over the period from 1986 to 1996 afforestation saw quite a dramatic growth in Ireland from a level of approximately 70 km2 annually to almost 240 km2 annually in 1996 largely driven by a growth in private forestry activities. Within HA09 however the current forest coverage as recorded in the 2006 CORINE land maps is relatively low apart from in the south east corner of the hydrometric area / UoM as shown in Figure 8.1.
Figure 8.1: CORINE 2006 Forest Coverage in HA09 Compared to the rest of Ireland
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The total forested area, including transitional woodland scrub, within HA09 is 110km² which is approximately 7% of the total area. The average for the country is approximately 10%. When we compare the CORINE 2006 database to the 2000 database there appear to have been some increase in the forested area as shown in Figure 8.2.
Figure 8.2: Forest Coverage Changes in HA09
As can be seen from Figure 8.2 there appears to be an increase in the amount of forested area overall but the increase has mostly been in transitional woodland scrub as opposed to actual forest. The areas of forest from the two periods of the CORINE 2006 database are broken down further in Table 8.1.
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Table 8.1: Afforestation from 2000 to 2006
CORINE CORINE Annualised Change 2000 2006 Change
Area % of Area % of Area % of Area % of (km²) catch. (km²) catch. (km²) catch. (km²) catch.
Forest 65 4.0 59 3.6 - 6 - 0.37 - 1.0 -0.062
Transitional Woodland Scrub 37 2.3 51 3.2 + 14 + 0.87 + 2.3 + 0.142
Total 102 6.3 110 6.8 + 8 + 0.50 + 1.3 + 0.080
Total Countrywide 6,631 9.4 7,087 10.1 456 + 0.65 76 +0.11
From Table 8.1 it can be shown that forest / woodland scrub has increased in HA09 between 2000 and 2006 but the actual forest coverage has dropped slightly. When considered together the total area of forest / woodland scrub as a proportion of the catchment is less than the national average of approximately 10%. The rate of increase between 2000 and 2006 is also less than the national average of + 0.11% per year. If the annualised increase in afforestation were to continue for the next 100 years it would more than double the forest coverage in HA09 from 110 km² (6.8%) to 240 km² (14.8%). This is based on a linear extrapolation of forest coverage added per year from 2000 to 2006 which may be limited by other factors such as the capacity of the industry to manage ever increasing forest area or national and global economic factors.
The strategic plan sets out a target for the increase of forest area to 11,890 km² by 2035 in order to achieve a critical mass for a successful high-value added pulp and paper processing industry and this is the main driver behind the increases in forested area. If this value is to be realised nationally the rates of forestation will need to double compared to the change observed between 2000 and 2006.
8.2.2 Impact on Hydrology
A number of studies have been carried out on a range of catchments in an attempt to capture the effects of afforestation on run-off rates and water yields. The DEFRA (UK) report ‘Review of impacts of rural land use management on flood generation’ (2004) considers a number of case studies where the effects of afforestation on the catchment run-off were considered. The report concluded that the effects of afforestation are complex and change over time. A summary of the main findings in relation to afforestation are given below in relation to the River Irthing catchment in the north of England:
Water yield tends to be less from forest than pasture
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In the Coalburn sub-catchment (1.5 km²) study peak flows were found to increase by 20% in the first 5 years and times to peak decreased, with the effect reducing over time (to 5% after 20 years) and the time to peak returning to pre-drainage values.
In the overall River Irthing catchment (335 km²) the same effect was observed but to a much smaller degree
The Coalburn catchment provides lessons which may be relevant to parts of HA09. However these effects are only likely to be relevant to the upland catchments which entirely fall within either of the Dodder or Upper Liffey catchments as can be seen from Figure 8.1. In the case of the Dodder this is to be considered through the separate Dodder CFRAM Study and subsequent review of the hydrological analysis (IBE0600Rp0017 Hydrology Review: FEM FRAM, Dodder FRAM and Tolka Flood Studies). In the case of the Upper Liffey the potential afforestation is almost entirely likely to happen upstream of Pollaphuca dam. Analysis of the flows released from the dam into the middle Liffey catchment for two record periods has already been considered in Chapter 6 and has shown that between two periods where forest cover is likely to have increased, 1975 – 1981 and 2006 – 2012 any affect that afforestation may have had is not evident from the record and appears that greater considerations, possibly the refinement of the management guidelines and increases in water abstraction, have overridden any affect afforestation may have had on flood flows, where they are released into the middle catchment. As such it is not proposed that future increases in flows in the middle and lower Liffey catchment due to afforestation in the upper catchment are considered. The Santry catchment is a largely urban catchment (62%) with no current forest coverage. It is not envisaged that the remaining rural portions of the Santry catchment will be given over to forestry uses considering its proximity to Dublin City and the Airport.
The Blessington AFA and sub-catchment does lie within the Upper Liffey catchment and as such it is recommended that increases in flow due to afforestation are considered in the future scenarios. In this sub-catchment the effects of afforestation will be modelled using the following recommended adjustments to the input parameters:
Table 8.2: Allowances for Effects of Forestation / Afforestation (100 year time horizon)
Mid Range Future Scenario High End Future Scenario (MRFS) (HEFS) - 1/3 Tp¹ - 1/6 Tp¹ + 10% SPR² Note 1: Reduce the time to peak (Tp) by one sixth / one third: This allows for potential accelerated run- off that may arise as a result of drainage of afforested land
Note 2: Add 10% to the Standard Percentage Run-off (SPR) rate: This allows for increased run-off rates that may arise following felling of forestry
(Extracted from ‘Assessment of Potential Future Scenarios for Flood Risk Management’ OPW, 2009)
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8.3 LAND USE AND URBANISATION
The proportion of people living in urban areas (classified as towns with a population of 1,500 or more) has increased dramatically in recent years with a nationwide increase of over 10% in the total urban population recorded between the 2006 census and the 2011 census.
Table 8.3: Population Growth in the Council Areas of HA09 (Source: CSO)
1991 1996 2002 2006 2011 Population (Number) 478,389 481,854 495,781 506,211 527,612 Actual Change Since Dublin -24,360 3,465 13,927 10,430 21,401 City Previous Census (Number) Population Change Since -4.8% 0.7% 2.9% 2.1% 4.2% Previous Census (%) Population (Number) 185,410 189,999 191,792 194,038 206,261 Actual Change Since 4,735 4,589 1,793 2,246 12,223 Dún Previous Census (Number) Laoghaire- Population Change Since Rathdown 2.6% 2.5% 0.9% 1.2% 6.3% Previous Census (%) Population (Number) 152,766 167,683 196,413 239,992 273,991 Actual Change Since 14,287 14,917 28,730 43,579 33,999 Fingal Previous Census (Number) Population Change Since 10.3% 9.8% 17.1% 22.2% 14.2% Previous Census (%) Population (Number) 122,656 134,992 163,944 186,335 210,312 Actual Change Since 6,409 12,336 28,952 22,391 23,977 Kildare Previous Census (Number) Population Change Since 5.5% 10.1% 21.4% 13.7% 12.9% Previous Census (%) Population (Number) 105,370 109,732 134,005 162,831 184,135 Actual Change Since 1,489 4,362 24,273 28,826 21,304 Meath Previous Census (Number) Population Change Since 1.4% 4.1% 22.1% 21.5% 13.1% Previous Census (%) Population (Number) 208,739 218,728 238,835 246,935 265,205 Actual Change Since South 9,193 9,989 20,107 8,100 18,270 Dublin Previous Census (Number) Population Change Since 4.6% 4.8% 9.2% 3.4% 7.4% Previous Census (%) Population (Number) 97,265 102,683 114,676 126,194 136,640 Actual Change Since 2,723 5,418 11,993 11,518 10,446 Wicklow Previous Census (Number) Population Change Since 2.9% 5.6% 11.7% 10.0% 8.3% Previous Census (%)
As demonstrated by Table 8.3 the total population within the local authority areas of HA09 has increased by varying degrees. For the Dublin City council area the population has seen modest growth of 0.2 % on average annually since 1986. This increases for the other County Dublin local authorities to 0.5% for Dún Laoghaire-Rathdown, 1.1% for South Dublin and jumps to 2.8% for the Fingal County
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Council area. The other counties outside Dublin have seen quite high average annual growth in population at 2.4% in Kildare, 2.3% in Meath and 1.5% in Wicklow. No county showed an increase in the share of the rural population since 2006 and as such the data would suggest that the population growth within HA09 has been almost entirely within the urban centres. The average annualised population growth rate from 1986 – 2011 for all of the local authority areas included in HA09 is 1.2%. When this is extrapolated out over the duration of the 100 year future scenario time span to be considered under the study this would see the population within HA09 more than treble in 100 years’ time.
The CSO has also produced Regional Population Predictions for the period of 2011 - 2026 based on a number of scenarios considering birth rates and emigration. Under all the modelled scenarios the Mid- East region is set to grow substantially with growth in Dublin set to be more modest, consistent with growth rates observed between 1986 and 2011. Under the M2F1 Traditional model, which tends to reflect longer term growth trends, the projected rise for the Mid East regions in the 15 year period equates to an average annual growth rate of 2%. Under the same model the projected rise for the Dublin area is 1.6%. Under the M0F1 Recent model, which tends to reflect more recent growth rates, the projected populations equate to an annual average growth rate of 2.1% for the Mid East region and -0.6% (decline) for the Dublin area.
To see if the population changes witnessed translate into equivalent increases in urbanised areas the CORINE land use database was examined within HA09 and the changes from 2000 to 2006 analysed. A simple comparison of the datasets within HA09 shows that there has been a significant increase in artificial surfaces within HA09 from 311 km² in 2000 to 354 km² in 2006 which represents an increase of approximately 14% in six years (see Figure 8.3).
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Figure 8.3: HA09 CORINE Artificial Surfaces (2000 / 2006)
The average annual growth in artificial surfaces from 2000 to 2006 can be shown to be 2.2%. When this rate is extrapolated out over the 100 year future scenario time span to be considered under the study this would see HA09 become completely urbanised in 100 years’ time.
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Any estimation of the rate of urbanisation should consider the two measures of recent growth which have been examined along with the projected population increases from CSO for the region. These are summarised in Figure 8.3 below:
Table 8.4: Historic Urbanisation Growth Indicators
Population Growth in Artificial Surfaces (CORINE) CSO Population HA09 LAs within HA09 AFA Extent Projection Ranges 1991 - 2011 2000 - 2006 2011 - 2016
Average Dublin -0.6% to 1.6% Annual 1.2% 2.2% Growth Rate (%) Mid East 1.5% to 2.6%
It is clear from all the data and projections available that future urbanisation growth rates in HA09 are likely to be high. At the high end of projections and based on recent observation a rate of approximately 2.5% per annum appears realistic for HA09 and at the lower end a rate of 1% per annum would seem representative of longer term trends. However continuation of these growth rates for 100 years, the period to be considered for the CFRAM Study future scenario, could lead to the Liffey catchment becoming completely urbanised. It must be noted that these estimates are based on linear extrapolations of growth rates, either current or projected up to 2026, and as such do not take into account future factors which are likely to significantly affect population and urban growth, but which at this point in time cannot be predicted.
8.3.1 Impact of Urbanisation on Hydrology
The effect of urbanisation on run-off is well documented. The transformation from natural surfaces to artificial surfaces which in almost all cases are less permeable increases surface run-off such that it is generally faster and more intense. If we consider the FSU ‘URBEXT’ catchment descriptor for the Liffey at Islandbridge currently at 5.3 which represents the percentage of urbanisation within the catchment, the URBEXT could potentially rise to between 14.4% urbanised (based on growth of 1% per annum) and 62.9% urbanised (based on growth of 2.5% per annum). Based on the FSU equation
(WP 2.3) for index flow estimation (Qmed) , which itself is based on a regression analysis of gauged Irish catchments, the Urban Adjustment Factor (UAF) for the Liffey catchment to Islandbridge would vary as follows for the 100 year high end (HEFS) and mid range (MRFS) future scenarios:
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Table 8.5: Potential Effect of Urbanisation on Qmed Flow in HA09
Growth Rate Total Catchment URBEXT² UAFS¹ (per annum) Qmed Flow
Present Day n.a. 5.32 1.080 84.11
100 Year MRFS 1% p.a. 14.39 1.221 95.09
100 Year HEFS 2.5% p.a. 62.85 2.060 160.43
Note 1: Urban Adjustment Factor (UAF) = (1 + URBEXT/100)1.482 Note 2: URBEXT is the percentage of urbanisation in the catchment
The effect of the likely significant urbanisation on the index flood flow in Liffey main channel at the Islandbridge within Dublin City is shown in Table 8.5. It can be shown that the effect of urbanisation on the total catchment could be as much as to double the index flood flow. This is the upper limit of the urbanisation estimates but does not reflect the potential for total urbanisation around the small tributary catchments affecting AFAs and the localised impact on these tributaries as a result.
The allowances for urbanisation are based on a robust analysis of population growth, recent increases in artificial surfaces and population projections from CSO. At the high end they represent a Liffey catchment which is predominantly urbanised. Although this is not beyond reason it is based on extrapolation of current growth rates which are dependent on complex social, economic and environmental factors. There is also a potential saturation level beyond which the urbanised area is unlikely to grow or it will at least slow as urban centres get larger and more dense. This appears to be the case with Dublin City where population and artificial surface growth has been modest. Furthermore the estimation of the Urban Adjustment Factor under FSU is based on data from existing urban catchments and therefore does not reflect the impact of recent policy changes and changes to drainage design guidelines where the emphasis is on developments replicating the existing ‘greenfield’ flow regime through attenuation and sustainable urban drainage systems. The adoption of these growth factors on top of high end scenarios for climate change could lead to flood flows and extents which have an extremely low joint probability. In light of all these considerations a more practical approach must be found.
The River Dodder Catchment Flood Risk Management Plan and the GDSDS Population and Land Use Study provide a useful basis for the practical consideration of future urbanisation. The following recommendations and rationale for the consideration of future urbanisation are extracted and may be useful for the consideration of future urbanisation in HA09:
85% limit on urbanisation within sub-catchments. It has been observed that urban development in the Greater Dublin area has been limited to 87% to 89% in the city centre and 83% to 85% in the urban areas outside the immediate city centre.
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It is assumed there will be no development above the 160m OD elevation line in the Wicklow Mountains (with the exception of Blessington in the case of HA09).
Combining these practical limitations with the projections analysed the following future scenarios will be considered for the effects of urbanisation within HA09:
Mid Range Future Scenario
Above the 160m OD elevation line the Liffey catchment remains totally rural (with the exception of Blessington and the area surrounding the town
Urbanisation within catchment to increase by 1% per annum (URBEXT multiplied by 2.7 up to a maximum of 85%)
High End Future Scenario
Above the 160m OD elevation line the Liffey catchment remains totally rural (with the exception of Blessington and the area surrounding the town
Urbanisation within catchment to increase by 2.5% per annum (URBEXT multiplied by 11.8 up to a maximum of 85%)
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8.4 ARTERIAL DRAINAGE
A further consideration in HA09 is the potential effect of arterial drainage on watercourse channel and floodplain geo-morphology. The original Arterial Drainage Act, 1945 was a result of the Browne Commission which examined the issue of flooding and the improvement of land through drainage works and was mainly focussed on the agricultural context. Following flood events in the mid to late 80s the emphasis on flood management shifted to the protection of urban areas and as such the Arterial Drainage Amendment Act was passed in 1995. This widened the scope of the act to cover the provision of localised flood relief schemes. The OPW have used the Arterial Drainage Acts to implement various catchment wide drainage and flood relief schemes. There have been no works to the main channel of the Liffey which has its flows controlled to varying degrees by ESB. However works have been undertaken in parts of HA09 most significantly on the Rye Water sub-catchment during the 1950s. Arterial drainage scheme works may consist of dredging of the existing watercourse channels, installation of field drains / drainage ditches and the construction of earthen embankments using dredged material to protect agricultural land. The extent of the watercourses affected by arterial drainage within HA 09 is captured in the FSU physical catchment descriptors defined under FSU Work Package 5.3. The catchment descriptor nodes which have a length of arterial drainage defined within the catchment are shown in Figure 8.4.
Figure 8.4: Watercourses affected by arterial drainage in HA09
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8.4.1 The Impact of Arterial Drainage Scheme on HA09 Hydrology
The effect of arterial drainage within HA09 is limited to the Rye Water, the Shinkeen Stream on the eastern edge of Celbridge and everything downstream of their confluence points on the Liffey main channel. The effect of arterial drainage schemes across Ireland was considered through the analysis of gauging station records where there was a pre and post arterial drainage scheme record. Analysis of the gauge station record showed a wide degree of variance in the pre and post arterial drainage index flood flow (Qmed) values but the average change was to increase the Qmed value by approximately 50%3. This is in line with previous research carried out on Irish catchments which suggested that arterial drainage schemes can lead to significant changes in peak discharge of up to 60% (Bailey and Bree 1981). The hydrological analysis and design flow estimation undertaken as part of this study seek to represent as accurately as possible the present day scenario. In the case of the AMAX series taken from the Rye Water gauging station at Leixlip (09001) the entire record consists of post arterial drainage years. All of the catchment descriptors within FSU are based on post drainage datasets. Likewise all of the catchment rainfall run-off models have been generated using the CORINE 2006 database and GSI datasets and have been calibrated against post scheme continuous flow data where available. As such the hydrological inputs derived so far for modelling are considered to accurately reflect the effect of arterial drainage and should represent the best estimates of the present day scenario.
No drawings were available for the drainage schemes on the Rye Water or Shinkeen. However a comparison of pre and post arterial drainage scheme cross section for The Boyne Catchment Drainage Scheme (HA07) and cross sections surveyed in 2012 as part of this study showed that to varying degrees the channels have returned to their pre drainage condition. This would be expected considering the effect of siltation is likely to return the channel to its natural state over a period of time. The fluctuating effect of the arterial drainage scheme on flood flows within HA09 can be considered by analysing the Qmed for changing record periods at the Leixlip gauging station on the Rye Water. The
Qmed for the various record periods is shown in Table 8.6.
Table 8.6: Qmed at Leixlip gauging station on Rye Water (09001 – OPW)
Time Period Qmed (m3/s) 1960 – 1969 48.7 1970 – 1979 32.5 1980 – 1989 36.8 1990 – 1999 28.8 2000 - 2009 46.7
3 Extracted from Table 13 of FSU Work Package 2.3
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Time Period Qmed (m3/s) 1956 - 2009 33.7
There is no discernible pattern in the Qmed values for the various decades and without any further gauge data in HA09 there is no evidence that the arterial drainage scheme on the Rye Water will have any future fluctuating effect on future flood behaviour in the HA09 catchment. However this cannot be ruled out and it is prudent that the potential for some uncertainty, particularly in the Shinkeen Stream and higher up in the Rye Water catchment is noted going forward (although the present day effect of arterial drainage is assessed as part of this study).
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8.5 HYDROGEOMORPHOLOGY
Hydrogeomorphology refers to the interacting hydrological, geological and surface processes which occur within a watercourse and its floodplain. Erosion and deposition of sediment are natural river processes that can be exacerbated by anthropogenic pressures such as land use practices and arterial drainage.
8.5.1 Channel Typology
As part of national Water Framework Directive studies on hydromorphology through River Basin District projects a national channel typology dataset was defined for Irish rivers4. It classified river channels into channel type at 100m node points along each reach. It is based on four key descriptors which categorise rivers according to channel type. Table 8.7 below outlines the four main channel types and how these relate to valley confinement, sinuosity, channel slope and geology.
Table 8.7: Channel Types and Associated Descriptors
Channel Type Confinement Sinuosity Slope Geology
StepPool / Cascade High Low High Solid
Bedrock High low variable Solid
Riffle & Pool Low - Mod Mod Mod drift / alluvium
Lowland Meander Low High Low Drift / Alluvium
Typical undisturbed channel behaviour in terms of flow is described as follows for each of the channel types shown.
Bedrock: Boulders and cobbles often exposed, but few isolated pools Overbank flows uncommon. Morphology only changes in very large floods.
Cascade and step-pool: At low flows, many of the largest particles (boulders, cobbles) may be exposed, but there should be continuous flow with few isolated pools
4 (http://www.wfdireland.ie/docs/20_FreshwaterMorphology/CompassInformatics_MorphologyReport)
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Pool-riffle: Gravel bars may be exposed in low water conditions, but gravels and cobbles in riffles as well as logs and snags are mainly submerged.
Lowland Meandering: In low flow conditions some bars or islands may be exposed, but water fills the majority of the channel.
In the national context, HA09 is representative of both high slope high energy systems to the south within the Wicklow Mountains, and lower energy, pool-riffle and lowland meandering systems to the north of the catchment as watercourses from Kildare and Meath flow to the east coast becoming increasingly urbanised along the way. The River Liffey is the largest watercourse in HA09, a significant portion of which is Lowland Meandering as it flows from the reservoirs created by Pollaphuca and Golden Falls. These act as a buffer between the higher slope watercourses that feed them, and the controlled River Liffey that leaves them under regulated conditions. Their role in managing flood risk by regulating flow in the Liffey downstream can also be considered to buffer sediment accumulation originating from the step-pool cascade watercourses above the reservoirs and the associated land uses in these areas which can increase sediment load. However, the remainder of the Liffey Catchment, its tributaries, and the watercourses within HA09 that are not part of the Liffey system must also be considered.
The predominance of step-pool-cascade and bedrock channels in the mountainous areas to south with lower lying areas to the north, west and east characterised by pool riffle and lowland meandering channels is indicated by Figure 8.5.
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Figure 8.5: WFD Channel Typology HA09
Figure 8.6 indicates channel type of the HPWs/MPWS within HA09. They are predominantly pool-riffle and lowland meandering watercourses with the exception of the upper reaches of the Griffeen and Camac urban watercourses which rise in the northern foothills of the Wicklow Mountains.
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Figure 8.6: HA09 Modelled Watercourses – Channel Type
These channel types also represent the change in channel slope from relatively steep in upland areas to relatively shallow moving downstream. Figure 8.7 indicates the change in channel steepness across HA09.
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Figure 8.7: Changes in Channel Slope HA09
The steepest channels are located to the South within the Wicklow Mountains with a maximum of 0.381 (in other words 1 in 3) and an average of approximately 0.1 (1 in 10) The lower slope channels are characteristic of the rest of HA09 ranging from 0.073 to 0.001 (1 in 14 to 1 in 1000) with an average of 0.006 (1 in 167).
These channel types are typical of Irish catchments. Sediment transport, erosion and deposition are natural morphological processes. In larger catchments it is expected that the upper reaches will be
IBE0600Rp00016 160 Rev F03 Eastern CFRAM Study HA09 Hydrology Report – FINAL more dynamic with erosion taking place and as the river moves to the lower lands, sediment is accumulated and transported. Sediment deposition is expected where the channel meanders and loses energy. As previously mentioned, the reservoirs at Pollaphuca; Golden Falls and Leixlip act as buffer / sediment traps along the Liffey System. Elsewhere, based on the aforementioned figures, the AFAs that could be affected by sediment deposition are:
Camac River HPW Griffeen River HPW
This only becomes an issue if too much sediment is transported from the upper reaches and deposited causing channel capacity issues or localised damage to flood defence structures from scour. Taking a closer look at morphological pressures within the catchment provides an indication if natural processes are exacerbated such that there is risk of such impacts.
8.5.2 Land Use and Morphological Pressures
Figure 8.8 illustrates the land use types within HA09. The urban fabric of the Greater Dublin area characterises the east and the adjacent coastline. There are also pockets of urban areas throughout HA09 including Newbridge, Naas, Blessington, Clane, Maynooth, Celbridge, and Leixlip. Urban fabric accounts for 23% of the total area of HA09. To the south of HA09, within the Wicklow Mountains, the predominant land use is peat bog with pockets of coniferous forestry. This characterises an area of over 150km2 (almost 10% of HA09). Pasture is the predominant land use across HA09 accounting for 43% of the total area. However this is punctuated with several pockets of arable land accounting for 176km2 across the catchment (11% of HA09).
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Figure 8.8: HA09 Land Use (CORINE 2006)
Drainage of bog lands and peat extraction activities potentially lead to large quantities of peat silt being discharged to the receiving waters. However, the waters draining the peat bog areas in HA09 are part of the Pollaphuca catchment basin or upstream of the Glensamole Reservoirs at the upper reaches of
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The predominance of pasture over arable land suggests that in general, the level of exposed soil is limited within the catchment. However there are several pockets of arable land in close proximity to modelled watercourses. Depending on agricultural practices, farming of arable land can lead to increased soil loss to receiving watercourses through ploughing and presence of exposed soils, which will be exacerbated if environmental measures such as buffer strips along river banks are not employed. Figure 8.9 indicates the HPWs/MPWs that flow through areas of arable land and the associated Model Numbers.
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Figure 8.9: HPWs/MPWs flowing through Arable Land in HA09.
As indicated by Figure 8.9, thirteen models have potential to receive additional sediment from arable land, depending on farming practices.
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Overgrazing of soils in areas of commonage areas is also a source of exposed soils washing into headwaters, increasing flashiness through more rapid run-off and erosion increased sediment load to rivers resulting in increased deposition downstream. The Commonage Areas Dataset published by National Parks and Wildlife Service 5 in February 2013 indicates that there are 91km2 of commonage areas within HA09. Under the Water Framework Directive this pressure was identified as a potential risk to river morphological status in the national context. The Commonage Framework Plans in County Wicklow do not indicate overgrazing as an issue and therefore does not pose a risk from a flood risk management perspective. Furthermore, the commonage areas are almost entirely within the peat bog areas shown on Figure 8.8. As previously mentioned, sediment loss from peat extraction activities is buffered by downstream lakes, as would any impacts from overgrazing.
The impact of hydro-geomorphological changes on HA09 ultimately applies to the performance of flood risk management options. The impact of sediment transport and deposition within the HPW/MPWs highlighted here will be considered further under the hydraulic modelling of options stage of the CFRAM Study.
The transportation of sediment and subsequent deposition within the Model Numbers is identified for further consideration under hydraulic modelling.
1 - Santry 2a - Baldonnel 2b – Lucan to Chapelizod 2d - Camac 3a - Leixlip 3b – Hazelhatch / Celbridge 4 - Maynooth 5 - Kilcock 6a - Clane 6b - Naas 7 – Turnings / Killeenmore (Morell) 8 - Newbridge
8.5.3 River Continuity
River continuity is primarily an environmental concept relating to the linear nature of the river eco system and its disruption due to manmade structures such as weirs and dams which alter river flow and can impede fish migration. It is a morphological pressure which has been given consideration under the Water Framework Directive. Any collated data is of use from a flood risk management perspective as it provides information on such structures and as such can be accounted for in terms of flow regulation in hydraulic modelling.
5 http://www.npws.ie/mapsanddata/habitatspeciesdata/
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The risk of impassability may also be an indication of significant hydraulic control and as such is useful in hydraulic modelling. The channel and structure survey undertaken specifically for the Eastern CFRAM Study includes full geometric survey of these structures, and as such ensures their inclusion in the hydraulic modelling phase.
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8.6 FUTURE SCENARIOS FOR FLOOD RISK MANAGEMENT
OPW does not have a specific policy for the design of flood relief schemes but has produced a draft guidance note ‘Assessment of Potential Future Scenarios for Flood Risk Management’ (OPW, 2009). The document gives guidance on the allowances for future scenarios based on climate change (including allowing for the isostatic movement of the earth’s crust), urbanisation and afforestation. Table 1 from the guidance has been adapted for the purposes of this study to take into account catchment specific effects and is presented here as the basis for the design flow adjustment for the mid range (MRFS) and high end (HEFS) future scenarios.
Table 8.8: HA09 Allowances for Future Scenarios (100 year time horizon)
MRFS HEFS
Extreme Rainfall Depths + 20% + 30%
Flood Flows + 20% + 30%
Mean Sea Level Rise + 500mm + 1000mm
Urbanisation URBEXT multiplied by 2.73 URBEXT multiplied by 11.83 Susceptible sub-catchments Susceptible sub-catchments URBEXT = 50%4 URBEXT = 85%4
Afforestation - 1/3 Tp¹ - 1/6 Tp¹ (Blessington Only) + 10% SPR² Note 1: Reduce the time to peak (Tp) by one sixth / one third: This allows for potential accelerated run-off that may arise as a result of drainage of afforested land
Note 2: Add 10% to the Standard Percentage Run-off (SPR) rate: This allows for increased run-off rates that may arise following felling of forestry
Note 3: Reflects growth rates of 1% and 2.5% p.a. for mid range and high end future scenarios. To be applied to FSU URBEXT Physical Catchment Descriptor (PCD) up to a maximum of 85%.
Note 4: Applied to areas of sub-catchment or tributary catchment within the AFA which are susceptible to rapid urbanisation but which at present are predominantly undeveloped (i.e. growth rates applied to existing low FSU URBEXT PCD would result in an unrealistically low future scenario URBEXT).
The peak flows for each of the future scenario design events for every HEP can be found in Appendix D.
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8.7 POLICY TO AID FLOOD REDUCTION
Considering the projected growth in population predicted within HA09 the main future change which could increase flood risk is urbanisation of the catchment. If not managed correctly rapid urbanisation could lead to large swathes of the catchment becoming hard paved and drained through conventional drainage systems which are designed to remove water from the urban area quickly and efficiently. This could have potentially significant implications for fluvial flooding as the flood flows in the watercourses and rivers would intensify. Some of the smaller watercourses in particular could become prone to flash flooding if they become urbanised and flooding similar to that observed along the smaller urban watercourses in south Dublin during the October 2011 event could become more widespread across the catchment.
Sustainable Urban Drainage (SuDS) policy has been about for over a decade now in the UK and Ireland and is being developed for an Irish, and specifically HA09, context through the Greater Dublin Strategic Drainage Strategy (GDSDS) and the Irish SuDS website (www.irishsuds.com). The term covers a range of practices and design options that aim to replicate the pre-development surface water run-off characteristics of the undeveloped catchment following development both in terms of water quality but more importantly, from the perspective of flood risk management, in terms of run-off peak flow, intensity and volume. Typical measures include soft engineered solutions such as filter strips, swales, ponds and wetlands and hard engineered solutions such as permeable paving, ‘grey water’ recycling underground storage and flow control devices. The implementation of successful SuDS requires a joined up policy that covers planning, design, construction and maintenance. One of the biggest issues surrounding SuDS implementation is long term ownership and maintenance although the long term benefits of SuDS can be shown to outweigh the costs associated with these issues.
If a comprehensive SuDS policy is implemented covering planning, implementation and maintenance, then the impacts of urbanisation on flood flows can be substantially mitigated.
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9 SENSITIVITY AND UNCERTAINTY
Hydrological analysis and design flow estimation are probabilistic assessments which originate from observed data. The long term conditions which affect the observations, whether they are climatic or catchment, have been shown to be changing over time to varying degrees. Further to this the degree of uncertainty within the sub-catchments analysed under the Eastern CFRAM Study varies greatly due to the quality and availability of observed data. The following factors which may affect the quality of both the analysed historic events and the estimation of the future design events are listed below:
Hydrometric data record length and gaps Hydrometric data quality (classified in terms of the rating confidence under FSU WP 2.1) High quality meteorological data availability Calibration quality of hydrological models (generally a result of all of the above) Standard error of flow estimation (catchment descriptor based) techniques Future catchment changes, urbanisation, afforestation etc. Climate change
The above list is not exhaustive but seeks to identify the main potential sources of uncertainty in the hydrological analysis. Further to these the list of factors which could potentially affect the uncertainty and sensitivity of the assessment of flood risk under the Eastern CFRAM Study is subject to further uncertainties and sensitivities related to the hydraulic modelling and mapping stages. Examples of some of the modelling considerations which will further affect the sensitivity / uncertainty of the CFRAM Study outputs going forward from the hydrological analysis are past and future culvert blockage and survey error (amongst others). These considerations will be considered through the hydraulic modelling and mapping report along with the hydrological considerations listed here to build a complete picture of uncertainty / sensitivity of Study outputs.
It is not possible to make a quantitative assessment of all of the uncertainties as some of the factors are extremely complex. Nevertheless it is important that an assessment is made such that the results can be taken forward and built upon through the subsequent phases of the study. It is also important that the potential sources of uncertainty in the hydrological analysis and design flow estimation are flagged such that the integrated process of refining the hydrological inputs and achieving model calibration can be achieved more efficiently through a targeted approach. A qualitative assessment has therefore been undertaken to assess the potential for uncertainty / sensitivity for each of the models and is provided in this chapter. The assessed risk of uncertainty is to be built upon as the study progresses through the hydraulic modelling and mapping stages. Following completion of the present day and future scenario models the assessed cumulative uncertainties can be rationalised into a sensitivity / uncertainty factor for each scenario such that a series of hydraulic model runs can be performed which will inform the margin of error on the flood extent maps.
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9.1 UNCERTAINTY / SENSITIVITY ASSESSMENT MODEL BY MODEL
Table 9.1: Assessment of contributing factors and cumulative effect of uncertainty / sensitivity in the hydrological analysis
Model Model Uncertainty / Sensitivity – Present Day Scenario Uncertainty / Sensitivity – Future Notes No. Name Scenarios
Observed Simulated Catchment Ungauged Forest- Urban- Climate Flow Flow Data3 Flow ation5 isation6 Change7 Data1 Data2 Estimates4
1 Santry Medium Low Medium / Low Low Medium High Gauge record < 14 years but good calibration of Low NAM model. Good certainty in Qmed at gauge and all ungauged estimates upstream or downstream on same channel. Some urbanisation in (short) gauge period and some potential future urbanisation. 2A Baldonnel Medium - Medium Medium Low High High Very good gauge record but downstream of model. (Griffeen) Some uncertainty in ungauged estimates due to small size and distance from gauge Fair degree of urbanisation from 2000 to 2006, scope for further urbanisation 2B Lucan to Medium - Medium Medium Low Medium High Good gauge record on Griffeen and fair on Liffey. Chapelizod Uncertainty in estimates of (small, urban) ungauged tribs. Past and future urbanisation of Griffeen and Milltown w.c. but Liffey less so. 2C Lower Medium - Medium / Medium / Low Medium High Short flow record on Liffey but controlled by ESB. All Liffey Low Low inflows to model gauged but outside of modelled reach. Some urbanisation in catchment but effect on main channel flows not as acute as in tribs. Scope for future urbanisation of catchment. 2D Camac Low Low High / Medium Low Medium High Good gauge supplemented by catchment flow Medium simulation although upper tribs have higher uncertainty due to evidence of recent catchment changes due to urbanisation. Made more acute in small complex trib network. 2E Poddle - High / Low Medium Low Low High No gauge record although some GDSDS and LA Medium event data. A range of estimation methods tested. Catchment already fully urbanised. 3A Leixlip High / - Medium Medium Low Medium High Good gauge data on main channels, none on tribs.
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Model Model Uncertainty / Sensitivity – Present Day Scenario Uncertainty / Sensitivity – Future Notes No. Name Scenarios
Observed Simulated Catchment Ungauged Forest- Urban- Climate Flow Flow Data3 Flow ation5 isation6 Change7 Data1 Data2 Estimates4 Low Rye Water subject to arterial drainage but no evidence of affecting Qmed. 3B Hazelhatch Medium / - Medium Medium Low High / High Good gauge data on main channel of Liffey. None on / Celbridge Low Medium tribs. Large potential for future urbanisation. Note that Shinkeen stream is affected by arterial drainage scheme. 4 Maynooth High Medium Medium / Medium Low High / High Gauge unreliable at flood flows but run-off model Low Medium brings some confidence in Qmed which has been used to aid adjustment of ungauged estimates. Arterial drainage scheme may have affected catchment run-off but gauge record quite recent. Large potential for future urbanisation. 5 Kilcock High Medium Medium / Medium Medium High / High Gauge unreliable at flood flows but run-off model Low / Low Medium brings some confidence in Qmed which has been used to aid adjustment of ungauged estimates. Arterial drainage scheme may have affected catchment run-off but gauge record quite recent. Large potential for future urbanisation and some possibility of afforestation in the head waters. 6A Clane High / - Medium / High / Low High / High Nearest gauge 10km downstream on main channel. Medium Low Medium Medium No gauges on tribs All estimates based on catchment descriptors. Potential for future urbanisation. 6B Naas High High High High Low High / High Very little gauge data and highly unreliable. Rainfall Medium run-off model calibration poor. Large uncertainty over contributing catchment due to overflows to and from canal. Large potential for urbanisation. 7 Turnings / Medium Low High Medium Low High / High 4 gauges but high uncertainty. Confidence in Qmed Killeenmore Medium improved by use of rainfall run-off models. Uncertainty in catchment delineation due to N7 and (Morell) canal. Large potential for future urbanisation. 8 Newbridge Medium - Medium Medium Low High / High Dam acts as gauge with flow regime in Liffey highly Medium controlled by ESB. Small, partly urban tribs affecting Newbridge AFA ungauged therefore estimates based on catchment descriptors have some uncertainty. Past evidence of and likely future urbanisation of
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Model Model Uncertainty / Sensitivity – Present Day Scenario Uncertainty / Sensitivity – Future Notes No. Name Scenarios
Observed Simulated Catchment Ungauged Forest- Urban- Climate Flow Flow Data3 Flow ation5 isation6 Change7 Data1 Data2 Estimates4 tribs. 9 Blessington - - Medium / High / High High / High Ungauged. Estimates based on catchment descriptor Low Medium Medium methods and large discrepancy between IH124 and FSU. Small but largely rural. Past evidence of and likely future afforestation and urbanisation.
1 Observed flow data left dashed where there is no gauged data to inform the flood flow estimation for the model. 2 Simulated data refers to data output from rainfall run-off models. This has not been possible on totally ungauged catchments or Liffey main channel catchments 3 Catchment data refers to delineated catchment extents or catchment descriptors. May have been subject to change since FSU due to urbanisation, afforestation, arterial drainage scheme. Some catchment extents carry a high degree of uncertainty due to canal or underground (unsurveyed) systems particularly in urban areas. 4 Ungauged flow estimates based on FSU WP 2.3 or IH 124 methodologies. Dependent on 1, 2 & 3 above. Where high quality gauge data is available along modelled reach upon which adjustment can be performed then uncertainty is considered low. Where no gauge data is available within catchment then certainty is considered medium to high. Uncertainty greater in smaller, urbanised catchments where ungauged estimation methodologies are considered to be more sensitive. 5 See Section 8.2 Considered to be low risk of uncertainty to hydrological analysis in HA09 with the exception of Blessington. 6 See Section 8.3 Considered generally to be a low risk of uncertainty to hydrological analysis in Dublin City as maximum urbanisation achieved. 7. See Section 8.1 Considered a high risk of uncertainty to hydrological analysis in all cases due to the large range of projections.
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9.2 CONCLUSIONS OF SENSITIVITY ANALYSIS
The assessment of uncertainty and sensitivity in each category is relative within HA09. The assessment of uncertainty as being medium or high does not suggest that the analysis is poor but rather in the context of the full suite of design flow estimation techniques being employed in the Eastern CFRAM Study that uncertainty in that category is towards the higher end of the range. For example the modelled watercourses which affect the Blessington AFA are small ungauged and mainly rural but are well defined in terms of catchment data. However the ungauged flow estimates have been designated as having a medium to high uncertainty as the consideration of both IH 124 and FSU ungauged catchment estimates indicates a large variance between the two methods. As there is no high quality gauge data above Pollaphuca dam within HA09 any adjustment to the flow estimates must be made using a gauge which is outside the upper Liffey catchment. The ungauged estimates have therefore been labelled as having a medium to high degree of uncertainty yet the procedure for estimating and adjusting is in line with best practice and would be consistent with the recommended estimation methodology for a typical ungauged rural Irish catchment.
In HA09 the largest degree of uncertainty for the present day scenarios is attributed to Naas. This is due to the uncertainty surrounding the delineation of the catchment, mainly due to the interaction of the watercourse network with the canal, the presence of historic underground reaches and the rapid recent urbanisation (including the widening of the N7 / M7). The adjacent Turnings / Killeenmore (Morell) model also has large uncertainty associated with the catchment delineation for the same reasons but this model has a number of points where gauge data of varying quality is available such that historic flow simulations have been developed using hourly gauge and radar based inputs to rainfall run-off (NAM) models and calibrated against the gauge records thus providing greater certainty in the index flood flows across the model. All other models are assessed as having a medium degree of uncertainty / sensitivity in the present day scenario unless the catchment is both defined to a high degree of certainty and has high quality observed / simulated long term flow data.
In the future scenarios climate change has been defined as a potential source of high uncertainty due to the inherent uncertainties surrounding climate change science and how these will translate into changes in fluvial flood flows in Ireland. Within HA09 it is considered that urbanisation is generally a source of medium to high uncertainty in the prediction of future flood flows with the exception of Dublin City, which is already fully urbanised and the upper catchment which is unlikely to be urbanised (with the exception of the expansion of Blessington). The factors which affect urbanisation are difficult to predict for a 100 year time horizon due to the complex social, cultural and economic factors which affect it. At the upper limit of the predictions large swathes of the catchment could become fully urbanised which could more than double some of the index flood flows. However there is also the effect of sustainable drainage to consider which adds a further degree of uncertainty depending on the extent to which it is successfully implemented. There is a high degree of certainty that there will be little afforestation within the middle and lower reaches of the Liffey catchment and as such this is only a significant source of uncertainty in Blessington and possibly Kilcock.
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10 CONCLUSIONS
Limited hydrometric data exists for the main channel of the Liffey. The flows are controlled by ESB to varying degrees from the Pollaphuca reservoir down to the tidal reaches and as such the collection of hydrometric data on the Liffey largely lies with ESB. For the same reason however, the flood risk is managed and the likelihood of extreme flood flows has been greatly reduced. On the tributaries of the Liffey and other watercourses which discharge directly to Dublin Bay, hydrometric data is widely available but of varying quality. High quality meteorological data exists for application in the hydrological analysis of HA09 following the processing of the Dublin Airport radar data as part of the Study. A comprehensive methodology has been applied combining the latest FSU statistically based and modelling based techniques for analysis, although due to the fluctuating ESB discharges, calibration of catchment run-off models has not been possible on the main channel of the Liffey. Rainfall run-off techniques though have been particularly useful within HA09 in the instances where gauge records exist but are of such high uncertainty or short record that the gauge records could not be used with any confidence in the prediction of the index flood flow (Morell, Rye Water and Santry sub-catchments). Where catchment rainfall run-off modelling has been applied this has been done in addition to the full suite of traditional statistically based methods such that an additional layer of simulated historic data is available. The results from both approaches are cross checked against one another such as to provide the most robust analysis possible to take forward for design flow estimation. In the small, heavily urbanised Poddle watercourse in south Dublin, following initial modelling the application of statistically based estimates was not found to be representative of measured flood flows in the heavily channelised / culverted sections of the watercourse due to hydraulic constrictions in the network which are not reflected in catchment run-off calculations. A model specific approach has been adopted here whereby the direct application of rainfall to an integrated drainage network / river model has been deemed necessary to capture the effect of flooding accurately. It is not envisaged that this will be necessary for other urban watercourses as none of the other watercourses to be modelled is quite so heavily urbanised, culverted and channelised. However as hydraulic modelling is progressed this approach will be undertaken if deemed necessary.
There is a fair degree of potential uncertainty within the ungauged tributary catchments where estimates of flood flow are derived from catchment descriptor based estimates and direct adjustment based on gauge data within the sub-catchment is not possible. Some sizeable variations have been identified in certain areas between the different catchment descriptor, regression equation based estimates of the index flood flow indicating uncertainty in the estimates. However these estimates have been compared to those for similar catchments where high quality gauge and / or simulated run- off data is available to arrive at improved adjusted estimates of flood flow. The calibration of the hydraulic models to historic flood data and observed evidence will further help to screen out design flow estimates which are not reflective of the actual behaviour of these sub-catchments.
There are many potential future changes to the catchment, margins of error and uncertainties which must be considered within the study. However the cumulative application of worst case scenarios, one on top of the other could lead to erroneous flood extents which do not take into account the
IBE0600Rp00016 174 Rev F03 Eastern CFRAM Study HA09 Hydrology Report – FINAL diminishing cumulative joint probability of these factors. For this reason this report has separated future HA09 changes that have a high degree of certainty in the projections from those changes which are less certain. Future changes which have a high degree of uncertainty, along with margins of error and other uncertainties have been risk assessed individually. This risk assessment is to be taken forward and built upon through the hydraulic modelling phase with the ultimate goal of providing a single error margin for the flood extent maps on an AFA by AFA basis. This rationalised single error margin is designed to inform end users in a practical way as to the varying degree of caution to which mapped flood extents are to be treated.
10.1 SUMMARY OF THE RESULTS AND GENERAL PATTERNS
The catchment can be characterised hydrologically as follows:
The catchment has a wide range of climatic and physiographic characteristics. The drier, lowland areas around Dublin and to the east have SAAR values as low as 700mm while the upper Liffey catchment in the Wicklow Mountains has SAAR values of up to 1550mm.
Hydrometric data is of variable quality and availability with a particular shortage of data on the main channel of the Liffey.
Meteorological data is of good quality and availability in the catchment, particularly following the processing of rainfall data from the Dublin radar.
Flood behaviour when defined in terms of the growth curve, i.e. in orders of magnitude greater than the median event, is relatively more extreme in the upper catchment than would have been thought based on older methodologies (FSR). This is in line with other more recent, catchment specific studies such as the GDSDS or FEMFRAMS.
The 1% AEP flood event ranges from approximately 1.9 (Liffey main channel) to 3.4 times larger than the median flood flow. This compares to approximately 2 under FSR.
Design flow estimation is the primary output of this study and has been developed based on the analysis contained in this report. This analysis is based on previous observed data and estimation / modelling techniques. This analysis will require further validation through the calibration of the hydraulic models. As modelling progresses there may be some elements of the hydrological analysis that might need to be questioned and interrogated further. This is reflective of best practice in hydrology / hydraulic modelling for flood risk assessment. RPS believe that through complementing statistical analysis techniques with rainfall run-off modelling that the design flow estimation has as high a degree of certainty as is possible prior to calibration / validation and that this will save time and increase accuracy as HA09 moves into the hydraulic modelling phase of the CFRAM Study process. Nevertheless the modelling may necessitate the adjustment of some of the design flows and as such any adjustments made will be summarised within the Hydraulic Modelling Report.
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10.2 RISKS IDENTIFIED
The main potential source of uncertainty in the analysis is due to a lack of hydrometric gauge data in the smaller ungauged catchments which are the main source of fluvial flood risk in many of the AFAs. This has been mitigated as much as possible by the use of a comprehensive range of analysis and estimation techniques from statistical, catchment descriptor based estimates to the use of rainfall run- off modelling.
After this cycle of the Eastern CFRAM Study the main potential adverse impact on the hydrological performance of the catchment is the effect of urbanisation. The population projections could translate into a rapid urbanisation of parts of the catchment and the potential for this to increase flood risk is obvious, particularly considering recent flood events, if this leads to development which is unsustainable from a drainage perspective.
10.3 OPPORTUNITIES / RECOMMENDATIONS
This study presents two potential opportunities to improve the hydrological analysis further in the next cycle of the Eastern CFRAM Study:
1. Four hydrometric gauging stations were identified for rating review in HA09 yet survey information and hydraulic models will be available for at least seven further active stations on modelled watercourses following completion of the study. These stations are all EPA operated and have no classification under FSU and as such there is high uncertainty in the ratings at flood flows. With minimal additional survey information all of these stations could have the ratings developed through the use of hydraulic modelling such that they could be used with greater confidence for flood flow estimation
2. The only hydrometric flow data which is currently being collected on the main channel of the Liffey is at the ESB dams6. The information currently available at these locations is provided by ESB on request from observations taken at the dam structures and is available from 2006. Longer term collection of this data would aid a better understanding of the changes in flood flow management and the probability of extreme flows occurring on the main channel of the Liffey. There is currently no observed flow data being generated on the main channel of the Liffey at Dublin City. The installation of a hydrometric gauge and development of a flood flow rating would provide data for a more comprehensive understanding of the relationship between the flows observed at the ESB dams, the contributing middle and lower catchment and flood behaviour at Dublin City. It would also be an important element in the development of a flood forecasting and warning system for Dublin City.
6 DCC have indicated that proposals are in place for a new weir and hydrometric gauge located at the Spa Hotel on the main channel of the Liffey at Lucan. IBE0600Rp00016 176 Rev F03 Eastern CFRAM Study HA09 Hydrology Report – FINAL
3. The rainfall run-off modelling carried out as part of this study has, due to programme and data constraints, been carried out following hydrological analysis of the gauge station data. The run-off modelling has effectively created a layer of additional simulated historic gauge station years for all of the gauge stations. This data has been utilised in the design flow estimation but could potentially be used to provide further statistical confidence to estimates of historic flood frequency or may even be used to inform hydrograph shape generation in future studies.
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11 REFERENCES:
1. EC Directive on the Assessment and Management of Flood Risks (2007/60/EC)
2. ‘River Tolka Flooding Study, Technical Report No. 2: River Modelling Report’ – RPS MCOS, (December 2003)
3. River Dodder Catchment Flood Risk Assessment and Management Study, Hydrological Analysis Report. (RPS, 2009)
4. S. Ahilan, J.J. O’Sullivan and M. Bruen (2012): Influences on flood frequency distributions in Irish river catchments. Hydrological Science Journal, Vol. 16, 1137-1150, 2012.
5. J.R.M. Hosking and J.R.W. Wallis (1997): Regional Frequency Analysis – An approach based on L-Moments. Cambridge University Press.
6. Flood Studies Update Programme – Work Package 2.1 – Review of Flood Flow Ratings for Flood Studies Update – Prepared by Hydrologic Ltd. for Office of Public Works (March 2006)
7. Flood Studies Update Programme – Work Package 2.2 – “Frequency Analysis” – Final Report – Prepared by the Department of Engineering Hydrology of National University of Ireland, Galway for Office of Public Works (September 2009).
8. Flood Studies Update Programme – Work Package 2.3 – Flood Estimation in Ungauged Catchments – Final Report – Prepared by Irish Climate Analysis and Research Units, Department of Geography, NUI Maynooth (June 2009)
9. Flood Studies Update Programme – Work Package 3.1 – Hydrograph Width Analysis – Final Report – Prepared by Department of Engineering Hydrology of National University of Ireland, Galway for Office of Public Works (September 2009)
10. Flood Studies Update Programme – Work Package 5.3 – Preparation of Digital Catchment Descriptors – Pre-Final Draft Report – Prepared by Compass Infomatics for Office of Public Works (January 2009)
11. Michael Bruen and Fasil Gebre (2005). An investigation of Flood Studies Report – Ungauged catchment method for Mid-Eastern Ireland and Dublin. Centre for Water Resources Research, University College Dublin.
12. Eastern CFRAM Study – HA09 Inception Report. Office of Public Works, June 2012.
13. Flood Estimation Handbook- Statistical Procedures for Flood Frequency Estimation, Vol. 3. Institute of Hydrology, UK (1999).
14. NERC, 1975. Flood Studies Report. Natural Environment Research Council.
IBE0600Rp00016 178 Rev F03 Eastern CFRAM Study HA09 Hydrology Report – FINAL
15. Fingal East Meath Flood Risk Assessment and Management Study – Hydrology Report (2010). Office of Public Works.
16. Institute of Hydrology Report No. 124 – Flood Estimation for Small Catchments (D.C.W. Marshall and A.C. Bayliss, June 1994)
17. Irish Coastal Protection Strategy Study, Phase 3 North East Coast – Prepared by RPS for Office of Public Works (June 2010)
18. Ireland in a Warmer World, Scientific Predictions of the Irish Climate in the Twenty First Century Prepared by Met Éireann and UCD (R. McGrath & P. Lynch, June 2008)
19. Growing for the Future – A Strategic Plan for the Development of the Forestry Sector in Ireland (Department for Agriculture, Food and Forestry, 1996)
20. Review of Impacts of rural land use management on flood generation (DEFRA, 2004)
21. Liffey Flood Controls and Flood Forecasting System Option report (RPS / Hydrologic, 2013)
22. Eastern CFRAM Study, Dublin Radar Data Analysis for the Dodder Catchment, Stage 1, (RPS / Hydrologic, 2012)
23. Stage 2 – Analysis of Dublin Radar Data for the Eastern CFRAM area (RPS / Hydrologic, 2013)
24. ‘Quantifying the cascade of uncertainty in climate change impacts for the water sector’ (Dept. of Geography, National University of Ireland, Maynooth, 2011).
25. Extracts from design flow estimation calculations for the 1st Calatrava Bridge (James Joyce Bridge) on the Liffey (M Bruen, UCD, 2000)
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APPENDIX A
HA09 HYDROMETRIC DATA STATUS TABLE
A1
APPENDIX B
ANALYSIS OF THE DUBLIN AIRPORT RADAR DATA
Analysis of the Dublin
Radar Data for the Eastern CFRAM Study Area
(Stage 2 – Draft report) DOCUMENT CONTROL SHEET
Client OPW
Project Title Eastern CFRAM Study (Dublin radar analysis project, Stage 2)
Document Title Analysis of the Dublin Radar Data for the Eastern CFRAM Study Area
Document No. IBE0600Rp0015
DCS TOC Text List of Tables List of Figures No. of This Document Appendices Comprises 1 1 20 1 1 2
Rev. Status Author(s) Reviewed By Approved By Office of Origin Issue Date
D01 Draft TE, SV, LR, BQ GG Amersfoort, Belfast 07.12.2012 JG D02 Draft TE, SV, LR, BQ GG Amersfoort, Belfast 07.01.2013 JG F01 Draft Final TE, SV, LR, BQ GG Amersfoort, Belfast 25.01.2013 JG F02 Final TE, SV, LR, BQ GG Amersfoort, Belfast 20.03.2013 JG
rpsgroup.com/Ireland | www.hydrologic.com
Eastern CFRAM Study Stage 2 Analysis of the Dublin Radar Data – Final Report
TABLE OF CONTENTS
1 INTRODUCTION ...... 3 1.1 CONTEXT ...... 3 1.2 STUDY OBJECTIVES ...... 3 1.3 METHODOLOGY ...... 3 2 AVAILABLE AND DELIVERED RAW DATA ...... 4 2.1 DATA DELIVERED ON TIME ...... 4 2.2 DATA DELIVERED LATER ...... 4 2.3 SELECTED DATA FOR PROCESSING ...... 5 3 PREPARATION OF THE DATA ...... 7 3.1 ANCILLARY DATA ...... 7 3.2 RAIN GAUGE DATA ...... 7 3.3 RADAR DATA ...... 7 4 QUALITY CONTROL OF THE DATA ...... 9 4.1 RAIN GAUGES ...... 9 4.2 DUBLIN RADAR DATA ...... 9 5 RADAR ADJUSTMENT TO RAIN GAUGES ...... 11 5.1 GENERAL PROCEDURE ...... 11 5.2 MUTLI DAY ADJUSTMENT ...... 11 5.3 RESULTS OF DUBLIN RADAR ANALYSIS ...... 11 5.4 EXAMPLE OF NAM MODEL FOR THE ATHBOY CATCHMENT ...... 15 6 STAGE 2 CONCLUSIONS AND OUTLOOK...... 19 7 ACKNOWLEDGEMENTS ...... 20 8 REFERENCES ...... 20
Radar Data Analysis Stage 2 1 F02 Eastern CFRAM Study Stage 2 Analysis of the Dublin Radar Data – Final Report
LIST OF ABBREVIATIONS
AAD Annual Average Damages AEP Annual Exceedance Probability AFA Area for Further Assessment CAPPI Constant Altitude Plan Position Indicator. Radar measurements are taken from several elevations of the radar to always have a measurement at approximately the same altitude in the atmosphere. The advantage of this method is that effects such as clutter close to the radar can be compensated; the disadvantage is that there are disruptions at the edge of each elevation used. CFRAM Catchment Flood Risk Assessment and Management DEM Digital Elevation Model DTM Digital Terrain Model EPS Ensemble Prediction System FSU Flood Study Update HA Hydrometric Area HDF5 Hierarchial Data Format 5. Format or Library used for storing large datasets. Suitable for storing multidimensional arrays of a homogeneous type HEP Hydrological Estimation Point IDW Inverse Distance Weighted interpolation HRU Hydrological Response Unit NAM Hydrological modelling system (DHI) OPW Office of the Public Works PAC Precipitation Accumulation (radar) PCR Pseudo CAPPI Rainfall (radar) PPI Plan Position Indicator. Radar measurement of one fixed elevation. This means that data from larger distances are measured higher above ground than data close to the radar. RRB Radar Reflective Balloon SCOUT Radar and rain gauge data processing software, property of hydro & meteo GmbH & Co. KG. TimeView Time series analysis tool, property of Hydrotec Engineers GmbH. UVF Data format: one time series format consisting of a header and data pairs "date/time value".
Radar Data Analysis Stage 2 2 F02 Eastern CFRAM Study Stage 2 Analysis of the Dublin Radar Data – Final Report
1 INTRODUCTION
1.1 CONTEXT
Radar measured rainfall data are nowadays a common means to derive spatially and temporally detailed rainfall information for a multitude of applications. The work required to obtain such data with reliable quality consists of pre-processing quality control steps both, for data from radar and for ground based stations as well as the merging of these two sources of information. Rainfall data produced in this way can be supplied as sub-daily time series either for a grid (e.g. 1 km) or for sub-catchments in the area of interest.
1.2 STUDY OBJECTIVES
The main objectives of the Stage 2 analysis of the Dublin radar data for the Eastern CFRAM study area are: Carry out radar data quality analysis and correction of the Dublin and Shannon radar data for the Eastern CFRAM study area using daily and sub-daily available rain gauges. Produce gauge-adjusted radar rainfall data sets for the period 1998-2010 for the Study Area in order to provide quality spatio-temporal rainfall input for the hydrological rainfall-runoff analysis. Preliminary comparison of the gauge-adjusted radar hourly time series against the area- weighted time series for the Athboy catchment area (covered in greater detail in report IBE0600Rp0013 Athboy Radar Analysis). Provide a brief report outlining the work done and the main findings.
1.3 METHODOLOGY
The methodology for merging the available rainfall data sources into a spatial hydrometeorological radar derived dataset included: - Preparation and quality control of the rain gauge rainfall data; - Quality control of the available radar data; - Radar correction (adjustment) using the rain gauge data; - Review of events (high-flow, heavy rainfall) for further hydrological analysis; - Preliminary verification of the radar time series using the weighted-area rainfall data and NAM hydrological modelling of the Athboy catchment; - Reporting and result presentation.
Radar Data Analysis Stage 2 3 F02 Eastern CFRAM Study Stage 2 Analysis of the Dublin Radar Data – Final Report
2 AVAILABLE AND DELIVERED RAW DATA
Due to the time frame set up for the project, all data to be used in the processing had to be available for processing by 8th August 2012. The majority of the radar data were delivered in time; however some of the rainfall data were delivered later and could not be used during this stage. The processed radar product is limited to the period for which there are concurrent rainfall and radar data.
GIS data for the geographical organisation and presentation of radar and rain gauge data comprise station coordinates, boundaries of hydrometric areas, catchments to be modelled and relevant municipalities. These data have been pre-processed for use in the SCOUT rainfall processing system.
2.1 DATA DELIVERED ON TIME
Delivered were radar data from Met Éireann for Dublin and Shannon radars:
Dublin:
PCR data 1h 480x480 km 1/1998 – 7/2012 PAC data 1h 200x200 km 1/1998 – 7/2012 RRB data 15 min 200x200 km 10/2005 – 7/2012 HDF5 data 5 min 240 km polar 2/2011 – 7/2012
Shannon:
PCR data 1h 480x480 km 1/1998 – 7/2012 PAC data 1h 200x200 km 8/1997 – 7/2012 RRB data 15 min 200x200 km 10/2005 – 7/2012 HDF5 data 5 min 240 km polar 3/2011 – 7/2012
Rain gauge data had been already delivered by Met Éireann for the Stage 1 of this project and therefore did not encompass the full duration of the radar data but ended within the first half of 2010:
986 stations overall 16 hourly stations
2.2 DATA DELIVERED LATER
Rain gauge data for the period 2010 till the end of May 2012 were received after 8th August 2012 and were therefore not included in this stage of the work. This had the effect of limiting the processed radar data product to mid 2010.
Radar Data Analysis Stage 2 4 F02 Eastern CFRAM Study Stage 2 Analysis of the Dublin Radar Data – Final Report
2.3 SELECTED DATA FOR PROCESSING
To produce adjusted radar data for the Eastern CFRAM study area, it is important to have the catchment areas covered by the radar data and to have available concurrent radar and rain gauge data.
Therefore, the first selection of data for processing took place with respect to spatial and temporal coverage of the study area and the processing interval. It turned out that many stations did not have data for the time interval where radar data were available. A summary of all the stations provided at project outset (generally covering the east of the Republic of Ireland) is indicated below:
986 station time series were available from study inception
303 had data for the period 1998 – 2010 but with some gaps
75 stations with complete data 1998 – 2010
It was originally intended that radar data with a 15 min temporal resolution would be processed but following receipt of the radar products it was found that only the radar products PCR and HDF5 cover all areas. For the HDF5 product no concurrent rain gauge data was available due to the missing temporal overlap of rain gauge station data (ending in 2010) and HDF5 radar data (starting in February/March 2011). Therefore, the hourly PCR product was selected for processing throughout Stages II and III of the project.
Figure 1 shows the stations for which data were available during the period 1998 – 2010 and the extent limitation for the 200 x 200 km radar coverage.
Radar Data Analysis Stage 2 5 F02 Eastern CFRAM Study Stage 2 Analysis of the Dublin Radar Data – Final Report
Stage 2 – Eastern Dublin Radar CFRAM Study Area
Stage 3 – SE CFRAM Study Area
Shannon Radar
Figure 1. Rain gauge stations with data within the period 1998 – 2010 (green dots) and radar coverage 200 x 200 km for Dublin and Shannon radars (rectangles). The black points are the locations of Dublin and Shannon radar.
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3 PREPARATION OF THE DATA
3.1 ANCILLARY DATA
GIS data for the geographical organisation and presentation of radar and rain gauge data comprise station coordinates, boundaries of hydrometric areas, catchments to be modelled and relevant municipalities. These data have been pre-processed for use in the SCOUT rainfall processing system.
3.2 RAIN GAUGE DATA
Quality control of the rain gauge measurements is a required preliminary step before the data can be used in connection with radar data. The following quality control steps were undertaken since the data did not include information on quality (the quality indicator is optional information for the data query from the data base):
- Re-formatting of the incoming data: the data were reformatted from text format or Excel to a time series format suitable to be used for further processing. Here, UVF format was selected. - Check for missing time intervals: gaps in the data were detected and flagged. - Check for values which are too high / outliers: A check was performed on the data. The criterion was that the data of the checked station had to be in accordance with the values of the neighbouring stations: a value was considered too high if it was twice as high as the next value in rank. All daily values that were too high could be attributed to multi-day sums. Multi-day sums were a very frequent observation hampering further use of the data in radar data adjustment. - Suspicious time intervals were documented and invalidated: Time intervals where the data were missing but not set to undefined and time intervals where data were too high were documented and set to undefined values. All findings were documented in the rain gauge data quality overview (Appendix A).
The quality of the rain gauges led to a lower number of gauges which could be used for cross- comparison to radar and for radar data adjustment.
Of the 378 stations time series with data within the time interval 1998 – 2010 mentioned in section 2.3
50 were outside the study areas 55 had poor data 10 had hourly and daily data – so only the hourly data were used 263 time series remained for adjustment
Appendix B gives the list of stations that were finally used for adjustment.
3.3 RADAR DATA
The PCR data product provides data on a Cartesian grid (1 km grid length) as hourly sum in [mm] in form of a CAPPI. The usability of the Dublin data was high (97.1%). However, due to incomplete data in the data base, about 3% of the data could not be used. Some data was also not useable as the associated radar images were found to be empty.
Radar Data Analysis Stage 2 7 F02 Eastern CFRAM Study Stage 2 Analysis of the Dublin Radar Data – Final Report
Since this PCR data product does not permit in-depth quality control and correction, e.g. for beam blockage or bright band effects (see Figure 2), the following quality corrections have been carried out:
- Correction of the permanent clutter pixels or areas (rings); - Correction of areas with a clear long-term overestimation or underestimation of rainfall
For these purposes, daily sum images have been produced by SCOUT, and cumulative rainfall has been analysed in detail.
Figure 2. Bright band effect on a CAPPI product: the radar beam intersects the melting layer at each elevation and thus produces a multiple ring structure
Radar Data Analysis Stage 2 8 F02 Eastern CFRAM Study Stage 2 Analysis of the Dublin Radar Data – Final Report
4 QUALITY CONTROL OF THE DATA
4.1 RAIN GAUGES
Quality control of the rain gauge measurements is a required preliminary step before the data can be used in conjunction with radar data. At the time of data processing, quality information was incomplete. Therefore the following steps were undertaken:
- Re-formatting of the incoming data - Checking for missing time intervals - Checking values which are too high - Double mass analysis - Suspicious time intervals are documented and invalidated
The data from daily rain gauges faced numerous problems, which were addressed: The rainfall value registered was the value for the previous or following day (time shifts) Daily values often showed 0 mm although rainfall had occurred according to readings from neighbouring stations or the radar The data for some of the rain gauges contained multi-day sums which cannot be checked or disassembled easily
More than 3000 time intervals had to be invalidated manually in the rain gauge data base because of the above observations. Details can be found in the Appendix A.
4.2 DUBLIN RADAR DATA
Data from the Dublin radar station was quality checked and processed as follows: correction for clutter by a pixel-wise clutter map (only clutter in and nearby the study area ) correction for no rain images (in case of strong clutter problems) smoothing of images (to reduce the effects of rings – over- and underestimations – due to the CAPPI product)
The observations of clutter and beam blockage with Dublin radar were variable in time, due to different versions of the radar software, maintenance, and construction of new buildings or new interfering emitters. Therefore, several clutter maps have been produced, each of them appropriate for a well- defined time interval only.
Clutter constitutes a major issue for the quality of Dublin radar. Although most clutter areas are outside the study area (e.g. Northern Ireland, Wales, see Figure 3), they occasionally cause problems and required also manual radar data inspection and processing.
Radar Data Analysis Stage 2 9 F02 Eastern CFRAM Study Stage 2 Analysis of the Dublin Radar Data – Final Report
Figure 3. Clutter areas on a clear day
The radar beam blockage is limited for the East CFRAMS Study Area. The blocked areas are small since they are quite close to the radar (Figure 4).
Figure 4. Beam blockage areas for Dublin radar
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5 RADAR ADJUSTMENT TO RAIN GAUGES
5.1 GENERAL PROCEDURE
The adjustment of the radar sums was performed using the daily sums from the quality checked rainfall gauges, based on a modified Brandes adjustment scheme (Wilson / Brandes, 1979) using an IDW interpolation. Particular problems arose from the numerous multi-day sums in the rain gauge data which had to be individually identified and eliminated as well as a number of format errors in the radar data leading to gaps in the radar data.
5.2 MUTLI DAY ADJUSTMENT
Due to the numerous multi day sums in the rain gauge data, the procedure for adjustment had to be extended over a longer time period. The comparison intervals to determine the correction factor field were set to three days, where the correction factor was computed over the day in the middle of the three day interval. Thus, weekend sums could be taken into account at the cost of decreased precision for single days.
5.3 RESULTS OF DUBLIN RADAR ANALYSIS
The processed radar product is reliable for most of the study area with respect to the yearly sums. They clearly offer improvement over using only daily gauges, as has been demonstrated by the trials through hydrological models for the Dodder (report ref: IBE0600Rp0007) and Athboy (report ref: IBE0600Rp0013) catchments. An example of the rainfall sums from the Athboy catchment is shown in Section 5.4. Figure 5 shows on the left hand yearly sum of the incoming radar data, and on the right hand side the yearly sum after quality control and adjustment. Clearly visible are the elimination of clutter on the Northern Irish coast and the increase of the average yearly sum from approx. 300 mm to more than 900 mm. Other issues, such as the blocked radar beam towards the southwest of the radar, remain and may locally disturb the subsequent application of the data.
Radar Data Analysis Stage 2 11 F02 Eastern CFRAM Study Stage 2 Analysis of the Dublin Radar Data – Final Report
Figure 5: Yearly (2009) sum of the original radar data (left) and quality controlled & adjusted radar data (right)
Radar Data Analysis Stage 2 12 F02 Eastern CFRAM Study Stage 2 Analysis of the Dublin Radar Data – Final Report
Figure 6 gives an assessment of the data quality for Dublin radar in terms of the factors between the rain gauges and the adjusted radar over the whole observation period.
Figure 6: Dublin radar: Factor between adjusted radar and rain gauges for those areas where the radar is not blocked
As a consequence of the above documented data quality checks, the gauge-adjusted radar data may have some shortcomings, which are important to mention and should be taken into account as inputs to the hydrological modelling:
Radar Data Analysis Stage 2 13 F02 Eastern CFRAM Study Stage 2 Analysis of the Dublin Radar Data – Final Report
The rainfall rates derived from radar data are expected to have an uncertainty generally within +/- 20% when checked against the rainfall gauges within the defined useable areas for a range of durations. The degree of uncertainty varies spatially, due to distance from the radar, distance from rainfall gauges (adjustment points) and due to proximity to other clutter blockage effects. An area with beam blockage exists from April 2007 to the south west of Dublin radar (Figure 5). In this region, the weighted area-average of the rain gauges should be used for the hydrological modelling Reliability of the radar derived data is less for 2010 due to the incomplete time series of rain gauge data for the entire year of 2010; the radar data for 2010 (and later) need to be adjusted with the corresponding rain gauge data. For hydrological modelling, modellers should be aware of the possibility of wrong scaling due to multi-day sums, i.e. that neighbouring days with 10 and 50 mm of rainfall may be attributed 50 mm and 10 mm instead after adjustment. This has been flagged and is being checked in the NAM model generation tool that flags such rainfall events to be manually inspected and compared to hydrometric gauge data (flow data). Due to the time constraints and the urgency of producing the gauge-adjusted radar data, it is important to note the following quality checks and implement proper procedures in the modelling process: - Limited control of the results and further validation of the generated rainfall time series (which includes the analyses of all days with suspiciously high deviations from the station measurement) was carried out. This will be a part of the hydrological modelling (calibration and model validation process); - Rainfall values due to temporal clutters may have produced rainfall in areas where there was none, or minimal. This has been flagged to the modellers and they have developed quality check of the rainfall data in correlation to the measured runoff (flows) at the gauging stations) in order to take this effect into account.
Figure 7 shows an example of the adjusted radar sum for 1999.
Radar Data Analysis Stage 2 14 F02 Eastern CFRAM Study Stage 2 Analysis of the Dublin Radar Data – Final Report
Artificial ring structure due to the CAPPI data
Area of less reliable radar
data in the CAPPI product
Figure 7: Example of the adjusted radar sum for 1999.
5.4 EXAMPLE OF NAM MODEL FOR THE ATHBOY CATCHMENT
For verification of hydrological modelling comparing weighted, area-averaged and radar-adjusted rainfall time series, the Athboy catchment has been selected. It is situated at a distance of approximately 50 [km] from the Dublin radar and Figure 8 shows a daily sum for the event of 18 November 2009 as an example. It is clearly visible that there is considerable variation of the rainfall sum over the catchment which could not be picked up by the rain gauges (green crosses): whereas the upper part of the catchment has received much more rainfall than the central rain gauge, the lower part has been touched by less rainfall volume.
Radar Data Analysis Stage 2 15 F02 Eastern CFRAM Study Stage 2 Analysis of the Dublin Radar Data – Final Report
Rain gauge
Radar Location
Figure 8. Adjusted radar sum 17 – 18 November 2009 with Athboy catchment and Radar location.
As an example, Figures 9 and 10 are two extreme examples of the differences that can exist in the rainfall data due to spatio-temporal differences between both radar-derived rainfall and simple weighted area-averaged method.
Figure 9. Difference between the radar-derived rainfall at the Tremblestown (07001 station) using both methods (13th June 2007).
Radar Data Analysis Stage 2 16 F02 Eastern CFRAM Study Stage 2 Analysis of the Dublin Radar Data – Final Report
Figure 10. Difference between the radar-derived rainfall at the Athboy (07023 station) using both methods (11th March 2006).
Simple weighted-average rainfall data
RMSE(Q) = 0.829 Peak squared- weighted RMSE(Q) = 2.5947 CC(Q) = 0.8496
Radar-adjusted rainfall data
RMSE(Q) = 0.7063 Peak squared- weighted RMSE(Q) = 1.9310 CC(Q) = 0.8935
Figure 11. Hydrological NAM model calibration results for Athboy (07023) using rainfall input as derived with both methods.
Radar Data Analysis Stage 2 17 F02 Eastern CFRAM Study Stage 2 Analysis of the Dublin Radar Data – Final Report
Simple weighted-average rainfall data (good quality of calibration data – 1975-1999)
RMSE(Q) = 2.0454 Peak squared- weighted RMSE(Q) = 4.6802 CC(Q) = 0.5673
Radar-derived rainfall data (poor quality of calibration flow data – 1998-2010)
RMSE(Q) = 2.3616 Peak squared- weighted RMSE(Q) = 7.1306 CC(Q) = 0.7372
Figure 12. Hydrological NAM model calibration results for Tremblestown (07001) using rainfall input as derived with both methods.
Figures 11 and 12 and the computed statistics (RMSE – root mean squared error, peak flows RMSE and the correlation coefficient - CC) demonstrate that the hydrological NAM model can be better calibrated using the radar-derived rainfall inputs when compared to the weighted area-averaged rainfall inputs. This is also evident for periods with poor quality of recorded flow data, such as the hydrometric gauge at Tremblestown (07001) for the period between 1998 and 2010.
Radar Data Analysis Stage 2 18 F02 Eastern CFRAM Study Stage 2 Analysis of the Dublin Radar Data – Final Report
6 STAGE 2 CONCLUSIONS AND OUTLOOK
The Stage 2 analysis of the Dublin radar data for the Eastern CFRAMS Study Area indicated the following conclusions:
Quality controlled and adjusted radar data are now available on a 1 km National Irish grid with a 1-hour time step from January 1998 to December 2009 (12 years). The spatio-temporal comparison between the radar data and the rain gauge data shows that Dublin radar underestimates rainfall on average by a factor of 3 to 5, compared to the rain gauge observations. The gauge-adjusted radar data is better quality controlled than the rain gauge data used up to now for modelling purposes. The gauge-adjusted radar data provide a much higher rainfall data resolution in time and space than rain gauge data alone. Therefor the gauge-adjusted radar data can substantially improve the hydrological and hydrodynamic modelling results for the purposes of producing the flood hazards and flood risk maps under the Eastern CFRAM Study and potentially other flood studies. The data set provides substantial information for large areas between rain gauge sites where no information has been available up to date. The rainfall-runoff hydrological modelling using the gauge-adjusted radar hourly time series has also demonstrated a significant improvement of the NAM hydrological model calibration for the Athboy catchment. More detailed results will be reported in a separate project report. The radar-adjustment methods set-up during this project could be the backbone for flood forecasting and early warning systems. Real-time gauge-adjusted radar rainfall time series for any of the 1x1 km grids would prove beneficial and will improve the lead time. When this radar information is combined with the existing and the planned hydrometric stations (water levels and discharges), the combined effect will lead to better calibrated and validated hydrological and hydrodynamic operational models. The gauge-adjusted radar data results can be used to optimise the location of daily and sub- daily rain gauges using probabilistic and information theory analyses. The gauge-adjusted radar rainfall dataset that has been developed in the framework of the CFRAM Studies can also be used for many other flood, drought and water quality related studies (i.e. for developing water balances, evaluation of historical flood events, EU Water Framework Directive related catchment analysis, calibration of models). To take full advantage of the possibilities of this dataset, it may be beneficial to offer the 1km x 1km gauge adjusted hourly data sets through a web portal, as outlined in the proposed Stage 4. With this portal staff from OPW or other organisations could easily access and use the enormous amounts of historical data for their studies.
Since the preparation time of the data, additional rain gauge data sets have become available, covering the time frame up to June 2012. Since radar data are already available for this time interval,
Radar Data Analysis Stage 2 19 F02 Eastern CFRAM Study Stage 2 Analysis of the Dublin Radar Data – Final Report the extension of the quality controlled and adjusted radar data for the years 2010, 2011 and the first half of 2012 (during which time some significant flood events occurred within the study area) are now feasible. It is recommended that these data sets are processed to provide high resolution rainfall data which can be used for validation of the hydrological models, particularly for the flood events of October 2011.
Since February 2011, radar data are also available as polar volume data with a 5 minute time step. This constitutes a major data improvement because data quality can be controlled and corrected with higher detail (e.g. beam blockage) than the CAPPI data. Also, the shorter time step of 5 minutes provides data which are suitable for urban catchment simulations.
Finally, other areas of Ireland would benefit from the same type of data - following the proofing of the methodologies and benefits of the data through trials.
7 ACKNOWLEDGEMENTS
We are grateful for the discussions with Met Éireann which helped to improve the quality of the data production.
8 REFERENCES
Wilson, J.W. and Brandes E.A. (1979). Radar measurement of rainfall – A summary, Bull. of the American Meteorological Society, 60, 1048-1058.
Radar Data Analysis Stage 2 20 F02
APPENDIX A
RAIN GAUGE DATA QUALITY CONTROL RESULTS
Explanation for the observations in the following table – comparison was made with the closest other gauges and with radar measurements.
Multi-day sum – misleading daily values
No precipitation – the station did not record precipitation, but neighbouring stations did uncertain partition into single days – the values recorded do not appear to represent the date given implausible – the values are very different from neighbouring recordings very high precipitation – the values are too high to appear plausible
Consequences:
Gap defined – This data was defined as a gap in the dataset
A1 station no. start end observation consequence 108 23.10.1998 25.10.1998 multi-day sum gap defined 108 22.10.2000 24.10.2000 multi-day sum gap defined 108 18.06.2001 20.06.2001 multi-day sum gap defined 108 22.10.2001 24.10.2001 multi-day sum gap defined 108 29.01.2002 31.01.2002 multi-day sum gap defined 108 28.04.2002 01.05.2002 multi-day sum gap defined 108 01.04.2004 06.04.2004 multi-day sum/uncertain partition into single days gap defined 108 25.06.2004 27.06.2004 multi-day sum gap defined 108 21.08.2005 22.08.2005 no precipitation gap defined 108 16.01.2007 18.01.2007 multi-day sum gap defined 108 03.03.2007 05.03.2007 multi-day sum gap defined 108 18.07.2007 21.07.2007 multi-day sum gap defined 108 09.07.2008 13.07.2008 multi-day sum gap defined 108 16.12.2008 19.12.2008 multi-day sum gap defined 108 16.01.2009 17.01.2009 no precipitation gap defined 108 25.01.2009 26.01.2009 no precipitation gap defined 108 29.01.2009 30.01.2009 no precipitation gap defined 108 16.06.2009 18.06.2009 multi-day sum gap defined 108 27.11.2009 30.11.2009 multi-day sum gap defined 108 21.03.2010 23.03.2010 multi-day sum gap defined 332 23.12.1999 25.12.1999 multi-day sum gap defined 332 01.09.2000 05.09.2000 multi-day sum gap defined 332 10.10.2000 13.10.2000 multi-day sum gap defined 332 17.05.2001 26.05.2001 multi-day sum gap defined 332 29.09.2001 01.10.2001 multi-day sum gap defined 332 08.10.2001 13.10.2001 multi-day sum gap defined 332 23.01.2002 25.01.2002 multi-day sum gap defined 332 28.02.2002 09.03.2002 multi-day sum gap defined 332 03.04.2002 11.04.2002 multi-day sum gap defined 332 08.11.2002 10.11.2002 multi-day sum gap defined 332 08.12.2002 17.12.2002 multi-day sum/uncertain partition into single days gap defined 332 28.12.2002 30.12.2002 multi-day sum gap defined 332 29.11.2003 02.12.2003 multi-day sum gap defined 332 13.03.2004 15.03.2004 multi-day sum gap defined 332 27.09.2005 29.09.2005 no precipitation gap defined 332 18.10.2005 20.10.2005 multi-day sum gap defined 332 11.11.2005 09.12.2005 uncertain partition into single days gap defined 332 23.02.2006 25.02.2006 multi-day sum gap defined 332 27.10.2006 31.01.2007 multi-day sum/uncertain partition into single days gap defined 422 02.01.1998 06.01.1998 multi-day sum gap defined 422 07.04.1998 09.04.1998 multi-day sum gap defined 422 17.07.1998 19.07.1998 multi-day sum gap defined 422 26.07.1998 28.07.1998 multi-day sum gap defined 422 02.08.1998 04.08.1998 multi-day sum gap defined 422 11.08.1998 13.08.1998 multi-day sum gap defined 422 01.11.1998 01.12.1998 no precipitation gap defined 422 17.12.1998 24.12.1998 multi-day sum gap defined 422 17.02.1999 23.02.1999 multi-day sum gap defined 422 02.03.1999 04.03.1999 multi-day sum gap defined 422 11.04.1999 13.04.1999 multi-day sum gap defined 422 08.05.1999 10.05.1999 multi-day sum gap defined 422 01.07.1999 03.07.1999 multi-day sum gap defined 422 12.09.1999 14.09.1999 multi-day sum gap defined 422 02.12.1999 01.03.2000 multi-day sum gap defined 422 16.04.2000 18.04.2000 multi-day sum gap defined 422 22.05.2000 24.05.2000 multi-day sum gap defined 422 09.07.2000 12.07.2000 multi-day sum/uncertain partition into single days gap defined 422 19.10.2000 22.10.2000 multi-day sum gap defined 422 04.11.2000 12.11.2000 multi-day sum/uncertain partition into single days gap defined 422 21.11.2000 27.11.2000 multi-day sum gap defined 422 15.12.2000 19.12.2000 multi-day sum gap defined 422 30.12.2000 02.02.2001 multi-day sum/no precipitation gap defined 422 27.03.2001 31.05.2001 multi-day sum gap defined 422 05.10.2001 07.10.2001 multi-day sum gap defined 422 06.11.2001 08.11.2001 multi-day sum gap defined 422 21.11.2001 24.11.2001 multi-day sum gap defined 422 24.05.2002 26.05.2002 multi-day sum gap defined station no. start end observation consequence 422 04.06.2002 06.06.2002 multi-day sum gap defined 422 05.11.2002 07.11.2002 multi-day sum gap defined 422 22.12.2002 24.12.2002 multi-day sum gap defined 422 18.07.2003 20.07.2003 multi-day sum gap defined 422 24.07.2003 30.07.2003 multi-day sum gap defined 422 05.12.2003 13.12.2003 implausible gap defined 422 23.02.2004 06.03.2004 multi-day sum gap defined 422 08.04.2004 13.04.2004 multi-day sum gap defined 422 05.07.2004 22.07.2004 implausible gap defined 422 01.09.2004 01.10.2004 multi-day sum gap defined 422 24.12.2004 06.01.2005 multi-day sum gap defined 422 21.01.2005 23.01.2005 multi-day sum gap defined 422 21.02.2005 26.02.2005 multi-day sum gap defined 422 06.04.2005 08.04.2005 multi-day sum gap defined 422 27.04.2005 30.04.2005 multi-day sum gap defined 422 01.07.2005 14.07.2005 multi-day sum gap defined 422 04.08.2005 14.08.2005 multi-day sum gap defined 422 15.09.2005 10.12.2005 multi-day sum gap defined 422 06.04.2006 09.04.2006 multi-day sum gap defined 422 01.05.2006 03.05.2006 multi-day sum gap defined 422 22.05.2006 25.05.2006 multi-day sum gap defined 422 30.07.2006 01.08.2006 multi-day sum gap defined 422 27.08.2006 31.01.2007 multi-day sum gap defined 422 23.04.2007 25.04.2007 multi-day sum gap defined 422 14.07.2007 31.12.2009 multi-day sum gap defined 538 04.05.1998 17.05.1998 multi-day sum gap defined 538 02.11.1998 07.11.1998 multi-day sum gap defined 538 02.06.1999 14.06.1999 multi-day sum gap defined 538 24.08.1999 30.08.1999 multi-day sum gap defined 538 08.09.2000 23.09.2000 multi-day sum gap defined 538 27.12.2000 29.12.2000 multi-day sum gap defined 538 13.05.2001 22.05.2001 multi-day sum gap defined 538 25.10.2001 30.10.2001 multi-day sum gap defined 538 15.03.2002 19.03.2002 multi-day sum gap defined 538 07.10.2002 14.10.2002 multi-day sum gap defined 538 27.05.2004 29.05.2004 multi-day sum gap defined 538 25.05.2005 01.06.2005 multi-day sum gap defined 538 15.05.2006 17.05.2006 multi-day sum gap defined 538 28.07.2006 01.08.2006 multi-day sum gap defined 538 09.12.2006 12.12.2006 multi-day sum gap defined 538 21.07.2007 28.07.2007 multi-day sum gap defined 538 04.06.2008 14.06.2008 multi-day sum gap defined 538 13.08.2008 15.08.2008 multi-day sum gap defined 538 09.10.2008 11.10.2008 multi-day sum gap defined 538 10.06.2009 12.06.2009 multi-day sum gap defined 538 03.07.2009 14.07.2009 multi-day sum gap defined 538 19.12.2009 12.01.2010 implausible gap defined 638 11.03.1999 13.03.1999 multi-day sum gap defined 638 27.03.1999 30.03.1999 multi-day sum gap defined 638 20.12.1999 23.12.1999 multi-day sum gap defined 638 19.05.2000 29.05.2000 multi-day sum gap defined 638 04.09.2000 06.09.2000 multi-day sum gap defined 638 30/09/2000 30/11/2000 no precipitation gap defined 707 22.04.2000 25.04.2000 multi-day sum gap defined 707 03.12.2001 05.12.2001 multi-day sum gap defined 707 01.11.2003 01.12.2003 no precipitation gap defined 707 02.03.2004 04.03.2004 multi-day sum gap defined 707 19.11.2004 21.11.2004 multi-day sum gap defined 707 23.02.2005 25.02.2005 multi-day sum gap defined 707 19.11.2007 21.11.2007 multi-day sum gap defined 737 24.08.1998 26.08.1998 multi-day sum gap defined 737 27.02.1999 01.03.1999 multi-day sum gap defined 737 13.05.1999 15.05.1999 uncertain partition into single days gap defined 737 07.09.1999 17.09.1999 multi-day sum gap defined 737 15.11.1999 17.11.1999 uncertain partition into single days gap defined 737 26.02.2000 28.02.2000 uncertain partition into single days gap defined 737 08.08.2000 12.08.2000 uncertain partition into single days gap defined station no. start end observation consequence 737 08.10.2000 17.10.2000 implausible gap defined 737 25.04.2002 27.04.2002 multi-day sum gap defined 737 22.07.2002 27.07.2002 implausible gap defined 737 08.02.2003 10.02.2003 multi-day sum gap defined 737 01/09/2004 30/04/2005 no precipitation gap defined 820 08.01.1998 10.01.1998 multi-day sum gap defined 820 17.01.1998 19.01.1998 multi-day sum gap defined 820 06.03.1998 08.03.1998 multi-day sum gap defined 820 22.04.1998 26.04.1998 uncertain partition into single days gap defined 820 07.05.1998 09.05.1998 multi-day sum gap defined 820 28.05.1998 31.05.1998 multi-day sum gap defined 820 06.06.1998 08.06.1998 multi-day sum gap defined 820 01.07.1998 19.07.1998 multi-day sum gap defined 820 02.03.1999 04.03.1999 multi-day sum gap defined 820 13.04.1999 15.04.1999 multi-day sum gap defined 820 19.06.1999 21.06.1999 multi-day sum gap defined 820 03.07.1999 05.07.1999 multi-day sum gap defined 820 26.11.1999 28.11.1999 multi-day sum gap defined 820 13.02.2000 16.02.2000 multi-day sum gap defined 820 01.04.2000 03.04.2000 multi-day sum gap defined 820 09.08.2000 21.08.2000 uncertain partition into single days gap defined 820 17.09.2000 19.09.2000 multi-day sum gap defined 820 02.10.2000 24.10.2000 multi-day sum/uncertain partition into single days gap defined 820 12.11.2000 17.11.2000 multi-day sum gap defined 820 01.12.2000 04.12.2000 multi-day sum gap defined 820 29.01.2001 31.01.2001 multi-day sum gap defined 820 27.02.2001 01.03.2001 multi-day sum gap defined 820 06.12.2001 08.12.2001 multi-day sum gap defined 820 10.06.2002 12.06.2002 multi-day sum gap defined 820 01.02.2003 04.02.2003 very high precipitation gap defined 820 01.03.2003 03.03.2003 multi-day sum gap defined 820 28.11.2003 30.11.2003 multi-day sum gap defined 820 19.12.2003 22.12.2003 multi-day sum gap defined 820 22.01.2004 28.01.2004 multi-day sum gap defined 820 06.04.2004 09.04.2004 multi-day sum gap defined 820 30.05.2004 01.06.2004 multi-day sum gap defined 820 02.07.2004 04.07.2004 multi-day sum gap defined 820 19.07.2004 21.07.2004 uncertain partition into single days gap defined 820 01/06/2005 31/08/2005 no precipitation gap defined 820 05.11.2005 08.11.2005 multi-day sum gap defined 820 01.12.2006 01.01.2007 multi-day sum/uncertain partition into single days gap defined 820 20.03.2007 23.03.2007 no precipitation gap defined 820 01/06/2008 30/06/2008 no precipitation gap defined 907 26.06.1998 30.06.1998 multi-day sum gap defined 907 07.11.1998 09.11.1998 multi-day sum gap defined 907 11.12.1998 15.12.1998 multi-day sum gap defined 907 12.01.1999 25.02.1999 multi-day sum gap defined 907 24.09.1999 26.09.1999 multi-day sum gap defined 907 26.11.1999 29.11.1999 multi-day sum gap defined 907 08.04.2001 10.04.2001 multi-day sum gap defined 907 15.05.2001 18.05.2001 multi-day sum gap defined 907 28.12.2001 01.02.2002 multi-day sum gap defined 907 06.10.2002 11.10.2002 multi-day sum gap defined 907 25.12.2003 27.12.2003 multi-day sum gap defined 907 12.10.2004 15.10.2004 multi-day sum gap defined 907 07.12.2004 09.04.2005 multi-day sum gap defined 907 16.06.2005 08.08.2005 multi-day sum/no precipitation gap defined 907 25.09.2005 20.05.2007 multi-day sum gap defined 907 28.06.2007 30.06.2007 multi-day sum gap defined 907 20.07.2007 15.02.2009 multi-day sum/no precipitation gap defined 907 22.04.2009 08.08.2009 multi-day sum gap defined 907 24.10.2009 01.11.2009 multi-day sum gap defined 908 03.04.1998 05.04.1998 multi-day sum gap defined 908 26.05.1998 29.05.1998 multi-day sum gap defined 908 20.08.1998 24.08.1998 multi-day sum gap defined 908 30.10.1998 08.11.1998 multi-day sum gap defined 908 21.11.1998 23.11.1998 multi-day sum gap defined station no. start end observation consequence 908 11.12.1998 13.12.1998 multi-day sum gap defined 908 21.12.1998 27.12.1998 multi-day sum gap defined 908 03.04.1999 05.04.1999 multi-day sum gap defined 908 10.09.1999 12.09.1999 multi-day sum gap defined 908 28.09.1999 30.09.1999 multi-day sum gap defined 908 16.11.1999 19.11.1999 multi-day sum gap defined 908 17.12.1999 19.12.1999 multi-day sum gap defined 908 27.01.2000 09.02.2000 multi-day sum gap defined 908 01.03.2000 07.03.2000 multi-day sum gap defined 908 01.06.2000 03.06.2000 multi-day sum gap defined 908 21.06.2000 23.06.2000 multi-day sum gap defined 908 13.10.2000 16.10.2000 multi-day sum gap defined 908 17.11.2000 27.11.2000 multi-day sum gap defined 908 23.12.2000 25.12.2000 multi-day sum gap defined 908 02.02.2001 05.02.2001 multi-day sum gap defined 908 10.02.2001 12.02.2001 multi-day sum gap defined 908 06.04.2001 09.04.2001 multi-day sum gap defined 908 30.05.2001 15.06.2001 multi-day sum gap defined 908 26.06.2001 01.07.2001 multi-day sum gap defined 908 25.10.2001 08.11.2001 multi-day sum gap defined 908 10.02.2002 12.02.2002 multi-day sum gap defined 908 26.04.2002 29.04.2002 multi-day sum gap defined 908 09.06.2002 11.06.2002 multi-day sum gap defined 908 20.06.2002 23.06.2002 multi-day sum gap defined 908 01.08.2002 04.08.2002 multi-day sum gap defined 908 08.10.2002 10.10.2002 multi-day sum gap defined 908 28.10.2002 31.10.2002 multi-day sum gap defined 908 08.11.2002 11.11.2002 multi-day sum gap defined 908 24.12.2002 28.12.2002 multi-day sum gap defined 908 02.01.2003 11.01.2003 multi-day sum gap defined 908 20.04.2003 01.06.2005 multi-day sum gap defined 908 01/08/2005 31/08/2005 no precipitation gap defined 908 16.02.2006 01.03.2006 multi-day sum gap defined 908 28.03.2006 08.05.2006 multi-day sum gap defined 908 17.08.2006 30.05.2007 multi-day sum gap defined 908 14.07.2007 30.11.2009 multi-day sum/uncertain partition into single days gap defined 915 02.03.2009 31.03.2009 multi-day sum gap defined 931 21.02.1998 23.02.1998 multi-day sum gap defined 931 10.07.1998 12.07.1998 multi-day sum gap defined 931 01.09.1998 03.09.1998 multi-day sum gap defined 931 05.11.1998 09.11.1998 multi-day sum gap defined 931 21.11.1998 23.11.1998 multi-day sum gap defined 931 17.12.1998 19.12.1998 multi-day sum gap defined 931 06.02.1999 08.02.1999 multi-day sum gap defined 931 01.04.1999 03.04.1999 multi-day sum gap defined 931 03.07.1999 06.07.1999 multi-day sum gap defined 931 30.10.2000 01.11.2000 multi-day sum gap defined 931 20.01.2001 11.02.2001 multi-day sum gap defined 931 21.04.2001 18.05.2001 multi-day sum/uncertain partition into single days gap defined 931 29.09.2001 01.10.2001 multi-day sum gap defined 931 20.11.2001 24.11.2001 implausible gap defined 931 09.03.2002 11.03.2002 multi-day sum gap defined 931 30.03.2002 01.04.2002 multi-day sum gap defined 931 06.09.2002 08.09.2002 multi-day sum gap defined 931 23.11.2002 25.11.2002 multi-day sum gap defined 931 20.02.2003 22.02.2003 multi-day sum gap defined 931 03.03.2003 11.03.2003 multi-day sum gap defined 931 01.04.2003 03.04.2003 multi-day sum gap defined 931 03.03.2004 07.03.2004 multi-day sum gap defined 931 29.05.2004 31.05.2004 multi-day sum gap defined 931 10.06.2004 22.06.2004 multi-day sum gap defined 931 15.07.2004 17.07.2004 multi-day sum gap defined 931 21.07.2004 06.08.2004 multi-day sum gap defined 931 20.08.2004 24.08.2004 multi-day sum gap defined 931 01/09/2004 30/09/2004 no precipitation gap defined 931 01/02/2005 28/02/2005 no precipitation gap defined 931 13.04.2005 15.04.2005 multi-day sum gap defined station no. start end observation consequence 931 14.06.2005 18.06.2005 multi-day sum gap defined 931 01/09/2005 30/09/2005 no precipitation gap defined 931 01.10.2005 31.10.2005 no precipitation gap defined 931 01/12/2005 31/12/2005 no precipitation gap defined 931 10.01.2006 15.01.2006 multi-day sum gap defined 931 23.02.2006 07.03.2006 implausible gap defined 931 01/05/2006 31/05/2006 no precipitation gap defined 931 15.06.2006 18.09.2006 uncertain partition into single days/no precipitation gap defined 931 17.10.2006 22.10.2006 multi-day sum gap defined 931 07.03.2007 31.03.2007 multi-day sum gap defined 931 10.05.2007 12.05.2007 multi-day sum gap defined 931 30.05.2007 01.06.2007 multi-day sum gap defined 931 14.06.2007 01.08.2007 implausible gap defined 1007 10.06.1998 13.06.1998 multi-day sum gap defined 1007 11.12.1998 13.12.1998 multi-day sum gap defined 1007 27.02.1999 01.03.1999 uncertain partition into single days gap defined 1007 16.08.1999 18.08.1999 multi-day sum gap defined 1007 10.01.2000 12.01.2000 multi-day sum gap defined 1007 17.10.2000 19.10.2000 multi-day sum gap defined 1007 28.11.2001 01.12.2001 multi-day sum gap defined 1008 23.08.1998 26.08.1998 multi-day sum gap defined 1008 27.12.1998 29.12.1998 multi-day sum gap defined 1008 17.05.2002 19.05.2002 multi-day sum gap defined 1008 28.05.2002 31.05.2002 multi-day sum gap defined 1008 13.10.2002 15.10.2002 multi-day sum gap defined 1008 01.07.2003 01.08.2003 no precipitation gap defined 1008 02.03.2004 01.07.2004 uncertain partition into single days gap defined 1008 27.02.2006 04.03.2006 multi-day sum gap defined 1008 23.04.2007 25.04.2007 multi-day sum gap defined 1008 04.02.2008 07.02.2008 multi-day sum gap defined 1008 20.03.2008 02.07.2008 multi-day sum/uncertain partition into single days gap defined 1008 15.08.2008 31.12.2009 multi-day sum/uncertain partition into single days gap defined 1020 04.02.1998 24.02.1998 uncertain partition into single days gap defined 1020 15.10.1998 17.10.1998 uncertain partition into single days gap defined 1020 12.08.2000 16.08.2000 multi-day sum gap defined 1020 14.11.2000 16.11.2000 uncertain partition into single days gap defined 1020 29.12.2003 01.01.2004 multi-day sum gap defined 1020 28.06.2006 07.07.2006 uncertain partition into single days gap defined 1020 24.11.2008 01.12.2008 no precipitation gap defined 1020 01.07.2009 03.07.2009 multi-day sum gap defined 1024 31.05.2000 04.06.2000 uncertain partition into single days gap defined 1024 01.11.2006 01.12.2006 no precipitation gap defined 1024 23.08.2008 25.08.2008 multi-day sum gap defined 1024 01.06.2009 01.07.2009 no precipitation gap defined 1024 01.09.2009 01.11.2009 no precipitation gap defined 1024 05.01.2010 08.01.2010 multi-day sum gap defined 1024 01.03.2010 01.04.2010 no precipitation gap defined 1106 24.09.1999 26.09.1999 multi-day sum gap defined 1106 13.07.2001 15.07.2001 multi-day sum gap defined 1106 09.08.2002 11.08.2002 uncertain partition into single days gap defined 1106 27.12.2003 30.12.2003 multi-day sum gap defined 1106 03.08.2004 05.08.2004 multi-day sum gap defined 1106 05.08.2005 07.08.2005 multi-day sum gap defined 1106 17.08.2006 19.08.2006 no precipitation gap defined 1106 04.06.2008 06.06.2008 multi-day sum gap defined 1106 28.06.2008 01.07.2008 multi-day sum gap defined 1107 05.07.1998 07.07.1998 multi-day sum gap defined 1107 19.04.2002 22.04.2002 multi-day sum gap defined 1107 23.05.2002 25.05.2002 multi-day sum gap defined 1107 14.11.2002 19.11.2002 multi-day sum gap defined 1107 21.12.2002 23.12.2002 multi-day sum gap defined 1107 10.12.2003 27.12.2003 multi-day sum gap defined 1107 05.01.2004 07.01.2004 multi-day sum gap defined 1107 12.01.2004 14.01.2004 multi-day sum gap defined 1107 22.02.2007 25.02.2007 multi-day sum gap defined 1107 11.03.2008 29.03.2008 multi-day sum gap defined 1107 16.06.2009 18.06.2009 multi-day sum gap defined station no. start end observation consequence 1108 12.12.1998 14.12.1998 multi-day sum gap defined 1108 29.10.1999 01.11.1999 multi-day sum gap defined 1108 13.09.2000 15.09.2000 multi-day sum gap defined 1108 27.09.2000 29.09.2000 multi-day sum gap defined 1108 01.10.2000 03.10.2000 multi-day sum gap defined 1108 24.11.2000 26.11.2000 multi-day sum gap defined 1108 11.12.2000 13.12.2000 multi-day sum gap defined 1108 02.02.2001 05.02.2001 multi-day sum gap defined 1108 05.10.2001 07.10.2001 multi-day sum gap defined 1108 07.11.2001 10.11.2001 multi-day sum gap defined 1108 01.04.2002 03.04.2002 multi-day sum gap defined 1108 19.04.2002 21.04.2002 multi-day sum gap defined 1108 12.11.2002 24.11.2002 multi-day sum gap defined 1108 26.12.2002 10.01.2003 multi-day sum gap defined 1108 26.02.2003 03.03.2003 multi-day sum gap defined 1108 20.04.2003 17.12.2004 multi-day sum gap defined 1108 03.05.2005 05.05.2005 multi-day sum gap defined 1108 01.07.2005 24.10.2005 multi-day sum gap defined 1108 27.12.2005 31.12.2009 multi-day sum/uncertain partition into single days gap defined 1116 05.10.2001 07.10.2001 multi-day sum gap defined 1130 station not used - cause: frequent multi-day sums gap defined 1207 29.06.1998 07.07.1998 multi-day sum gap defined 1207 26.12.2002 28.12.2002 multi-day sum gap defined 1207 16.09.2006 18.09.2006 multi-day sum gap defined 1207 15.06.2007 18.06.2007 multi-day sum gap defined 1207 12.07.2007 14.07.2007 multi-day sum gap defined 1207 13.09.2008 15.09.2008 uncertain partition into single days gap defined 1207 01.01.2010 01.02.2010 multi-day sum gap defined 1208 01.07.1999 06.07.1999 multi-day sum gap defined 1208 24.07.2003 26.07.2003 multi-day sum gap defined 1208 08.09.2008 10.09.2008 multi-day sum gap defined 1216 16.11.1999 24.11.1999 multi-day sum/uncertain partition into single days gap defined 1216 17.12.1999 19.12.1999 multi-day sum gap defined 1216 23.10.2000 18.11.2000 uncertain partition into single days gap defined 1216 27.04.2001 30.04.2001 multi-day sum gap defined 1216 19.09.2003 21.09.2003 multi-day sum gap defined 1216 25.12.2003 27.12.2003 multi-day sum gap defined 1216 01/04/2005 30/04/2005 no precipitation gap defined 1216 01.07.2005 04.07.2005 multi-day sum gap defined 1216 07.12.2005 09.12.2005 multi-day sum gap defined 1216 07.04.2006 10.04.2006 multi-day sum gap defined 1216 04.07.2006 06.07.2006 multi-day sum gap defined 1216 18.02.2007 02.06.2007 uncertain partition into single days gap defined 1216 12.08.2007 14.08.2007 multi-day sum gap defined 1216 29.01.2008 01.02.2008 multi-day sum gap defined 1216 13.04.2008 06.09.2008 uncertain partition into single days gap defined 1216 08.12.2008 09.12.2008 no precipitation gap defined 1216 12.03.2009 30.05.2010 uncertain partition into single days gap defined 1232 28.11.1998 07.12.1998 multi-day sum gap defined 1232 01.04.2002 03.04.2002 multi-day sum gap defined 1232 01.05.2002 03.05.2002 multi-day sum gap defined 1232 02.07.2002 06.07.2002 multi-day sum gap defined 1237 02.01.1998 06.01.1998 multi-day sum gap defined 1237 26.06.1998 29.06.1998 multi-day sum gap defined 1237 24.09.1998 29.09.1998 multi-day sum gap defined 1237 29.12.2001 03.01.2002 multi-day sum gap defined 1237 01.04.2002 04.04.2002 multi-day sum gap defined 1237 31.05.2008 02.06.2008 multi-day sum gap defined 1307 15.09.1998 18.09.1998 multi-day sum gap defined 1307 06.11.1998 16.11.1998 multi-day sum gap defined 1307 23.12.1998 26.12.1998 multi-day sum gap defined 1307 24.12.1999 26.12.1999 multi-day sum gap defined 1307 24.12.2000 26.12.2000 multi-day sum gap defined 1307 06.06.2001 08.06.2001 multi-day sum gap defined 1307 18.06.2001 20.06.2001 multi-day sum gap defined 1307 16.07.2001 18.07.2001 multi-day sum gap defined 1307 05.10.2001 07.10.2001 multi-day sum gap defined station no. start end observation consequence 1307 18.10.2001 25.10.2001 uncertain partition into single days gap defined 1307 26.01.2002 28.01.2002 multi-day sum gap defined 1307 15.03.2002 18.03.2002 multi-day sum gap defined 1307 01.08.2002 31.08.2002 no precipitation gap defined 1308 01.07.1999 06.07.1999 multi-day sum gap defined 1308 25.12.1999 27.12.1999 multi-day sum gap defined 1308 13.02.2000 15.02.2000 multi-day sum gap defined 1308 25.03.2000 27.03.2000 multi-day sum gap defined 1308 01.07.2000 10.07.2000 multi-day sum gap defined 1308 18.06.2001 18.07.2001 multi-day sum gap defined 1308 06.10.2001 08.10.2001 multi-day sum gap defined 1308 19.04.2002 21.04.2002 multi-day sum gap defined 1308 30.06.2002 08.07.2002 multi-day sum gap defined 1308 01/10/2002 31/10/2002 no precipitation gap defined 1308 01.11.2002 03.11.2002 multi-day sum gap defined 1308 10.12.2002 13.12.2002 multi-day sum gap defined 1308 20.12.2002 09.02.2003 multi-day sum gap defined 1308 07.03.2003 09.03.2003 multi-day sum gap defined 1308 03.05.2003 05.05.2003 multi-day sum gap defined 1308 29.06.2003 16.07.2003 multi-day sum gap defined 1308 25.12.2003 27.12.2003 multi-day sum gap defined 1308 25.06.2004 01.08.2004 multi-day sum gap defined 1308 18.11.2004 20.11.2004 multi-day sum gap defined 1308 07.01.2005 10.01.2005 multi-day sum gap defined 1308 22.02.2005 24.02.2005 multi-day sum gap defined 1308 16.03.2006 26.03.2006 multi-day sum gap defined 1308 01.07.2006 16.07.2006 multi-day sum gap defined 1308 21.02.2007 23.02.2007 multi-day sum gap defined 1308 03.03.2007 05.03.2007 multi-day sum gap defined 1308 24.06.2007 10.07.2007 multi-day sum gap defined 1308 06.03.2008 11.03.2008 multi-day sum gap defined 1308 11.06.2008 14.06.2008 multi-day sum gap defined 1308 29.06.2008 14.07.2008 multi-day sum gap defined 1308 20.11.2008 24.11.2008 multi-day sum gap defined 1308 01.05.2009 04.05.2009 multi-day sum gap defined 1308 04.07.2009 19.07.2009 multi-day sum gap defined 1308 03.11.2009 05.11.2009 multi-day sum gap defined 1332 05.11.2000 07.11.2000 multi-day sum gap defined 1332 03.02.2009 06.02.2009 multi-day sum gap defined 1338 10.02.1998 12.02.1998 multi-day sum gap defined 1338 22.01.1999 31.01.1999 multi-day sum gap defined 1338 26.05.2001 28.05.2001 multi-day sum gap defined 1338 15.03.2002 17.03.2002 multi-day sum gap defined 1338 02.09.2006 14.09.2006 multi-day sum gap defined 1338 18.11.2007 23.11.2007 multi-day sum gap defined 1338 21.02.2008 25.02.2008 multi-day sum gap defined 1407 02.03.2004 04.03.2004 multi-day sum gap defined 1407 16.07.2004 17.07.2004 no precipitation gap defined 1407 30.01.2009 01.02.2009 multi-day sum gap defined 1416 27.11.1999 12.12.1999 multi-day sum/uncertain partition into single days gap defined 1416 22.05.2000 24.05.2000 multi-day sum gap defined 1416 01.12.2000 17.12.2000 multi-day sum gap defined 1416 01.02.2001 22.03.2001 multi-day sum gap defined 1416 24.07.2001 04.08.2001 multi-day sum gap defined 1416 14.10.2001 08.12.2001 multi-day sum/uncertain partition into single days gap defined 1416 16.03.2002 19.03.2002 multi-day sum gap defined 1416 14.05.2002 28.05.2002 multi-day sum/uncertain partition into single days gap defined 1416 10.07.2002 12.07.2002 multi-day sum gap defined 1416 01/11/2002 30/11/2002 no precipitation gap defined 1416 01.12.2002 04.01.2003 multi-day sum/uncertain partition into single days gap defined 1416 19.02.2003 21.02.2003 multi-day sum gap defined 1416 19.05.2003 21.05.2003 multi-day sum gap defined 1416 19.09.2003 21.09.2003 multi-day sum gap defined 1416 29.09.2003 01.10.2003 multi-day sum gap defined 1416 27.10.2003 23.02.2004 multi-day sum/uncertain partition into single days gap defined 1416 20.07.2004 23.07.2004 multi-day sum gap defined 1416 01/11/2004 30/11/2004 no precipitation gap defined station no. start end observation consequence 1416 10.12.2004 30.09.2006 multi-day sum gap defined 1416 07.11.2006 22.06.2007 multi-day sum gap defined 1416 01.10.2007 12.07.2009 multi-day sum gap defined 1416 11.10.2009 03.12.2009 multi-day sum gap defined 1420 22.12.1999 24.12.1999 multi-day sum gap defined 1420 30.07.2000 01.08.2000 multi-day sum gap defined 1420 01.02.2001 04.02.2001 multi-day sum gap defined 1420 27.02.2001 10.03.2001 multi-day sum gap defined 1420 26.03.2001 28.03.2001 multi-day sum gap defined 1420 03.04.2001 05.04.2001 multi-day sum gap defined 1420 08.08.2001 10.08.2001 multi-day sum gap defined 1420 20.08.2001 26.08.2001 multi-day sum gap defined 1420 17.12.2001 22.12.2001 multi-day sum gap defined 1420 14.12.2002 22.12.2002 multi-day sum gap defined 1420 29.01.2003 01.02.2003 multi-day sum gap defined 1420 19.07.2004 21.07.2004 uncertain partition into single days gap defined 1420 15.09.2004 20.09.2004 multi-day sum gap defined 1420 16.10.2004 21.10.2004 multi-day sum gap defined 1420 23.11.2004 17.12.2004 multi-day sum/uncertain partition into single days gap defined 1420 26.12.2004 30.12.2004 multi-day sum gap defined 1420 26.01.2005 07.02.2005 multi-day sum/uncertain partition into single days gap defined 1420 13.02.2005 08.04.2005 multi-day sum/uncertain partition into single days gap defined 1420 27.07.2005 01.08.2005 multi-day sum gap defined 1420 17.08.2005 19.08.2005 multi-day sum gap defined 1420 07.12.2005 10.12.2005 multi-day sum gap defined 1420 15.02.2006 17.02.2006 uncertain partition into single days gap defined 1420 18.10.2006 22.10.2006 multi-day sum gap defined 1420 01.12.2006 28.12.2006 uncertain partition into single days gap defined 1420 03.01.2007 05.01.2007 multi-day sum gap defined 1420 15.01.2007 17.01.2007 multi-day sum gap defined 1420 07.02.2007 09.02.2007 multi-day sum gap defined 1420 18.02.2007 20.02.2007 multi-day sum gap defined 1420 17.09.2007 29.10.2007 multi-day sum/uncertain partition into single days gap defined 1420 30.01.2008 29.05.2008 multi-day sum/uncertain partition into single days gap defined 1420 01.12.2008 03.12.2008 multi-day sum gap defined 1420 03.04.2009 10.04.2009 uncertain partition into single days gap defined 1420 30.04.2009 03.05.2009 multi-day sum gap defined 1420 18.10.2009 23.10.2009 multi-day sum/uncertain partition into single days gap defined 1420 09.12.2009 16.02.2010 multi-day sum/uncertain partition into single days gap defined 1420 01.03.2010 01.04.2010 no precipitation gap defined 1420 01.05.2010 03.05.2010 multi-day sum gap defined 1507 02.01.1998 01.06.1999 multi-day sum gap defined 1507 26.11.1999 01.06.2000 multi-day sum gap defined 1507 16.08.2000 20.09.2000 multi-day sum gap defined 1507 30.09.2000 02.10.2000 multi-day sum gap defined 1507 26.10.2000 12.11.2000 multi-day sum gap defined 1507 23.12.2000 17.01.2001 multi-day sum gap defined 1507 11.02.2001 16.02.2001 multi-day sum gap defined 1507 15.06.2001 18.06.2001 multi-day sum gap defined 1507 17.10.2001 19.10.2001 multi-day sum gap defined 1507 05.12.2001 04.10.2004 multi-day sum/uncertain partition into single days gap defined 1507 16.11.2004 22.05.2006 multi-day sum gap defined 1507 17.08.2006 14.09.2006 multi-day sum gap defined 1507 05.10.2006 09.10.2006 multi-day sum gap defined 1507 20.11.2006 09.12.2007 multi-day sum gap defined 1507 15.01.2008 17.01.2008 multi-day sum gap defined 1507 03.02.2008 12.11.2008 multi-day sum gap defined 1507 16.01.2009 16.04.2009 multi-day sum gap defined 1507 30.04.2009 02.05.2009 multi-day sum gap defined 1507 15.06.2009 18.06.2009 uncertain partition into single days gap defined 1507 20.08.2009 23.08.2009 multi-day sum gap defined 1507 01.09.2009 11.10.2009 multi-day sum gap defined 1507 28.10.2009 30.10.2009 multi-day sum gap defined 1507 05.11.2009 08.11.2009 multi-day sum gap defined 1507 23.12.2009 30.12.2009 multi-day sum gap defined 1516 25.03.1998 27.03.1998 multi-day sum gap defined 1516 22.04.1998 24.04.1998 multi-day sum gap defined station no. start end observation consequence 1516 25.04.1998 27.04.1998 multi-day sum gap defined 1516 18.01.1999 20.01.1999 multi-day sum gap defined 1516 06.05.1999 09.05.1999 multi-day sum gap defined 1516 28.02.2000 04.03.2000 multi-day sum gap defined 1516 22.10.2000 28.10.2000 multi-day sum gap defined 1516 21.01.2001 27.01.2001 multi-day sum gap defined 1516 11.04.2001 16.04.2001 multi-day sum gap defined 1516 09.07.2001 12.07.2001 multi-day sum gap defined 1516 20.08.2001 25.08.2001 multi-day sum gap defined 1516 06.11.2001 09.11.2001 multi-day sum gap defined 1516 01.10.2002 05.10.2002 multi-day sum gap defined 1516 08.01.2003 15.01.2003 multi-day sum gap defined 1516 13.05.2003 21.05.2003 multi-day sum gap defined 1516 18.09.2003 21.09.2003 multi-day sum gap defined 1516 28.10.2003 01.11.2003 multi-day sum gap defined 1516 10.12.2003 17.12.2003 multi-day sum gap defined 1516 08.01.2004 17.01.2004 multi-day sum/uncertain partition into single days gap defined 1516 10.09.2004 16.09.2004 multi-day sum gap defined 1516 23.11.2004 02.12.2004 multi-day sum gap defined 1516 04.08.2005 06.08.2005 multi-day sum gap defined 1516 05.12.2005 14.12.2005 multi-day sum gap defined 1516 22.08.2006 28.08.2006 multi-day sum/uncertain partition into single days gap defined 1516 28.11.2006 30.11.2006 multi-day sum gap defined 1516 05.12.2006 10.12.2006 multi-day sum gap defined 1616 12.05.2003 17.05.2003 multi-day sum/uncertain partition into single days gap defined 1616 09.08.2003 11.08.2003 multi-day sum gap defined 1616 20.09.2003 23.09.2003 multi-day sum gap defined 1616 28.11.2003 30.11.2003 multi-day sum gap defined 1616 17.03.2004 21.03.2004 multi-day sum gap defined 1616 12.08.2005 16.08.2005 multi-day sum gap defined 1616 13.09.2005 16.09.2005 multi-day sum gap defined 1616 30.12.2005 10.01.2006 multi-day sum gap defined 1616 06.05.2006 08.05.2006 multi-day sum gap defined 1616 12.05.2006 14.05.2006 multi-day sum/uncertain partition into single days gap defined 1616 30.06.2006 05.07.2006 multi-day sum gap defined 1616 16.08.2006 23.08.2006 multi-day sum gap defined 1616 19.10.2006 23.10.2006 multi-day sum gap defined 1616 16.11.2006 21.11.2006 multi-day sum gap defined 1616 10.05.2007 15.05.2007 multi-day sum gap defined 1616 14.06.2007 18.06.2007 multi-day sum gap defined 1616 30.09.2007 06.10.2007 multi-day sum gap defined 1616 23.08.2008 25.08.2008 multi-day sum gap defined 1616 04.09.2008 06.09.2008 multi-day sum gap defined 1616 24.09.2008 30.09.2008 multi-day sum gap defined 1616 12.12.2008 16.12.2008 no precipitation gap defined 1616 13.05.2009 15.05.2009 multi-day sum gap defined 1616 03.07.2009 07.07.2009 multi-day sum gap defined 1616 17.07.2009 28.07.2009 uncertain partition into single days gap defined 1616 15.08.2009 04.09.2009 multi-day sum/uncertain partition into single days gap defined 1616 07.11.2009 12.11.2009 multi-day sum gap defined 1616 23.11.2009 25.11.2009 multi-day sum gap defined 1616 06.12.2009 08.12.2009 multi-day sum gap defined 1616 17.12.2009 20.12.2009 multi-day sum gap defined 1637 28.05.1998 02.06.1998 multi-day sum gap defined 1637 18.12.1998 20.12.1998 multi-day sum gap defined 1637 01.08.1999 31.08.1999 no precipitation gap defined 1637 02.11.1999 25.11.1999 multi-day sum gap defined 1637 01.12.1999 01.01.2000 no precipitation gap defined 1637 01.08.2000 08.08.2000 multi-day sum gap defined 1637 14.08.2000 01.11.2000 multi-day sum/no precipitation gap defined 1637 09.07.2001 12.07.2001 multi-day sum gap defined 1637 20.07.2001 01.11.2002 multi-day sum/no precipitation gap defined 1637 01.12.2002 31.01.2003 multi-day sum/no precipitation gap defined 1637 01.03.2003 12.04.2003 multi-day sum gap defined 1637 28.05.2003 06.01.2005 multi-day sum gap defined 1637 01.02.2005 01.05.2006 multi-day sum gap defined 1637 01.11.2006 01.02.2007 multi-day sum gap defined station no. start end observation consequence 1637 01.11.2008 28.02.2009 multi-day sum gap defined 1707 02.01.1998 18.05.2002 multi-day sum/no precipitation gap defined 1707 03.03.2003 05.03.2003 multi-day sum gap defined 1707 11.05.2003 13.05.2003 multi-day sum gap defined 1707 18.05.2003 20.05.2003 multi-day sum gap defined 1707 01.06.2003 04.06.2003 multi-day sum gap defined 1707 26.06.2003 28.06.2003 multi-day sum gap defined 1707 19.11.2003 21.11.2003 multi-day sum gap defined 1707 02.05.2005 04.05.2005 multi-day sum gap defined 1707 03.07.2006 05.07.2006 multi-day sum gap defined 1707 12.09.2006 14.09.2006 multi-day sum gap defined 1707 10.10.2006 12.10.2006 multi-day sum gap defined 1707 27.11.2006 30.11.2006 multi-day sum gap defined 1707 20.02.2007 26.02.2007 multi-day sum gap defined 1707 21.06.2007 23.06.2007 multi-day sum gap defined 1707 25.07.2007 27.07.2007 multi-day sum gap defined 1707 18.01.2009 29.01.2009 multi-day sum gap defined 1707 11.11.2009 13.11.2009 multi-day sum gap defined 1712 18.10.1998 20.10.1998 multi-day sum gap defined 1712 23.10.1998 25.10.1998 multi-day sum gap defined 1712 04.04.1999 06.04.1999 multi-day sum gap defined 1712 03.06.1999 07.06.1999 multi-day sum gap defined 1712 08.09.1999 10.09.1999 multi-day sum gap defined 1712 17.11.1999 19.11.1999 multi-day sum gap defined 1712 22.12.1999 24.12.1999 multi-day sum gap defined 1712 20.02.2000 22.02.2000 multi-day sum gap defined 1712 22.03.2001 25.03.2001 multi-day sum gap defined 1712 12.04.2001 14.04.2001 multi-day sum gap defined 1712 08.08.2001 12.08.2001 multi-day sum gap defined 1712 24.08.2001 26.08.2001 multi-day sum gap defined 1712 18.10.2001 21.10.2001 multi-day sum gap defined 1712 24.10.2001 27.10.2001 multi-day sum gap defined 1712 02.12.2001 03.12.2001 multi-day sum gap defined 1712 27.01.2002 29.01.2002 multi-day sum gap defined 1712 01/08/2002 30/04/2008 no precipitation, multi-day sum gap defined 1716 23.12.2007 29.12.2007 multi-day sum gap defined 1716 01/11/2008 30/11/2008 no precipitation gap defined 1716 24.04.2009 17.06.2009 multi-day sum gap defined 1716 22.08.2009 24.08.2009 multi-day sum gap defined 1716 18.12.2009 31.12.2009 multi-day sum gap defined 1719 10.03.2001 12.03.2001 multi-day sum gap defined 1719 08.09.2008 10.09.2008 multi-day sum gap defined 1719 06.07.2009 08.11.2009 multi-day sum gap defined 1719 10.12.2009 20.12.2009 multi-day sum gap defined 1723 26.02.2001 28.02.2001 multi-day sum gap defined 1723 07.10.2005 09.10.2005 multi-day sum gap defined 1723 27.10.2007 15.11.2007 implausible gap defined 1807 20.09.1999 25.09.1999 uncertain partition into single days gap defined 1807 25.08.2000 28.08.2000 uncertain partition into single days gap defined 1812 18.10.1998 20.10.1998 multi-day sum gap defined 1812 15.10.2002 17.10.2002 multi-day sum gap defined 1812 19.07.2004 21.07.2004 multi-day sum gap defined 1812 10.12.2006 12.12.2006 uncertain partition into single days gap defined 1812 23.11.2009 24.11.2009 multi-day sum gap defined 1812 19.01.2010 23.01.2010 multi-day sum gap defined 1819 01/04/2002 30/04/2002 no precipitation gap defined 1830 01.07.1998 31.07.1998 multi-day sum gap defined 1830 19.03.2001 31.03.2001 implausible gap defined 1830 30.07.2001 01.08.2001 uncertain partition into single days gap defined 1830 31.12.2004 02.01.2005 uncertain partition into single days gap defined 1830 14.04.2005 16.04.2005 multi-day sum gap defined 1838 01/02/1999 28/02/1999 no precipitation gap defined 1838 20.03.1999 30.03.1999 multi-day sum gap defined 1838 26.05.2000 28.05.2000 multi-day sum gap defined 1838 03.12.2000 05.12.2000 multi-day sum gap defined 1838 01.08.2001 03.08.2001 multi-day sum gap defined 1838 31.08.2001 14.09.2001 multi-day sum gap defined station no. start end observation consequence 1838 11.07.2002 16.07.2002 multi-day sum gap defined 1838 21.02.2005 23.02.2005 multi-day sum gap defined 1838 26.07.2007 28.07.2007 multi-day sum gap defined 1838 01/03/2008 31/03/2008 no precipitation gap defined 1838 22.04.2008 25.04.2008 multi-day sum gap defined 1838 06.07.2008 08.07.2008 multi-day sum gap defined 1838 07.12.2008 09.12.2008 multi-day sum gap defined 1838 09.10.2009 22.10.2009 multi-day sum gap defined 1923 11.01.2009 31.01.2009 no precipitation gap defined 2012 11.01.1998 13.01.1998 multi-day sum gap defined 2012 11.02.1998 20.02.1998 multi-day sum gap defined 2012 23.03.1998 25.03.1998 multi-day sum gap defined 2012 09.04.1998 19.04.1998 multi-day sum gap defined 2012 22.06.1998 24.06.1998 multi-day sum gap defined 2012 09.12.1998 14.12.1998 multi-day sum gap defined 2012 27.12.1998 29.12.1998 multi-day sum gap defined 2012 01.12.1999 07.12.1999 multi-day sum gap defined 2012 31.12.1999 09.01.2000 multi-day sum gap defined 2012 28.01.2000 30.01.2000 multi-day sum gap defined 2012 23.05.2000 01.02.2002 multi-day sum gap defined 2012 01/02/2002 31/03/2002 no precipitation gap defined 2012 22.05.2002 24.05.2002 multi-day sum gap defined 2012 20.06.2002 23.06.2002 multi-day sum gap defined 2012 17.08.2002 04.10.2002 multi-day sum/uncertain partition into single days gap defined 2012 24.01.2003 26.01.2003 multi-day sum gap defined 2012 19.09.2003 22.09.2003 multi-day sum gap defined 2012 11.11.2003 13.11.2003 multi-day sum gap defined 2012 26.11.2003 30.11.2003 multi-day sum gap defined 2012 20.03.2004 02.04.2004 multi-day sum/uncertain partition into single days gap defined 2012 28.05.2004 23.06.2004 multi-day sum gap defined 2012 10.07.2004 12.07.2004 multi-day sum gap defined 2012 07.08.2004 09.08.2004 multi-day sum gap defined 2012 01.10.2004 06.10.2004 multi-day sum gap defined 2012 17.12.2004 21.12.2004 multi-day sum gap defined 2012 02.06.2005 06.06.2005 multi-day sum gap defined 2012 29.09.2005 01.10.2005 multi-day sum gap defined 2012 30.03.2006 01.04.2006 multi-day sum gap defined 2012 18.11.2006 21.11.2006 multi-day sum gap defined 2012 27.05.2007 31.05.2007 multi-day sum gap defined 2012 09.07.2007 12.07.2007 multi-day sum gap defined 2012 02.07.2008 04.07.2008 multi-day sum gap defined 2012 20.10.2008 22.10.2008 multi-day sum gap defined 2012 05.10.2009 07.10.2009 multi-day sum gap defined 2030 03.04.2001 07.04.2001 multi-day sum gap defined 2030 05.07.2007 07.08.2007 multi-day sum gap defined 2030 11.01.2008 13.01.2008 uncertain partition into single days gap defined 2030 09.11.2008 11.11.2008 multi-day sum gap defined 2037 16.12.1999 18.12.1999 multi-day sum gap defined 2037 01.04.2000 03.04.2000 multi-day sum gap defined 2037 28.07.2000 31.07.2000 multi-day sum gap defined 2037 09.07.2001 11.07.2001 multi-day sum gap defined 2037 06.08.2001 01.11.2002 implausible gap defined 2037 23.02.2004 25.02.2004 multi-day sum gap defined 2037 03.07.2004 08.08.2004 implausible gap defined 2037 01.09.2004 01.10.2004 no precipitation gap defined 2037 21.01.2005 23.01.2005 multi-day sum gap defined 2037 25.04.2005 27.05.2005 multi-day sum gap defined 2037 01.06.2005 30.06.2005 no precipitation gap defined 2037 03.07.2005 06.07.2005 multi-day sum gap defined 2037 01.09.2005 30.09.2005 no precipitation gap defined 2037 10.10.2005 12.10.2005 multi-day sum gap defined 2037 01.11.2005 09.12.2005 multi-day sum/no precipitation gap defined 2037 09.04.2006 12.04.2006 multi-day sum gap defined 2037 27.07.2006 01.08.2006 multi-day sum gap defined 2037 01.10.2006 31.10.2006 no precipitation gap defined 2037 27.12.2006 29.12.2006 multi-day sum gap defined 2037 15.01.2007 17.01.2007 multi-day sum gap defined station no. start end observation consequence 2037 20.04.2007 23.04.2007 multi-day sum/uncertain partition into single days gap defined 2037 23.05.2007 01.06.2007 multi-day sum/uncertain partition into single days gap defined 2037 11.07.2007 13.07.2007 multi-day sum gap defined 2037 02.10.2007 04.10.2007 multi-day sum gap defined 2037 14.10.2007 17.10.2007 multi-day sum gap defined 2037 12.01.2008 14.01.2008 multi-day sum gap defined 2037 23.03.2008 25.03.2008 multi-day sum gap defined 2037 30.05.2008 06.06.2008 multi-day sum gap defined 2037 13.09.2008 16.09.2008 multi-day sum gap defined 2037 07.12.2008 09.12.2008 multi-day sum gap defined 2037 06.05.2009 08.05.2009 multi-day sum gap defined 2037 30.06.2009 02.07.2009 multi-day sum gap defined 2037 29.07.2009 31.07.2009 multi-day sum gap defined 2037 04.12.2009 06.12.2009 multi-day sum gap defined 2038 07.03.2003 10.03.2003 multi-day sum gap defined 2038 21.09.2003 01.10.2003 multi-day sum gap defined 2038 01.11.2003 03.11.2003 multi-day sum gap defined 2038 05.09.2005 20.09.2005 multi-day sum gap defined 2038 10.09.2006 16.09.2006 multi-day sum gap defined 2038 05.09.2008 12.09.2008 multi-day sum gap defined 2038 07.11.2008 09.11.2008 multi-day sum gap defined 2112 01.05.1998 31.05.1998 multi-day sum gap defined 2112 13.07.1998 01.08.1998 multi-day sum gap defined 2112 11.09.1998 18.09.1998 multi-day sum gap defined 2112 29.09.1998 01.10.1998 multi-day sum gap defined 2112 10.10.1998 16.10.1998 multi-day sum gap defined 2112 27.10.1998 29.11.1998 multi-day sum/uncertain partition into single days gap defined 2112 11.02.1999 18.02.1999 multi-day sum gap defined 2112 26.02.1999 01.03.1999 multi-day sum/uncertain partition into single days gap defined 2115 02.07.2000 16.07.2000 multi-day sum gap defined 2115 13.08.2000 17.08.2000 multi-day sum gap defined 2115 28.09.2000 02.10.2000 multi-day sum gap defined 2115 26.11.2001 28.11.2001 multi-day sum gap defined 2115 06.08.2004 13.08.2004 multi-day sum gap defined 2115 20.06.2008 22.06.2008 multi-day sum gap defined 2115 04.02.2009 08.02.2009 multi-day sum gap defined 2130 01.06.1999 30.09.2009 station not trustful - cause: multi-day sums gap defined 2230 14.09.2000 16.09.2000 multi-day sum gap defined 2230 05.10.2001 07.10.2001 multi-day sum gap defined 2230 08.02.2002 11.02.2002 multi-day sum gap defined 2230 03.02.2004 05.02.2004 multi-day sum gap defined 2230 30.06.2008 02.07.2008 multi-day sum gap defined 2230 21.11.2008 25.11.2008 implausible gap defined 2232 01.01.1998 31.12.2000 station not used - cause: frequent multi-day sums gap defined 2232 01/12/1999 31/12/1999 no precipitation gap defined 2322 27.02.1998 01.03.1998 multi-day sum gap defined 2322 03.04.1998 05.04.1998 multi-day sum gap defined 2322 25.07.1998 04.08.1998 multi-day sum gap defined 2322 23.10.1998 09.11.1998 multi-day sum gap defined 2322 22.12.1998 30.12.1998 multi-day sum gap defined 2322 29.10.1999 31.10.1999 multi-day sum gap defined 2322 29.01.2000 31.01.2000 multi-day sum gap defined 2322 26.02.2000 28.02.2000 multi-day sum gap defined 2322 25.03.2000 27.03.2000 multi-day sum gap defined 2322 09.07.2000 11.07.2000 uncertain partition into single days gap defined 2322 29.07.2000 25.09.2000 multi-day sum gap defined 2322 18.11.2000 20.11.2000 multi-day sum gap defined 2322 27.12.2000 01.01.2001 multi-day sum/uncertain partition into single days gap defined 2322 10.03.2001 12.03.2001 multi-day sum gap defined 2322 21.04.2001 23.04.2001 multi-day sum gap defined 2322 13.05.2001 15.05.2001 multi-day sum gap defined 2322 06.10.2001 08.10.2001 multi-day sum gap defined 2322 24.01.2002 26.01.2002 multi-day sum gap defined 2322 09.03.2002 11.03.2002 multi-day sum gap defined 2322 20.04.2002 22.04.2002 multi-day sum gap defined 2322 10.08.2002 12.08.2002 multi-day sum gap defined 2322 01.11.2002 04.11.2002 multi-day sum/uncertain partition into single days gap defined station no. start end observation consequence 2322 29.11.2002 01.12.2002 multi-day sum gap defined 2322 07.03.2003 10.03.2003 multi-day sum gap defined 2322 03.05.2003 05.05.2003 multi-day sum gap defined 2322 17.05.2003 19.05.2003 multi-day sum gap defined 2322 31.05.2003 02.06.2003 multi-day sum gap defined 2322 27.07.2003 29.07.2003 multi-day sum gap defined 2322 19.09.2003 22.09.2003 multi-day sum gap defined 2322 28.11.2003 30.11.2003 multi-day sum gap defined 2322 28.12.2003 12.01.2004 multi-day sum gap defined 2322 16.03.2004 18.03.2004 multi-day sum gap defined 2322 03.04.2004 05.04.2004 multi-day sum gap defined 2322 17.04.2004 19.04.2004 multi-day sum gap defined 2322 13.08.2004 24.08.2004 multi-day sum/uncertain partition into single days gap defined 2322 17.01.2005 21.01.2005 multi-day sum gap defined 2322 20.02.2005 22.02.2005 multi-day sum gap defined 2322 18.04.2005 20.04.2005 multi-day sum gap defined 2322 29.04.2005 01.05.2005 multi-day sum gap defined 2322 20.08.2005 02.09.2005 multi-day sum gap defined 2322 30.12.2005 01.01.2006 uncertain partition into single days gap defined 2322 26.03.2006 31.03.2006 multi-day sum gap defined 2322 16.04.2006 29.05.2006 multi-day sum gap defined 2322 23.11.2006 31.12.2006 multi-day sum gap defined 2324 02.06.1998 04.06.1998 multi-day sum/no precipitation gap defined 2324 05.11.2000 08.11.2000 multi-day sum gap defined 2324 26.02.2001 01.03.2001 multi-day sum gap defined 2324 20.04.2001 22.04.2001 multi-day sum gap defined 2324 08.06.2004 13.06.2004 uncertain partition into single days gap defined 2324 19.10.2005 21.10.2005 multi-day sum gap defined 2324 28.10.2005 30.10.2005 multi-day sum gap defined 2324 30.10.2008 01.11.2008 multi-day sum gap defined 2324 03.03.2009 05.03.2009 multi-day sum gap defined 2324 11.06.2009 18.06.2009 multi-day sum gap defined 2324 30.10.2009 01.12.2009 multi-day sum/no precipitation gap defined 2324 04.12.2009 31.12.2009 multi-day sum gap defined 2332 08.01.2002 16.01.2002 multi-day sum/uncertain partition into single days gap defined 2332 01.04.2003 01.05.2003 multi-day sum gap defined 2332 19.06.2004 23.06.2004 multi-day sum gap defined 2332 21.02.2005 24.02.2005 uncertain partition into single days gap defined 2411 01.02.1998 01.03.1998 no precipitation gap defined 2411 23.03.1998 30.03.1998 multi-day sum gap defined 2411 04.10.1998 14.10.1998 multi-day sum gap defined 2415 15.06.2000 21.07.2000 multi-day sum gap defined 2415 10.07.2002 12.07.2002 multi-day sum gap defined 2415 01.04.2010 03.04.2010 multi-day sum gap defined 2420 12.01.1998 14.01.1998 multi-day sum gap defined 2420 03.04.1998 05.04.1998 multi-day sum gap defined 2420 13.11.1998 15.11.1998 multi-day sum gap defined 2420 26.09.1999 28.09.1999 multi-day sum gap defined 2420 01.12.1999 01.01.2000 no precipitation gap defined 2420 30.08.2000 01.09.2000 multi-day sum gap defined 2420 05.12.2000 07.12.2000 multi-day sum gap defined 2420 01.03.2001 01.04.2001 no precipitation gap defined 2420 01.06.2001 01.07.2001 no precipitation gap defined 2420 16.08.2001 19.08.2001 multi-day sum gap defined 2420 01.10.2001 01.12.2001 no precipitation gap defined 2420 14.10.2002 16.10.2002 multi-day sum gap defined 2420 09.11.2002 11.11.2002 multi-day sum gap defined 2420 14.11.2002 16.11.2002 multi-day sum gap defined 2420 15.01.2003 20.01.2003 multi-day sum gap defined 2420 23.02.2003 13.03.2003 uncertain partition into single days gap defined 2420 02.05.2003 04.05.2003 multi-day sum gap defined 2420 20.07.2003 02.08.2003 multi-day sum/uncertain partition into single days gap defined 2420 20.09.2003 24.09.2003 uncertain partition into single days gap defined 2420 01.11.2003 04.04.2004 no precipitation/uncertain partition into single days gap defined 2420 01.06.2004 01.07.2004 no precipitation gap defined 2420 23.08.2004 25.08.2004 multi-day sum gap defined 2420 29.09.2004 31.12.2009 no precipitation/uncertain partition into single days gap defined station no. start end observation consequence 2423 01/07/1999 30/09/1999 no precipitation gap defined 2423 01/12/1999 30/03/2000 no precipitation gap defined 2423 03.07.2001 05.07.2001 multi-day sum gap defined 2423 24.08.2001 26.08.2001 multi-day sum gap defined 2432 09.10.1998 12.10.1998 multi-day sum gap defined 2432 07.11.1998 09.11.1998 multi-day sum gap defined 2432 18.12.1998 24.12.1998 multi-day sum gap defined 2432 09.07.1999 25.07.1999 multi-day sum gap defined 2432 13.08.1999 15.08.1999 multi-day sum gap defined 2432 24.09.1999 28.09.1999 multi-day sum gap defined 2432 16.06.2001 01.07.2001 multi-day sum gap defined 2432 05.07.2002 11.07.2002 multi-day sum gap defined 2432 01.10.2004 09.10.2004 multi-day sum gap defined 2432 01.09.2009 30.10.2009 no precipitation gap defined 2520 04.07.1999 17.07.1999 multi-day sum/uncertain partition into single days gap defined 2520 01.08.1999 03.08.1999 no precipitation gap defined 2520 11.11.1999 04.01.2000 multi-day sum/uncertain partition into single days gap defined 2520 05.03.2000 28.03.2000 uncertain partition into single days gap defined 2520 27.05.2000 06.09.2000 uncertain partition into single days gap defined 2520 23.12.2000 01.01.2001 uncertain partition into single days gap defined 2520 01/01/2001 28/02/2001 no precipitation gap defined 2520 05.03.2001 18.03.2001 multi-day sum/uncertain partition into single days gap defined 2520 01/04/2001 30/04/2001 no precipitation gap defined 2520 04.05.2001 16.05.2001 multi-day sum gap defined 2520 03.08.2001 08.09.2001 uncertain partition into single days gap defined 2520 08.10.2001 15.10.2001 multi-day sum gap defined 2520 17.11.2001 01.12.2001 multi-day sum/uncertain partition into single days gap defined 2520 08.01.2002 12.01.2002 multi-day sum gap defined 2520 25.07.2003 27.07.2003 multi-day sum gap defined 2520 27.05.2004 22.06.2004 multi-day sum/uncertain partition into single days gap defined 2520 28.06.2004 07.07.2004 multi-day sum/uncertain partition into single days gap defined 2520 12.05.2006 14.05.2006 multi-day sum/uncertain partition into single days gap defined 2520 01.09.2006 05.09.2006 multi-day sum/uncertain partition into single days gap defined 2520 01.03.2007 01.04.2007 no precipitation gap defined 2520 13.05.2007 29.05.2007 multi-day sum/uncertain partition into single days gap defined 2520 08.01.2008 10.01.2008 multi-day sum gap defined 2520 30.03.2008 01.04.2008 multi-day sum gap defined 2520 27.05.2008 05.06.2008 uncertain partition into single days gap defined 2520 02.02.2009 04.02.2009 multi-day sum gap defined 2520 17.05.2009 19.05.2009 multi-day sum gap defined 2520 08.10.2009 10.10.2009 uncertain partition into single days gap defined 2522 02.01.1998 31.08.2005 station not trustful - cause: multi-day sums gap defined 2523 29.02.2000 01.04.2000 no precipitation gap defined 2523 01/05/2000 31/07/2000 no precipitation gap defined 2523 01/10/2000 31/10/2000 no precipitation gap defined 2523 01/01/2001 28/02/2001 no precipitation gap defined 2523 07.10.2001 09.10.2001 multi-day sum gap defined 2523 01/11/2001 30/11/2001 no precipitation gap defined 2523 01/04/2002 30/04/2002 no precipitation gap defined 2523 05.06.2002 11.06.2002 multi-day sum gap defined 2523 01/09/2002 30/09/2002 no precipitation gap defined 2523 01.11.2002 04.11.2002 multi-day sum gap defined 2523 06.11.2002 08.11.2002 uncertain partition into single days gap defined 2523 01/01/2003 28/02/2003 no precipitation gap defined 2523 16.06.2004 23.06.2004 multi-day sum gap defined 2523 13.09.2004 18.09.2004 multi-day sum gap defined 2523 08.12.2005 10.12.2005 multi-day sum gap defined 2523 16.06.2006 28.06.2006 multi-day sum gap defined 2523 04.08.2006 13.08.2006 multi-day sum gap defined 2523 25.08.2006 30.08.2006 multi-day sum gap defined 2523 03.03.2007 05.03.2007 multi-day sum gap defined 2523 17.05.2008 21.05.2008 multi-day sum gap defined 2531 11.04.1999 13.04.1999 uncertain partition into single days gap defined 2531 31.10.1999 06.11.1999 multi-day sum gap defined 2531 10.12.1999 12.12.1999 multi-day sum gap defined 2531 15.02.2000 17.02.2000 multi-day sum gap defined 2531 27.12.2000 24.03.2001 multi-day sum/uncertain partition into single days gap defined station no. start end observation consequence 2531 25.06.2001 01.07.2001 multi-day sum gap defined 2531 05.10.2001 07.10.2001 multi-day sum gap defined 2531 15.10.2001 18.10.2001 multi-day sum gap defined 2531 16.01.2002 18.01.2002 multi-day sum gap defined 2531 09.09.2003 01.10.2003 multi-day sum/uncertain partition into single days gap defined 2532 13.08.1999 28.08.1999 multi-day sum gap defined 2532 01.07.2006 13.07.2006 multi-day sum gap defined 2532 21.08.2006 29.08.2006 multi-day sum gap defined 2532 12.06.2007 17.06.2007 multi-day sum gap defined 2532 14.08.2009 16.08.2009 multi-day sum gap defined 2620 24.08.1999 26.08.1999 multi-day sum gap defined 2620 01.06.2000 04.06.2000 multi-day sum gap defined 2620 05.09.2000 07.09.2000 multi-day sum gap defined 2620 23.09.2000 25.09.2000 multi-day sum gap defined 2620 10.11.2000 12.11.2000 multi-day sum gap defined 2620 12.12.2000 14.12.2000 multi-day sum gap defined 2620 26.02.2001 01.03.2001 multi-day sum gap defined 2620 20.03.2001 22.03.2001 multi-day sum gap defined 2620 26.03.2001 28.03.2001 multi-day sum gap defined 2620 27.04.2001 29.04.2001 multi-day sum gap defined 2620 01/01/2002 31/01/2002 no precipitation gap defined 2620 29.04.2002 01.05.2002 uncertain partition into single days gap defined 2620 14.04.2004 16.04.2004 multi-day sum gap defined 2632 19.04.2002 22.04.2002 multi-day sum gap defined 2632 26.04.2002 29.04.2002 multi-day sum gap defined 2632 01.06.2002 01.07.2002 multi-day sum/uncertain partition into single days gap defined 2632 02.11.2002 30.12.2002 multi-day sum/uncertain partition into single days gap defined 2632 08.02.2003 10.02.2003 multi-day sum gap defined 2632 08.03.2003 10.03.2003 multi-day sum gap defined 2632 26.04.2003 28.04.2003 multi-day sum gap defined 2632 03.05.2003 05.05.2003 multi-day sum gap defined 2632 01.06.2003 11.06.2003 multi-day sum gap defined 2632 10.01.2004 16.01.2004 multi-day sum gap defined 2632 20.03.2004 22.03.2004 multi-day sum gap defined 2632 17.04.2004 19.04.2004 multi-day sum gap defined 2632 30.05.2004 02.06.2004 uncertain partition into single days gap defined 2632 25.06.2004 12.07.2004 multi-day sum/uncertain partition into single days gap defined 2632 20.11.2004 22.11.2004 multi-day sum gap defined 2632 18.12.2004 01.08.2005 multi-day sum gap defined 2632 29.10.2005 07.11.2005 multi-day sum/uncertain partition into single days gap defined 2632 11.02.2006 02.10.2006 multi-day sum/uncertain partition into single days gap defined 2632 10.11.2006 13.11.2006 multi-day sum gap defined 2632 25.12.2006 03.06.2007 multi-day sum gap defined 2632 18.08.2007 20.08.2007 multi-day sum gap defined 2632 28.09.2007 19.11.2007 multi-day sum gap defined 2632 08.12.2007 05.01.2008 multi-day sum gap defined 2632 15.03.2008 14.04.2008 multi-day sum gap defined 2632 01.08.2008 18.08.2008 multi-day sum/uncertain partition into single days gap defined 2632 04.10.2008 06.10.2008 multi-day sum gap defined 2632 25.10.2008 24.11.2008 multi-day sum gap defined 2632 24.04.2009 17.08.2009 multi-day sum gap defined 2632 23.10.2009 27.10.2009 multi-day sum gap defined 2632 05.12.2009 07.12.2009 multi-day sum gap defined 2632 19.12.2009 29.12.2009 multi-day sum gap defined 2638 06.02.1998 08.02.1998 multi-day sum gap defined 2638 02.03.1998 07.03.1998 multi-day sum gap defined 2638 17.07.1998 20.07.1998 multi-day sum gap defined 2638 18.01.1999 20.01.1999 multi-day sum gap defined 2638 14.02.1999 23.02.1999 multi-day sum gap defined 2638 30.10.1999 01.11.1999 multi-day sum gap defined 2638 20.01.2001 22.01.2001 multi-day sum gap defined 2638 20.10.2001 22.10.2001 multi-day sum gap defined 2638 18.01.2002 21.01.2002 multi-day sum gap defined 2638 17.05.2002 19.05.2002 multi-day sum gap defined 2638 22.12.2002 24.12.2002 multi-day sum gap defined 2638 05.10.2003 07.10.2003 multi-day sum gap defined 2638 13.04.2004 15.04.2004 multi-day sum gap defined station no. start end observation consequence 2638 29.10.2005 31.10.2005 multi-day sum gap defined 2638 18.12.2005 20.12.2005 multi-day sum gap defined 2638 25.10.2007 26.10.2007 very high precipitation gap defined 2638 10.11.2007 06.12.2007 implausible gap defined 2638 12.04.2008 14.04.2008 multi-day sum gap defined 2638 18.08.2008 20.08.2008 multi-day sum gap defined 2638 01/09/2008 30/09/2008 no precipitation gap defined 2638 11.12.2008 13.12.2008 multi-day sum gap defined 2638 24.03.2009 31.03.2009 multi-day sum gap defined 2638 26.06.2009 12.07.2009 multi-day sum gap defined 2638 14.08.2009 16.08.2009 uncertain partition into single days gap defined 2638 25.08.2009 27.08.2009 multi-day sum gap defined 2638 05.10.2009 11.10.2009 multi-day sum gap defined 2638 24.03.2010 26.03.2010 multi-day sum gap defined 2719 25.09.1998 12.11.1998 implausible gap defined 2719 02.03.1999 04.03.1999 multi-day sum gap defined 2719 01.11.1999 01.12.1999 no precipitation gap defined 2719 11.04.2000 01.05.2000 multi-day sum gap defined 2719 17.08.2000 21.08.2000 multi-day sum gap defined 2719 27.10.2000 05.11.2000 implausible gap defined 2719 01.01.2001 05.01.2001 multi-day sum gap defined 2719 29.04.2001 01.05.2001 multi-day sum gap defined 2719 01.08.2001 07.12.2001 multi-day sum/uncertain partition into single days gap defined 2719 22.01.2002 24.01.2002 multi-day sum gap defined 2719 25.05.2002 27.05.2002 multi-day sum gap defined 2719 12.06.2002 17.06.2002 multi-day sum/uncertain partition into single days gap defined 2719 08.09.2002 03.11.2002 multi-day sum gap defined 2719 01.12.2002 03.12.2002 multi-day sum/uncertain partition into single days gap defined 2719 26.01.2003 28.01.2003 multi-day sum gap defined 2719 27.02.2003 24.04.2003 multi-day sum/uncertain partition into single days gap defined 2719 16.05.2003 31.12.2009 multi-day sum gap defined 2720 25.10.2001 27.10.2001 multi-day sum gap defined 2720 16.11.2001 25.11.2001 multi-day sum gap defined 2720 23.12.2001 05.01.2002 multi-day sum/uncertain partition into single days gap defined 2720 26.01.2002 31.01.2002 multi-day sum/uncertain partition into single days gap defined 2720 07.02.2002 09.02.2002 multi-day sum gap defined 2720 20.03.2002 22.03.2002 multi-day sum gap defined 2720 22.05.2002 06.06.2002 multi-day sum/uncertain partition into single days gap defined 2723 06.01.1998 01.01.1999 multi-day sum/no precipitation gap defined 2737 10.07.1998 12.07.1998 multi-day sum gap defined 2737 12.11.1998 17.11.1998 multi-day sum gap defined 2737 27.11.1998 04.12.1998 multi-day sum gap defined 2737 28.11.2003 01.12.2003 multi-day sum gap defined 2824 06.09.1998 14.09.1998 uncertain partition into single days gap defined 2824 12.10.1998 13.10.1998 very high precipitation gap defined 2824 09.12.1999 11.12.1999 uncertain partition into single days gap defined 2824 04.02.2000 06.02.2000 multi-day sum gap defined 2824 10.10.2001 14.10.2001 multi-day sum gap defined 2824 16.05.2002 18.05.2002 uncertain partition into single days gap defined 2824 24.01.2004 26.01.2004 multi-day sum gap defined 2824 07.08.2008 09.08.2008 uncertain partition into single days gap defined 2924 21.02.1998 01.03.1998 multi-day sum gap defined 2924 03.04.1998 05.04.1998 multi-day sum gap defined 2924 29.05.1998 29.12.1998 multi-day sum/no precipitation gap defined 2924 24.02.1999 01.06.1999 no precipitation gap defined 2924 15.06.1999 01.11.1999 no precipitation gap defined 2931 10.06.2008 16.06.2008 uncertain partition into single days gap defined 2931 19.12.2008 21.12.2008 multi-day sum gap defined 2938 24.11.2002 01.12.2002 multi-day sum gap defined 2938 19.06.2003 28.06.2003 multi-day sum gap defined 2938 07.02.2006 09.02.2006 multi-day sum gap defined 2938 23.11.2009 06.12.2009 implausible gap defined 3015 06.06.2001 15.06.2001 multi-day sum gap defined 3015 23.06.2002 30.06.2002 multi-day sum gap defined 3037 02.01.1998 04.01.1998 multi-day sum gap defined 3037 13.01.1998 15.01.1998 multi-day sum gap defined 3037 22.01.1998 24.01.1998 multi-day sum gap defined station no. start end observation consequence 3037 06.02.1998 08.02.1998 multi-day sum gap defined 3037 09.02.1998 11.02.1998 multi-day sum gap defined 3037 05.03.1998 12.03.1998 multi-day sum gap defined 3037 28.05.1998 30.05.1998 multi-day sum gap defined 3037 05.06.1998 08.06.1998 multi-day sum gap defined 3037 09.10.1998 11.10.1998 multi-day sum gap defined 3037 15.10.1998 17.10.1998 multi-day sum gap defined 3037 02.03.1999 08.03.1999 implausible gap defined 3037 11.04.1999 13.04.1999 multi-day sum gap defined 3037 17.04.1999 19.04.1999 multi-day sum gap defined 3037 22.06.1999 24.06.1999 multi-day sum gap defined 3037 05.08.1999 07.08.1999 multi-day sum gap defined 3037 28.09.1999 30.09.1999 multi-day sum gap defined 3037 23.11.1999 29.11.1999 multi-day sum gap defined 3037 03.12.1999 05.12.1999 multi-day sum gap defined 3037 28.01.2000 30.01.2000 multi-day sum gap defined 3037 13.02.2000 15.02.2000 multi-day sum gap defined 3037 07.06.2000 09.06.2000 multi-day sum gap defined 3037 01.08.2000 03.08.2000 multi-day sum gap defined 3037 09.09.2000 12.09.2000 multi-day sum gap defined 3037 23.09.2000 27.09.2000 multi-day sum gap defined 3037 03.01.2001 08.01.2001 multi-day sum gap defined 3037 24.01.2001 01.02.2001 multi-day sum gap defined 3037 06.04.2001 08.04.2001 multi-day sum gap defined 3037 14.04.2001 16.04.2001 multi-day sum gap defined 3037 27.04.2001 30.04.2001 multi-day sum gap defined 3037 01.09.2001 03.02.2003 no precipitation gap defined 3037 01.05.2003 31.05.2003 no precipitation gap defined 3037 03.06.2003 05.06.2003 multi-day sum gap defined 3037 07.06.2003 09.06.2003 multi-day sum gap defined 3037 01.08.2003 30.11.2009 implausible gap defined 3038 02.01.1998 05.01.1998 multi-day sum gap defined 3038 17.01.1998 19.01.1998 multi-day sum gap defined 3038 10.07.1998 12.07.1998 multi-day sum gap defined 3038 01.04.1999 03.04.1999 multi-day sum gap defined 3038 05.11.1999 07.11.1999 multi-day sum gap defined 3038 15.12.2000 02.01.2001 multi-day sum gap defined 3038 14.04.2001 16.04.2001 multi-day sum gap defined 3038 18.08.2001 20.08.2001 multi-day sum gap defined 3038 01.02.2002 04.02.2002 multi-day sum gap defined 3038 26.10.2002 28.10.2002 multi-day sum gap defined 3038 21.02.2004 22.02.2004 very high precipitation gap defined 3038 21.03.2004 23.03.2004 multi-day sum gap defined 3038 07.01.2005 09.01.2005 multi-day sum gap defined 3038 17.06.2006 19.06.2006 multi-day sum gap defined 3038 31.08.2006 02.09.2006 multi-day sum gap defined 3038 11.08.2007 13.08.2007 multi-day sum gap defined 3038 03.03.2009 05.03.2009 multi-day sum gap defined 3038 23.10.2009 25.10.2009 multi-day sum gap defined 3038 16.05.2010 23.05.2010 multi-day sum gap defined 3122 01.10.1998 31.10.1998 multi-day sum gap defined 3122 13.08.1999 29.09.1999 multi-day sum gap defined 3124 04.01.1998 06.01.1998 multi-day sum gap defined 3124 11.01.1999 14.01.1999 multi-day sum gap defined 3124 15.04.2000 17.04.2000 multi-day sum gap defined 3124 06.03.2001 08.03.2001 multi-day sum gap defined 3124 27.11.2002 29.11.2002 multi-day sum gap defined 3124 31.12.2003 01.01.2004 no precipitation gap defined 3124 08.10.2005 09.10.2005 very high precipitation gap defined 3124 11.02.2006 13.02.2006 multi-day sum gap defined 3124 07.05.2006 09.05.2006 uncertain partition into single days gap defined 3124 14.01.2009 16.01.2009 multi-day sum gap defined 3124 03.03.2009 11.03.2009 multi-day sum gap defined 3124 01.05.2009 09.05.2009 multi-day sum gap defined 3124 22.05.2009 08.06.2009 multi-day sum gap defined 3138 23.03.1998 27.03.1998 multi-day sum gap defined 3222 09.07.1998 12.07.1998 uncertain partition into single days gap defined station no. start end observation consequence 3222 05.08.2006 07.08.2006 multi-day sum gap defined 3222 08.03.2009 11.03.2009 multi-day sum gap defined 3223 02.01.1998 31.12.2009 implausible gap defined 3224 01.07.1999 01.08.1999 no precipitation gap defined 3224 16.04.2000 18.04.2000 multi-day sum gap defined 3238 14.10.2004 16.10.2004 multi-day sum gap defined 3238 13.12.2004 16.12.2004 multi-day sum gap defined 3238 23.12.2004 27.12.2004 multi-day sum gap defined 3238 04.06.2008 06.06.2008 multi-day sum gap defined 3238 01.07.2008 04.07.2008 multi-day sum gap defined 3322 10.05.1998 12.05.1998 multi-day sum gap defined 3322 10.09.1999 15.09.1999 multi-day sum gap defined 3322 09.09.2000 14.09.2000 multi-day sum gap defined 3322 28.10.2002 30.10.2002 multi-day sum gap defined 3323 11.07.1998 24.08.1998 multi-day sum/uncertain partition into single days gap defined 3323 25.09.1998 27.09.1998 multi-day sum gap defined 3323 17.10.1998 02.11.1998 multi-day sum/uncertain partition into single days gap defined 3323 27.12.1998 01.01.1999 no precipitation gap defined 3323 07.06.1999 28.06.1999 multi-day sum gap defined 3323 17.07.1999 19.07.1999 multi-day sum gap defined 3323 01.08.1999 20.03.2001 multi-day sum gap defined 3323 23.08.2001 25.08.2001 multi-day sum gap defined 3323 09.01.2004 13.01.2004 multi-day sum gap defined 3323 23.01.2004 26.01.2004 multi-day sum gap defined 3323 19.03.2004 22.03.2004 multi-day sum gap defined 3323 09.04.2004 13.04.2004 multi-day sum gap defined 3323 16.08.2004 20.08.2004 multi-day sum gap defined 3323 13.10.2004 29.11.2004 multi-day sum gap defined 3323 21.02.2005 25.02.2005 multi-day sum gap defined 3323 09.09.2005 16.09.2005 multi-day sum gap defined 3323 28.10.2005 01.11.2005 multi-day sum gap defined 3323 11.03.2006 13.03.2006 multi-day sum gap defined 3323 28.07.2006 08.08.2006 multi-day sum gap defined 3323 24.11.2006 26.11.2006 uncertain partition into single days gap defined 3323 26.12.2006 29.12.2006 multi-day sum gap defined 3323 19.01.2007 20.02.2007 multi-day sum gap defined 3323 22.04.2007 25.04.2007 multi-day sum/uncertain partition into single days gap defined 3323 11.05.2007 14.05.2007 multi-day sum gap defined 3323 04.06.2008 09.06.2008 multi-day sum gap defined 3323 03.08.2008 10.08.2008 uncertain partition into single days gap defined 3323 16.01.2009 04.02.2009 multi-day sum gap defined 3323 03.04.2009 14.04.2009 multi-day sum gap defined 3323 01/07/2009 31/07/2009 no precipitation gap defined 3323 08.08.2009 29.08.2009 multi-day sum gap defined 3324 18.04.1998 30.04.1998 multi-day sum/uncertain partition into single days gap defined 3324 05.09.1998 07.09.1998 uncertain partition into single days gap defined 3324 07.12.1998 24.12.1998 uncertain partition into single days gap defined 3324 20.12.1999 24.12.1999 multi-day sum gap defined 3324 07.01.2000 09.01.2000 multi-day sum gap defined 3324 18.04.2000 25.05.2000 uncertain partition into single days gap defined 3324 13.06.2000 15.06.2000 multi-day sum gap defined 3324 07.07.2000 02.08.2000 multi-day sum/uncertain partition into single days gap defined 3324 09.09.2000 11.09.2000 multi-day sum gap defined 3324 18.11.2000 03.12.2000 multi-day sum/uncertain partition into single days gap defined 3324 15.12.2000 17.12.2000 multi-day sum gap defined 3324 23.04.2001 25.04.2001 uncertain partition into single days gap defined 3324 01.10.2002 27.04.2003 multi-day sum/no precipitation gap defined 3324 01.07.2003 01.08.2003 no precipitation gap defined 3324 12.11.2003 14.11.2003 multi-day sum gap defined 3324 03.12.2003 13.12.2003 multi-day sum gap defined 3324 08.01.2004 23.04.2004 multi-day sum/uncertain partition into single days gap defined 3324 17.07.2004 22.07.2004 multi-day sum gap defined 3324 01.09.2004 01.10.2004 no precipitation gap defined 3324 21.10.2004 23.10.2004 multi-day sum gap defined 3324 01.12.2004 01.10.2008 multi-day sum/no precipitation gap defined 3324 15.01.2009 19.01.2009 multi-day sum gap defined 3324 20.07.2009 01.08.2009 multi-day sum gap defined station no. start end observation consequence 3331 03.01.1998 05.01.1998 multi-day sum gap defined 3331 17.01.1998 19.01.1998 multi-day sum gap defined 3331 28.02.1998 11.03.1998 multi-day sum/uncertain partition into single days gap defined 3331 08.09.1998 10.09.1998 multi-day sum gap defined 3331 09.11.1998 11.11.1998 uncertain partition into single days gap defined 3331 09.12.1998 11.12.1998 multi-day sum gap defined 3331 13.12.1998 15.12.1998 uncertain partition into single days gap defined 3331 03.06.1999 05.06.1999 uncertain partition into single days gap defined 3331 09.02.2000 25.02.2000 uncertain partition into single days gap defined 3331 02.06.2000 04.06.2000 uncertain partition into single days gap defined 3331 07.08.2000 09.08.2000 uncertain partition into single days gap defined 3331 10.10.2000 12.10.2000 uncertain partition into single days gap defined 3331 23.10.2000 26.10.2000 uncertain partition into single days gap defined 3331 10.12.2000 12.12.2000 uncertain partition into single days gap defined 3331 25.02.2001 28.02.2001 multi-day sum/uncertain partition into single days gap defined 3331 25.06.2001 30.06.2001 multi-day sum/uncertain partition into single days gap defined 3331 30.03.2002 01.04.2002 multi-day sum gap defined 3331 18.01.2003 04.02.2003 multi-day sum/uncertain partition into single days gap defined 3331 26.06.2003 28.06.2003 multi-day sum gap defined 3331 12.12.2003 14.12.2003 uncertain partition into single days gap defined 3331 19.12.2003 24.12.2003 implausible gap defined 3331 23.02.2004 18.03.2004 multi-day sum/uncertain partition into single days gap defined 3331 03.05.2004 29.05.2004 uncertain partition into single days gap defined 3331 21.12.2004 29.12.2004 multi-day sum gap defined 3331 20.03.2005 27.03.2005 multi-day sum gap defined 3331 12.08.2005 14.08.2005 multi-day sum gap defined 3331 26.09.2005 30.09.2005 multi-day sum gap defined 3331 20.10.2005 22.10.2005 multi-day sum gap defined 3331 29.03.2006 31.03.2006 multi-day sum gap defined 3331 10.04.2006 12.04.2006 multi-day sum gap defined 3331 30.04.2006 03.05.2006 multi-day sum gap defined 3331 10.05.2006 12.05.2006 uncertain partition into single days gap defined 3331 23.08.2006 01.10.2006 uncertain partition into single days gap defined 3331 01.11.2006 31.12.2006 multi-day sum/uncertain partition into single days gap defined 3338 08.07.1998 15.07.1998 multi-day sum gap defined 3338 12.08.1998 14.08.1998 multi-day sum gap defined 3338 26.06.1999 28.06.1999 uncertain partition into single days gap defined 3338 10.01.2000 01.02.2000 uncertain partition into single days gap defined 3338 29.02.2000 31.12.2009 multi-day sum gap defined 3422 06.06.2002 08.06.2002 multi-day sum gap defined 3422 23.11.2002 02.12.2002 multi-day sum/uncertain partition into single days gap defined 3422 09.06.2003 14.06.2003 multi-day sum gap defined 3422 07.09.2003 09.09.2003 multi-day sum gap defined 3422 20.10.2004 22.10.2004 uncertain partition into single days gap defined 3422 02.06.2005 08.06.2005 multi-day sum gap defined 3422 20.08.2005 22.08.2005 multi-day sum gap defined 3422 17.10.2006 30.10.2006 multi-day sum gap defined 3422 04.12.2009 07.12.2009 multi-day sum gap defined 3431 15.03.2004 17.03.2004 multi-day sum gap defined 3438 12.08.1998 14.08.1998 multi-day sum gap defined 3438 30.06.1999 03.07.1999 multi-day sum gap defined 3438 24.08.1999 26.08.1999 multi-day sum gap defined 3438 20.06.2000 22.06.2000 multi-day sum gap defined 3438 04.09.2000 06.09.2000 multi-day sum gap defined 3438 12.11.2000 14.11.2000 multi-day sum gap defined 3438 15.05.2001 17.05.2001 multi-day sum gap defined 3438 23.10.2001 25.10.2001 multi-day sum gap defined 3438 28.08.2002 31.08.2002 multi-day sum gap defined 3438 17.08.2005 19.08.2005 multi-day sum gap defined 3438 04.08.2006 06.08.2006 multi-day sum gap defined 3438 20.02.2007 22.02.2007 multi-day sum gap defined 3438 24.02.2008 16.03.2008 implausible gap defined 3438 14.10.2008 16.10.2008 multi-day sum gap defined 3438 01.02.2010 28.02.2010 no precipitation gap defined 3513 15.09.1998 25.09.1998 implausible gap defined 3513 03.10.1998 05.10.1998 multi-day sum gap defined 3513 11.12.1998 20.12.1998 implausible gap defined station no. start end observation consequence 3513 27.01.1999 07.02.1999 multi-day sum gap defined 3513 18.02.2000 24.02.2000 uncertain partition into single days gap defined 3513 18.04.2000 10.05.2000 multi-day sum gap defined 3513 27.07.2000 29.07.2000 multi-day sum gap defined 3513 28.02.2005 06.03.2005 implausible gap defined 3513 22.05.2005 26.05.2005 multi-day sum/uncertain partition into single days gap defined 3513 04.07.2006 22.08.2006 implausible gap defined 3513 08.04.2009 10.04.2009 multi-day sum gap defined 3513 27.04.2009 04.05.2009 multi-day sum/uncertain partition into single days gap defined 3513 02.01.2010 10.01.2010 multi-day sum gap defined 3513 22.03.2010 24.03.2010 multi-day sum gap defined 3513 12.05.2010 14.05.2010 multi-day sum gap defined 3522 18.05.2009 20.05.2009 multi-day sum gap defined 3524 22.08.1998 06.09.1998 uncertain partition into single days gap defined 3524 01.11.1998 03.11.1998 multi-day sum gap defined 3524 01.01.1999 03.01.1999 multi-day sum gap defined 3524 10.01.1999 16.01.1999 multi-day sum gap defined 3524 27.11.1999 29.11.1999 multi-day sum gap defined 3524 24.12.1999 01.01.2000 multi-day sum gap defined 3524 29.01.2000 31.01.2000 multi-day sum gap defined 3524 06.03.2000 08.03.2000 multi-day sum gap defined 3524 15.04.2000 17.04.2000 multi-day sum gap defined 3524 24.04.2000 26.04.2000 multi-day sum gap defined 3524 11.05.2000 13.05.2000 multi-day sum gap defined 3524 29.05.2000 22.06.2000 multi-day sum gap defined 3524 15.08.2000 17.08.2000 multi-day sum gap defined 3524 08.10.2000 10.10.2000 multi-day sum gap defined 3524 21.11.2000 23.11.2000 multi-day sum gap defined 3524 28.11.2000 30.11.2000 multi-day sum gap defined 3524 08.12.2000 10.12.2000 multi-day sum gap defined 3524 21.12.2000 23.01.2001 multi-day sum gap defined 3524 10.02.2001 12.02.2001 multi-day sum gap defined 3524 13.05.2001 15.05.2001 multi-day sum gap defined 3524 27.05.2001 29.05.2001 multi-day sum gap defined 3524 25.06.2001 25.09.2001 multi-day sum/uncertain partition into single days gap defined 3524 20.12.2001 27.01.2002 multi-day sum/uncertain partition into single days gap defined 3524 08.03.2002 10.03.2002 multi-day sum gap defined 3524 15.04.2002 07.11.2002 multi-day sum/uncertain partition into single days gap defined 3524 18.01.2003 01.06.2004 multi-day sum/uncertain partition into single days gap defined 3524 17.08.2004 19.08.2004 multi-day sum gap defined 3524 15.09.2004 04.10.2004 multi-day sum gap defined 3524 21.12.2004 23.12.2004 multi-day sum gap defined 3524 21.12.2005 02.01.2006 multi-day sum gap defined 3524 24.02.2006 27.03.2006 multi-day sum gap defined 3524 23.08.2006 20.09.2006 multi-day sum gap defined 3524 25.11.2006 17.12.2006 multi-day sum gap defined 3524 01.06.2007 04.06.2007 multi-day sum gap defined 3524 11.04.2008 13.04.2008 multi-day sum gap defined 3524 05.07.2008 08.08.2008 multi-day sum/uncertain partition into single days gap defined 3524 15.11.2008 28.01.2009 uncertain partition into single days gap defined 3524 24.03.2009 18.04.2009 multi-day sum/uncertain partition into single days gap defined 3524 15.06.2009 27.06.2009 multi-day sum gap defined 3524 13.07.2009 15.07.2009 multi-day sum gap defined 3524 09.11.2009 12.11.2009 multi-day sum gap defined 3524 20.12.2009 27.12.2009 multi-day sum gap defined 3524 06.01.2010 11.01.2010 multi-day sum gap defined 3524 30.03.2010 03.04.2010 multi-day sum gap defined 3524 11.05.2010 13.05.2010 multi-day sum gap defined 3538 15.02.1998 17.02.1998 multi-day sum gap defined 3538 16.10.1999 18.10.1999 multi-day sum gap defined 3538 28.02.2000 01.03.2000 multi-day sum gap defined 3538 29.07.2002 31.07.2002 uncertain partition into single days gap defined 3538 01.03.2003 03.03.2003 multi-day sum gap defined 3538 24.09.2005 28.09.2005 multi-day sum gap defined 3538 18.03.2007 20.03.2007 multi-day sum gap defined 3538 29.07.2008 31.07.2008 multi-day sum gap defined 3606 18.05.2000 22.05.2000 multi-day sum gap defined station no. start end observation consequence 3606 25.12.2000 31.12.2000 multi-day sum gap defined 3606 25.06.2001 27.06.2001 multi-day sum gap defined 3606 13.07.2003 17.07.2003 multi-day sum gap defined 3606 25.12.2009 27.12.2009 multi-day sum gap defined 3613 06.02.2007 08.02.2007 uncertain partition into single days gap defined 3623 14.06.2005 17.06.2005 multi-day sum gap defined 3623 01/04/2006 30/04/2006 no precipitation gap defined 3623 16.05.2007 18.05.2007 multi-day sum gap defined 3623 05.10.2009 07.10.2009 multi-day sum gap defined 3624 01.09.1998 14.09.1998 multi-day sum gap defined 3624 18.08.1999 01.09.1999 multi-day sum gap defined 3624 21.10.1999 26.10.1999 multi-day sum gap defined 3624 09.09.2000 11.09.2000 multi-day sum gap defined 3624 05.09.2001 27.09.2001 multi-day sum gap defined 3624 26.11.2002 03.12.2002 multi-day sum gap defined 3624 11.08.2004 17.08.2004 uncertain partition into single days gap defined 3624 10.09.2004 20.09.2004 multi-day sum gap defined 3624 01.09.2005 01.10.2005 no precipitation gap defined 3624 23.08.2006 06.09.2006 multi-day sum gap defined 3624 28.06.2007 06.08.2007 multi-day sum/no precipitation gap defined 3637 12.11.1998 13.11.1998 very high precipitation gap defined 3637 19.12.1998 20.12.1998 very high precipitation gap defined 3637 18.01.1999 20.01.1999 multi-day sum gap defined 3637 21.02.1999 01.03.1999 multi-day sum/uncertain partition into single days gap defined 3637 22.04.1999 23.04.1999 very high precipitation gap defined 3637 10.01.2000 12.01.2000 uncertain partition into single days gap defined 3637 08.02.2000 10.02.2000 uncertain partition into single days gap defined 3637 16.02.2000 18.02.2000 uncertain partition into single days gap defined 3637 19.10.2000 21.10.2000 multi-day sum gap defined 3637 29.08.2002 31.08.2002 multi-day sum gap defined 3637 22.10.2004 24.10.2004 multi-day sum gap defined 3637 25.11.2004 27.11.2004 multi-day sum gap defined 3637 10.10.2006 12.10.2006 multi-day sum gap defined 3637 20.01.2007 22.01.2007 multi-day sum gap defined 3637 01/02/2007 28/02/2007 no precipitation gap defined 3637 21.04.2007 24.04.2007 multi-day sum gap defined 3637 16.09.2007 18.09.2007 multi-day sum gap defined 3637 26.10.2007 30.10.2007 multi-day sum gap defined 3637 13.07.2009 15.07.2009 multi-day sum gap defined 3637 17.11.2009 23.11.2009 multi-day sum/uncertain partition into single days gap defined 3706 10.05.1998 14.05.1998 multi-day sum gap defined 3706 06.09.1998 09.09.1998 multi-day sum gap defined 3706 29.09.1998 01.10.1998 multi-day sum gap defined 3706 07.11.1998 09.11.1998 multi-day sum gap defined 3706 17.12.1998 20.12.1998 multi-day sum gap defined 3706 04.02.1999 09.02.1999 multi-day sum gap defined 3706 01.03.1999 07.05.1999 multi-day sum/no precipitation gap defined 3706 19.05.1999 23.05.1999 multi-day sum gap defined 3706 19.07.1999 10.10.1999 multi-day sum/no precipitation gap defined 3706 24.10.1999 26.10.1999 multi-day sum gap defined 3706 23.11.1999 25.11.1999 multi-day sum gap defined 3706 03.01.2000 05.01.2000 multi-day sum gap defined 3706 01.03.2000 01.04.2000 no precipitation gap defined 3706 03.06.2000 05.06.2000 multi-day sum gap defined 3706 02.07.2000 06.07.2000 multi-day sum/uncertain partition into single days gap defined 3706 14.09.2000 17.09.2000 multi-day sum gap defined 3706 24.12.2000 31.12.2000 multi-day sum gap defined 3706 12.03.2001 14.03.2001 multi-day sum gap defined 3706 07.08.2001 09.08.2001 multi-day sum gap defined 3706 29.07.2002 31.07.2002 multi-day sum gap defined 3706 28.12.2002 30.12.2002 multi-day sum gap defined 3706 27.01.2003 01.02.2003 multi-day sum gap defined 3706 01.07.2003 01.09.2003 no precipitation gap defined 3706 04.10.2003 01.02.2004 no precipitation/uncertain partition into single days gap defined 3706 25.02.2004 05.03.2004 multi-day sum/uncertain partition into single days gap defined 3706 22.03.2004 24.03.2004 multi-day sum gap defined 3706 01.06.2004 01.11.2004 no precipitation/uncertain partition into single days gap defined station no. start end observation consequence 3706 22.12.2004 01.02.2005 no precipitation/uncertain partition into single days gap defined 3706 04.03.2005 08.03.2005 multi-day sum gap defined 3706 28.03.2005 04.06.2005 no precipitation/uncertain partition into single days gap defined 3706 28.06.2005 06.07.2005 multi-day sum/uncertain partition into single days gap defined 3706 01.09.2005 01.10.2005 no precipitation gap defined 3706 14.11.2005 26.11.2005 multi-day sum gap defined 3706 01.01.2006 04.01.2006 multi-day sum gap defined 3706 11.02.2006 14.02.2006 multi-day sum gap defined 3706 01.03.2006 16.08.2006 multi-day sum/no precipitation gap defined 3706 11.09.2006 19.09.2006 multi-day sum gap defined 3706 26.09.2006 14.11.2006 multi-day sum/no precipitation gap defined 3706 16.01.2007 18.01.2007 multi-day sum gap defined 3706 05.08.2007 07.08.2007 multi-day sum gap defined 3706 01.09.2007 15.11.2007 multi-day sum/no precipitation gap defined 3706 01.12.2007 10.01.2008 multi-day sum/no precipitation gap defined 3706 05.04.2008 24.04.2008 multi-day sum/uncertain partition into single days gap defined 3706 30.04.2008 13.06.2008 multi-day sum/uncertain partition into single days gap defined 3706 09.08.2008 11.08.2008 multi-day sum gap defined 3706 14.08.2008 18.08.2008 multi-day sum gap defined 3706 14.09.2008 16.09.2008 multi-day sum gap defined 3706 25.10.2008 27.10.2008 uncertain partition into single days gap defined 3706 30.10.2008 09.11.2008 multi-day sum gap defined 3706 02.12.2008 09.12.2008 multi-day sum gap defined 3706 19.12.2008 13.04.2009 multi-day sum/no precipitation gap defined 3706 06.05.2009 16.05.2009 multi-day sum gap defined 3706 13.06.2009 26.06.2009 uncertain partition into single days gap defined 3706 28.06.2009 09.07.2009 multi-day sum/uncertain partition into single days gap defined 3706 18.08.2009 23.08.2009 multi-day sum gap defined 3706 09.10.2009 31.10.2009 multi-day sum/uncertain partition into single days gap defined 3706 14.12.2009 31.12.2009 multi-day sum gap defined 3731 22.12.1999 24.12.1999 multi-day sum gap defined 3731 30.12.2003 01.01.2004 multi-day sum gap defined 3731 26.01.2004 30.01.2004 multi-day sum gap defined 3731 18.08.2006 20.08.2006 multi-day sum gap defined 3731 25.05.2007 28.05.2007 multi-day sum gap defined 3738 09.09.1998 11.09.1998 multi-day sum gap defined 3738 12.08.1999 17.08.1999 multi-day sum gap defined 3738 05.11.1999 07.11.1999 multi-day sum gap defined 3738 16.12.1999 18.12.1999 multi-day sum gap defined 3738 26.02.2001 28.02.2001 multi-day sum gap defined 3738 28.06.2001 30.06.2001 multi-day sum gap defined 3738 24.05.2003 26.05.2003 multi-day sum gap defined 3738 24.09.2004 26.09.2004 multi-day sum gap defined 3738 28.10.2004 04.11.2004 multi-day sum gap defined 3738 08.01.2005 15.02.2005 multi-day sum gap defined 3738 01.05.2005 20.05.2005 multi-day sum gap defined 3738 29.07.2005 16.08.2005 multi-day sum gap defined 3738 09.11.2005 14.11.2005 multi-day sum gap defined 3823 20.02.1998 23.02.1998 multi-day sum gap defined 3823 25.09.1998 28.09.1998 multi-day sum gap defined 3823 03.02.2000 07.02.2000 multi-day sum gap defined 3823 27.02.2000 01.03.2000 multi-day sum gap defined 3823 02.07.2000 04.07.2000 multi-day sum gap defined 3823 20.01.2001 22.01.2001 multi-day sum gap defined 3823 26.03.2001 28.03.2001 multi-day sum gap defined 3823 07.11.2001 09.11.2001 multi-day sum gap defined 3823 04.01.2002 12.01.2002 multi-day sum gap defined 3823 02.11.2002 04.11.2002 multi-day sum gap defined 3823 12.03.2004 15.03.2004 multi-day sum gap defined 3823 17.01.2005 19.01.2005 multi-day sum gap defined 3823 13.03.2006 15.03.2006 uncertain partition into single days gap defined 3823 01.07.2006 01.08.2006 no precipitation gap defined 3823 18.03.2007 20.03.2007 multi-day sum gap defined 3823 28.09.2007 09.10.2007 multi-day sum gap defined 3823 23.11.2007 26.11.2007 multi-day sum gap defined 3823 07.12.2007 10.12.2007 multi-day sum/uncertain partition into single days gap defined 3823 04.01.2008 07.01.2008 multi-day sum gap defined station no. start end observation consequence 3823 01.05.2008 04.05.2008 multi-day sum gap defined 3823 25.10.2008 27.10.2008 multi-day sum gap defined 3823 06.11.2008 08.11.2008 uncertain partition into single days gap defined 3823 17.06.2009 22.06.2009 multi-day sum gap defined 3823 23.11.2009 25.11.2009 multi-day sum gap defined 3824 01.07.1998 31.12.1999 very low precipitation amount gap defined 3831 13.05.1998 16.05.1998 uncertain partition into single days gap defined 3831 01/07/1998 28/02/1999 no precipitation gap defined 3831 26.05.2001 01.06.2001 multi-day sum gap defined 3831 01/06/2001 30/06/2001 no precipitation gap defined 3831 01/08/2001 31/12/2001 no precipitation gap defined 3831 01/06/2002 30/06/2002 no precipitation gap defined 3831 01/10/2002 30/11/2002 no precipitation gap defined 3831 06.12.2002 09.12.2002 multi-day sum gap defined 3831 01/03/2003 31/03/2003 no precipitation gap defined 3831 23.05.2003 25.05.2003 multi-day sum gap defined 3831 01/07/2003 31/07/2003 no precipitation gap defined 3831 23.02.2004 25.02.2004 multi-day sum gap defined 3831 01/04/2004 31/05/2004 no precipitation gap defined 3831 01/07/2004 31/07/2004 no precipitation gap defined 3838 01.03.1999 04.03.1999 multi-day sum gap defined 3838 08.07.2000 10.07.2000 uncertain partition into single days gap defined 3838 28.03.2001 30.03.2001 multi-day sum gap defined 3838 15.03.2002 17.03.2002 multi-day sum gap defined 3838 03.02.2003 06.02.2003 multi-day sum gap defined 3838 28.07.2003 30.07.2003 multi-day sum gap defined 3838 20.06.2006 22.06.2006 multi-day sum gap defined 3838 27.03.2008 29.03.2008 multi-day sum gap defined 3838 07.12.2008 09.12.2008 multi-day sum gap defined 3838 19.08.2009 21.08.2009 multi-day sum gap defined 3923 19.12.2002 04.01.2003 multi-day sum gap defined 3923 23.02.2003 28.02.2003 uncertain partition into single days gap defined 3923 24.04.2003 29.04.2003 multi-day sum gap defined 3923 28.05.2003 30.05.2003 multi-day sum gap defined 3923 29.06.2003 01.07.2003 multi-day sum gap defined 3923 17.03.2004 21.04.2004 multi-day sum gap defined 3923 11.08.2004 18.08.2004 multi-day sum gap defined 3923 07.01.2008 09.01.2008 uncertain partition into single days gap defined 3923 01.10.2008 08.10.2008 multi-day sum gap defined 3923 31.12.2009 31.05.2010 uncertain partition into single days gap defined 3924 03.05.2004 04.05.2004 no precipitation gap defined 3924 17.08.2007 21.08.2007 uncertain partition into single days gap defined 3937 04.01.1998 06.01.1998 multi-day sum gap defined 3937 24.11.1998 19.12.1998 implausible gap defined 3937 01.01.1999 04.01.1999 multi-day sum gap defined 3937 15.01.1999 17.01.1999 multi-day sum gap defined 3937 31.03.1999 04.05.1999 multi-day sum gap defined 3937 29.01.2000 31.01.2000 multi-day sum gap defined 3937 26.03.2000 15.05.2000 no precipitation gap defined 3937 25.05.2000 27.05.2000 multi-day sum gap defined 3937 25.10.2000 27.10.2000 uncertain partition into single days gap defined 3937 02.02.2001 05.02.2001 multi-day sum gap defined 3937 06.03.2001 08.03.2001 multi-day sum gap defined 3937 25.05.2001 28.05.2001 multi-day sum gap defined 3937 11.11.2001 14.11.2001 multi-day sum gap defined 3937 24.12.2003 26.12.2003 multi-day sum gap defined 3937 11.02.2006 13.02.2006 multi-day sum gap defined 3937 12.12.2008 14.12.2008 multi-day sum gap defined 4006 15.05.2001 17.05.2001 multi-day sum gap defined 4006 18.11.2002 20.11.2002 multi-day sum gap defined 4006 14.01.2003 16.01.2003 multi-day sum gap defined 4006 19.01.2003 21.01.2003 multi-day sum gap defined 4006 23.02.2004 05.03.2004 multi-day sum gap defined 4006 10.02.2007 12.02.2007 multi-day sum gap defined 4006 12.01.2009 14.01.2009 multi-day sum gap defined 4006 24.01.2009 26.01.2009 multi-day sum gap defined 4006 08.02.2009 12.02.2009 multi-day sum gap defined station no. start end observation consequence 4006 14.08.2009 17.08.2009 multi-day sum gap defined 4006 30.11.2009 02.12.2009 multi-day sum gap defined 4006 20.12.2009 29.12.2009 multi-day sum gap defined 4013 10.06.2000 13.06.2000 multi-day sum gap defined 4013 14.05.2001 16.05.2001 multi-day sum gap defined 4031 28.05.1999 30.05.1999 multi-day sum gap defined 4031 04.08.1999 07.08.1999 multi-day sum gap defined 4031 13.08.1999 15.08.1999 multi-day sum gap defined 4031 01/02/2001 28/02/2001 no precipitation gap defined 4031 05.08.2001 07.08.2001 multi-day sum gap defined 4031 28.01.2003 30.01.2003 multi-day sum gap defined 4031 03.08.2004 07.08.2004 multi-day sum gap defined 4031 21.08.2005 27.08.2005 multi-day sum gap defined 4031 24.07.2007 28.07.2007 multi-day sum gap defined 4031 28.07.2008 01.08.2008 multi-day sum gap defined 4037 08.07.1998 10.07.1998 multi-day sum gap defined 4037 11.01.1999 13.01.1999 multi-day sum gap defined 4037 28.07.2002 01.08.2002 multi-day sum gap defined 4037 23.12.2005 25.12.2005 multi-day sum gap defined 4037 16.02.2006 18.02.2006 multi-day sum gap defined 4037 20.06.2007 22.06.2007 multi-day sum gap defined 4037 07.12.2008 09.12.2008 multi-day sum gap defined 4106 01.06.2000 01.07.2000 multi-day sum gap defined 4106 18.11.2004 20.11.2004 multi-day sum gap defined 4106 27.09.2005 01.12.2005 no precipitation gap defined 4106 16.08.2006 25.08.2006 multi-day sum gap defined 4106 12.06.2007 15.06.2007 multi-day sum gap defined 4106 12.08.2007 14.08.2007 multi-day sum gap defined 4106 02.10.2007 04.10.2007 multi-day sum gap defined 4106 13.09.2008 16.09.2008 multi-day sum gap defined 4113 01.07.1999 21.07.1999 multi-day sum/uncertain partition into single days gap defined 4113 16.02.2000 18.02.2000 multi-day sum gap defined 4113 15.09.2000 01.11.2000 uncertain partition into single days gap defined 4113 30.12.2000 01.01.2001 multi-day sum gap defined 4113 08.02.2001 10.02.2001 multi-day sum gap defined 4113 12.03.2001 17.05.2001 multi-day sum/uncertain partition into single days gap defined 4113 05.03.2003 13.04.2003 uncertain partition into single days gap defined 4113 05.08.2004 08.08.2004 multi-day sum gap defined 4115 station not used - cause: frequent multi-day sums gap defined 4137 14.06.2001 16.06.2001 multi-day sum gap defined 4137 07.03.2006 09.03.2006 multi-day sum gap defined 4137 20.06.2006 23.06.2006 multi-day sum/uncertain partition into single days gap defined 4137 30.09.2006 02.10.2006 uncertain partition into single days gap defined 4213 11.04.1998 15.04.1998 multi-day sum gap defined 4213 20.04.2000 22.04.2000 multi-day sum gap defined 4213 09.10.2000 12.10.2000 multi-day sum gap defined 4213 30.05.2001 02.06.2001 multi-day sum gap defined 4213 13.07.2001 17.07.2001 multi-day sum gap defined 4213 05.11.2001 08.11.2001 multi-day sum gap defined 4213 16.01.2002 18.01.2002 multi-day sum gap defined 4213 01/08/2003 31/08/2003 no precipitation gap defined 4213 26.11.2003 30.11.2003 multi-day sum gap defined 4213 20.04.2004 23.04.2004 multi-day sum gap defined 4213 06.05.2004 08.05.2004 multi-day sum gap defined 4213 12.08.2004 15.08.2004 multi-day sum gap defined 4213 01/10/2005 31/10/2005 no precipitation gap defined 4213 08.03.2006 15.03.2006 multi-day sum gap defined 4213 16.05.2006 20.05.2006 multi-day sum gap defined 4213 26.05.2007 28.05.2007 multi-day sum gap defined 4213 06.12.2007 08.12.2007 multi-day sum gap defined 4213 01.03.2008 04.03.2008 multi-day sum gap defined 4213 09.03.2008 11.03.2008 multi-day sum gap defined 4213 04.06.2008 12.06.2008 uncertain partition into single days gap defined 4213 27.07.2008 30.07.2008 multi-day sum gap defined 4213 04.12.2008 07.12.2008 multi-day sum gap defined 4213 12.12.2008 15.12.2008 multi-day sum gap defined 4213 06.03.2009 10.03.2009 multi-day sum gap defined station no. start end observation consequence 4213 16.06.2009 18.06.2009 multi-day sum gap defined 4215 15.06.2009 17.06.2009 multi-day sum gap defined 4223 17.08.2001 19.08.2001 multi-day sum gap defined 4223 02.02.2004 05.02.2004 multi-day sum/uncertain partition into single days gap defined 4223 16.03.2004 18.03.2004 multi-day sum gap defined 4223 02.04.2004 04.04.2004 multi-day sum gap defined 4223 15.04.2004 19.04.2004 multi-day sum gap defined 4223 04.05.2004 06.05.2004 multi-day sum gap defined 4223 09.07.2004 13.07.2004 multi-day sum gap defined 4223 17.11.2004 25.02.2005 multi-day sum/uncertain partition into single days gap defined 4223 27.07.2005 31.07.2005 multi-day sum/uncertain partition into single days gap defined 4223 14.09.2005 09.11.2005 multi-day sum gap defined 4223 14.03.2006 04.04.2006 multi-day sum gap defined 4223 25.05.2006 27.05.2006 multi-day sum gap defined 4223 08.07.2006 21.08.2006 multi-day sum gap defined 4223 04.10.2006 06.10.2006 multi-day sum gap defined 4223 21.10.2006 23.10.2006 multi-day sum gap defined 4223 09.01.2007 11.01.2007 multi-day sum gap defined 4223 18.01.2007 11.07.2007 multi-day sum gap defined 4223 02.09.2007 10.10.2007 multi-day sum gap defined 4223 08.08.2008 10.08.2008 multi-day sum gap defined 4223 10.11.2008 12.11.2008 multi-day sum gap defined 4223 12.01.2009 15.01.2009 multi-day sum/uncertain partition into single days gap defined 4223 03.04.2009 11.04.2009 multi-day sum/uncertain partition into single days gap defined 4223 24.04.2009 22.05.2009 multi-day sum/uncertain partition into single days gap defined 4223 28.06.2009 01.07.2009 multi-day sum gap defined 4223 01/07/2009 31/07/2009 no precipitation gap defined 4223 24.10.2009 31.05.2010 multi-day sum/uncertain partition into single days gap defined 4237 26.12.1998 28.12.1998 multi-day sum gap defined 4237 08.12.2000 10.12.2000 multi-day sum gap defined 4237 05.09.2002 12.09.2002 multi-day sum gap defined 4237 18.09.2003 22.09.2003 multi-day sum gap defined 4237 01.12.2006 09.12.2006 multi-day sum gap defined 4237 01/10/2007 31/12/2007 no precipitation gap defined 4237 01/04/2008 31/12/2008 no precipitation gap defined 4237 19.04.2009 20.04.2009 very high precipitation gap defined 4237 29.04.2009 01.05.2009 multi-day sum gap defined 4237 25.06.2009 02.07.2009 implausible gap defined 4237 15.11.2009 17.11.2009 multi-day sum gap defined 4237 21.01.2010 01.03.2010 no precipitation gap defined 4331 06.04.2006 09.04.2006 multi-day sum gap defined 4331 18.04.2006 20.04.2006 multi-day sum gap defined 4331 15.07.2009 18.07.2009 multi-day sum gap defined 4331 09.11.2009 11.11.2009 multi-day sum gap defined 4337 25.12.1998 27.12.1998 multi-day sum gap defined 4337 29.12.1999 31.12.1999 multi-day sum gap defined 4337 02.11.2000 04.11.2000 multi-day sum gap defined 4337 15.11.2000 17.11.2000 multi-day sum gap defined 4337 27.12.2000 05.01.2001 multi-day sum gap defined 4337 21.06.2002 24.06.2002 multi-day sum gap defined 4337 22.12.2003 26.12.2003 uncertain partition into single days gap defined 4337 13.03.2004 17.03.2004 multi-day sum gap defined 4337 02.07.2005 04.07.2005 multi-day sum gap defined 4337 02.11.2005 27.11.2005 multi-day sum gap defined 4337 16.11.2006 18.11.2006 multi-day sum gap defined 4337 15.07.2009 17.07.2009 uncertain partition into single days gap defined 4413 05.03.1998 07.03.1998 multi-day sum gap defined 4413 04.04.1998 06.04.1998 multi-day sum gap defined 4413 18.07.1998 20.07.1998 multi-day sum gap defined 4413 22.08.1998 24.08.1998 multi-day sum gap defined 4413 09.09.1998 12.09.1998 multi-day sum gap defined 4413 26.10.1998 01.11.1998 multi-day sum gap defined 4413 23.02.1999 01.03.1999 multi-day sum gap defined 4413 20.04.1999 22.04.1999 multi-day sum gap defined 4413 15.04.2000 17.04.2000 multi-day sum gap defined 4413 21.06.2000 23.06.2000 multi-day sum gap defined 4413 28.10.2000 30.10.2000 multi-day sum gap defined station no. start end observation consequence 4413 06.11.2000 08.11.2000 multi-day sum gap defined 4413 18.11.2000 20.11.2000 multi-day sum gap defined 4413 27.11.2000 29.11.2000 multi-day sum gap defined 4413 12.12.2000 18.12.2000 multi-day sum gap defined 4413 03.02.2001 05.02.2001 multi-day sum gap defined 4413 10.02.2001 12.02.2001 multi-day sum gap defined 4413 05.04.2001 07.04.2001 multi-day sum gap defined 4413 28.04.2001 30.04.2001 multi-day sum gap defined 4413 09.03.2002 11.03.2002 multi-day sum gap defined 4413 26.12.2002 28.12.2002 multi-day sum gap defined 4413 11.11.2003 13.11.2003 multi-day sum gap defined 4413 11.09.2004 16.09.2004 multi-day sum gap defined 4413 18.11.2004 20.11.2004 multi-day sum gap defined 4413 25.12.2004 27.12.2004 multi-day sum gap defined 4413 09.02.2005 11.02.2005 multi-day sum gap defined 4413 02.03.2005 05.03.2005 multi-day sum gap defined 4413 23.03.2005 25.03.2005 multi-day sum gap defined 4413 22.07.2005 24.07.2005 multi-day sum gap defined 4413 14.02.2006 16.02.2006 multi-day sum gap defined 4413 23.02.2006 25.02.2006 multi-day sum gap defined 4413 27.03.2006 29.03.2006 multi-day sum gap defined 4413 02.05.2006 04.05.2006 multi-day sum gap defined 4413 11.05.2006 13.05.2006 multi-day sum gap defined 4413 05.08.2006 08.08.2006 multi-day sum gap defined 4413 23.09.2006 25.09.2006 multi-day sum gap defined 4413 09.11.2006 24.11.2006 multi-day sum gap defined 4413 17.01.2007 20.01.2007 multi-day sum gap defined 4413 24.04.2007 26.04.2007 multi-day sum gap defined 4413 02.07.2007 04.07.2007 multi-day sum gap defined 4413 24.07.2007 26.07.2007 multi-day sum gap defined 4413 24.09.2007 01.10.2007 multi-day sum gap defined 4413 17.11.2007 03.12.2007 multi-day sum gap defined 4413 03.05.2008 05.05.2008 multi-day sum gap defined 4413 21.06.2008 23.06.2008 multi-day sum gap defined 4413 15.08.2008 17.08.2008 multi-day sum gap defined 4413 09.09.2008 12.09.2008 multi-day sum/uncertain partition into single days gap defined 4413 07.05.2009 28.05.2009 multi-day sum/uncertain partition into single days gap defined 4413 22.08.2009 24.08.2009 multi-day sum gap defined 4413 07.11.2009 09.11.2009 multi-day sum gap defined 4413 21.11.2009 23.11.2009 multi-day sum gap defined 4415 03.01.1998 05.01.1998 multi-day sum gap defined 4415 06.02.1998 09.02.1998 multi-day sum gap defined 4415 27.02.1998 01.03.1998 multi-day sum gap defined 4415 12.06.1998 14.06.1998 multi-day sum gap defined 4415 26.06.1998 01.09.1998 multi-day sum gap defined 4415 01.11.1998 03.11.1998 multi-day sum gap defined 4415 23.12.1998 29.12.1998 multi-day sum gap defined 4415 04.01.1999 06.01.1999 multi-day sum gap defined 4415 12.05.1999 14.05.1999 multi-day sum gap defined 4415 24.08.1999 30.08.1999 multi-day sum gap defined 4415 05.02.2000 08.02.2000 multi-day sum gap defined 4415 08.09.2000 09.10.2000 multi-day sum gap defined 4415 15.11.2000 17.11.2000 multi-day sum gap defined 4415 07.12.2000 13.12.2000 multi-day sum gap defined 4415 21.12.2000 31.12.2000 multi-day sum gap defined 4415 15.03.2001 01.08.2001 multi-day sum/uncertain partition into single days gap defined 4415 26.09.2001 28.09.2001 multi-day sum gap defined 4415 22.10.2001 25.10.2001 multi-day sum gap defined 4415 15.01.2002 22.01.2002 multi-day sum gap defined 4415 18.04.2002 29.04.2002 multi-day sum gap defined 4415 21.06.2002 08.11.2002 multi-day sum gap defined 4415 07.03.2003 10.03.2003 multi-day sum gap defined 4415 17.05.2003 29.07.2003 multi-day sum gap defined 4415 27.11.2003 01.12.2003 multi-day sum gap defined 4415 19.12.2003 22.12.2003 multi-day sum gap defined 4415 09.01.2004 01.03.2004 multi-day sum gap defined 4415 21.04.2004 23.04.2004 multi-day sum gap defined station no. start end observation consequence 4415 25.06.2004 01.04.2005 multi-day sum/no precipitation gap defined 4415 27.05.2005 31.05.2005 multi-day sum gap defined 4415 30.06.2005 08.08.2005 multi-day sum/no precipitation gap defined 4415 22.10.2005 24.10.2005 multi-day sum gap defined 4415 17.12.2005 30.12.2005 multi-day sum gap defined 4415 12.04.2006 13.05.2006 multi-day sum gap defined 4415 02.07.2006 05.07.2006 multi-day sum gap defined 4415 12.01.2009 18.01.2009 multi-day sum gap defined 4415 24.01.2009 26.01.2009 multi-day sum gap defined 4415 16.06.2009 18.06.2009 multi-day sum gap defined 4512 20.02.1998 07.03.1998 multi-day sum/no precipitation gap defined 4512 19.04.1998 21.04.1998 multi-day sum gap defined 4512 23.04.1998 31.05.1998 multi-day sum/uncertain partition into single days gap defined 4512 03.09.1998 01.10.1998 multi-day sum/uncertain partition into single days gap defined 4512 01.11.1998 02.11.1998 multi-day sum gap defined 4512 08.12.1998 01.01.1999 multi-day sum gap defined 4513 07.01.1998 09.01.1998 multi-day sum gap defined 4513 01.03.1998 01.06.1998 multi-day sum/uncertain partition into single days gap defined 4513 29.09.1998 01.10.1998 multi-day sum gap defined 4513 23.10.1998 24.10.1998 multi-day sum gap defined 4513 21.11.1998 23.11.1998 multi-day sum gap defined 4513 13.04.1999 15.04.1999 multi-day sum gap defined 4513 08.09.1999 10.09.1999 multi-day sum gap defined 4513 17.11.1999 19.11.1999 multi-day sum gap defined 4513 09.12.1999 11.12.1999 multi-day sum gap defined 4513 25.11.2000 27.11.2000 multi-day sum gap defined 4513 11.11.2001 26.11.2001 multi-day sum gap defined 4513 05.02.2002 08.02.2002 multi-day sum gap defined 4513 24.02.2002 26.02.2002 multi-day sum gap defined 4513 20.04.2002 22.04.2002 multi-day sum gap defined 4513 12.08.2002 14.08.2002 multi-day sum gap defined 4513 23.12.2002 25.12.2002 multi-day sum gap defined 4513 16.05.2003 19.05.2003 multi-day sum gap defined 4513 16.07.2003 18.07.2003 multi-day sum gap defined 4513 30.07.2003 01.08.2003 multi-day sum gap defined 4513 05.11.2003 07.11.2003 multi-day sum gap defined 4513 12.12.2003 16.01.2004 multi-day sum gap defined 4513 30.06.2004 03.07.2004 multi-day sum gap defined 4513 17.07.2004 23.07.2004 multi-day sum/uncertain partition into single days gap defined 4513 04.10.2004 06.10.2004 multi-day sum gap defined 4513 21.10.2004 23.10.2004 multi-day sum gap defined 4513 21.12.2004 05.01.2005 multi-day sum/uncertain partition into single days gap defined 4513 22.03.2005 25.03.2005 multi-day sum gap defined 4513 05.04.2005 07.04.2005 multi-day sum gap defined 4513 27.04.2005 06.06.2005 multi-day sum gap defined 4513 28.07.2005 30.07.2005 multi-day sum gap defined 4513 28.09.2005 30.09.2005 multi-day sum gap defined 4513 29.09.2006 01.10.2006 multi-day sum gap defined 4513 06.12.2006 08.12.2006 multi-day sum gap defined 4513 27.02.2007 01.03.2007 multi-day sum gap defined 4513 23.04.2007 01.05.2007 multi-day sum gap defined 4513 26.05.2007 28.05.2007 multi-day sum gap defined 4513 04.07.2007 11.07.2007 multi-day sum gap defined 4513 07.01.2008 10.01.2008 multi-day sum gap defined 4513 22.04.2008 24.04.2008 multi-day sum gap defined 4513 07.09.2008 09.09.2008 uncertain partition into single days gap defined 4513 13.10.2008 27.10.2008 multi-day sum/uncertain partition into single days gap defined 4513 07.12.2008 11.12.2008 multi-day sum gap defined 4513 24.04.2009 26.04.2009 multi-day sum gap defined 4513 20.05.2009 22.05.2009 multi-day sum gap defined 4513 21.07.2009 24.07.2009 multi-day sum gap defined 4513 02.08.2009 05.08.2009 multi-day sum gap defined 4514 16.10.2004 19.10.2004 multi-day sum gap defined 4515 29.03.1998 31.03.1998 multi-day sum gap defined 4515 13.10.1998 15.10.1998 multi-day sum gap defined 4515 24.10.1998 26.10.1998 multi-day sum gap defined 4515 11.09.1999 20.09.1999 multi-day sum gap defined station no. start end observation consequence 4515 26.11.1999 29.11.1999 multi-day sum gap defined 4515 07.06.2000 09.06.2000 multi-day sum gap defined 4515 28.10.2000 30.10.2000 multi-day sum gap defined 4515 17.11.2000 30.11.2000 multi-day sum/uncertain partition into single days gap defined 4515 26.02.2001 01.03.2001 multi-day sum gap defined 4515 16.05.2001 01.06.2001 multi-day sum/uncertain partition into single days gap defined 4515 12.07.2001 09.08.2001 multi-day sum gap defined 4515 29.09.2001 01.10.2001 multi-day sum gap defined 4515 30.11.2001 02.12.2001 multi-day sum gap defined 4515 21.01.2002 23.01.2002 multi-day sum gap defined 4515 03.02.2002 12.02.2002 multi-day sum gap defined 4515 01/04/2002 31/12/2009 no precipitation, multi-day sum gap defined 4531 26.06.1999 28.06.1999 multi-day sum gap defined 4531 26.11.1999 29.11.1999 multi-day sum gap defined 4531 08.12.2000 10.12.2000 multi-day sum gap defined 4531 13.12.2000 15.12.2000 multi-day sum gap defined 4531 16.04.2002 18.04.2002 multi-day sum gap defined 4531 15.04.2004 19.04.2004 multi-day sum gap defined 4531 10.05.2005 03.08.2005 uncertain partition into single days gap defined 4531 20.08.2006 23.08.2006 multi-day sum gap defined 4531 05.09.2008 07.09.2008 multi-day sum gap defined 4531 09.10.2009 11.10.2009 multi-day sum gap defined 4537 07.11.1998 09.11.1998 multi-day sum gap defined 4537 12.12.1998 14.12.1998 multi-day sum gap defined 4537 24.08.1999 26.08.1999 multi-day sum gap defined 4537 19.04.2000 01.05.2000 multi-day sum gap defined 4612 10.05.1998 12.05.1998 multi-day sum gap defined 4612 05.06.1998 08.06.1998 multi-day sum gap defined 4612 04.09.1998 06.09.1998 multi-day sum gap defined 4612 11.09.1998 01.10.1998 multi-day sum gap defined 4612 24.11.1999 29.11.1999 multi-day sum gap defined 4612 28.01.2000 30.01.2000 multi-day sum/uncertain partition into single days gap defined 4612 10.02.2000 01.03.2000 multi-day sum gap defined 4612 23.04.2000 29.04.2000 multi-day sum gap defined 4612 28.07.2000 01.08.2000 multi-day sum gap defined 4612 01.11.2000 03.11.2000 multi-day sum gap defined 4612 01.01.2001 01.02.2001 multi-day sum gap defined 4612 01.06.2001 20.06.2001 multi-day sum gap defined 4612 01/07/2001 31/08/2001 no precipitation gap defined 4612 01.09.2001 26.09.2001 multi-day sum gap defined 4612 26.10.2001 04.02.2002 multi-day sum gap defined 4612 01/03/2002 30/04/2002 no precipitation gap defined 4612 01/06/2002 30/06/2002 no precipitation gap defined 4612 08.09.2002 10.09.2002 multi-day sum gap defined 4612 11.10.2002 21.10.2002 multi-day sum gap defined 4612 19.09.2003 21.09.2003 multi-day sum gap defined 4612 27.12.2003 30.12.2003 multi-day sum gap defined 4612 16.03.2004 19.03.2004 multi-day sum gap defined 4612 07.08.2004 09.08.2004 multi-day sum gap defined 4612 20.11.2004 22.11.2004 multi-day sum gap defined 4612 16.04.2005 18.04.2005 multi-day sum gap defined 4612 18.05.2005 21.05.2005 multi-day sum gap defined 4612 28.05.2005 06.06.2005 multi-day sum gap defined 4612 14.10.2005 17.10.2005 multi-day sum gap defined 4612 25.12.2009 27.12.2009 multi-day sum gap defined 4614 02.01.1998 30.06.2006 multi-day sum/no precipitation gap defined 4615 21.02.1998 23.02.1998 multi-day sum gap defined 4615 24.12.1999 26.12.1999 multi-day sum gap defined 4615 11.05.2000 13.05.2000 multi-day sum gap defined 4615 14.08.2000 12.09.2000 multi-day sum/uncertain partition into single days gap defined 4615 15.11.2000 17.11.2000 multi-day sum gap defined 4615 24.12.2000 26.12.2000 multi-day sum gap defined 4615 29.08.2001 31.08.2001 multi-day sum gap defined 4615 16.03.2002 20.03.2002 multi-day sum gap defined 4615 25.05.2002 29.05.2002 multi-day sum gap defined 4615 14.08.2002 17.08.2002 multi-day sum gap defined 4615 25.12.2002 27.12.2002 multi-day sum gap defined station no. start end observation consequence 4615 28.11.2003 30.11.2003 multi-day sum gap defined 4615 19.12.2003 21.12.2003 multi-day sum gap defined 4615 25.12.2003 27.12.2003 multi-day sum gap defined 4615 18.03.2004 25.03.2004 multi-day sum/uncertain partition into single days gap defined 4615 04.05.2004 05.05.2004 no precipitation gap defined 4615 30.09.2004 02.10.2004 uncertain partition into single days gap defined 4615 26.10.2004 29.10.2004 multi-day sum gap defined 4615 27.12.2004 29.12.2004 multi-day sum gap defined 4615 17.01.2005 19.01.2005 multi-day sum gap defined 4615 24.02.2005 26.02.2005 multi-day sum gap defined 4615 28.06.2005 02.07.2005 uncertain partition into single days gap defined 4615 13.09.2005 16.09.2005 multi-day sum gap defined 4615 23.05.2006 25.05.2006 multi-day sum gap defined 4615 02.07.2006 04.07.2006 multi-day sum gap defined 4615 21.01.2007 23.01.2007 multi-day sum gap defined 4615 10.02.2007 12.02.2007 multi-day sum gap defined 4615 14.06.2007 16.06.2007 multi-day sum gap defined 4615 18.08.2007 20.08.2007 multi-day sum gap defined 4615 01/11/2008 30/11/2008 no precipitation gap defined 4615 13.06.2009 27.07.2009 multi-day sum gap defined 4615 27.11.2009 30.11.2009 multi-day sum gap defined 4631 08.10.2002 10.10.2002 multi-day sum gap defined 4631 28.03.2008 30.03.2008 multi-day sum gap defined 4631 01/05/2009 31/05/2009 no precipitation gap defined 4631 30.10.2009 01.11.2009 multi-day sum gap defined 4637 29.05.1998 31.05.1998 multi-day sum gap defined 4637 22.08.1998 24.08.1998 multi-day sum gap defined 4637 24.04.1999 27.04.1999 multi-day sum gap defined 4637 02.01.2002 04.01.2002 multi-day sum gap defined 4637 15.12.2004 17.12.2004 multi-day sum gap defined 4637 14.06.2007 16.06.2007 multi-day sum gap defined 4637 26.12.2009 28.12.2009 multi-day sum gap defined 4713 05.06.1998 15.06.1998 multi-day sum/uncertain partition into single days gap defined 4713 12.11.1998 17.11.1998 multi-day sum/uncertain partition into single days gap defined 4713 18.02.1999 20.02.1999 multi-day sum gap defined 4713 26.04.2000 29.04.2000 multi-day sum/uncertain partition into single days gap defined 4715 17.01.1998 19.01.1998 multi-day sum gap defined 4715 27.04.1998 29.04.1998 multi-day sum gap defined 4715 25.06.1998 29.06.1998 uncertain partition into single days gap defined 4715 11.10.1998 14.10.1998 multi-day sum gap defined 4715 19.06.1999 21.06.1999 multi-day sum gap defined 4715 07.08.2000 01.10.2000 multi-day sum/uncertain partition into single days gap defined 4715 18.11.2000 20.11.2000 multi-day sum gap defined 4715 20.01.2001 22.01.2001 multi-day sum gap defined 4715 14.08.2001 31.08.2001 multi-day sum gap defined 4715 06.03.2003 09.03.2003 multi-day sum gap defined 4715 02.05.2003 06.05.2003 multi-day sum gap defined 4715 26.06.2003 28.06.2003 multi-day sum gap defined 4715 20.09.2003 02.10.2003 uncertain partition into single days gap defined 4715 21.02.2005 24.02.2005 multi-day sum gap defined 4715 02.10.2007 04.10.2007 multi-day sum gap defined 4715 09.03.2008 11.03.2008 multi-day sum gap defined 4715 30.03.2008 01.04.2008 multi-day sum gap defined 4715 11.12.2008 18.12.2008 uncertain partition into single days gap defined 4715 09.03.2009 11.03.2009 multi-day sum gap defined 4715 20.05.2009 22.05.2009 multi-day sum gap defined 4715 02.07.2009 04.07.2009 multi-day sum gap defined 4715 13.07.2009 15.07.2009 multi-day sum gap defined 4719 20.02.1998 22.02.1998 multi-day sum gap defined 4719 16.12.1998 23.12.1998 multi-day sum gap defined 4719 02.01.1999 04.01.1999 multi-day sum gap defined 4719 01.02.1999 16.03.1999 multi-day sum/no precipitation gap defined 4719 17.06.1999 23.06.1999 multi-day sum gap defined 4719 17.09.1999 19.09.1999 multi-day sum gap defined 4719 26.09.1999 28.09.1999 multi-day sum gap defined 4719 22.10.1999 30.10.1999 multi-day sum gap defined 4719 26.11.1999 28.11.1999 multi-day sum gap defined station no. start end observation consequence 4719 12.12.1999 14.12.1999 multi-day sum gap defined 4719 27.12.1999 30.12.1999 multi-day sum gap defined 4719 08.01.2000 10.01.2000 multi-day sum gap defined 4719 08.03.2000 11.03.2000 multi-day sum gap defined 4719 22.03.2000 27.03.2000 multi-day sum gap defined 4719 18.04.2000 20.04.2000 multi-day sum gap defined 4719 01.08.2000 04.08.2000 multi-day sum gap defined 4719 27.12.2000 31.12.2000 multi-day sum gap defined 4719 07.03.2001 14.03.2001 multi-day sum gap defined 4719 11.04.2001 02.06.2001 multi-day sum/no precipitation gap defined 4719 07.06.2001 15.06.2001 multi-day sum gap defined 4719 01.09.2001 04.09.2001 multi-day sum gap defined 4719 27.09.2001 30.09.2001 multi-day sum gap defined 4719 07.12.2001 19.01.2002 multi-day sum gap defined 4719 04.03.2002 06.03.2002 multi-day sum gap defined 4719 20.03.2002 22.03.2002 multi-day sum gap defined 4719 02.04.2002 06.04.2002 multi-day sum gap defined 4719 01.07.2002 09.09.2002 multi-day sum/uncertain partition into single days gap defined 4719 12.10.2002 18.10.2002 multi-day sum gap defined 4719 01.11.2002 01.12.2002 multi-day sum gap defined 4719 03.12.2002 22.12.2002 multi-day sum gap defined 4719 03.01.2003 13.01.2003 multi-day sum gap defined 4719 19.01.2003 25.01.2003 multi-day sum gap defined 4719 01.02.2003 01.03.2003 multi-day sum gap defined 4719 01.04.2003 01.06.2003 no precipitation gap defined 4719 05.11.2003 08.03.2008 no precipitation/uncertain partition into single days gap defined 4719 20.05.2008 30.05.2008 uncertain partition into single days gap defined 4719 01.12.2008 14.12.2008 multi-day sum gap defined 4719 19.01.2009 21.01.2009 multi-day sum gap defined 4719 22.04.2009 24.04.2009 multi-day sum gap defined 4719 06.05.2009 17.05.2009 multi-day sum/uncertain partition into single days gap defined 4719 06.06.2009 08.06.2009 multi-day sum gap defined 4719 17.06.2009 26.06.2009 multi-day sum gap defined 4719 01.08.2009 01.09.2009 no precipitation gap defined 4719 18.09.2009 20.09.2009 multi-day sum gap defined 4719 24.10.2009 26.10.2009 multi-day sum gap defined 4719 09.11.2009 11.11.2009 multi-day sum gap defined 4811 15.04.2001 22.04.2001 multi-day sum gap defined 4811 11.11.2002 13.11.2002 multi-day sum gap defined 4811 17.08.2003 30.08.2003 multi-day sum/uncertain partition into single days gap defined 4811 19.10.2005 21.10.2005 uncertain partition into single days gap defined 4811 24.11.2005 27.11.2005 uncertain partition into single days gap defined 4811 22.11.2006 24.11.2006 multi-day sum gap defined 4811 08.01.2007 10.01.2007 multi-day sum gap defined 4811 22.05.2008 05.06.2008 multi-day sum gap defined 4811 25.10.2008 27.10.2008 multi-day sum gap defined 4811 01.03.2009 10.03.2009 multi-day sum gap defined 4811 28.04.2009 05.05.2009 no precipitation gap defined 4811 19.12.2009 29.12.2009 multi-day sum gap defined 4813 03.01.1999 05.01.1999 multi-day sum gap defined 4813 29.12.1999 31.12.1999 multi-day sum gap defined 4813 05.12.2000 11.12.2000 uncertain partition into single days gap defined 4813 02.04.2002 05.04.2002 multi-day sum gap defined 4813 27.12.2002 28.02.2003 uncertain partition into single days gap defined 4813 23.05.2003 05.06.2003 multi-day sum/uncertain partition into single days gap defined 4813 19.12.2003 21.12.2003 multi-day sum gap defined 4813 02.03.2004 04.03.2004 multi-day sum gap defined 4813 21.03.2004 23.03.2004 multi-day sum gap defined 4813 04.05.2004 11.07.2004 multi-day sum gap defined 4813 17.09.2004 19.09.2004 multi-day sum gap defined 4813 27.05.2005 29.05.2005 multi-day sum gap defined 4813 17.08.2005 19.08.2005 multi-day sum gap defined 4813 26.09.2005 27.09.2005 no precipitation gap defined 4813 23.02.2006 26.02.2006 multi-day sum gap defined 4813 13.03.2006 15.03.2006 multi-day sum gap defined 4813 01.04.2006 01.05.2006 no precipitation gap defined 4813 16.09.2006 20.09.2006 multi-day sum gap defined station no. start end observation consequence 4813 01.10.2006 04.10.2006 no precipitation gap defined 4813 12.11.2006 16.11.2006 multi-day sum/uncertain partition into single days gap defined 4813 21.11.2006 25.11.2006 multi-day sum gap defined 4813 13.12.2006 28.12.2006 multi-day sum gap defined 4813 17.01.2007 19.01.2007 multi-day sum gap defined 4813 08.02.2007 16.02.2007 multi-day sum/uncertain partition into single days gap defined 4813 01.05.2007 29.05.2007 multi-day sum/uncertain partition into single days gap defined 4813 26.10.2007 29.10.2007 multi-day sum gap defined 4813 05.01.2008 08.01.2008 multi-day sum gap defined 4813 16.03.2008 12.08.2008 multi-day sum/uncertain partition into single days gap defined 4813 01/09/2008 30/09/2008 no precipitation gap defined 4813 07.12.2008 10.12.2008 multi-day sum gap defined 4813 18.01.2009 27.01.2009 multi-day sum gap defined 4813 23.03.2009 22.05.2009 multi-day sum gap defined 4813 09.10.2009 11.10.2009 multi-day sum gap defined 4813 21.10.2009 23.10.2009 multi-day sum gap defined 4813 03.11.2009 05.11.2009 multi-day sum gap defined 4815 10.09.1999 12.09.1999 multi-day sum gap defined 4815 20.12.2005 31.12.2005 multi-day sum gap defined 4815 05.08.2007 07.08.2007 multi-day sum gap defined 4815 06.12.2007 10.12.2007 multi-day sum gap defined 4815 03.02.2008 08.02.2008 multi-day sum gap defined 4815 22.03.2008 31.03.2008 multi-day sum gap defined 4815 08.02.2009 12.02.2009 multi-day sum gap defined 4815 13.06.2009 15.07.2009 multi-day sum/uncertain partition into single days gap defined 4815 05.01.2010 08.01.2010 multi-day sum gap defined 4815 01.02.2010 01.03.2010 no precipitation gap defined 4815 10.05.2010 14.05.2010 uncertain partition into single days gap defined 4819 27.11.1998 06.12.1998 multi-day sum gap defined 4819 01.08.1999 14.08.1999 multi-day sum gap defined 4819 29.07.2001 01.08.2001 multi-day sum gap defined 4819 02.09.2001 28.09.2001 multi-day sum/uncertain partition into single days gap defined 4819 03.11.2001 06.03.2002 multi-day sum/uncertain partition into single days gap defined 4831 22.04.1998 24.04.1998 multi-day sum gap defined 4831 23.06.2005 29.06.2005 multi-day sum gap defined 4831 07.02.2009 11.02.2009 multi-day sum gap defined 4906 14.01.1998 16.01.1998 multi-day sum gap defined 4906 21.01.1998 23.01.1998 multi-day sum gap defined 4906 19.02.1998 03.03.1998 multi-day sum gap defined 4906 23.04.1998 25.04.1998 multi-day sum gap defined 4906 26.05.1998 29.05.1998 multi-day sum gap defined 4906 12.06.1998 14.06.1998 multi-day sum gap defined 4906 17.09.1998 01.01.2000 multi-day sum gap defined 4906 27.01.2000 30.01.2000 multi-day sum gap defined 4906 10.05.2000 28.05.2000 multi-day sum gap defined 4906 09.07.2000 12.07.2000 multi-day sum gap defined 4906 16.08.2000 18.03.2001 multi-day sum gap defined 4906 23.06.2001 01.07.2001 multi-day sum gap defined 4906 07.10.2001 20.10.2001 multi-day sum gap defined 4906 07.11.2001 13.11.2001 multi-day sum gap defined 4906 04.12.2001 04.01.2002 multi-day sum gap defined 4906 26.01.2002 30.01.2002 multi-day sum gap defined 4906 04.02.2002 06.02.2002 multi-day sum gap defined 4906 20.02.2002 23.04.2002 multi-day sum gap defined 4906 06.06.2002 14.06.2002 multi-day sum gap defined 4913 30.07.2006 01.08.2006 multi-day sum gap defined 4913 20.02.2010 27.04.2010 no precipitation/uncertain partition into single days gap defined 4915 27.05.1998 29.05.1998 multi-day sum gap defined 4915 14.09.1998 17.09.1998 multi-day sum gap defined 4915 12.12.1998 14.12.1998 multi-day sum gap defined 4915 07.02.1999 09.02.1999 multi-day sum gap defined 4919 28.02.1998 02.03.1998 multi-day sum gap defined 4919 27.08.2000 31.08.2000 multi-day sum gap defined 4919 05.07.2009 07.07.2009 uncertain partition into single days gap defined 5012 01/04/1998 30/04/1998 no precipitation gap defined 5012 05.06.1998 07.06.1998 multi-day sum gap defined 5012 14.04.1999 18.04.1999 multi-day sum gap defined station no. start end observation consequence 5012 05.05.1999 08.05.1999 multi-day sum gap defined 5012 17.07.1999 18.10.1999 multi-day sum/uncertain partition into single days gap defined 5012 27.01.2000 29.01.2000 multi-day sum gap defined 5012 10.02.2000 13.02.2000 multi-day sum gap defined 5012 06.09.2000 14.09.2000 multi-day sum/uncertain partition into single days gap defined 5012 03.12.2000 14.12.2000 uncertain partition into single days gap defined 5012 27.12.2000 31.12.2000 multi-day sum gap defined 5012 01/04/2003 30/04/2003 no precipitation gap defined 5012 09.05.2003 12.05.2003 no precipitation gap defined 5012 17.08.2003 23.08.2003 multi-day sum/uncertain partition into single days gap defined 5012 08.11.2007 14.11.2007 multi-day sum gap defined 5012 18.10.2008 20.10.2008 multi-day sum gap defined 5013 27.10.1998 29.10.1998 multi-day sum gap defined 5013 22.04.2000 24.04.2000 multi-day sum gap defined 5013 22.05.2000 24.05.2000 multi-day sum gap defined 5013 16.11.2000 20.11.2000 multi-day sum gap defined 5013 17.12.2000 19.12.2000 multi-day sum gap defined 5013 30.12.2000 01.01.2001 multi-day sum gap defined 5013 16.10.2001 18.10.2001 multi-day sum gap defined 5013 30.11.2001 07.01.2002 multi-day sum gap defined 5013 16.03.2002 18.03.2002 multi-day sum gap defined 5013 19.10.2002 21.10.2002 multi-day sum gap defined 5013 25.12.2002 27.12.2002 multi-day sum gap defined 5013 11.05.2003 04.06.2003 multi-day sum/uncertain partition into single days gap defined 5013 18.07.2003 20.07.2003 multi-day sum gap defined 5013 14.01.2004 16.01.2004 multi-day sum gap defined 5013 17.09.2004 19.09.2004 multi-day sum gap defined 5013 17.01.2005 19.01.2005 multi-day sum gap defined 5013 29.09.2005 30.09.2005 no precipitation gap defined 5013 17.10.2005 19.10.2005 multi-day sum gap defined 5013 30.12.2005 01.01.2006 multi-day sum gap defined 5013 27.03.2006 29.03.2006 multi-day sum gap defined 5013 15.05.2006 17.05.2006 no precipitation gap defined 5013 26.05.2006 28.05.2006 multi-day sum gap defined 5013 23.06.2006 25.06.2006 uncertain partition into single days gap defined 5013 19.09.2006 21.09.2006 multi-day sum gap defined 5013 19.10.2006 21.10.2006 multi-day sum gap defined 5013 17.07.2007 19.07.2007 multi-day sum gap defined 5013 28.12.2007 07.01.2008 multi-day sum/uncertain partition into single days gap defined 5013 17.01.2008 19.01.2008 multi-day sum gap defined 5013 01.03.2008 05.03.2008 multi-day sum gap defined 5013 10.04.2008 16.04.2008 multi-day sum gap defined 5013 19.07.2008 28.07.2008 multi-day sum gap defined 5013 10.08.2008 17.08.2008 multi-day sum gap defined 5013 23.10.2008 27.10.2008 uncertain partition into single days gap defined 5013 09.11.2008 11.11.2008 multi-day sum gap defined 5013 07.12.2008 10.12.2008 uncertain partition into single days gap defined 5013 25.07.2009 27.07.2009 multi-day sum gap defined 5013 01.09.2009 03.09.2009 multi-day sum gap defined 5013 24.11.2009 26.11.2009 multi-day sum gap defined 5015 12.01.1998 14.01.1998 multi-day sum gap defined 5015 16.12.1998 19.12.1998 multi-day sum gap defined 5015 19.10.2008 01.11.2008 multi-day sum/uncertain partition into single days gap defined 5031 07.06.1998 13.06.1998 multi-day sum/uncertain partition into single days gap defined 5031 24.06.1998 27.06.1998 multi-day sum gap defined 5031 27.07.1998 01.08.1998 multi-day sum gap defined 5031 24.09.1998 27.09.1998 multi-day sum gap defined 5031 24.01.1999 26.01.1999 multi-day sum gap defined 5031 11.03.1999 13.03.1999 multi-day sum gap defined 5031 11.04.1999 23.04.1999 multi-day sum/uncertain partition into single days gap defined 5031 10.05.1999 12.05.1999 multi-day sum gap defined 5031 09.07.1999 15.07.1999 multi-day sum gap defined 5031 17.08.1999 19.08.1999 multi-day sum gap defined 5031 07.10.1999 09.10.1999 multi-day sum gap defined 5031 02.12.1999 04.12.1999 multi-day sum gap defined 5031 12.01.2000 10.02.2000 multi-day sum/uncertain partition into single days gap defined 5031 05.04.2001 08.04.2001 multi-day sum gap defined station no. start end observation consequence 5031 25.04.2001 27.04.2001 multi-day sum gap defined 5031 25.06.2001 27.06.2001 multi-day sum gap defined 5031 20.07.2001 22.07.2001 multi-day sum gap defined 5031 23.12.2001 25.12.2001 multi-day sum gap defined 5031 22.08.2003 24.08.2003 multi-day sum gap defined 5031 11.08.2004 12.08.2004 multi-day sum gap defined 5031 02.05.2005 04.05.2005 multi-day sum gap defined 5031 01.08.2006 07.09.2006 multi-day sum/no precipitation gap defined 5031 01.12.2006 03.12.2006 multi-day sum gap defined 5031 24.02.2007 26.02.2007 multi-day sum gap defined 5031 01.06.2007 04.06.2007 multi-day sum gap defined 5031 24.07.2007 27.07.2007 multi-day sum/uncertain partition into single days gap defined 5031 17.08.2007 19.08.2007 multi-day sum gap defined 5031 04.06.2008 06.06.2008 multi-day sum gap defined 5031 21.06.2008 23.06.2008 multi-day sum gap defined 5031 11.08.2008 13.08.2008 multi-day sum gap defined 5037 07.10.1999 09.10.1999 multi-day sum gap defined 5037 09.09.2003 11.09.2003 multi-day sum gap defined 5037 17.08.2005 19.08.2005 multi-day sum gap defined 5037 07.02.2006 09.02.2006 multi-day sum gap defined 5037 12.12.2008 14.12.2008 multi-day sum gap defined 5037 14.01.2009 17.01.2009 multi-day sum gap defined 5113 05.01.1998 31.05.2003 multi-day sum/no precipitation gap defined 5114 06.01.1998 08.01.1998 multi-day sum gap defined 5114 21.10.1998 29.10.1998 multi-day sum/uncertain partition into single days gap defined 5114 20.09.1999 25.09.1999 uncertain partition into single days gap defined 5114 01.10.2000 06.10.2000 multi-day sum gap defined 5114 15.05.2001 17.05.2001 multi-day sum gap defined 5114 13.07.2001 15.07.2001 multi-day sum gap defined 5114 29.01.2002 31.01.2002 multi-day sum gap defined 5114 18.05.2002 24.05.2002 multi-day sum gap defined 5114 02.07.2002 04.07.2002 multi-day sum gap defined 5114 06.08.2002 08.08.2002 multi-day sum gap defined 5114 01/11/2002 30/11/2002 no precipitation gap defined 5114 01/03/2003 31/03/2003 no precipitation gap defined 5114 25.04.2003 18.05.2003 multi-day sum gap defined 5131 07.09.2002 10.09.2002 multi-day sum gap defined 5131 18.09.2004 25.09.2004 multi-day sum gap defined 5131 17.08.2005 19.08.2005 multi-day sum gap defined 5213 27.11.1998 29.11.1998 multi-day sum gap defined 5213 07.01.1999 09.01.1999 multi-day sum gap defined 5213 23.01.1999 27.01.1999 multi-day sum gap defined 5213 07.10.1999 09.10.1999 multi-day sum gap defined 5213 09.05.2000 11.05.2000 multi-day sum gap defined 5213 01.07.2000 01.08.2000 no precipitation gap defined 5213 25.08.2000 27.08.2000 multi-day sum gap defined 5213 01.09.2000 03.09.2000 multi-day sum gap defined 5213 28.09.2000 01.10.2000 multi-day sum gap defined 5213 15.10.2000 17.10.2000 multi-day sum gap defined 5213 14.11.2000 28.11.2000 multi-day sum/uncertain partition into single days gap defined 5213 10.07.2001 12.07.2001 multi-day sum gap defined 5213 04.08.2001 10.08.2001 multi-day sum gap defined 5213 08.10.2001 20.10.2001 multi-day sum gap defined 5213 01/01/2002 30/09/2002 no precipitation gap defined 5213 27.12.2002 30.12.2002 multi-day sum gap defined 5213 01.01.2003 01.02.2003 no precipitation gap defined 5213 28/02/2003 30/04/2003 no precipitation gap defined 5214 19.02.1998 22.02.1998 multi-day sum gap defined 5214 21.06.1998 01.07.1998 multi-day sum gap defined 5214 28.12.1998 30.12.1998 multi-day sum gap defined 5214 18.01.1999 09.02.1999 multi-day sum/uncertain partition into single days gap defined 5214 13.06.1999 27.06.1999 multi-day sum/uncertain partition into single days gap defined 5214 31.01.2000 31.03.2000 multi-day sum gap defined 5214 19.06.2000 30.09.2000 multi-day sum/uncertain partition into single days gap defined 5214 18.12.2000 20.12.2000 multi-day sum gap defined 5214 27.04.2001 30.04.2001 multi-day sum gap defined 5214 31.08.2001 03.09.2001 multi-day sum gap defined station no. start end observation consequence 5214 09.11.2001 17.04.2002 multi-day sum gap defined 5214 29.09.2002 01.10.2002 multi-day sum gap defined 5214 23.11.2002 11.03.2003 multi-day sum/uncertain partition into single days gap defined 5214 22.01.2004 10.07.2006 multi-day sum/uncertain partition into single days gap defined 5214 18.10.2006 11.11.2006 multi-day sum gap defined 5214 15.12.2006 17.12.2006 multi-day sum gap defined 5214 13.01.2007 17.01.2007 multi-day sum gap defined 5214 08.02.2007 22.02.2007 multi-day sum/uncertain partition into single days gap defined 5214 29.06.2007 01.07.2007 multi-day sum gap defined 5214 26.11.2007 29.11.2007 multi-day sum gap defined 5214 26.12.2007 14.01.2008 multi-day sum gap defined 5214 03.03.2008 22.05.2008 multi-day sum/uncertain partition into single days gap defined 5214 13.08.2008 17.08.2008 multi-day sum gap defined 5214 20.01.2009 23.01.2009 multi-day sum gap defined 5214 06.02.2009 09.02.2009 multi-day sum gap defined 5214 01.04.2009 02.05.2009 no precipitation gap defined 5214 13.06.2009 18.06.2009 multi-day sum gap defined 5214 19.07.2009 22.07.2009 multi-day sum gap defined 5214 29.10.2009 31.10.2009 multi-day sum gap defined 5214 03.11.2009 05.11.2009 multi-day sum gap defined 5215 28.12.1998 30.12.1998 multi-day sum gap defined 5215 13.06.2000 15.06.2000 multi-day sum gap defined 5215 01.07.2000 01.08.2000 no precipitation gap defined 5215 03.02.2001 05.02.2001 multi-day sum gap defined 5215 26.11.2001 28.11.2001 multi-day sum gap defined 5215 30.03.2002 01.04.2002 multi-day sum gap defined 5215 19.10.2002 21.10.2002 multi-day sum gap defined 5215 10.08.2004 24.08.2004 multi-day sum gap defined 5215 13.10.2004 18.10.2004 multi-day sum gap defined 5215 28.06.2005 30.09.2005 multi-day sum gap defined 5215 13.01.2006 15.01.2006 multi-day sum gap defined 5215 20.04.2006 16.12.2006 multi-day sum/uncertain partition into single days gap defined 5215 15.02.2007 25.02.2007 multi-day sum gap defined 5215 21.04.2007 22.04.2007 no precipitation gap defined 5215 20.09.2007 22.09.2007 multi-day sum gap defined 5215 27.10.2007 29.10.2007 multi-day sum gap defined 5215 07.01.2008 09.01.2008 multi-day sum gap defined 5215 20.03.2008 30.03.2008 multi-day sum gap defined 5215 01/05/2008 31/05/2008 no precipitation gap defined 5215 17.06.2008 05.07.2008 multi-day sum gap defined 5215 07.10.2008 12.10.2008 multi-day sum gap defined 5215 09.11.2008 31.12.2009 multi-day sum/uncertain partition into single days gap defined 5231 02.11.1999 06.11.1999 multi-day sum gap defined 5231 07.03.2000 11.03.2000 multi-day sum gap defined 5231 20.12.2000 01.01.2001 multi-day sum/uncertain partition into single days gap defined 5231 13.05.2001 15.05.2001 multi-day sum gap defined 5231 04.12.2001 06.12.2001 multi-day sum gap defined 5231 24.12.2001 26.12.2001 multi-day sum gap defined 5231 01/01/2002 31/01/2002 no precipitation gap defined 5231 06.08.2002 08.08.2002 multi-day sum gap defined 5231 01/02/2003 28/02/2003 no precipitation gap defined 5231 09.03.2003 11.03.2003 multi-day sum gap defined 5231 28.04.2003 30.04.2003 multi-day sum gap defined 5231 15.11.2003 21.12.2003 multi-day sum/uncertain partition into single days gap defined 5231 17.04.2004 19.04.2004 multi-day sum gap defined 5231 27.05.2004 04.06.2004 multi-day sum gap defined 5231 01/10/2004 31/10/2004 no precipitation gap defined 5231 25.12.2004 28.12.2004 multi-day sum gap defined 5231 01/07/2005 31/07/2005 no precipitation gap defined 5231 14.09.2005 16.09.2005 uncertain partition into single days gap defined 5231 01/10/2005 31/10/2005 no precipitation gap defined 5231 01/12/2005 31/12/2005 no precipitation gap defined 5231 01/02/2006 31/03/2006 no precipitation gap defined 5231 01.04.2006 01.08.2006 multi-day sum/uncertain partition into single days gap defined 5231 08.11.2007 10.11.2007 multi-day sum gap defined 5231 04.01.2008 07.01.2008 multi-day sum gap defined 5231 12.03.2008 14.03.2008 uncertain partition into single days gap defined station no. start end observation consequence 5231 09.05.2008 11.05.2008 uncertain partition into single days gap defined 5231 11.12.2008 18.06.2009 multi-day sum/uncertain partition into single days gap defined 5306 26.12.2004 29.12.2004 multi-day sum gap defined 5306 17.08.2009 24.08.2009 multi-day sum gap defined 5313 01.01.2002 01.02.2002 no precipitation gap defined 5313 09.08.2004 14.08.2004 uncertain partition into single days gap defined 5313 04.02.2005 07.02.2005 multi-day sum gap defined 5313 06.07.2006 09.07.2006 multi-day sum gap defined 5313 25.10.2007 30.10.2007 uncertain partition into single days gap defined 5313 15.06.2008 15.09.2008 very high precipitation gap defined 5313 04.12.2008 20.12.2008 uncertain partition into single days gap defined 5313 09.10.2009 11.10.2009 multi-day sum gap defined 5323 01.04.2000 03.04.2000 multi-day sum gap defined 5323 30.08.2000 01.09.2000 multi-day sum gap defined 5323 19.12.2000 21.12.2000 multi-day sum gap defined 5323 29.10.2002 31.10.2002 multi-day sum gap defined 5323 20.05.2003 22.05.2003 multi-day sum gap defined 5323 09.09.2003 11.09.2003 multi-day sum gap defined 5323 01.11.2003 03.11.2003 multi-day sum gap defined 5323 10.12.2003 21.12.2003 multi-day sum gap defined 5323 16.12.2004 19.12.2004 multi-day sum gap defined 5323 25.04.2005 27.04.2005 multi-day sum gap defined 5323 22.07.2005 25.07.2005 multi-day sum gap defined 5323 19.05.2006 22.05.2006 multi-day sum gap defined 5323 05.09.2008 07.09.2008 multi-day sum gap defined 5323 01.02.2009 01.03.2009 no precipitation gap defined 5323 06.06.2009 08.06.2009 multi-day sum gap defined 5323 26.06.2009 01.07.2009 multi-day sum gap defined 5323 01/07/2009 31/07/2009 no precipitation gap defined 5323 30.08.2009 01.09.2009 multi-day sum gap defined 5323 01/10/2009 31/10/2009 no precipitation gap defined 5331 30.12.2000 01.01.2001 multi-day sum gap defined 5331 12.10.2004 14.10.2004 multi-day sum gap defined 5331 03.01.2008 05.01.2008 uncertain partition into single days gap defined 5331 09.10.2009 11.10.2009 multi-day sum gap defined 5406 04.01.1998 06.01.1998 multi-day sum gap defined 5406 09.01.1998 11.01.1998 multi-day sum gap defined 5406 26.05.1998 28.05.1998 multi-day sum gap defined 5406 06.02.1999 08.02.1999 multi-day sum gap defined 5406 04.03.1999 12.03.1999 multi-day sum gap defined 5406 26.03.1999 28.03.1999 multi-day sum gap defined 5406 29.09.1999 04.10.1999 multi-day sum/uncertain partition into single days gap defined 5406 13.12.1999 17.12.1999 multi-day sum gap defined 5406 26.12.1999 30.12.1999 multi-day sum gap defined 5406 04.02.2000 06.02.2000 multi-day sum gap defined 5406 23.02.2000 01.03.2000 multi-day sum gap defined 5406 18.05.2000 01.06.2000 multi-day sum gap defined 5406 01.08.2000 03.08.2000 multi-day sum gap defined 5406 15.08.2000 17.08.2000 multi-day sum gap defined 5406 21.08.2000 26.08.2000 multi-day sum gap defined 5406 21.12.2000 31.12.2000 multi-day sum/uncertain partition into single days gap defined 5406 05.12.2001 07.12.2001 multi-day sum gap defined 5406 10.06.2002 13.06.2002 multi-day sum gap defined 5406 12.11.2002 15.11.2002 multi-day sum gap defined 5406 01.01.2003 13.01.2003 multi-day sum gap defined 5406 24.01.2003 29.01.2003 multi-day sum gap defined 5406 07.05.2003 12.05.2003 multi-day sum gap defined 5406 03.06.2003 05.06.2003 multi-day sum gap defined 5406 26.06.2003 30.06.2003 multi-day sum gap defined 5406 20.09.2003 22.09.2003 multi-day sum gap defined 5406 12.10.2003 14.10.2003 multi-day sum gap defined 5406 15.01.2005 17.01.2005 multi-day sum gap defined 5406 01.07.2005 01.08.2005 no precipitation gap defined 5406 26.08.2005 29.08.2005 multi-day sum gap defined 5406 26.09.2005 30.09.2005 multi-day sum gap defined 5406 09.06.2006 18.06.2006 multi-day sum gap defined 5406 28.11.2006 30.11.2006 multi-day sum gap defined station no. start end observation consequence 5406 06.12.2006 08.12.2006 multi-day sum gap defined 5406 22.01.2007 24.01.2007 multi-day sum gap defined 5406 20.02.2007 22.02.2007 multi-day sum gap defined 5406 24.02.2007 27.02.2007 multi-day sum gap defined 5406 04.03.2007 06.03.2007 multi-day sum gap defined 5406 12.05.2007 14.05.2007 multi-day sum gap defined 5406 30.12.2007 04.01.2008 multi-day sum gap defined 5406 29.01.2008 05.02.2008 multi-day sum gap defined 5406 12.03.2008 15.03.2008 multi-day sum gap defined 5406 25.03.2008 27.03.2008 multi-day sum gap defined 5406 17.04.2008 02.05.2008 multi-day sum/uncertain partition into single days gap defined 5406 23.06.2008 25.06.2008 multi-day sum gap defined 5406 04.12.2008 21.12.2008 multi-day sum gap defined 5406 01.02.2009 05.02.2009 uncertain partition into single days gap defined 5406 04.03.2009 06.03.2009 multi-day sum gap defined 5406 10.03.2009 14.03.2009 multi-day sum gap defined 5406 13.04.2009 16.04.2009 multi-day sum gap defined 5406 28.04.2009 04.05.2009 uncertain partition into single days gap defined 5406 23.05.2009 27.05.2009 uncertain partition into single days gap defined 5406 27.07.2009 01.09.2009 multi-day sum/no precipitation gap defined 5406 05.10.2009 19.11.2009 multi-day sum/uncertain partition into single days gap defined 5406 08.12.2009 17.12.2009 multi-day sum/uncertain partition into single days gap defined 5411 07.02.1999 09.02.1999 multi-day sum gap defined 5414 27.01.1999 07.02.1999 multi-day sum gap defined 5414 04.03.1999 12.03.1999 multi-day sum gap defined 5414 21.04.1999 25.04.1999 multi-day sum gap defined 5414 26.06.1999 28.06.1999 multi-day sum gap defined 5414 25.12.1999 27.12.1999 multi-day sum gap defined 5414 13.01.2000 07.02.2000 multi-day sum/uncertain partition into single days gap defined 5414 11.04.2000 14.04.2000 multi-day sum gap defined 5414 02.06.2000 16.06.2000 multi-day sum gap defined 5414 04.02.2001 18.05.2001 multi-day sum/uncertain partition into single days gap defined 5414 14.08.2001 18.09.2001 multi-day sum gap defined 5414 14.10.2001 16.10.2001 multi-day sum gap defined 5414 22.02.2002 21.03.2002 multi-day sum/uncertain partition into single days gap defined 5414 08.06.2002 11.09.2002 multi-day sum/uncertain partition into single days gap defined 5414 01.12.2002 13.12.2002 multi-day sum gap defined 5414 27.02.2003 07.03.2003 multi-day sum gap defined 5414 30.04.2003 02.05.2003 multi-day sum gap defined 5414 05.09.2003 07.09.2003 multi-day sum gap defined 5414 03.03.2004 05.03.2004 multi-day sum gap defined 5414 14.04.2004 22.04.2004 multi-day sum gap defined 5414 18.06.2004 25.04.2005 multi-day sum gap defined 5414 30.05.2005 06.06.2005 multi-day sum gap defined 5414 24.09.2005 25.09.2005 no precipitation gap defined 5414 15.12.2005 29.12.2005 multi-day sum gap defined 5414 23.02.2006 07.08.2006 multi-day sum gap defined 5414 23.09.2006 25.09.2006 multi-day sum gap defined 5414 01/11/2006 30/11/2006 no precipitation gap defined 5414 02.12.2006 04.12.2006 multi-day sum gap defined 5414 16.07.2007 21.07.2007 multi-day sum gap defined 5414 24.06.2008 29.06.2008 multi-day sum gap defined 5414 24.01.2009 25.01.2009 no precipitation gap defined 5414 07.02.2009 09.02.2009 no precipitation gap defined 5414 30.06.2009 14.07.2009 multi-day sum/uncertain partition into single days gap defined 5414 27.08.2009 29.08.2009 multi-day sum gap defined 5414 07.11.2009 10.11.2009 multi-day sum gap defined 5415 08.07.2004 02.10.2004 uncertain partition into single days gap defined 5415 23.11.2009 25.11.2009 multi-day sum gap defined 5419 06.03.1998 08.03.1998 multi-day sum gap defined 5419 03.09.1998 05.09.1998 no precipitation gap defined 5419 11.02.1999 14.02.1999 multi-day sum gap defined 5419 31.03.1999 02.04.1999 multi-day sum gap defined 5419 27.07.2000 30.07.2000 multi-day sum gap defined 5419 03.09.2000 05.09.2000 multi-day sum gap defined 5419 21.11.2000 23.11.2000 multi-day sum gap defined 5419 25.01.2001 27.01.2001 multi-day sum gap defined station no. start end observation consequence 5419 07.09.2001 15.09.2001 multi-day sum gap defined 5419 16.04.2002 18.04.2002 multi-day sum gap defined 5419 08.05.2003 11.05.2003 multi-day sum gap defined 5419 15.05.2003 18.05.2003 multi-day sum gap defined 5419 24.05.2003 10.06.2003 multi-day sum gap defined 5419 20.07.2004 22.07.2004 multi-day sum gap defined 5419 15.04.2005 17.04.2005 multi-day sum gap defined 5431 26.02.2001 28.02.2001 multi-day sum gap defined 5431 01/08/2001 31/08/2001 no precipitation gap defined 5431 03.09.2001 17.09.2001 multi-day sum gap defined 5431 22.02.2002 24.02.2002 multi-day sum gap defined 5431 14.03.2002 01.04.2002 multi-day sum gap defined 5431 02.08.2002 04.08.2002 multi-day sum gap defined 5431 19.11.2002 21.11.2002 multi-day sum gap defined 5431 24.12.2002 26.12.2002 multi-day sum gap defined 5431 23.01.2003 25.01.2003 uncertain partition into single days gap defined 5431 01.02.2003 10.02.2003 multi-day sum gap defined 5431 24.04.2003 26.04.2003 multi-day sum gap defined 5431 25.11.2003 30.11.2003 multi-day sum gap defined 5431 13.12.2003 16.12.2003 multi-day sum gap defined 5431 01/03/2004 30/09/2004 no precipitation gap defined 5431 24.09.2005 26.09.2005 multi-day sum gap defined 5431 25.10.2005 27.10.2005 multi-day sum gap defined 5431 24.11.2005 26.11.2005 multi-day sum gap defined 5431 07.12.2005 20.12.2005 multi-day sum gap defined 5431 29.12.2005 31.12.2005 multi-day sum gap defined 5431 22.02.2006 24.02.2006 multi-day sum gap defined 5431 25.08.2006 28.08.2006 multi-day sum gap defined 5431 11.08.2007 13.08.2007 multi-day sum gap defined 5431 17.08.2007 19.08.2007 uncertain partition into single days gap defined 5431 05.12.2007 07.12.2007 multi-day sum gap defined 5431 08.03.2008 10.03.2008 multi-day sum gap defined 5431 27.03.2008 31.03.2008 multi-day sum/uncertain partition into single days gap defined 5431 01.04.2008 03.04.2008 multi-day sum gap defined 5431 23.08.2008 25.08.2008 multi-day sum gap defined 5431 10.10.2008 12.10.2008 multi-day sum gap defined 5431 01.12.2008 04.12.2008 multi-day sum gap defined 5431 12.07.2009 14.07.2009 multi-day sum gap defined 5431 24.07.2009 26.07.2009 multi-day sum gap defined 5431 11.11.2009 14.11.2009 multi-day sum/uncertain partition into single days gap defined 5431 08.12.2009 11.12.2009 multi-day sum gap defined 5431 29.12.2009 01.01.2010 multi-day sum gap defined 5437 29.06.2001 01.07.2001 multi-day sum gap defined 5437 20.07.2001 22.07.2001 multi-day sum gap defined 5437 20.04.2004 22.04.2004 multi-day sum gap defined 5437 01/01/2009 31/01/2009 no precipitation gap defined 5437 24.07.2009 26.07.2009 multi-day sum gap defined 5506 18.04.1998 22.04.1998 multi-day sum gap defined 5506 25.07.1998 27.07.1998 multi-day sum gap defined 5506 30.08.1998 05.09.1998 multi-day sum gap defined 5506 15.10.1998 17.10.1998 multi-day sum gap defined 5506 22.10.1998 24.10.1998 multi-day sum gap defined 5506 10.12.1998 12.12.1998 multi-day sum gap defined 5506 17.12.1998 19.12.1998 multi-day sum gap defined 5506 07.01.1999 16.01.1999 multi-day sum gap defined 5506 06.05.1999 08.05.1999 multi-day sum gap defined 5506 01.07.1999 03.07.1999 multi-day sum gap defined 5506 02.10.1999 30.10.1999 multi-day sum gap defined 5506 25.11.1999 27.11.1999 multi-day sum gap defined 5506 10.12.1999 12.12.1999 multi-day sum gap defined 5506 30.06.2000 03.07.2000 uncertain partition into single days gap defined 5506 30.08.2000 01.09.2000 multi-day sum gap defined 5506 14.09.2000 16.09.2000 multi-day sum gap defined 5506 28.09.2000 01.10.2000 multi-day sum gap defined 5506 26.10.2000 26.11.2000 multi-day sum gap defined 5506 05.02.2001 07.02.2001 multi-day sum gap defined 5506 04.02.2002 06.02.2002 multi-day sum gap defined station no. start end observation consequence 5506 01.04.2002 03.04.2002 multi-day sum gap defined 5506 20.05.2002 22.05.2002 multi-day sum gap defined 5506 15.06.2002 17.06.2002 multi-day sum gap defined 5506 26.10.2002 30.10.2002 multi-day sum gap defined 5506 20.12.2002 30.12.2002 multi-day sum/uncertain partition into single days gap defined 5506 07.06.2003 11.06.2003 multi-day sum gap defined 5506 03.08.2004 09.08.2004 multi-day sum/uncertain partition into single days gap defined 5506 06.01.2005 08.01.2005 multi-day sum gap defined 5506 16.04.2005 18.04.2005 multi-day sum gap defined 5506 17.05.2005 20.05.2005 multi-day sum gap defined 5506 02.08.2005 07.08.2005 multi-day sum gap defined 5506 25.08.2005 28.08.2005 multi-day sum gap defined 5506 12.05.2006 14.05.2006 multi-day sum gap defined 5506 04.10.2006 06.10.2006 multi-day sum gap defined 5506 14.12.2006 16.12.2006 multi-day sum gap defined 5506 12.07.2007 14.07.2007 multi-day sum gap defined 5506 28.07.2007 13.08.2007 multi-day sum gap defined 5506 26.06.2008 28.06.2008 multi-day sum gap defined 5506 17.01.2009 23.01.2009 multi-day sum gap defined 5506 07.02.2009 09.02.2009 multi-day sum gap defined 5506 11.04.2009 18.04.2009 multi-day sum gap defined 5506 04.07.2009 06.07.2009 multi-day sum gap defined 5506 14.07.2009 20.07.2009 multi-day sum gap defined 5506 22.08.2009 24.08.2009 multi-day sum gap defined 5506 29.08.2009 31.08.2009 multi-day sum gap defined 5506 18.11.2009 21.11.2009 multi-day sum gap defined 5506 29.11.2009 01.12.2009 multi-day sum gap defined 5506 08.12.2009 01.01.2010 multi-day sum/uncertain partition into single days gap defined 5512 01/04/2007 30/04/2007 no precipitation gap defined 5512 21.12.2007 29.12.2007 multi-day sum gap defined 5512 10.01.2008 14.01.2008 multi-day sum gap defined 5512 20.06.2008 22.06.2008 multi-day sum gap defined 5512 01/06/2009 28/02/2010 no precipitation gap defined 5514 04.02.1999 09.02.1999 multi-day sum gap defined 5514 25.06.2001 27.06.2001 multi-day sum gap defined 5514 22.10.2001 25.10.2001 multi-day sum gap defined 5514 28.11.2001 30.11.2001 multi-day sum gap defined 5514 12.07.2002 16.07.2002 multi-day sum gap defined 5514 01/01/2003 31/01/2003 no precipitation gap defined 5514 01.07.2003 01.08.2003 no precipitation gap defined 5514 28.07.2004 30.07.2004 multi-day sum gap defined 5514 25.03.2006 27.03.2006 multi-day sum gap defined 5514 05.05.2006 07.05.2006 multi-day sum gap defined 5514 12.05.2009 28.05.2009 uncertain partition into single days gap defined 5514 06.07.2009 08.07.2009 multi-day sum gap defined 5523 11.01.2009 31.01.2009 no precipitation gap defined 5531 08.09.2003 10.09.2003 implausible gap defined 5531 14.02.2006 16.02.2006 multi-day sum gap defined 5531 12.06.2007 13.06.2007 very high precipitation gap defined 5531 24.01.2009 26.01.2009 multi-day sum gap defined 5531 26.07.2009 29.07.2009 multi-day sum gap defined 5537 02.07.2000 04.07.2000 uncertain partition into single days gap defined 5537 11.10.2000 15.10.2000 multi-day sum gap defined 5537 10.11.2000 12.11.2000 multi-day sum gap defined 5537 15.12.2000 21.12.2000 multi-day sum gap defined 5537 14.10.2001 16.10.2001 multi-day sum gap defined 5537 22.02.2002 24.02.2002 multi-day sum gap defined 5537 19.03.2002 21.03.2002 multi-day sum gap defined 5537 21.06.2002 23.06.2002 multi-day sum gap defined 5537 09.07.2002 11.07.2002 multi-day sum gap defined 5537 13.08.2002 15.08.2002 multi-day sum gap defined 5537 22.12.2002 24.12.2002 multi-day sum gap defined 5537 23.05.2003 25.05.2003 multi-day sum gap defined 5537 05.09.2003 07.09.2003 multi-day sum gap defined 5537 19.12.2003 21.12.2003 multi-day sum gap defined 5537 20.03.2004 22.03.2004 multi-day sum gap defined 5537 08.04.2004 10.04.2004 multi-day sum gap defined station no. start end observation consequence 5537 04.05.2004 06.05.2004 multi-day sum gap defined 5537 27.05.2004 01.06.2004 multi-day sum gap defined 5537 13.10.2004 15.10.2004 multi-day sum gap defined 5537 05.04.2005 07.04.2005 multi-day sum gap defined 5537 01/05/2005 31/05/2005 no precipitation gap defined 5537 06.03.2006 08.03.2006 multi-day sum gap defined 5537 10.04.2006 12.04.2006 multi-day sum gap defined 5537 17.05.2006 19.05.2006 multi-day sum gap defined 5537 25.08.2006 27.08.2006 multi-day sum gap defined 5537 19.10.2006 23.10.2006 multi-day sum gap defined 5537 10.11.2006 12.11.2006 multi-day sum gap defined 5537 26.11.2006 28.11.2006 multi-day sum gap defined 5537 10.02.2007 12.02.2007 multi-day sum gap defined 5537 18.05.2007 20.05.2007 multi-day sum gap defined 5537 06.03.2008 18.03.2008 multi-day sum gap defined 5537 01.10.2008 03.10.2008 multi-day sum gap defined 5537 12.11.2008 14.11.2008 multi-day sum gap defined 5537 21.11.2009 23.11.2009 multi-day sum gap defined 5613 19.12.2003 21.12.2003 multi-day sum gap defined 5623 26.04.2003 28.04.2003 uncertain partition into single days gap defined 5623 02.10.2004 04.10.2004 uncertain partition into single days gap defined 5623 11.01.2009 31.01.2009 no precipitation gap defined 5631 07.09.2003 09.09.2003 multi-day sum gap defined 5631 01.12.2003 03.12.2003 multi-day sum gap defined 5631 02.03.2004 04.03.2004 multi-day sum gap defined 5631 20.06.2004 22.06.2004 uncertain partition into single days gap defined 5631 23.10.2004 25.10.2004 multi-day sum gap defined 5631 07.04.2005 09.04.2005 multi-day sum gap defined 5631 18.05.2005 28.05.2005 multi-day sum gap defined 5631 10.11.2006 12.11.2006 multi-day sum gap defined 5631 21.09.2007 24.09.2007 implausible gap defined 5631 05.10.2008 10.10.2008 multi-day sum/uncertain partition into single days gap defined 5631 10.11.2008 12.11.2008 multi-day sum gap defined 5631 16.12.2008 18.12.2008 multi-day sum gap defined 5637 25.01.2001 28.01.2001 multi-day sum gap defined 5637 08.03.2001 12.03.2001 multi-day sum gap defined 5637 26.06.2001 01.07.2001 multi-day sum/uncertain partition into single days gap defined 5637 01/10/2002 31/10/2002 no precipitation gap defined 5637 21.11.2002 23.11.2002 uncertain partition into single days gap defined 5637 01.04.2003 03.04.2003 multi-day sum gap defined 5637 01/06/2003 30/06/2003 no precipitation gap defined 5637 01/09/2003 30/09/2003 no precipitation gap defined 5637 10.12.2003 12.12.2003 multi-day sum gap defined 5637 01/02/2004 29/02/2004 no precipitation gap defined 5637 23.10.2004 25.10.2004 multi-day sum gap defined 5637 14.03.2005 18.03.2005 multi-day sum/uncertain partition into single days gap defined 5637 24.05.2005 26.05.2005 multi-day sum gap defined 5637 03.08.2005 07.08.2005 multi-day sum gap defined 5637 01/10/2005 31/10/2005 no precipitation gap defined 5637 05.11.2005 12.11.2005 multi-day sum gap defined 5637 01/12/2005 31/01/2006 no precipitation gap defined 5637 01/03/2006 30/04/2006 no precipitation gap defined 5637 30.10.2006 01.11.2006 multi-day sum gap defined 5637 12.05.2007 14.05.2007 uncertain partition into single days gap defined 5637 02.10.2007 04.10.2007 multi-day sum gap defined 5637 01.12.2007 04.12.2007 multi-day sum gap defined 5637 08.01.2008 10.01.2008 multi-day sum gap defined 5637 06.03.2008 08.03.2008 uncertain partition into single days gap defined 5637 29.03.2008 31.08.2008 implausible gap defined 5637 29.09.2008 06.10.2008 multi-day sum gap defined 5637 01.11.2008 30.11.2008 implausible gap defined 5637 01.02.2009 03.03.2009 implausible gap defined 5637 08.05.2009 10.05.2009 multi-day sum gap defined 5637 14.07.2009 16.07.2009 multi-day sum gap defined 5637 18.10.2009 20.10.2009 multi-day sum gap defined 5637 08.11.2009 15.11.2009 implausible gap defined 5637 03.12.2009 11.12.2009 implausible gap defined station no. start end observation consequence 5714 23.12.2000 25.12.2000 multi-day sum gap defined 5714 26.09.2001 28.09.2001 multi-day sum gap defined 5714 21.01.2002 24.01.2002 multi-day sum gap defined 5714 07.11.2002 09.11.2002 multi-day sum gap defined 5714 30.10.2003 01.11.2003 multi-day sum gap defined 5714 03.07.2006 05.07.2006 multi-day sum gap defined 5714 25.08.2006 28.08.2006 multi-day sum gap defined 5714 01.06.2007 04.06.2007 multi-day sum gap defined 5714 28.03.2008 30.03.2008 multi-day sum gap defined 5714 24.06.2008 26.06.2008 multi-day sum gap defined 5714 13.08.2008 15.08.2008 multi-day sum gap defined 5714 10.10.2008 12.10.2008 multi-day sum gap defined 5714 12.04.2009 14.04.2009 multi-day sum gap defined 5714 25.07.2009 26.07.2009 no precipitation gap defined 5714 18.08.2009 21.08.2009 multi-day sum gap defined 5714 03.09.2009 09.09.2009 uncertain partition into single days gap defined 5714 21.10.2009 01.11.2009 multi-day sum/uncertain partition into single days gap defined 5714 23.11.2009 25.11.2009 uncertain partition into single days gap defined 5714 09.12.2009 29.12.2009 multi-day sum/uncertain partition into single days gap defined 5811 01.02.1998 01.03.1998 no precipitation gap defined 5811 23.03.1998 25.03.1998 multi-day sum gap defined 5811 08.07.1998 12.07.1998 multi-day sum gap defined 5811 27.11.1998 01.12.1998 multi-day sum gap defined 5811 19.01.1999 23.01.1999 multi-day sum gap defined 5811 26.01.1999 30.01.1999 multi-day sum gap defined 5811 01.06.1999 01.07.1999 no precipitation gap defined 5811 05.08.2000 08.08.2000 multi-day sum gap defined 5811 06.03.2001 09.03.2001 multi-day sum gap defined 5811 17.06.2001 19.06.2001 multi-day sum gap defined 5811 26.06.2001 28.06.2001 multi-day sum gap defined 5811 27.12.2001 30.12.2001 multi-day sum gap defined 5811 27.02.2002 01.03.2002 multi-day sum gap defined 5811 17.04.2002 19.04.2002 multi-day sum gap defined 5811 08.06.2002 10.06.2002 multi-day sum gap defined 5811 25.06.2002 30.06.2002 multi-day sum gap defined 5811 27.08.2002 01.10.2002 multi-day sum/no precipitation gap defined 5811 01.04.2003 01.05.2003 no precipitation gap defined 5811 09.06.2003 12.06.2003 multi-day sum gap defined 5811 01.08.2003 01.09.2003 no precipitation gap defined 5811 01.06.2004 01.07.2004 no precipitation gap defined 5811 20.09.2004 01.11.2004 multi-day sum/no precipitation gap defined 5819 12.12.1998 18.12.1998 multi-day sum gap defined 5819 02.08.1999 05.08.1999 multi-day sum gap defined 5819 08.09.2000 10.09.2000 multi-day sum gap defined 5819 27.09.2000 29.09.2000 multi-day sum gap defined 5819 19.11.2000 21.11.2000 multi-day sum gap defined 5819 25.02.2001 26.02.2001 no precipitation gap defined 5819 22.06.2002 27.06.2002 multi-day sum gap defined 5819 07.08.2002 10.08.2002 multi-day sum gap defined 5819 11.11.2002 13.11.2002 multi-day sum gap defined 5819 17.11.2002 19.11.2002 multi-day sum gap defined 5819 26.12.2003 28.12.2003 multi-day sum gap defined 5819 15.01.2004 17.01.2004 multi-day sum gap defined 5819 03.07.2004 07.07.2004 multi-day sum gap defined 5819 15.12.2005 19.12.2005 multi-day sum gap defined 5819 05.01.2006 07.01.2006 multi-day sum gap defined 5819 01.08.2006 18.08.2006 multi-day sum/uncertain partition into single days gap defined 5819 12.09.2006 17.09.2006 multi-day sum gap defined 5819 19.11.2006 21.11.2006 multi-day sum gap defined 5819 13.01.2007 03.02.2007 uncertain partition into single days gap defined 5819 23.12.2007 25.12.2007 uncertain partition into single days gap defined 5819 03.05.2008 04.05.2008 no precipitation gap defined 5819 25.12.2009 27.12.2009 multi-day sum gap defined 5819 27.01.2010 03.02.2010 multi-day sum gap defined 5819 21.02.2010 30.03.2010 multi-day sum/uncertain partition into single days gap defined 5837 27.10.2000 31.10.2000 multi-day sum gap defined 5837 26.07.2003 29.07.2003 multi-day sum gap defined station no. start end observation consequence 5837 01/12/2005 31/12/2005 no precipitation gap defined 5837 06.03.2006 08.03.2006 multi-day sum gap defined 5912 24.04.1998 26.04.1998 multi-day sum gap defined 5912 24.12.1998 26.12.1998 multi-day sum gap defined 5912 03.01.1999 05.01.1999 multi-day sum gap defined 5912 11.01.1999 15.01.1999 multi-day sum gap defined 5912 11.02.1999 14.02.1999 multi-day sum gap defined 5912 10.12.1999 13.12.1999 multi-day sum gap defined 5912 30.07.2000 28.08.2000 multi-day sum gap defined 5912 14.06.2001 16.06.2001 multi-day sum gap defined 5912 06.08.2001 08.08.2001 multi-day sum gap defined 5912 12.04.2003 15.04.2003 multi-day sum gap defined 5912 11.05.2003 13.05.2003 multi-day sum gap defined 5912 10.12.2003 12.12.2003 multi-day sum gap defined 5912 02.03.2004 04.03.2004 multi-day sum gap defined 5912 10.09.2004 12.09.2004 multi-day sum gap defined 5912 12.10.2004 14.10.2004 multi-day sum gap defined 5912 04.06.2005 06.06.2005 multi-day sum gap defined 5912 09.04.2009 12.04.2009 multi-day sum gap defined 5912 05.10.2009 11.10.2009 multi-day sum gap defined 5912 29.10.2009 31.10.2009 multi-day sum gap defined 5914 26.05.1998 06.06.1998 multi-day sum/uncertain partition into single days gap defined 5914 08.09.1998 30.09.1998 multi-day sum gap defined 5914 17.11.1998 31.07.2001 multi-day sum/uncertain partition into single days gap defined 5919 20.02.1998 23.02.1998 multi-day sum gap defined 5919 16.11.1998 18.11.1998 multi-day sum gap defined 5919 06.02.2000 11.02.2000 multi-day sum gap defined 5919 05.12.2000 09.12.2000 multi-day sum gap defined 5919 21.07.2001 28.07.2001 multi-day sum gap defined 5919 28.09.2001 30.09.2001 multi-day sum gap defined 5919 02.03.2003 06.03.2003 multi-day sum gap defined 5919 28.03.2003 30.03.2003 multi-day sum gap defined 5919 27.05.2003 29.05.2003 uncertain partition into single days gap defined 5919 30.01.2004 01.02.2004 multi-day sum gap defined 5919 15.08.2004 21.08.2004 multi-day sum gap defined 5919 23.05.2006 28.05.2006 multi-day sum gap defined 5919 05.10.2006 07.10.2006 multi-day sum gap defined 5919 22.04.2007 29.04.2007 multi-day sum gap defined 5919 19.05.2007 01.08.2007 multi-day sum gap defined 5919 01.07.2008 30.07.2008 multi-day sum gap defined 5919 26.12.2009 30.12.2009 multi-day sum gap defined 5919 15.05.2010 23.05.2010 multi-day sum gap defined 6019 10.07.2001 12.07.2001 multi-day sum gap defined 6019 01.12.2009 01.06.2010 no precipitation gap defined 6114 24.03.1998 28.03.1998 multi-day sum gap defined 6114 07.04.1998 10.04.1998 multi-day sum gap defined 6114 30.10.1999 01.11.1999 multi-day sum gap defined 6114 26.07.2000 29.07.2000 multi-day sum gap defined 6114 05.11.2000 10.11.2000 multi-day sum gap defined 6114 24.01.2001 26.01.2001 multi-day sum gap defined 6114 10.02.2001 12.02.2001 multi-day sum gap defined 6114 16.05.2001 18.05.2001 multi-day sum gap defined 6114 28.09.2001 30.09.2001 multi-day sum gap defined 6114 06.10.2001 08.10.2001 multi-day sum gap defined 6114 29.11.2001 01.12.2001 multi-day sum gap defined 6114 26.01.2002 28.01.2002 multi-day sum gap defined 6114 25.05.2002 28.05.2002 multi-day sum gap defined 6114 19.08.2002 21.08.2002 multi-day sum gap defined 6114 01/12/2002 31/12/2002 no precipitation gap defined 6114 20.04.2003 25.04.2003 multi-day sum gap defined 6114 01.06.2003 03.06.2003 multi-day sum gap defined 6114 05.09.2003 11.09.2003 multi-day sum gap defined 6114 31/12/2003 31/12/2003 no precipitation gap defined 6114 28.01.2004 03.02.2004 multi-day sum gap defined 6114 02.03.2004 04.03.2004 multi-day sum gap defined 6114 02.04.2004 04.04.2004 multi-day sum gap defined 6114 03.05.2004 06.05.2004 multi-day sum gap defined station no. start end observation consequence 6114 01/07/2004 31/07/2004 no precipitation gap defined 6114 01.08.2004 04.08.2004 multi-day sum gap defined 6114 07.08.2004 09.08.2004 multi-day sum gap defined 6114 14.08.2004 16.08.2004 multi-day sum gap defined 6114 14.12.2004 17.12.2004 multi-day sum gap defined 6114 27.12.2004 29.12.2004 multi-day sum gap defined 6114 24.02.2005 26.02.2005 multi-day sum gap defined 6114 16.04.2005 28.04.2005 uncertain partition into single days gap defined 6114 01/07/2005 31/07/2005 no precipitation gap defined 6114 04.08.2005 16.01.2006 multi-day sum/uncertain partition into single days gap defined 6114 06.12.2006 08.12.2006 multi-day sum gap defined 6114 26.12.2006 01.01.2007 multi-day sum gap defined 6114 08.02.2007 12.02.2007 multi-day sum gap defined 6114 17.08.2007 19.08.2007 multi-day sum gap defined 6114 20.01.2008 22.01.2008 multi-day sum gap defined 6114 11.12.2008 13.12.2008 multi-day sum gap defined 6114 24.02.2009 27.03.2009 multi-day sum gap defined 6114 01.05.2009 03.05.2009 multi-day sum gap defined 6114 29.08.2009 31.08.2009 multi-day sum gap defined 6114 03.11.2009 09.11.2009 multi-day sum gap defined 6114 27.11.2009 30.11.2009 multi-day sum gap defined 6119 16.11.1998 19.11.1998 multi-day sum/uncertain partition into single days gap defined 6119 19.06.1999 22.06.1999 multi-day sum gap defined 6119 20.05.2000 26.05.2000 uncertain partition into single days gap defined 6119 23.01.2002 25.01.2002 multi-day sum gap defined 6119 05.11.2003 07.11.2003 multi-day sum gap defined 6119 24.02.2004 26.02.2004 multi-day sum gap defined 6119 19.11.2004 21.11.2004 multi-day sum gap defined 6119 24.12.2004 26.12.2004 multi-day sum gap defined 6119 03.01.2005 05.01.2005 multi-day sum gap defined 6119 27.04.2005 01.05.2005 multi-day sum gap defined 6119 14.06.2005 17.06.2005 multi-day sum gap defined 6119 28.06.2005 06.07.2005 multi-day sum/uncertain partition into single days gap defined 6119 08.09.2005 16.09.2005 multi-day sum gap defined 6119 07.10.2005 18.10.2005 multi-day sum gap defined 6119 05.11.2005 07.11.2005 multi-day sum gap defined 6119 29.11.2005 01.12.2005 multi-day sum gap defined 6119 15.02.2006 17.02.2006 multi-day sum gap defined 6119 23.03.2006 25.03.2006 multi-day sum gap defined 6119 06.04.2006 19.04.2006 multi-day sum gap defined 6119 01.05.2006 07.07.2006 multi-day sum gap defined 6119 14.08.2006 20.08.2006 multi-day sum/uncertain partition into single days gap defined 6119 28.08.2006 31.08.2006 multi-day sum gap defined 6119 07.02.2007 16.02.2007 multi-day sum/uncertain partition into single days gap defined 6119 08.03.2007 10.03.2007 multi-day sum gap defined 6119 21.04.2007 11.05.2007 multi-day sum/uncertain partition into single days gap defined 6119 13.06.2007 16.06.2007 multi-day sum gap defined 6119 16.09.2007 19.09.2007 multi-day sum gap defined 6119 23.03.2008 25.03.2008 multi-day sum gap defined 6119 09.04.2008 31.12.2009 multi-day sum/uncertain partition into single days gap defined 6312 13.07.2001 15.07.2001 multi-day sum gap defined 6312 29.06.2002 03.07.2002 multi-day sum gap defined 6312 07.09.2008 09.09.2008 uncertain partition into single days gap defined 6312 29.01.2009 01.02.2009 multi-day sum/uncertain partition into single days gap defined 6314 06.03.2001 08.03.2001 multi-day sum gap defined 6314 30.07.2003 01.08.2003 multi-day sum gap defined 6314 27.06.2009 29.06.2009 multi-day sum gap defined 6319 26.09.1998 28.09.1998 multi-day sum gap defined 6319 01.11.1998 03.11.1998 multi-day sum gap defined 6319 06.01.1999 08.01.1999 multi-day sum gap defined 6319 12.01.1999 14.01.1999 multi-day sum gap defined 6319 08.09.1999 10.09.1999 multi-day sum gap defined 6319 16.02.2000 18.02.2000 multi-day sum gap defined 6319 28.04.2000 30.04.2000 multi-day sum gap defined 6319 14.08.2000 16.08.2000 multi-day sum gap defined 6319 28.04.2002 01.05.2002 multi-day sum gap defined 6319 17.06.2003 19.06.2003 uncertain partition into single days gap defined station no. start end observation consequence 6319 02.08.2003 04.08.2003 multi-day sum gap defined 6319 17.08.2003 20.08.2003 multi-day sum gap defined 6319 10.12.2003 12.12.2003 multi-day sum gap defined 6319 17.11.2004 19.11.2004 multi-day sum gap defined 6319 22.12.2004 03.01.2005 multi-day sum gap defined 6319 26.04.2005 28.04.2005 multi-day sum gap defined 6319 02.06.2005 04.06.2005 multi-day sum gap defined 6319 28.07.2005 01.08.2005 multi-day sum gap defined 6319 29.09.2005 01.10.2005 multi-day sum gap defined 6319 07.10.2005 10.10.2005 multi-day sum gap defined 6319 28.10.2005 31.12.2005 multi-day sum gap defined 6323 08.06.1998 14.06.1998 multi-day sum gap defined 6323 13.08.1998 15.08.1998 multi-day sum gap defined 6323 31.08.1998 11.09.1998 multi-day sum/uncertain partition into single days gap defined 6323 08.10.1998 18.11.1998 multi-day sum/uncertain partition into single days gap defined 6323 19.02.1999 22.02.1999 multi-day sum gap defined 6323 19.04.1999 26.04.1999 multi-day sum/no precipitation gap defined 6323 01/07/1999 31/08/1999 no precipitation gap defined 6323 07.09.1999 11.09.1999 multi-day sum gap defined 6323 21.09.1999 01.11.1999 multi-day sum gap defined 6323 01/11/1999 31/12/1999 no precipitation gap defined 6323 10.06.2000 01.08.2000 multi-day sum/uncertain partition into single days gap defined 6323 01/08/2000 31/10/2000 no precipitation gap defined 6406 22.12.1998 26.12.1998 multi-day sum gap defined 6406 15.01.1999 17.01.1999 multi-day sum gap defined 6406 25.09.2001 27.09.2001 multi-day sum gap defined 6406 01.10.2001 15.10.2001 multi-day sum gap defined 6406 06.10.2002 15.10.2002 multi-day sum gap defined 6406 14.04.2005 17.04.2005 multi-day sum gap defined 6406 26.05.2005 27.05.2005 no precipitation gap defined 6406 24.05.2006 28.05.2006 multi-day sum gap defined 6406 01/06/2006 30/06/2006 no precipitation gap defined 6406 01/10/2007 31/10/2007 no precipitation gap defined 6406 14.03.2008 16.03.2008 multi-day sum gap defined 6406 04.07.2009 06.07.2009 multi-day sum gap defined 6412 13.10.1998 15.10.1998 multi-day sum gap defined 6412 26.02.2001 28.02.2001 multi-day sum gap defined 6412 10.08.2002 12.08.2002 multi-day sum gap defined 6412 15.08.2004 17.08.2004 multi-day sum gap defined 6412 08.02.2005 10.02.2005 multi-day sum gap defined 6412 17.08.2005 19.08.2005 multi-day sum gap defined 6412 30.03.2006 01.04.2006 multi-day sum gap defined 6412 05.02.2008 07.02.2008 uncertain partition into single days gap defined 6412 28.07.2008 30.07.2008 multi-day sum gap defined 6412 15.07.2009 17.07.2009 uncertain partition into single days gap defined 6412 05.10.2009 10.10.2009 multi-day sum gap defined 6412 25.12.2009 27.12.2009 multi-day sum gap defined 6414 26.07.1998 01.08.1998 multi-day sum gap defined 6414 01.11.1998 03.11.1998 multi-day sum gap defined 6414 04.08.1999 16.09.1999 multi-day sum gap defined 6414 10.06.2000 18.06.2000 multi-day sum gap defined 6414 30.07.2000 28.09.2000 multi-day sum gap defined 6414 02.08.2001 06.08.2001 multi-day sum gap defined 6414 15.03.2002 19.03.2002 multi-day sum gap defined 6414 16.06.2002 18.06.2002 multi-day sum gap defined 6414 28.07.2002 25.08.2002 multi-day sum gap defined 6414 27.07.2003 01.08.2003 multi-day sum gap defined 6414 13.11.2003 15.11.2003 multi-day sum gap defined 6414 25.11.2003 27.11.2003 multi-day sum gap defined 6414 29.07.2004 01.08.2004 multi-day sum gap defined 6414 24.07.2005 01.08.2005 multi-day sum gap defined 6414 19.10.2005 21.10.2005 multi-day sum gap defined 6414 06.04.2006 14.04.2006 multi-day sum gap defined 6414 30.07.2006 01.08.2006 multi-day sum gap defined 6414 22.09.2006 24.09.2006 multi-day sum gap defined 6414 10.12.2006 13.12.2006 multi-day sum gap defined 6414 02.07.2007 11.07.2007 multi-day sum gap defined station no. start end observation consequence 6414 28.07.2007 06.08.2007 multi-day sum gap defined 6414 28.07.2008 04.08.2008 multi-day sum gap defined 6414 01/12/2008 31/12/2008 no precipitation gap defined 6414 03.04.2009 05.04.2009 multi-day sum gap defined 6414 25.05.2009 30.05.2009 multi-day sum gap defined 6414 26.07.2009 10.08.2009 multi-day sum/uncertain partition into single days gap defined 6414 02.09.2009 04.09.2009 multi-day sum gap defined 6419 16.11.1998 22.11.1998 multi-day sum/uncertain partition into single days gap defined 6419 01.07.1999 20.07.1999 multi-day sum gap defined 6419 09.01.2000 12.01.2000 multi-day sum gap defined 6419 17.08.2000 19.08.2000 multi-day sum gap defined 6419 14.06.2001 16.06.2001 multi-day sum gap defined 6419 20.07.2001 29.07.2001 multi-day sum gap defined 6419 17.10.2001 20.10.2001 multi-day sum gap defined 6419 01.04.2002 06.04.2002 multi-day sum gap defined 6419 24.05.2002 28.05.2002 multi-day sum gap defined 6419 27.07.2002 30.07.2002 no precipitation/uncertain partition into single days gap defined 6419 11.08.2002 14.08.2002 multi-day sum gap defined 6419 24.12.2002 27.12.2002 multi-day sum gap defined 6419 23.04.2003 26.04.2003 multi-day sum gap defined 6419 26.06.2003 28.06.2003 multi-day sum gap defined 6419 21.08.2003 23.08.2003 multi-day sum gap defined 6419 03.08.2004 07.08.2004 multi-day sum gap defined 6419 16.04.2005 22.04.2005 multi-day sum gap defined 6419 22.07.2006 28.07.2006 multi-day sum gap defined 6419 23.08.2006 29.08.2006 multi-day sum gap defined 6419 23.06.2007 01.07.2007 multi-day sum gap defined 6419 19.07.2007 21.08.2007 multi-day sum gap defined 6419 04.01.2008 06.01.2008 multi-day sum gap defined 6419 08.01.2008 11.01.2008 uncertain partition into single days gap defined 6419 30.05.2008 11.06.2008 multi-day sum gap defined 6419 28.07.2008 01.08.2008 multi-day sum gap defined 6419 30.01.2009 01.02.2009 multi-day sum gap defined 6419 25.06.2009 30.06.2009 multi-day sum gap defined 6419 24.08.2009 28.08.2009 multi-day sum gap defined 6419 25.12.2009 28.12.2009 multi-day sum gap defined 6512 05.06.1998 07.06.1998 multi-day sum gap defined 6512 17.07.1999 19.07.1999 multi-day sum gap defined 6512 28.10.2000 30.10.2000 multi-day sum gap defined 6512 04.11.2000 06.11.2000 multi-day sum gap defined 6512 30.12.2000 01.01.2001 multi-day sum gap defined 6512 03.02.2001 05.02.2001 multi-day sum gap defined 6512 27.04.2001 29.04.2001 multi-day sum gap defined 6512 27.04.2002 29.04.2002 multi-day sum gap defined 6512 01.11.2002 03.11.2002 multi-day sum gap defined 6512 03.05.2003 05.05.2003 multi-day sum gap defined 6512 08.01.2004 10.01.2004 multi-day sum gap defined 6512 03.04.2004 05.04.2004 multi-day sum gap defined 6512 14.07.2004 14.08.2004 multi-day sum gap defined 6512 21.01.2005 23.01.2005 multi-day sum gap defined 6512 29.04.2005 01.05.2005 multi-day sum gap defined 6512 05.05.2006 07.05.2006 multi-day sum gap defined 6512 20.05.2006 22.05.2006 multi-day sum gap defined 6512 22.09.2006 24.09.2006 multi-day sum gap defined 6512 26.12.2006 01.01.2007 multi-day sum gap defined 6512 15.01.2007 17.01.2007 multi-day sum gap defined 6512 07.02.2007 09.02.2007 multi-day sum gap defined 6512 01.12.2007 01.01.2008 no precipitation gap defined 6512 25.02.2008 27.02.2008 multi-day sum gap defined 6512 08.05.2008 12.05.2008 multi-day sum gap defined 6512 19.10.2008 21.10.2008 multi-day sum gap defined 6512 01/12/2008 31/12/2008 no precipitation gap defined 6512 10.01.2009 16.01.2009 multi-day sum/uncertain partition into single days gap defined 6512 25.01.2009 27.01.2009 multi-day sum gap defined 6512 31.01.2009 28.02.2009 multi-day sum gap defined 6512 10.03.2009 27.04.2009 multi-day sum gap defined 6512 23.05.2009 27.07.2009 multi-day sum gap defined station no. start end observation consequence 6512 23.08.2009 22.09.2009 multi-day sum gap defined 6512 01.11.2009 06.11.2009 multi-day sum gap defined 6512 29.11.2009 01.01.2010 multi-day sum gap defined 6514 05.01.1998 17.08.1998 multi-day sum gap defined 6514 18.12.1998 23.12.1998 multi-day sum gap defined 6514 16.01.1999 09.01.2000 multi-day sum/uncertain partition into single days gap defined 6514 18.08.2000 21.08.2000 multi-day sum gap defined 6514 01.09.2000 05.09.2000 multi-day sum gap defined 6514 14.10.2000 25.10.2000 multi-day sum gap defined 6514 16.11.2000 19.11.2000 multi-day sum gap defined 6514 23.01.2001 15.09.2001 multi-day sum/uncertain partition into single days gap defined 6514 20.02.2002 25.02.2002 multi-day sum/uncertain partition into single days gap defined 6514 11.07.2002 17.01.2003 multi-day sum/uncertain partition into single days gap defined 6514 01.07.2003 01.08.2005 no precipitation/uncertain partition into single days gap defined 6514 25.10.2005 27.10.2005 multi-day sum gap defined 6514 01/02/2006 28/02/2006 no precipitation gap defined 6514 18.08.2006 20.08.2006 multi-day sum gap defined 6514 30.08.2006 01.09.2006 multi-day sum gap defined 6514 10.11.2006 12.11.2006 multi-day sum gap defined 6514 17.11.2006 29.05.2007 multi-day sum gap defined 6514 01.08.2007 01.10.2007 multi-day sum gap defined 6514 21.12.2007 01.11.2009 multi-day sum gap defined 6614 01.04.1998 03.04.1998 multi-day sum gap defined 6614 04.05.1998 08.05.1998 multi-day sum gap defined 6614 16.06.1998 18.06.1998 multi-day sum gap defined 6614 22.08.1998 24.08.1998 multi-day sum gap defined 6614 02.01.1999 19.01.1999 multi-day sum gap defined 6614 28.03.1999 30.03.1999 multi-day sum gap defined 6614 03.06.1999 14.07.1999 multi-day sum/uncertain partition into single days gap defined 6614 04.11.1999 06.11.1999 multi-day sum gap defined 6614 21.11.1999 29.11.1999 multi-day sum/uncertain partition into single days gap defined 6614 12.01.2000 14.01.2000 multi-day sum gap defined 6614 20.02.2000 22.02.2000 multi-day sum gap defined 6614 03.01.2001 05.01.2001 multi-day sum gap defined 6614 07.08.2001 11.08.2001 multi-day sum gap defined 6614 04.12.2001 06.12.2001 multi-day sum gap defined 6614 24.01.2002 26.01.2002 multi-day sum gap defined 6614 09.02.2002 03.04.2002 multi-day sum/uncertain partition into single days gap defined 6614 25.04.2002 28.04.2002 no precipitation gap defined 6614 01.06.2002 04.07.2002 multi-day sum gap defined 6614 21.10.2002 24.11.2002 multi-day sum gap defined 6614 09.03.2003 11.03.2003 multi-day sum gap defined 6614 12.05.2003 14.05.2003 multi-day sum gap defined 6614 03.06.2003 05.06.2003 multi-day sum gap defined 6614 30/06/2003 31/07/2003 no precipitation gap defined 6619 10.05.1998 12.05.1998 multi-day sum gap defined 6619 01/12/1999 31/03/2002 no precipitation gap defined 6623 06.02.1998 08.02.1998 multi-day sum gap defined 6623 14.08.1999 16.08.1999 multi-day sum gap defined 6623 02.03.2000 08.03.2000 multi-day sum gap defined 6623 24.05.2000 28.05.2000 multi-day sum gap defined 6623 26.02.2001 28.02.2001 multi-day sum gap defined 6623 24.04.2001 03.05.2001 multi-day sum/uncertain partition into single days gap defined 6623 01/06/2001 01/01/2007 no precipitation gap defined 6623 02.09.2007 03.10.2007 multi-day sum gap defined 6623 24.11.2007 02.01.2008 multi-day sum/uncertain partition into single days gap defined 6623 30.01.2008 01.02.2008 multi-day sum gap defined 6712 02.01.1998 04.01.1998 multi-day sum gap defined 6712 28.08.1999 30.09.1999 uncertain partition into single days gap defined 6712 29.12.1999 31.12.1999 multi-day sum gap defined 6712 01.07.2000 04.07.2000 multi-day sum gap defined 6712 01/08/2000 30/08/2000 no precipitation gap defined 6712 01.09.2000 12.09.2000 multi-day sum gap defined 6712 25.10.2001 27.10.2001 uncertain partition into single days gap defined 6712 29.01.2002 31.01.2002 multi-day sum gap defined 6714 10.09.1999 17.10.1999 multi-day sum gap defined 6714 29.12.1999 31.12.1999 multi-day sum gap defined station no. start end observation consequence 6714 01.08.2000 08.08.2000 multi-day sum gap defined 6714 28.09.2001 30.09.2001 multi-day sum gap defined 6714 04.01.2002 07.01.2002 multi-day sum gap defined 6714 19.10.2002 21.10.2002 multi-day sum gap defined 6714 26.10.2005 28.10.2005 multi-day sum gap defined 6714 07.01.2006 16.01.2006 uncertain partition into single days gap defined 6714 07.04.2006 11.04.2006 multi-day sum gap defined 6714 02.07.2006 04.07.2006 multi-day sum gap defined 6714 15/09/2006 30/09/2006 no precipitation gap defined 6714 13.06.2007 17.06.2007 uncertain partition into single days gap defined 6714 15.01.2008 21.01.2008 multi-day sum gap defined 6714 03.07.2008 17.08.2008 multi-day sum/uncertain partition into single days gap defined 6714 16.01.2009 04.03.2009 multi-day sum/uncertain partition into single days gap defined 6714 02.05.2009 04.05.2009 multi-day sum gap defined 6714 06.06.2009 08.06.2009 multi-day sum gap defined 6714 04.12.2009 06.12.2009 multi-day sum gap defined 6719 20.04.1998 22.04.1998 multi-day sum gap defined 6719 05.09.1998 07.09.1998 multi-day sum gap defined 6719 02.06.1999 08.06.1999 multi-day sum gap defined 6719 05.01.2000 07.01.2000 multi-day sum gap defined 6719 29.09.2000 01.11.2000 no precipitation gap defined 6719 23.06.2006 25.06.2006 multi-day sum gap defined 6719 12.01.2007 15.01.2007 multi-day sum gap defined 6719 24.06.2007 04.07.2007 uncertain partition into single days gap defined 6719 01/01/2008 31/01/2008 no precipitation gap defined 6719 03.03.2008 08.03.2008 uncertain partition into single days gap defined 6719 01.04.2008 12.05.2008 uncertain partition into single days gap defined 6812 13.05.2000 15.05.2000 multi-day sum gap defined 6812 12.11.2009 14.11.2009 multi-day sum gap defined 6814 02.02.2002 04.02.2002 multi-day sum gap defined 6814 19.03.2002 12.11.2002 multi-day sum/uncertain partition into single days gap defined 6814 25.04.2003 26.04.2003 no precipitation gap defined 6814 12.11.2003 14.11.2003 multi-day sum gap defined 6814 12.01.2004 14.01.2004 multi-day sum gap defined 6814 15.07.2004 17.07.2004 multi-day sum gap defined 6814 25.11.2004 27.11.2004 multi-day sum gap defined 6814 09.01.2005 11.01.2005 multi-day sum gap defined 6814 29.03.2006 31.03.2006 multi-day sum gap defined 6814 06.05.2006 08.05.2006 multi-day sum gap defined 6814 21.05.2008 23.05.2008 multi-day sum gap defined 6814 04.08.2008 06.08.2008 multi-day sum gap defined 6814 29.04.2009 01.05.2009 multi-day sum gap defined 6814 08.05.2009 10.05.2009 multi-day sum gap defined 6912 15.10.1998 17.10.1998 multi-day sum gap defined 6912 26.02.1999 01.03.1999 multi-day sum gap defined 6912 16.04.1999 25.04.1999 multi-day sum gap defined 6912 22.12.1999 24.12.1999 multi-day sum gap defined 6912 14.02.2000 16.02.2000 multi-day sum gap defined 6912 23.02.2000 26.02.2000 multi-day sum gap defined 6912 14.08.2000 21.08.2000 uncertain partition into single days gap defined 6912 11.04.2001 13.04.2001 multi-day sum gap defined 6912 14.10.2001 16.10.2001 multi-day sum gap defined 6912 19.12.2003 21.12.2003 multi-day sum gap defined 6912 23.10.2004 25.10.2004 multi-day sum gap defined 6912 01.12.2005 08.12.2005 multi-day sum gap defined 6912 28.12.2005 30.12.2005 multi-day sum gap defined 6912 07.07.2007 09.07.2007 multi-day sum gap defined 6912 16.05.2009 18.05.2009 multi-day sum gap defined 6914 10.06.2003 12.06.2003 multi-day sum gap defined 6914 10.11.2003 01.01.2004 multi-day sum/uncertain partition into single days gap defined 6914 23.01.2004 25.01.2004 multi-day sum gap defined 6914 18.03.2004 20.03.2004 multi-day sum gap defined 6914 27.04.2004 15.06.2004 multi-day sum gap defined 6914 01.09.2004 01.02.2005 no precipitation gap defined 6919 08.10.2006 11.10.2006 multi-day sum gap defined 6919 15.01.2007 17.01.2007 multi-day sum gap defined 6919 28.06.2007 30.06.2007 multi-day sum gap defined station no. start end observation consequence 6919 22.07.2007 25.07.2007 multi-day sum gap defined 6919 27.06.2008 01.07.2008 multi-day sum gap defined 6919 13.08.2008 15.08.2008 multi-day sum gap defined 6919 27.11.2008 06.12.2008 multi-day sum/uncertain partition into single days gap defined 6919 03.03.2009 05.03.2009 multi-day sum gap defined 7014 01.11.2003 06.11.2003 multi-day sum/uncertain partition into single days gap defined 7014 01/03/2004 31/03/2004 no precipitation gap defined 7014 25.12.2004 27.12.2004 multi-day sum gap defined 7014 21.01.2005 24.01.2005 no precipitation/uncertain partition into single days gap defined 7014 04.11.2005 06.11.2005 multi-day sum gap defined 7014 20.10.2006 22.10.2006 multi-day sum gap defined 7014 24.11.2006 26.11.2006 multi-day sum gap defined 7014 17.07.2007 19.07.2007 multi-day sum gap defined 7014 03.10.2008 05.10.2008 uncertain partition into single days gap defined 7014 16.01.2009 18.01.2009 multi-day sum gap defined 7014 14.07.2009 25.07.2009 multi-day sum gap defined 7014 11.11.2009 13.11.2009 uncertain partition into single days gap defined 7112 29.06.2003 01.07.2003 multi-day sum gap defined 7112 21.02.2005 23.02.2005 multi-day sum gap defined 7112 02.07.2005 05.07.2005 multi-day sum gap defined 7112 25.07.2008 31.07.2008 multi-day sum gap defined 7114 11.01.2004 13.01.2004 multi-day sum gap defined 7114 23.01.2004 25.01.2004 multi-day sum gap defined 7114 16.09.2004 18.09.2004 multi-day sum gap defined 7114 14.12.2004 06.11.2005 multi-day sum/uncertain partition into single days gap defined 7223 02.01.1998 30.06.2001 station not trustful - cause: multi-day sums gap defined 7412 01.03.1998 04.03.1998 multi-day sum gap defined 7412 21.04.1998 24.04.1998 multi-day sum gap defined 7412 01.06.1998 03.06.1998 multi-day sum gap defined 7412 26.06.1999 28.06.1999 multi-day sum gap defined 7412 22.08.1999 24.08.1999 multi-day sum gap defined 7412 08.09.1999 10.09.1999 multi-day sum gap defined 7412 16.12.1999 18.12.1999 multi-day sum gap defined 7412 09.02.2000 12.02.2000 uncertain partition into single days gap defined 7412 22.04.2000 27.04.2000 multi-day sum gap defined 7412 13.05.2000 15.05.2000 multi-day sum gap defined 7412 28.09.2000 03.10.2000 multi-day sum gap defined 7412 01.11.2000 03.11.2000 multi-day sum gap defined 7412 10.11.2000 12.11.2000 multi-day sum gap defined 7412 21.11.2000 24.11.2000 multi-day sum gap defined 7412 07.12.2000 11.12.2000 multi-day sum gap defined 7412 30.12.2000 01.01.2001 multi-day sum gap defined 7412 09.07.2001 11.07.2001 multi-day sum gap defined 7412 18.01.2002 26.01.2002 multi-day sum gap defined 7412 26.10.2002 28.10.2002 multi-day sum gap defined 7412 19.12.2002 23.12.2002 multi-day sum gap defined 7412 26.02.2003 28.02.2003 multi-day sum gap defined 7412 17.05.2003 19.05.2003 multi-day sum gap defined 7412 11.12.2003 14.12.2003 multi-day sum gap defined 7412 10.03.2004 04.04.2004 multi-day sum gap defined 7412 17.09.2004 19.09.2004 multi-day sum gap defined 7412 16.12.2004 19.12.2004 multi-day sum gap defined 7412 17.05.2005 20.05.2005 multi-day sum gap defined 7412 04.08.2005 07.08.2005 multi-day sum gap defined 7412 09.09.2005 11.09.2005 multi-day sum gap defined 7412 17.10.2005 19.10.2005 multi-day sum gap defined 7412 26.10.2005 31.10.2005 multi-day sum gap defined 7412 29.03.2006 21.04.2006 multi-day sum gap defined 7412 17.05.2006 18.05.2006 multi-day sum gap defined 7412 20.09.2006 22.09.2006 multi-day sum gap defined 7412 08.11.2006 13.11.2006 multi-day sum gap defined 7412 20.11.2006 27.12.2006 multi-day sum gap defined 7412 07.07.2007 09.07.2007 multi-day sum gap defined 7412 13.08.2007 15.08.2007 multi-day sum gap defined 7412 27.11.2007 04.01.2008 multi-day sum gap defined 7412 18.01.2008 20.01.2008 multi-day sum gap defined 7412 06.02.2008 08.02.2008 multi-day sum gap defined station no. start end observation consequence 7412 08.04.2008 12.04.2008 multi-day sum gap defined 7412 25.04.2008 27.04.2008 multi-day sum gap defined 7412 01/05/2008 31/05/2008 no precipitation gap defined 7412 17.06.2008 22.06.2009 multi-day sum gap defined 7412 28.07.2009 01.08.2009 multi-day sum gap defined 7412 18.08.2009 21.08.2009 multi-day sum gap defined 7412 07.09.2009 13.09.2009 multi-day sum gap defined 7412 27.10.2009 29.10.2009 multi-day sum gap defined 7412 20.11.2009 01.01.2010 multi-day sum gap defined 7512 18.01.1998 20.01.1998 multi-day sum gap defined 7512 05.05.1998 07.05.1998 multi-day sum gap defined 7512 11.07.1998 13.07.1998 multi-day sum gap defined 7512 18.11.1998 20.11.1998 multi-day sum gap defined 7512 03.01.1999 06.06.1999 multi-day sum gap defined 7512 01.08.1999 07.08.1999 multi-day sum gap defined 7512 13.09.1999 26.09.1999 multi-day sum gap defined 7606 22.03.1998 30.03.1998 uncertain partition into single days gap defined 7606 07.05.1998 09.05.1998 multi-day sum gap defined 7606 12.06.1998 14.06.1998 multi-day sum gap defined 7606 27.06.1998 18.08.1998 multi-day sum/no precipitation gap defined 7606 16.12.1998 18.12.1998 multi-day sum gap defined 7606 06.10.1999 08.10.1999 multi-day sum gap defined 7606 01.02.2000 01.03.2000 no precipitation gap defined 7606 01.06.2000 01.09.2000 multi-day sum/no precipitation gap defined 7606 01.01.2001 01.02.2001 no precipitation gap defined 7606 25.02.2001 27.02.2001 multi-day sum gap defined 7606 06.10.2001 10.10.2001 multi-day sum gap defined 7612 24.04.1998 28.04.1998 multi-day sum gap defined 7612 17.06.1998 25.06.1998 multi-day sum gap defined 7612 02.08.1998 04.08.1998 multi-day sum gap defined 7612 13.11.1998 17.11.1998 multi-day sum gap defined 7612 04.12.2001 06.12.2001 multi-day sum gap defined 7612 14.05.2002 17.05.2002 multi-day sum gap defined 7612 24.05.2002 26.05.2002 multi-day sum gap defined 7612 14.06.2002 23.06.2002 multi-day sum gap defined 7612 01.08.2002 08.08.2002 multi-day sum gap defined 7612 10.09.2003 22.09.2003 multi-day sum gap defined 7612 10.10.2003 16.10.2003 multi-day sum gap defined 7612 30.10.2003 01.11.2003 multi-day sum gap defined 7612 24.11.2003 26.11.2003 multi-day sum gap defined 7612 29.11.2003 09.12.2003 multi-day sum gap defined 7612 27.12.2003 08.01.2004 multi-day sum gap defined 7612 15.02.2004 17.02.2004 multi-day sum gap defined 7612 07.08.2004 10.08.2004 multi-day sum gap defined 7612 19.09.2004 21.09.2004 multi-day sum gap defined 7612 09.11.2004 10.11.2004 multi-day sum gap defined 7612 04.12.2004 08.12.2004 multi-day sum gap defined 7612 17.12.2004 20.12.2004 multi-day sum gap defined 7612 11.01.2005 14.01.2005 multi-day sum gap defined 7612 16.01.2005 18.01.2005 multi-day sum gap defined 7612 01/02/2005 31/05/2005 no precipitation gap defined 7612 03.06.2005 06.06.2005 multi-day sum gap defined 7612 29.10.2005 31.10.2005 uncertain partition into single days gap defined 7612 11.01.2006 14.01.2006 multi-day sum gap defined 7612 30.03.2006 01.04.2006 multi-day sum gap defined 7612 01/04/2006 30/04/2006 no precipitation gap defined 7612 19.05.2006 21.05.2006 multi-day sum gap defined 7612 10.09.2006 12.09.2006 multi-day sum gap defined 7612 21.09.2006 24.09.2006 multi-day sum gap defined 7612 23.11.2006 25.11.2006 multi-day sum gap defined 7612 16.01.2007 20.01.2007 multi-day sum gap defined 7612 01/02/2007 28/02/2007 no precipitation gap defined 7612 22.06.2007 25.06.2007 multi-day sum gap defined 7612 18.08.2007 21.08.2007 multi-day sum gap defined 7612 10.01.2008 30.01.2008 multi-day sum gap defined 7612 22.03.2008 12.06.2008 multi-day sum gap defined 7612 15.08.2008 17.08.2008 multi-day sum gap defined station no. start end observation consequence 7612 31.08.2008 02.09.2008 multi-day sum gap defined 7612 16.09.2008 30.09.2008 multi-day sum gap defined 7612 01/10/2008 30/11/2008 no precipitation gap defined 7612 02.12.2008 04.12.2008 multi-day sum gap defined 7612 01/02/2009 30/06/2009 no precipitation gap defined 7612 05.07.2009 10.07.2009 multi-day sum gap defined 7612 16.07.2009 20.07.2009 multi-day sum gap defined 7612 29.07.2009 31.07.2009 multi-day sum gap defined 7612 15.08.2009 19.08.2009 multi-day sum gap defined 7612 22.08.2009 26.08.2009 multi-day sum gap defined 7806 01.10.2000 05.10.2000 multi-day sum gap defined 7806 04.11.2000 06.11.2000 multi-day sum gap defined 7806 03.04.2001 05.04.2001 multi-day sum gap defined 7806 15.07.2003 17.07.2003 multi-day sum gap defined 7806 16.03.2004 18.03.2004 multi-day sum gap defined 7806 03.04.2004 05.04.2004 multi-day sum gap defined 7806 17.04.2004 20.04.2004 multi-day sum gap defined 7806 03.05.2004 05.05.2004 multi-day sum gap defined 7806 09.07.2004 12.07.2004 multi-day sum gap defined 7806 02.10.2004 11.10.2004 multi-day sum gap defined 7806 28.06.2005 08.07.2005 multi-day sum gap defined 7806 08.10.2005 11.10.2005 multi-day sum gap defined 7806 27.06.2006 01.07.2006 multi-day sum gap defined 7806 14.09.2006 25.09.2006 multi-day sum gap defined 7806 16.11.2006 20.11.2006 multi-day sum gap defined 7806 24.02.2007 27.02.2007 multi-day sum gap defined 7806 16.05.2007 18.05.2007 multi-day sum gap defined 7806 24.07.2007 26.07.2007 multi-day sum gap defined 7806 21.10.2007 24.10.2007 multi-day sum gap defined 7806 21.06.2008 24.06.2008 multi-day sum gap defined 7806 05.07.2008 20.07.2008 multi-day sum gap defined 7812 05.04.1999 07.04.1999 multi-day sum gap defined 7812 03.06.1999 05.06.1999 multi-day sum gap defined 7812 01.07.1999 03.07.1999 multi-day sum gap defined 7812 01.08.1999 03.08.1999 multi-day sum gap defined 7812 12.08.1999 19.08.1999 multi-day sum gap defined 7812 27.09.1999 07.10.1999 multi-day sum gap defined 7812 24.10.1999 30.10.1999 multi-day sum gap defined 7812 18.12.1999 01.01.2000 multi-day sum/uncertain partition into single days gap defined 7906 05.12.2001 07.12.2001 multi-day sum gap defined 7906 20.06.2002 23.06.2002 multi-day sum gap defined 7906 04.09.2003 06.09.2003 multi-day sum gap defined 7906 16.04.2005 18.04.2005 multi-day sum gap defined 7906 11.02.2006 13.02.2006 multi-day sum gap defined 7906 09.03.2006 12.03.2006 multi-day sum gap defined 7906 17.09.2006 19.09.2006 multi-day sum gap defined 7906 04.09.2008 15.09.2008 multi-day sum/uncertain partition into single days gap defined 7906 22.10.2008 24.10.2008 multi-day sum gap defined 7906 07.07.2009 12.07.2009 multi-day sum gap defined 7906 20.11.2009 22.11.2009 multi-day sum gap defined 7906 08.12.2009 10.12.2009 multi-day sum gap defined 7906 28.12.2009 30.12.2009 multi-day sum gap defined 7923 02.01.1998 31.12.2009 station not trustful - cause: multi-day sums gap defined 8006 08.10.2001 21.10.2001 multi-day sum gap defined 8006 17.03.2002 23.03.2002 multi-day sum gap defined 8006 19.04.2002 21.04.2002 multi-day sum gap defined 8006 17.05.2002 19.05.2002 multi-day sum gap defined 8006 06.10.2002 13.10.2002 multi-day sum gap defined 8006 04.06.2003 30.06.2003 multi-day sum gap defined 8006 06.09.2003 21.09.2003 multi-day sum gap defined 8006 11.10.2003 15.10.2003 multi-day sum gap defined 8006 02.11.2003 04.11.2003 multi-day sum gap defined 8006 10.03.2004 12.03.2004 multi-day sum gap defined 8006 18.09.2004 21.09.2004 multi-day sum gap defined 8006 16.11.2004 01.12.2004 multi-day sum gap defined 8006 07.01.2005 09.01.2005 multi-day sum gap defined 8006 19.05.2005 21.05.2005 multi-day sum gap defined station no. start end observation consequence 8006 14.09.2005 16.09.2005 multi-day sum gap defined 8006 01/10/2005 31/10/2005 no precipitation gap defined 8006 01.11.2005 07.11.2005 multi-day sum gap defined 8006 16.05.2006 18.05.2006 multi-day sum gap defined 8006 28.09.2006 01.10.2006 multi-day sum gap defined 8006 11.02.2007 13.02.2007 multi-day sum gap defined 8006 19.02.2007 22.02.2007 multi-day sum gap defined 8006 18.03.2007 29.04.2007 multi-day sum gap defined 8006 15.05.2007 17.06.2007 multi-day sum gap defined 8006 03.07.2007 08.07.2007 multi-day sum gap defined 8006 22.09.2007 01.11.2007 multi-day sum gap defined 8006 22.02.2008 28.02.2008 multi-day sum gap defined 8006 03.06.2008 09.06.2008 multi-day sum gap defined 8006 13.09.2008 15.09.2008 uncertain partition into single days gap defined 8006 14.01.2009 26.01.2009 multi-day sum gap defined 8006 28.06.2009 30.06.2009 multi-day sum gap defined 8006 18.07.2009 20.07.2009 multi-day sum gap defined 8006 26.07.2009 29.07.2009 multi-day sum gap defined 8006 28.10.2009 30.10.2009 multi-day sum gap defined 8006 27.11.2009 30.11.2009 multi-day sum gap defined 8012 02.01.1998 03.01.1998 multi-day sum gap defined 8012 24.03.1998 27.03.1998 multi-day sum gap defined 8012 25.06.1998 30.06.1998 multi-day sum gap defined 8012 18.04.1999 24.04.1999 multi-day sum gap defined 8012 01/05/1999 31/05/1999 no precipitation gap defined 8012 02.06.1999 04.06.1999 multi-day sum gap defined 8012 27.11.1999 29.11.1999 multi-day sum gap defined 8012 17.05.2000 25.05.2000 multi-day sum gap defined 8012 01/06/2000 30/06/2000 no precipitation gap defined 8012 19.08.2000 21.08.2000 multi-day sum gap defined 8012 01.09.2000 03.09.2000 multi-day sum gap defined 8012 27.09.2000 01.11.2000 multi-day sum/no precipitation gap defined 8012 12.11.2000 20.11.2000 multi-day sum gap defined 8106 07.08.2002 09.08.2002 multi-day sum gap defined 8106 19.10.2002 21.10.2002 multi-day sum gap defined 8106 14.07.2004 16.07.2004 uncertain partition into single days gap defined 8106 07.08.2004 09.08.2004 multi-day sum gap defined 8106 26.04.2005 28.04.2005 multi-day sum gap defined 8106 17.08.2005 22.08.2005 multi-day sum gap defined 8106 24.09.2005 26.09.2005 multi-day sum gap defined 8106 08.10.2006 10.10.2006 multi-day sum gap defined 8106 20.10.2006 22.10.2006 multi-day sum gap defined 8106 10.11.2006 12.11.2006 multi-day sum gap defined 8106 01.07.2008 03.07.2008 multi-day sum gap defined 8106 04.10.2008 06.10.2008 multi-day sum gap defined 8106 06.09.2009 08.09.2009 multi-day sum gap defined 8106 17.11.2009 22.11.2009 multi-day sum gap defined 8112 30.05.1998 01.06.1998 multi-day sum gap defined 8112 17.11.1998 19.11.1998 multi-day sum gap defined 8112 29.12.1999 31.12.1999 multi-day sum gap defined 8112 13.06.2000 15.06.2000 multi-day sum gap defined 8112 13.09.2000 15.09.2000 multi-day sum gap defined 8112 01.10.2000 11.11.2000 multi-day sum gap defined 8112 08.04.2001 10.04.2001 multi-day sum gap defined 8112 24.04.2001 26.04.2001 multi-day sum gap defined 8112 11.07.2001 13.07.2001 very high precipitation gap defined 8112 18.08.2001 26.08.2001 multi-day sum gap defined 8112 05.10.2001 18.10.2001 multi-day sum gap defined 8112 19.04.2002 21.04.2002 multi-day sum gap defined 8112 02.08.2002 05.08.2002 multi-day sum gap defined 8112 26.11.2002 01.01.2003 multi-day sum/no precipitation gap defined 8112 08.07.2003 01.08.2003 multi-day sum/uncertain partition into single days gap defined 8112 20.12.2003 08.01.2004 multi-day sum gap defined 8112 09.07.2004 12.07.2004 multi-day sum gap defined 8112 09.08.2004 12.08.2004 multi-day sum gap defined 8112 15.08.2004 17.10.2004 multi-day sum/uncertain partition into single days gap defined 8112 01.12.2004 09.12.2004 multi-day sum gap defined station no. start end observation consequence 8112 30.04.2005 02.05.2005 uncertain partition into single days gap defined 8112 21.09.2005 26.09.2005 multi-day sum gap defined 8112 20.10.2005 22.10.2005 multi-day sum gap defined 8112 30.10.2005 01.11.2005 multi-day sum gap defined 8112 01.09.2006 06.09.2006 multi-day sum gap defined 8112 29.05.2008 02.06.2008 multi-day sum gap defined 8112 16.11.2008 23.12.2008 multi-day sum/uncertain partition into single days gap defined 8112 07.04.2009 09.04.2009 multi-day sum gap defined 8112 14.05.2009 16.05.2009 multi-day sum gap defined 8123 02.01.1998 15.06.1998 station not trustful - cause: multi-day sums gap defined 8123 08.09.1998 18.09.1998 multi-day sum gap defined 8123 08.11.1998 11.11.1998 multi-day sum gap defined 8123 09.12.1998 15.12.1998 multi-day sum/uncertain partition into single days gap defined 8123 14.01.1999 20.01.1999 multi-day sum/uncertain partition into single days gap defined 8123 06.02.1999 09.02.1999 multi-day sum/uncertain partition into single days gap defined 8123 29.10.1999 18.12.1999 multi-day sum/uncertain partition into single days gap defined 8123 01.09.2000 20.09.2000 multi-day sum gap defined 8123 18.11.2000 20.11.2000 multi-day sum gap defined 8123 29.03.2001 05.04.2001 multi-day sum gap defined 8123 28.05.2001 17.06.2001 multi-day sum gap defined 8123 06.12.2001 08.12.2001 multi-day sum gap defined 8123 02.02.2002 11.03.2002 multi-day sum/uncertain partition into single days gap defined 8123 22.08.2002 12.10.2002 multi-day sum gap defined 8123 01.11.2002 09.11.2002 multi-day sum gap defined 8123 19.12.2002 01.10.2005 station not trustful - cause: multi-day sums gap defined 8123 01/10/2005 31/10/2005 no precipitation gap defined 8206 18.10.2001 20.10.2001 multi-day sum gap defined 8206 26.12.2001 29.12.2001 multi-day sum gap defined 8206 23.02.2002 25.02.2002 multi-day sum gap defined 8206 22.05.2002 25.05.2002 multi-day sum gap defined 8206 03.06.2002 07.06.2002 multi-day sum gap defined 8206 02.12.2002 14.12.2002 multi-day sum gap defined 8206 09.02.2003 11.02.2003 multi-day sum gap defined 8206 03.03.2003 05.03.2003 multi-day sum gap defined 8206 23.07.2003 25.07.2003 multi-day sum gap defined 8206 29.07.2003 31.07.2003 multi-day sum gap defined 8206 09.09.2003 19.09.2003 multi-day sum gap defined 8206 20.09.2003 22.09.2003 multi-day sum gap defined 8206 19.11.2003 21.11.2003 multi-day sum gap defined 8206 12.01.2004 17.01.2004 multi-day sum gap defined 8206 04.02.2004 17.03.2004 multi-day sum gap defined 8206 19.04.2004 21.04.2004 multi-day sum gap defined 8206 08.06.2004 22.06.2004 multi-day sum gap defined 8206 11.07.2004 31.12.2009 multi-day sum gap defined 8212 25.04.2003 27.04.2003 multi-day sum gap defined 8212 17.08.2005 19.08.2005 multi-day sum gap defined 8212 16.05.2006 22.05.2006 multi-day sum gap defined 8212 10.12.2006 12.12.2006 multi-day sum gap defined 8212 29.12.2006 31.12.2006 multi-day sum gap defined 8212 22.12.2007 24.12.2007 uncertain partition into single days gap defined 8212 29.01.2009 01.02.2009 multi-day sum gap defined 8212 02.12.2009 04.12.2009 multi-day sum gap defined 8306 02.07.2002 08.07.2002 multi-day sum gap defined 8306 19.11.2002 21.11.2002 multi-day sum gap defined 8306 29.04.2003 01.05.2003 multi-day sum gap defined 8306 27.05.2003 01.06.2003 multi-day sum gap defined 8306 27.10.2003 31.10.2003 uncertain partition into single days gap defined 8306 16.04.2005 18.04.2005 multi-day sum gap defined 8306 20.10.2005 22.10.2005 multi-day sum gap defined 8306 16.02.2006 18.02.2006 multi-day sum gap defined 8306 16.09.2006 18.09.2006 multi-day sum gap defined 8306 29.06.2008 03.07.2008 uncertain partition into single days gap defined 8306 09.10.2009 10.10.2009 no precipitation gap defined 8312 11.09.1998 14.09.1998 multi-day sum gap defined 8312 13.10.1998 27.10.1998 multi-day sum gap defined 8312 21.04.1999 24.04.1999 multi-day sum gap defined 8312 10.09.1999 19.09.1999 multi-day sum gap defined station no. start end observation consequence 8312 22.10.1999 24.10.1999 multi-day sum gap defined 8312 26.11.1999 28.11.1999 multi-day sum gap defined 8312 25.12.1999 31.12.1999 multi-day sum/uncertain partition into single days gap defined 8312 28.01.2000 30.01.2000 multi-day sum/uncertain partition into single days gap defined 8312 25.05.2000 28.05.2000 multi-day sum gap defined 8312 03.06.2000 05.06.2000 multi-day sum gap defined 8312 02.11.2000 04.11.2000 multi-day sum gap defined 8312 15.12.2000 17.12.2000 multi-day sum gap defined 8312 09.02.2001 11.02.2001 multi-day sum gap defined 8312 19.03.2001 22.03.2001 multi-day sum gap defined 8312 15.05.2001 17.05.2001 multi-day sum gap defined 8312 15.06.2001 18.06.2001 multi-day sum gap defined 8312 06.08.2002 08.09.2002 multi-day sum gap defined 8312 29.07.2003 01.08.2003 uncertain partition into single days gap defined 8312 09.10.2003 13.10.2003 multi-day sum gap defined 8312 24.11.2003 26.11.2003 multi-day sum gap defined 8406 26.07.1998 29.07.1998 multi-day sum gap defined 8406 01.07.2005 04.07.2005 multi-day sum gap defined 8412 01/11/1998 30/11/1998 no precipitation gap defined 8412 11.01.1999 13.01.1999 multi-day sum gap defined 8412 23.02.1999 25.02.1999 multi-day sum gap defined 8412 17.09.1999 19.09.1999 multi-day sum gap defined 8506 25.11.2003 28.11.2003 multi-day sum gap defined 8506 22.06.2004 24.06.2004 multi-day sum gap defined 8506 20.11.2004 30.11.2004 multi-day sum gap defined 8506 15.01.2005 17.01.2005 multi-day sum gap defined 8506 14.09.2005 19.09.2005 multi-day sum gap defined 8506 29.11.2005 01.12.2005 multi-day sum gap defined 8506 18.04.2006 01.05.2006 multi-day sum gap defined 8506 15.08.2006 19.08.2006 multi-day sum gap defined 8506 12.09.2006 14.09.2006 multi-day sum gap defined 8506 27.11.2006 29.11.2006 multi-day sum gap defined 8506 23.02.2007 25.02.2007 multi-day sum gap defined 8506 12.06.2007 15.06.2007 multi-day sum gap defined 8506 12.07.2007 17.07.2007 multi-day sum gap defined 8506 14.08.2007 16.08.2007 multi-day sum gap defined 8512 05.05.1999 10.05.1999 multi-day sum gap defined 8512 13.05.2000 15.05.2000 multi-day sum gap defined 8512 28.09.2000 30.09.2000 multi-day sum gap defined 8512 19.10.2000 22.10.2000 uncertain partition into single days gap defined 8512 30.12.2000 01.01.2001 multi-day sum gap defined 8512 22.01.2002 28.01.2002 multi-day sum gap defined 8512 21.02.2002 24.02.2002 multi-day sum gap defined 8512 01/03/2002 31/03/2002 no precipitation gap defined 8512 01/06/2002 30/06/2002 no precipitation gap defined 8512 03.06.2003 05.06.2003 multi-day sum gap defined 8512 29.10.2003 31.10.2003 multi-day sum gap defined 8512 05.11.2003 07.11.2003 multi-day sum gap defined 8512 01.12.2003 04.12.2003 multi-day sum gap defined 8512 19.12.2003 21.12.2003 multi-day sum gap defined 8512 25.12.2003 29.12.2003 multi-day sum gap defined 8512 20.04.2004 07.05.2004 uncertain partition into single days gap defined 8512 26.06.2004 17.08.2004 multi-day sum gap defined 8512 10.12.2004 31.12.2004 multi-day sum gap defined 8512 13.04.2005 28.05.2005 multi-day sum gap defined 8512 01/06/2005 30/06/2005 no precipitation gap defined 8512 15.09.2005 08.10.2005 multi-day sum/uncertain partition into single days gap defined 8512 09.11.2005 15.11.2005 multi-day sum gap defined 8512 01/12/2005 31/12/2005 no precipitation gap defined 8512 01/03/2006 31/08/2006 no precipitation gap defined 8512 16.09.2006 18.09.2006 multi-day sum gap defined 8512 01/10/2006 31/10/2006 no precipitation gap defined 8512 01/12/2006 31/12/2006 no precipitation gap defined 8512 06.01.2007 09.01.2007 multi-day sum gap defined 8512 18.03.2007 20.03.2007 multi-day sum gap defined 8512 10.08.2007 01.11.2007 multi-day sum/uncertain partition into single days gap defined 8512 27.11.2007 29.11.2007 multi-day sum gap defined station no. start end observation consequence 8512 28.03.2008 01.04.2008 multi-day sum gap defined 8512 03.05.2008 25.06.2008 multi-day sum gap defined 8512 08.08.2008 10.08.2008 multi-day sum gap defined 8512 23.08.2008 25.08.2008 multi-day sum gap defined 8512 07.11.2008 09.11.2008 multi-day sum gap defined 8512 01/04/2009 30/04/2009 no precipitation gap defined 8512 16.06.2009 16.08.2009 multi-day sum gap defined 8612 09.12.1998 11.12.1998 multi-day sum gap defined 8612 13.10.2000 16.10.2000 multi-day sum gap defined 8612 15.12.2000 17.12.2000 multi-day sum gap defined 8612 14.04.2005 17.04.2005 multi-day sum gap defined 8612 12.03.2006 14.03.2006 multi-day sum gap defined 8612 26.06.2008 27.06.2008 no precipitation gap defined 8612 28.10.2008 31.10.2008 no precipitation gap defined 8612 22.08.2009 27.08.2009 multi-day sum gap defined 8612 08.11.2009 14.11.2009 multi-day sum/uncertain partition into single days gap defined 8623 23.06.1998 25.06.1998 uncertain partition into single days gap defined 8623 18.07.1998 21.07.1998 multi-day sum gap defined 8623 14.09.1998 19.09.1998 multi-day sum gap defined 8623 09.10.1998 11.10.1998 multi-day sum gap defined 8623 11.11.1998 13.11.1998 uncertain partition into single days gap defined 8623 22.12.1998 24.12.1998 multi-day sum gap defined 8623 28.05.1999 30.05.1999 multi-day sum gap defined 8623 03.06.1999 05.06.1999 multi-day sum gap defined 8623 12.07.1999 14.07.1999 multi-day sum gap defined 8623 06.10.1999 14.10.1999 multi-day sum gap defined 8623 08.03.2000 09.03.2000 very high precipitation gap defined 8623 13.09.2000 23.09.2000 multi-day sum gap defined 8623 23.12.2000 25.12.2000 uncertain partition into single days gap defined 8623 21.01.2001 31.01.2001 multi-day sum gap defined 8623 14.04.2001 16.04.2001 multi-day sum gap defined 8623 18.06.2001 20.06.2001 multi-day sum gap defined 8623 17.07.2001 23.07.2001 multi-day sum gap defined 8623 11.11.2001 13.11.2001 multi-day sum gap defined 8623 01.03.2002 01.04.2002 no precipitation gap defined 8623 28.04.2002 30.04.2002 multi-day sum gap defined 8623 02.06.2002 07.06.2002 multi-day sum gap defined 8623 19.07.2002 31.07.2002 multi-day sum gap defined 8623 25.10.2002 27.10.2002 multi-day sum gap defined 8623 20.07.2003 31.07.2003 multi-day sum gap defined 8623 22.12.2003 27.12.2003 multi-day sum gap defined 8623 10.07.2004 10.08.2004 multi-day sum gap defined 8623 23.09.2004 14.10.2004 multi-day sum/uncertain partition into single days gap defined 8623 17.11.2004 23.11.2004 multi-day sum gap defined 8623 14.12.2004 16.12.2004 multi-day sum gap defined 8623 21.01.2005 23.01.2005 multi-day sum gap defined 8623 13.04.2005 15.04.2005 multi-day sum gap defined 8623 01.06.2005 01.07.2005 no precipitation gap defined 8623 22.07.2005 30.07.2005 multi-day sum gap defined 8623 08.09.2005 11.09.2005 multi-day sum gap defined 8623 09.11.2005 12.11.2005 multi-day sum gap defined 8623 28.07.2006 01.08.2006 multi-day sum gap defined 8623 19.11.2006 21.11.2006 multi-day sum gap defined 8623 22.04.2007 25.04.2007 multi-day sum gap defined 8623 27.07.2007 29.07.2007 uncertain partition into single days gap defined 8623 16.09.2007 25.09.2007 multi-day sum gap defined 8623 23.01.2008 29.01.2008 multi-day sum gap defined 8623 02.03.2008 03.03.2008 very high precipitation gap defined 8623 06.11.2008 08.11.2008 multi-day sum gap defined 8623 26.03.2009 01.04.2009 multi-day sum gap defined 8623 16.05.2009 19.05.2009 multi-day sum gap defined 8623 03.07.2009 23.07.2009 multi-day sum gap defined 8623 05.11.2009 07.11.2009 multi-day sum gap defined 8623 17.11.2009 19.11.2009 multi-day sum gap defined 8623 25.12.2009 28.12.2009 multi-day sum gap defined 8706 04.09.2008 15.09.2008 multi-day sum/uncertain partition into single days gap defined 8706 22.04.2009 26.04.2009 uncertain partition into single days gap defined station no. start end observation consequence 8712 26.08.1999 28.08.1999 multi-day sum gap defined 8712 08.09.1999 09.09.1999 no precipitation gap defined 8712 15.02.2000 17.02.2000 multi-day sum gap defined 8712 01.02.2001 03.02.2001 uncertain partition into single days gap defined 8712 24.04.2001 30.04.2001 multi-day sum gap defined 8712 26.12.2001 29.12.2001 multi-day sum gap defined 8712 02.04.2002 21.04.2002 multi-day sum gap defined 8712 10.08.2002 13.08.2002 multi-day sum gap defined 8712 07.11.2002 15.11.2002 multi-day sum gap defined 8712 06.03.2003 08.03.2003 multi-day sum gap defined 8712 23.04.2003 25.04.2003 multi-day sum gap defined 8712 29.04.2003 01.05.2003 multi-day sum gap defined 8712 23.07.2003 27.07.2003 multi-day sum gap defined 8712 02.11.2003 04.11.2003 multi-day sum gap defined 8712 12.11.2003 14.11.2003 multi-day sum gap defined 8712 19.04.2004 12.06.2004 multi-day sum gap defined 8712 16.11.2004 19.11.2004 multi-day sum gap defined 8712 19.12.2004 24.12.2004 multi-day sum gap defined 8712 14.03.2005 16.03.2005 multi-day sum gap defined 8712 14.04.2005 24.04.2005 multi-day sum/uncertain partition into single days gap defined 8712 18.05.2005 20.05.2005 multi-day sum gap defined 8712 03.06.2005 05.06.2005 multi-day sum gap defined 8712 11.11.2005 13.11.2005 multi-day sum gap defined 8712 09.01.2006 11.01.2006 multi-day sum gap defined 8712 12.03.2006 14.03.2006 multi-day sum gap defined 8712 04.05.2006 06.05.2006 multi-day sum gap defined 8712 01/06/2006 31/07/2006 no precipitation gap defined 8712 27.08.2006 17.09.2006 multi-day sum gap defined 8712 26.10.2006 30.10.2006 multi-day sum gap defined 8712 11.03.2007 26.04.2007 multi-day sum gap defined 8712 14.06.2007 16.06.2007 multi-day sum gap defined 8712 21.06.2007 23.06.2007 multi-day sum gap defined 8712 13.07.2007 18.07.2007 multi-day sum gap defined 8712 01/08/2007 31/08/2007 no precipitation gap defined 8712 03.12.2007 11.12.2007 multi-day sum gap defined 8712 11.04.2008 28.04.2008 multi-day sum gap defined 8712 17.06.2008 19.06.2008 multi-day sum gap defined 8712 01/11/2008 30/11/2008 no precipitation gap defined 8712 01.12.2008 13.12.2008 multi-day sum gap defined 8712 03.03.2009 05.03.2009 multi-day sum gap defined 8712 10.04.2009 15.04.2009 multi-day sum/uncertain partition into single days gap defined 8712 15.05.2009 30.06.2009 multi-day sum gap defined 8712 15.07.2009 20.07.2009 multi-day sum gap defined 8712 15.08.2009 07.10.2009 multi-day sum/no precipitation gap defined 8712 02.12.2009 05.12.2009 multi-day sum gap defined 8712 09.12.2009 29.12.2009 multi-day sum gap defined 8812 04.07.2000 06.07.2000 multi-day sum gap defined 8812 06.08.2000 08.08.2000 multi-day sum gap defined 8812 06.12.2000 08.12.2000 multi-day sum gap defined 8812 18.12.2000 21.12.2000 multi-day sum gap defined 8812 01/06/2001 31/03/2002 no precipitation gap defined 8812 30.05.2003 02.06.2003 multi-day sum gap defined 8812 10.01.2004 12.01.2004 multi-day sum gap defined 8812 01/01/2005 31/01/2005 no precipitation gap defined 8812 28.07.2005 31.07.2005 multi-day sum gap defined 8823 13.06.1998 15.06.1998 multi-day sum gap defined 8823 14.01.1999 16.01.1999 multi-day sum gap defined 8823 20.09.1999 22.09.1999 multi-day sum gap defined 8823 15.02.2000 17.02.2000 multi-day sum gap defined 8823 12.04.2000 14.04.2000 multi-day sum gap defined 8823 15.12.2000 18.12.2000 multi-day sum gap defined 8823 01.01.2001 03.01.2001 multi-day sum gap defined 8823 25.01.2001 28.01.2001 multi-day sum gap defined 8823 25.02.2001 28.02.2001 multi-day sum gap defined 8823 26.03.2001 06.04.2001 multi-day sum gap defined 8823 27.05.2001 29.05.2001 multi-day sum gap defined 8823 01/06/2001 30/06/2001 no precipitation gap defined station no. start end observation consequence 8823 09.07.2001 14.07.2001 multi-day sum/uncertain partition into single days gap defined 8823 05.08.2001 07.08.2001 multi-day sum gap defined 8823 08.02.2002 10.02.2002 multi-day sum gap defined 8823 25.04.2002 14.05.2002 multi-day sum gap defined 8823 01/06/2002 30/06/2002 no precipitation gap defined 8823 07.07.2002 13.07.2002 multi-day sum gap defined 8823 01.08.2002 01.10.2002 no precipitation gap defined 8823 24.10.2002 28.10.2002 multi-day sum gap defined 8823 07.11.2002 09.11.2002 uncertain partition into single days gap defined 8823 27.12.2002 31.12.2002 multi-day sum/uncertain partition into single days gap defined 8823 01/05/2003 31/05/2003 no precipitation gap defined 8823 01.07.2003 01.08.2003 no precipitation gap defined 8823 18.09.2003 23.09.2003 multi-day sum gap defined 8823 22.10.2003 16.12.2003 multi-day sum gap defined 8823 03.02.2004 05.02.2004 multi-day sum gap defined 8823 02.03.2004 05.03.2004 multi-day sum gap defined 8823 17.04.2004 19.04.2004 multi-day sum gap defined 8823 10.06.2004 20.06.2004 multi-day sum/uncertain partition into single days gap defined 8823 01.07.2004 01.08.2004 no precipitation gap defined 8823 01/09/2004 30/09/2004 no precipitation gap defined 8823 22.10.2004 25.10.2004 multi-day sum gap defined 8823 17.11.2004 19.11.2004 multi-day sum gap defined 8823 27.12.2004 29.12.2004 multi-day sum gap defined 8823 06.02.2005 08.02.2005 multi-day sum gap defined 8823 23.02.2005 25.02.2005 multi-day sum gap defined 8823 01.07.2005 01.08.2005 no precipitation gap defined 8823 01.09.2005 01.10.2005 no precipitation gap defined 8823 01.11.2005 01.12.2005 no precipitation gap defined 8823 16.03.2006 19.03.2006 multi-day sum gap defined 8823 25.05.2006 27.05.2006 multi-day sum gap defined 8823 29.06.2006 01.07.2006 multi-day sum gap defined 8823 10.11.2006 20.11.2006 multi-day sum/uncertain partition into single days gap defined 8823 01/12/2006 31/12/2006 no precipitation gap defined 8823 01/02/2007 28/02/2007 no precipitation gap defined 8823 11.06.2007 14.06.2007 multi-day sum gap defined 8823 13.08.2007 15.08.2007 uncertain partition into single days gap defined 8823 01.09.2007 01.10.2007 no precipitation gap defined 8823 01.11.2007 01.12.2007 no precipitation gap defined 8823 27.12.2007 29.12.2007 multi-day sum gap defined 8823 01/01/2008 31/01/2008 no precipitation gap defined 8823 31.01.2008 31.12.2009 multi-day sum/uncertain partition into single days gap defined 8912 17.04.2004 19.04.2004 multi-day sum gap defined 8912 28.09.2004 01.10.2004 multi-day sum gap defined 8912 19.11.2004 21.11.2004 multi-day sum gap defined 8912 14.04.2005 17.04.2005 multi-day sum gap defined 8912 22.05.2005 24.05.2005 multi-day sum gap defined 8912 17.11.2005 19.11.2005 multi-day sum gap defined 8912 16.01.2006 21.01.2006 multi-day sum gap defined 8912 16.01.2007 18.01.2007 multi-day sum gap defined 8912 15.10.2007 24.10.2007 multi-day sum gap defined 8912 27.11.2007 29.11.2007 multi-day sum gap defined 8912 02.02.2008 04.02.2008 multi-day sum gap defined 8912 13.09.2008 15.09.2008 uncertain partition into single days gap defined 8912 08.11.2008 10.11.2008 multi-day sum gap defined 8912 25.03.2009 15.04.2009 uncertain partition into single days gap defined 8912 05.10.2009 07.10.2009 multi-day sum gap defined 8912 23.12.2009 31.12.2009 multi-day sum gap defined 8923 31.08.1998 02.09.1998 multi-day sum gap defined 8923 11.12.1998 13.12.1998 multi-day sum gap defined 8923 20.05.1999 25.05.1999 multi-day sum gap defined 8923 01.07.1999 01.08.1999 no precipitation gap defined 8923 07.02.2000 11.02.2000 multi-day sum gap defined 9023 02.01.1998 08.01.1998 multi-day sum gap defined 9023 01.09.1998 01.10.1998 no precipitation gap defined 9023 09.10.1998 13.10.1998 uncertain partition into single days gap defined 9112 20.01.2007 22.01.2007 multi-day sum gap defined 9112 21.05.2008 05.06.2008 multi-day sum gap defined station no. start end observation consequence 9112 26.11.2008 28.11.2008 multi-day sum gap defined 9112 14.05.2009 16.05.2009 multi-day sum gap defined 9112 16.06.2009 18.06.2009 multi-day sum gap defined 9112 05.10.2009 10.10.2009 multi-day sum/uncertain partition into single days gap defined 9112 17.12.2009 31.12.2009 multi-day sum gap defined 9123 20.06.1998 01.08.1998 multi-day sum gap defined 9123 11.11.1998 15.11.1998 multi-day sum gap defined 9123 22.11.1998 25.11.1998 multi-day sum gap defined 9123 03.01.1999 05.01.1999 multi-day sum gap defined 9123 27.05.1999 29.05.1999 multi-day sum gap defined 9123 19.06.1999 21.06.1999 multi-day sum gap defined 9123 22.09.1999 24.09.1999 multi-day sum gap defined 9123 25.12.1999 27.12.1999 multi-day sum gap defined 9123 07.01.2000 09.01.2000 multi-day sum gap defined 9123 25.02.2000 28.02.2000 multi-day sum gap defined 9123 24.05.2000 26.05.2000 multi-day sum gap defined 9123 18.08.2000 22.08.2000 multi-day sum gap defined 9123 28.09.2000 02.06.2001 multi-day sum/uncertain partition into single days gap defined 9123 08.08.2001 08.09.2001 multi-day sum/uncertain partition into single days gap defined 9123 23.01.2002 12.03.2002 multi-day sum/uncertain partition into single days gap defined 9123 28.05.2002 04.07.2002 multi-day sum/uncertain partition into single days gap defined 9123 29.08.2002 31.08.2002 multi-day sum gap defined 9123 01/10/2002 30/11/2002 no precipitation gap defined 9123 08.12.2002 21.05.2003 multi-day sum/uncertain partition into single days gap defined 9123 01.07.2003 01.08.2003 no precipitation gap defined 9123 28.08.2003 30.08.2003 multi-day sum gap defined 9123 30.10.2003 01.11.2003 multi-day sum/uncertain partition into single days gap defined 9123 14.11.2003 17.11.2003 multi-day sum/uncertain partition into single days gap defined 9123 11.03.2004 14.03.2004 multi-day sum gap defined 9123 20.03.2004 22.03.2004 multi-day sum gap defined 9123 18.06.2004 01.08.2004 multi-day sum/uncertain partition into single days gap defined 9123 01/08/2004 31/08/2004 no precipitation gap defined 9123 17.11.2004 21.11.2004 multi-day sum gap defined 9123 24.12.2004 26.12.2004 multi-day sum gap defined 9123 04.02.2005 16.03.2005 multi-day sum/uncertain partition into single days gap defined 9123 16.04.2005 20.02.2006 multi-day sum/uncertain partition into single days gap defined 9123 12.04.2006 31.08.2006 uncertain partition into single days gap defined 9212 17.12.2009 30.12.2009 multi-day sum gap defined 9223 25.06.1998 27.07.1998 multi-day sum gap defined 9223 05.07.1999 30.07.1999 multi-day sum gap defined 9223 01.10.1999 05.10.1999 multi-day sum gap defined 9223 27.07.2000 08.08.2000 multi-day sum gap defined 9223 30.07.2001 10.08.2001 multi-day sum gap defined 9223 04.07.2002 08.07.2002 multi-day sum gap defined 9223 18.08.2006 20.08.2006 multi-day sum gap defined 9312 03.12.2008 05.12.2008 multi-day sum gap defined 9312 26.05.2009 28.05.2009 multi-day sum gap defined 9423 01.09.1999 31.10.1999 station not trustful - cause: multi-day sums gap defined 9623 01.03.2004 30.06.2005 station not trustful - cause: multi-day sums gap defined 9813 01.01.2001 31.12.2009 no precipitation gap defined 9907 02.01.1998 30.11.2009 no precipitation gap defined
APPENDIX B
RAIN GAUGE STATIONS USED FOR ADJUSTMENT
B1 STATION_NO file name NAME CATCHMENT AREA HEIGHT XY 1004H n1004H.uvf Roches_Point_hourly 4 SE 43 183100 60100 1075H n1075H.uvf ROCHES_POINT_2_hourly 4 SE 40 182779 60625 1475H n1475H.uvf GURTEEN_hourly 19 SE 75 199467 198376 2437H n2437H.uvf CLONES_hourly 37 E 89 250000 326300 2615H n2615H.uvf Rosslare_hourly 15 E 26 313700 112200 2922H n2922H.uvf Mullingar_2_hourly 22 E 101 242000 254300 3613H n3613H.uvf Kilkenny_hourly 13 SE 65 249400 157400 3723H n3723H.uvf CASEMENT AERODROME_hourly 23 E 94 304100 229500 375H n375H.uvf OAK_PARK_hourly 14 E 62 273000 179500 3904H n3904H.uvf Cork_Airport_hourly 4 SE 155 166500 66200 475H n475H.uvf JOHNSTOWN_CASTLE_hourly 15 E 52 302300 116600 4919H n4919H.uvf Birr_hourly 19 SE 72 207400 204400 518H n518H.uvf Shannon_Airport_hourly 18 E 4 137900 160300 532H n532H.uvf Dublin_Airport_hourly 32 E 71 316900 243400 675H n675H.uvf BALLYHAISE_hourly 37 E 78 245200 311600 875H n875H.uvf MULLINGAR_hourly 22 E 101 243000 254300 108 n0108.uvf FOULKESMILLS_LONGRAIGUE 8 SE 71 284100 118400 332 n0332.uvf SKERRIES_MILVERTON_HALL 32 E 64 323100 259300 422 n0422.uvf TYRRELLSPASS 22 E 101 240100 235500 538 n0538.uvf DUNDALK_ANNASKEAGH_W_W 38 E 61 308000 312800 638 n0638.uvf NOBBER 38 E 60 283000 286500 707 n0707.uvf BELLELAKE_FILTERSTN 7 SE 34 266800 105200 737 n0737.uvf BALLYHAISE_AGR_COLL 37 E 67 245200 311600 820 n0820.uvf MONEYSTOWN 20 E 207 319200 195900 907 n0907.uvf MONATRAYEAST 7 SE 55 214000 76600 908 n0908.uvf DUNCANNON 8 SE 34 274300 107500 915 n0915.uvf JOHNSTOWN_CASTLE 15 E 49 302300 116600 931 n0931.uvf KELLS_HEADFORT 31 E 67 276100 276900 1007 n1007.uvf GRANGE_BALLYLANGADON 7 SE 101 217200 82700 1008 n1008.uvf TACUMSHANE 8 SE 24 307700 107500 1020 n1020.uvf ARKLOW_W_W 20 E 34 321900 173000 1024 n1024.uvf ROUNDWOOD_FILTER_BEDS 24 E 195 321600 201800 1106 n1106.uvf CAPPOQUIN_MT_MELLERAY 6 SE 213 209500 104100 1107 n1107.uvf FENOR_ISLANDTARSNEY 7 SE 73 254300 100300 1108 n1108.uvf BANNOW 8 SE 15 282900 107200 1116 n1116.uvf CAHORE_KILMICHAEL_HOUSE 16 E 30 321300 147100 1207 n1207.uvf TRAMORE_KNOCKANDUFF 7 SE 55 257200 101700 1208 n1208.uvf TAGHMON_KILGARVAN 8 SE 58 288800 122900 1216 n1216.uvf GOREY_TREATMENT_WORKS 16 E 40 315900 158800 1232 n1232.uvf KINSALEY_AGR_RES_STN 32 E 19 321500 242900 1237 n1237.uvf CARRIGALLEN_G_S 37 E 88 223100 302900 1307 n1307.uvf WATERFORDAIRPORT 7 SE 30 262800 104400 1308 n1308.uvf OLDROSS_DUNANORE 8 SE 93 278500 127500 1332 n1332.uvf MALAHIDE_CASTLE 32 E 18 322200 245400 1338 n1338.uvf OMEATH 38 E 12 314200 316600 1407 n1407.uvf DUNGARVAN_CARRIGLEA 7 SE 18 221900 92800 1416 n1416.uvf MONAMOLIN 16 E 91 311400 145500 1420 n1420.uvf GLENMACNASS 20 E 238 311700 202300 1507 n1507.uvf KILMACTHOMAS_GRAIGUERUSH 7 SE 88 235400 106800 1516 n1516.uvf KILDERMOT 16 E 53 320800 161200 1616 n1616.uvf COOLGREANEY_ST_MARTINS 16 E 67 318700 169700 1637 n1637.uvf KESHCARRIGAN_G_S 37 E 69 203800 307700 1707 n1707.uvf Fenor_Tramore 7 SE 32 261600 98100 1712 n1712.uvf KNOCKADERRYRESV_NO_1 12 SE 71 249800 106700 1716 n1716.uvf ARDAMINE_HOUSE_MIDDLETOWN_HSE 16 E 72 319300 155000 1719 n1719.uvf BANAGHER_CANALHSE 19 SE 37 200400 216000 1723 n1723.uvf DUBLIN_PHOENIX_PARK 23 E 49 310000 236100 1807 n1807.uvf STRADBALLY 7 SE 76 236500 98200 1812 n1812.uvf WATERFORD_TYCOR 12 SE 49 259400 111600 1830 n1830.uvf GRANARD_SPRINGSTOWN 30 E 70 238100 280900 1838 n1838.uvf ARDEE_ST_BRIGID_S_HOSP 38 E 32 295700 290400 1923 n1923.uvf GLENASMOLE_D_C_W_W 23 E 158 309000 222200 2012 n2012.uvf CASHEL_BALLINAMONA 12 SE 80 204900 140000 2030 n2030.uvf BALLYJAMESDUFF_KILCULLY 30 E 125 252600 290200 2037 n2037.uvf CUILCAGH_MTNS 37 E 290 213000 324100 2038 n2038.uvf CARRICKMACROSS_DUNOGE 38 E 88 281800 303900 2112 n2112.uvf CLONMEL_BALLINGARRANE 12 SE 73 217100 119800 2115 n2115.uvf HACKETSTOWN_VOC_SCH 15 E 189 297500 179900 2230 n2230.uvf COOLE_COOLURE 30 E 73 241500 269400 2322 n2322.uvf BOORA 22 E 58 218000 219700 2324 n2324.uvf ENNISKERRY_KILMALIN 24 E 274 319800 217700 2332 n2332.uvf BELLEWSTOWN_COLLIERSTOWN 32 E 123 308400 267000 2411 n2411.uvf KILMALLOCK_G_S 11 SE 89 160900 127400 2415 n2415.uvf GLEN_IMAAL_FOR_STN 15 E 213 297200 194600 2420 n2420.uvf OLDBRIDGE_OAKVIEW 20 E 335 315300 201100 2423 n2423.uvf DUBLIN_CLONTARF 23 E 5 318100 236300 2432 n2432.uvf RATOATH 32 E 91 302200 251400 2520 n2520.uvf TINAHELY_MUCKLAGH 20 E 107 308000 174800 2523 n2523.uvf DUBLIN_RINGSEND 23 E 7 318900 233900 2531 n2531.uvf NAVAN 31 E 50 286100 267200 2532 n2532.uvf DUNSHAUGHLIN_LAGORE 32 E 105 298800 253500 2620 n2620.uvf LARAGH_TROOPERSTOWN 20 E 162 315800 197000 2632 n2632.uvf FAIRYHOUSE_RACECOURSE 32 E 91 302000 249400 2638 n2638.uvf ARDEE_BOHARNAMOE 38 E 31 294100 290200 2719 n2719.uvf KILTORMER 19 SE 78 181900 221000 2720 n2720.uvf ARKLOW_COOLADANGAN_HOUSE 20 E 61 322400 171300 2737 n2737.uvf ROCKCORRY 37 E 99 264600 319000 2824 n2824.uvf GLENEALY_KILMACURRAGH_PARK 24 E 122 324500 188100 2924 n2924.uvf BALLYMAN_BRAY 24 E 171 323300 219900 2931 n2931.uvf WARRENSTOWN 31 E 90 292100 253500 2938 n2938.uvf MELLIFONT_ABBEY 38 E 183 300300 283200 3015 n3015.uvf CLONROCHE 15 E 116 285300 132000 3037 n3037.uvf SWANLINBAR 37 E 69 219400 327500 3038 n3038.uvf KINGSCOURT_GYPSUM 38 E 67 278800 292200 3124 n3124.uvf ASHFORD_GLANMORE_GARDENS 24 E 110 324700 198500 3138 n3138.uvf CASTLEBLAYNEY_DRUMGRISTON 38 E 117 285600 316800 3222 n3222.uvf CLONASLEE_WATERWORKS_2 22 E 131 231700 210300 3224 n3224.uvf WICKLOW_BALLINTESKIN 24 E 46 329800 190200 3238 n3238.uvf CASTLEBELLINGHAM_LYNNS 38 E 21 307500 295000 3322 n3322.uvf BELMONT_MILLS 22 E 46 206800 221800 3323 n3323.uvf POULAPHUCA_GEN_STN 23 E 174 294500 208600 3324 n3324.uvf ARKLOW_BALLYRICHARD_HOUSE 24 E 70 326100 177500 3331 n3331.uvf TIMAHOE_SOUTH 31 E 88 278700 229200 3338 n3338.uvf CLOGHER_HEAD_PORT 38 E 27 313300 289500 3422 n3422.uvf GEASHILL 22 E 85 245400 220900 3431 n3431.uvf DERRYGREENAGH 31 E 90 249300 238200 3438 n3438.uvf RIVERSTOWN_GLENMORE_UPPER 38 E 165 315500 311000 3513 n3513.uvf SLIEVEBLOOMMTNS_NEALSTOWN 13 SE 219 219900 193600 3522 n3522.uvf HORSELEAP 22 E 72 228000 237300 3524 n3524.uvf BALLYEDMONDUFF_HOUSE 24 E 335 318500 221800 3538 n3538.uvf TOGHER_BARMEATH_CASTLE 38 E 79 309700 287600 3606 n3606.uvf FERMOY_MOOREPARK 6 SE 55 181900 101400 3613 n3613.uvf Kilkenny 13 SE 66 249400 157400 3623 n3623.uvf NAAS_OSBERSTOWN 23 E 84 287300 220000 3624 n3624.uvf KILCOOLE_TREATMENT_PLANT 24 E 9 330500 207400 3637 n3637.uvf NEWBLISS_DRUMSHANNON 37 E 137 257300 323900 3706 n3706.uvf RATHLUIRC_FOR_STN 6 SE 131 157300 118500 3731 n3731.uvf DUNSANY_GRANGE 31 E 90 288800 252800 3738 n3738.uvf DUNDALK_KNOCKBRIDGE 38 E 59 301300 303700 3823 n3823.uvf BALLYMORE_EUSTACE_D_C_W_W 23 E 172 293300 209200 3824 n3824.uvf BALLYNAHINCH 24 E 287 322800 204500 3831 n3831.uvf DROGHEDA_KILLINEER 31 E 47 307300 277400 3838 n3838.uvf CASTLEBLAYNEY_CARRICKASLANE 38 E 122 280600 324400 3923 n3923.uvf DUBLIN_MERRION_SQUARE 23 E 13 316400 233500 3924 n3924.uvf ASHFORD_CRONYKEERY 24 E 15 329300 198800 3937 n3937.uvf AUGHNASHEELAN_MISKAWN 37 E 155 208500 315100 4006 n4006.uvf KNOCKANORE 6 SE 122 207500 89100 4013 n4013.uvf COON 13 SE 178 259600 170600 4031 n4031.uvf BAILIEBORO_DUNEENA 31 E 158 264600 299900 4037 n4037.uvf LOUGH_GOWNA_GLENBROOK 37 E 91 231200 292100 4106 n4106.uvf YOUGHAL_GLENDINEW_W 6 SE 107 206400 83900 4113 n4113.uvf CALLAN_MOONARCHE 13 SE 79 239400 142700 4137 n4137.uvf CAVAN_DRUMCONNICK 37 E 88 239800 305300 4213 n4213.uvf PARKNAHOWNCULLAHILL 13 SE 110 234300 173900 4215 n4215.uvf BUNCLODY_CORRAGH 15 E 116 294300 159900 4223 n4223.uvf LEIXLIP_GEN_STN 23 E 42 300700 235800 4237 n4237.uvf NEWBLISS_CRAPPAGH 37 E 113 258600 321500 4331 n4331.uvf RATHWIRE 31 E 98 257000 251300 4337 n4337.uvf CAVAN_LORETO_COLLEGE 37 E 64 241200 307200 4413 n4413.uvf TULLAROAN_BALLYBEAGH 13 SE 299 233300 157800 4415 n4415.uvf TULLOW_WATERWORKS 15 E 76 284700 173400 4512 n4512.uvf RATHGORMACK 12 SE 160 233800 117400 4513 n4513.uvf KILKENNY_LAVISTOWNHOUSE_2 13 SE 52 254300 154300 4514 n4514.uvf JOHN_F_KENNEDY_PARK 14 E 70 272300 118900 4515 n4515.uvf TULLOW_ARDOYNE_GLEBE 15 E 79 288200 169800 4531 n4531.uvf NAVAN_TARA_MINES 31 E 52 284700 268400 4537 n4537.uvf KILLESHANDRA_TOWN_LAKE 37 E 61 231100 308200 4612 n4612.uvf CAHIR_VOC_SCH 12 SE 53 205400 125200 4615 n4615.uvf BOOLAVOGUE_KNOCKAVOCCA 15 E 73 305100 146200 4631 n4631.uvf KINNEGAD_MULLINGAR_ROAD 31 E 82 259000 245900 4637 n4637.uvf BALLYCONNELL_MULLAGHDUFF 37 E 84 228200 317700 4713 n4713.uvf ABBEYLEIX 13 SE 104 243800 184800 4715 n4715.uvf FERNS_3 15 E 61 298300 154600 4719 n4719.uvf NEWPORT_KILLOSCULLY 19 SE 180 178000 168400 4811 n4811.uvf PATRICKSWELL_DOONEEN 11 SE 27 154500 149600 4813 n4813.uvf CALLAN_MALLARDSTOWN 13 SE 70 244100 142300 4815 n4815.uvf WEXFORD_WILDFOWL_RESERVE 15 E 1 307600 123900 4819 n4819.uvf SILVERMINESMTNS_CURREENY 19 SE 312 190100 164700 4831 n4831.uvf CORBETSTOWN 31 E 80 255500 240000 4906 n4906.uvf CONNA_CARRIGEENHILL 6 SE 70 195500 95500 4913 n4913.uvf THOMASTOWN_MT_JULIET 13 SE 49 254900 141500 4915 n4915.uvf CAIM_MONGLASS 15 E 61 291000 141300 4919 n4919.uvf Birr 19 SE 73 207400 204400 5012 n5012.uvf BANSHA_AHERLOWW_W 12 SE 128 191700 128400 5013 n5013.uvf DUNGARVAN_CASTLEFIELD 13 SE 75 259700 148500 5015 n5015.uvf CARNEW_CRONYHORN 15 E 76 300500 163900 5031 n5031.uvf WILKINSTOWN_YELLOW_RIVER 31 E 61 284100 276100 5037 n5037.uvf BELTURBET_NAUGHAN 37 E 76 236700 320700 5114 n5114.uvf ATHY_ST_JOSEPH_S_TERRACE 14 E 61 268100 194500 5131 n5131.uvf KILSKYRE_ROBINSTOWN 31 E 87 268500 272000 5213 n5213.uvf BALLACOLLA_FARRENHOUSE 13 SE 116 235200 184800 5214 n5214.uvf COOLGREANY_CASTLEWARREN 14 E 262 259600 162300 5215 n5215.uvf CASTLEBRIDGE_SEWAGE_WORKS 15 E 9 305000 126800 5231 n5231.uvf SLANE_ARDCALF 31 E 125 294600 277400 5306 n5306.uvf MOUNTRUSSELL 6 SE 195 161300 119800 5313 n5313.uvf BALLYROAN_OATLANDS 13 SE 134 245100 186000 5323 n5323.uvf NAAS_C_B_S 23 E 98 289600 219500 5331 n5331.uvf DELVIN_CASTLE_G_C 31 E 91 259100 262900 5406 n5406.uvf GALTEEMOUNTAINS_SKEHEENARINKY 6 SE 335 188700 119500 5411 n5411.uvf KILFINNANE_EDUCATIONCENTRE 11 SE 165 168000 123200 5414 n5414.uvf CASTLEDERMOT_KILKEA_HOUSE 14 E 85 274500 187700 5415 n5415.uvf CLONROCHE_KNOXTOWN 15 E 117 282100 133200 5419 n5419.uvf NEWPORT_VOC_SCH 19 SE 61 172600 162600 5431 n5431.uvf VIRGINIA_MURMOD 31 E 122 260600 289100 5437 n5437.uvf SHANTONAGH_TOOA 37 E 152 275300 312300 5506 n5506.uvf BALLINAMULT_DOON 6 SE 168 217200 106800 5512 n5512.uvf CLONMEL_REDMONDSTOWN 12 SE 64 223400 124700 5514 n5514.uvf PAULSTOWN_SHANKHILL_CASTLE 14 E 63 266200 160000 5523 n5523.uvf GLENASMOLE_CASTLEKELLY 23 E 183 310200 220800 5531 n5531.uvf MOYNALTY_SHANCARNAN 31 E 91 271700 283700 5537 n5537.uvf CLONES_DUNSEARK 37 E 137 251900 322200 5613 n5613.uvf KILKENNY_Greenshill 13 SE 61 250500 156900 5623 n5623.uvf GLENASMOLE_SUPT_S_LODGE 23 E 152 309200 222200 5631 n5631.uvf ENFIELD_NEWCASTLE_HOUSE 31 E 91 275700 241600 5637 n5637.uvf TULLYCO_ARTONAGH 37 E 140 254200 306300 5714 n5714.uvf NEW_ROSS_W_W 14 E 64 272400 128300 5811 n5811.uvf MEANUS 11 SE 50 158400 140200 5819 n5819.uvf NENAGH_CONNOLLYPARK 19 SE 55 187200 180000 5837 n5837.uvf KILLESHANDRA_BAWN 37 E 72 230000 306900 5912 n5912.uvf PILTOWN_KILDALTONAGR_COLL 12 SE 18 247700 122400 5914 n5914.uvf BAGENALSTOWN_KILDREENAGH 14 E 128 274900 163400 5919 n5919.uvf CASTLECONNELL 19 SE 37 167800 162300 6019 n6019.uvf KILLALOEDOCKS 19 SE 40 169700 173200 6114 n6114.uvf POLLMOUNTY_FISH_FARM 14 E 24 274600 135600 6119 n6119.uvf ROSCREA_NEWROAD 19 SE 111 214700 190800 6312 n6312.uvf MULLINAHONE_KILLAGHY 12 SE 76 233400 140900 6314 n6314.uvf EDENDERRY_BALLINLA 14 E 91 258300 231600 6319 n6319.uvf BANAGHERMALTINGCOMPANY 19 SE 46 201500 213600 6323 n6323.uvf MILLTOWN_GOLF_CLUB 23 E 30 316500 229900 6406 n6406.uvf TALLOWKILMORE 6 SE 104 201200 91300 6412 n6412.uvf CAHIRPARKII 12 SE 61 204500 122800 6414 n6414.uvf ATHY_CHANTERLANDS 14 E 61 268800 193200 6419 n6419.uvf COOGALOWERDOON 19 SE 88 181500 150800 6512 n6512.uvf DUNDRUM_STOOKW_W 12 SE 183 200300 153900 6514 n6514.uvf GOWRAN 14 E 55 262900 153200 6614 n6614.uvf GRANGE_CON 14 E 157 285400 195500 6619 n6619.uvf CLOUGHJORDAN_DEERPARK 19 SE 107 197900 188800 6623 n6623.uvf BALLYBODEN 23 E 107 313100 226500 6712 n6712.uvf LITTLETONIIB_NAM 12 SE 126 220400 151100 6714 n6714.uvf KILBERRY_2 14 E 61 267300 198500 6719 n6719.uvf LIMERICKJUNCTION_SOLOHEAD 19 SE 101 186000 139400 6812 n6812.uvf CARRICK_ON_SUIR_2 12 SE 18 240500 121200 6814 n6814.uvf GRAIGUENAMANAGH_BALLYOGAN_HOUSE 14 E 30 272000 140200 6912 n6912.uvf MULLINAVAT_GLENDONNELL 12 SE 94 257500 123800 6914 n6914.uvf GARRYHILL_MILLTOWN 14 E 107 278600 158700 6919 n6919.uvf NEWPORT_COOLE 19 SE 72 172900 163800 7014 n7014.uvf ATHY_LEVITSTOWN 14 E 61 270900 187900 7112 n7112.uvf FETHARD_PARSONSHILL 12 SE 165 223800 140300 7114 n7114.uvf MOONE_STERRICK_HALL 14 E 107 277700 193700 7412 n7412.uvf ADAMSTOWN 12 SE 46 252400 108800 7512 n7512.uvf CASHEL_BALLYKELLY 12 SE 110 210000 144800 7606 n7606.uvf GALTEEW_W_LOUGHANANNA 6 SE 209 187400 118000 7612 n7612.uvf CASHEL_BALLYDOYLEHOUSE 12 SE 123 211900 134400 7806 n7806.uvf MITCHELSTOWMN_CORKSTREET 6 SE 91 181700 112800 7812 n7812.uvf CLOGHEEN_CASTLEGRACE 12 SE 46 203300 114300 7906 n7906.uvf BALLYHOOLY_CASTLEBLAGH 6 SE 140 171900 97600 8006 n8006.uvf GLENCAIRN_TOURTANEHOUSE 6 SE 34 203300 96700 8012 n8012.uvf DUNDRUM_GARRYDUFF 12 SE 94 196000 145200 8106 n8106.uvf CAPPOQUIN_STATIONHOUSE 6 SE 30 210600 99200 8112 n8112.uvf CLONOULTY_CLOGHER 12 SE 82 204400 152200 8123 n8123.uvf CELBRIDGE_ARDRASS_HOUSE 23 E 62 297200 233500 8206 n8206.uvf MITCHELSTOWN_GLENATLUCKEY 6 SE 168 183000 109700 8212 n8212.uvf PORTLAW_MAYFIELD_2 12 SE 8 247700 115700 8306 n8306.uvf SHANBALLYMORE 6 SE 75 167200 107600 8312 n8312.uvf CASHEL_CASTLEBLAKE 12 SE 96 213600 132800 8406 n8406.uvf CONNA_CASTLEVIEW 6 SE 30 195600 94500 8412 n8412.uvf CLONMEL_ORCHARDSTOWN 12 SE 69 219100 127200 8506 n8506.uvf LISMORE 6 SE 53 204800 98000 8512 n8512.uvf FAITHLEGG_GOLFCLUB 12 SE 30 266800 111700 8612 n8612.uvf ARDFINNAN_GARRYDUFF 12 SE 56 207800 115600 8623 n8623.uvf BLESSINGTON_HEMPSTOWN 23 E 213 299900 217400 8706 n8706.uvf kilworthy_kilally 6 SE 108 182300 104000 8712 n8712.uvf THURLESRACECOURSE 12 SE 110 211500 159500 8812 n8812.uvf SLIEVENAMONG_C 12 SE 67 220100 130300 8823 n8823.uvf STRAFFAN_TURNINGS 23 E 70 291700 227000 8912 n8912.uvf PORTLAW_BALLYVALLICAN 12 SE 85 243000 113600 8923 n8923.uvf NAAS_NEWLAND_NORTH 23 E 93 286400 217100 9023 n9023.uvf DUNDRUM_DROMARTIN 23 E 64 317700 227700 9112 n9112.uvf KILSHEELAN 12 SE 72 228900 123200 9123 n9123.uvf BARROCKSTOWN 23 E 84 292100 242000 9212 n9212.uvf CLONMELRACECOURSE 12 SE 72 221700 123800 9223 n9223.uvf DUN_LAOGHAIRE 23 E 30 324500 227800 9312 n9312.uvf CAHIR_TOUREEN 12 SE 72 200700 128700
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APPENDIX C
RATING REVIEW
LEIXLIP (09001)
The gauging station at Leixlip (09001) is located on the River Ryewater in Leixlip, County Kildare approximately 800m upstream of its confluence with the River Liffey. The staff gauge and recorder house are located on the left hand bank of an open channel section downstream of the Distillery Lane Bridge and upstream of a weir. The channel is approximately 11 m wide with a minimum bed level of 26.776m OD Malin and bank levels of 29.219m OD Malin (left bank) and 29.063m OD Malin (right bank). The current OPW ordnance level of the gauge zero is 29.66m OD Poolbeg (26.96m OD Malin). It is noted that the survey drawing (4163_09RYEW_RyeWater_Rev 2) states that the level of the gauge one metre level is 28.274m OD Malin, meaning that there is a difference of 0.314m between the surveyed SG0 level and the OPW SG0 level. For the purposes of this rating review and such that it is consistent with the OPW data, it is assumed that the OPW level is correct.
Figure C 0.1: Modelled Watercourse and Gauge Station Location
The gauge is operated by the OPW and was installed in 1940 becoming automated in 1956. The weir (see Figure 2) installed in 1980 acts as a control structure, drowning out at the highest flood levels. The photographs below (Figure 3) show that the gauging station was moved from the right bank to the
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left bank between July 1998 and 2002. A by-pass channel has been constructed conveying some discharge from upstream of the bridge to downstream of the weir (which is located downstream of the gauging station) - see photographs P1010691 and P1010690 respectively. The date of construction of the bypass channel is unknown but appears to be after May 2008 (see photograph PB130508G09001) when a flood defence wall along the left bank upstream of the bridge was constructed.
Figure C 0.2: Model cross-section at gauge location (Top); Photo of bridge & Recorder housing (looking upstream) (Bottom)
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PA080798G09001 - View of Left Bank 08/07/98 PB080798G09001 - View of Right Bank 08/07/98
PD230702G09001 - View of Left Bank 23/07/02 PB130508G09001 - View u/s of bridge 13/05/2008
P1010691 - View of bypass channel u/s of bridge P1010690 - View of bypass channel & gauge
Figure C 0.3: Photographs of the previous gauging station location and the bypass channel.
The study reach included within the Leixlip model extends approximately 7km in the upstream direction and over 5km in the downstream direction from the gauge, changing from the River Ryewater to the River Liffey. There is a bridge immediately upstream of the gauge and one other bridge within the 2 km upstream of the gauge location. There is a weir immediately downstream of the gauge and a
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series of weirs within 600m downstream of the gauge location before the Rye Bridge, which is just upstream of the Liffey confluence. The bed level at the Liffey confluence is 4 m lower than the bed level at the gauge and so will not influence the stage-discharge relationship at this location. The upstream boundary consists of a hydrograph with a peak flow of 108.65m3/s, equivalent to an estimated 0.1% AEP event. There are 133 water level and flow gaugings recorded for this site from 14th December 1950 to 22nd June 2010. The largest spot gauging is 39.738m3/s recorded on the 12th 3 June 1993. Qmed for this site is estimated to be 33.7m /s.
A national review under FSU classified the station at Leixlip as an A1 quality rating (from 1980 to
2004), meaning the rating is good for flood flows well above Qmed with the highest gauged flow greater than 1.3 x Qmed and/or with a good confidence of extrapolation up to 2 times Qmed, bankfull or, using suitable survey data, including flows across the floodplain. The highest flow spot gauging is 39.738m3/s. The upper confidence limit of the existing OPW rating equation is at a staff gauge level of 1.55m, which corresponds with the highest spot gauging.
The construction of the bypass channel, conveying discharge from the existing river channel upstream of the gauging station and returning this discharge downstream of the gauging station, will have altered the stage-discharge relationship at the gauging station. Consequently, the stage-discharge relationship at the gauging station location in the model (which includes the bypass channel) can only be compared to spot gaugings recorded after the bypass channel was constructed. It is not known if any of the spot gaugings fall within this time period although there are two spot gaugings from November 2009 and June 2010 which may fall within it, as shown in Figure 4 below. The RPS rating curve does not correlate well with the OPW rating curve and deviates by up to 200mm. This is considered to be due to changes to the channel such as the construction of the bypass channel and walls adjacent to the channel.
The results of the rating review are shown below in Figure 4 and Table 1. The graph demonstrates the RPS model curve and shows the comparison with the OPW rating curve. The model can be considered to be a better representation of the stage - discharge relationship of the Ryewater in its current state. However use of the new rating relationship should be validated through further spot gauging prior to its use.
Manning's roughness values of 0.045 for the in-channel (1D) portion of the model and 0.045 for the floodplain (2D) portion of the model on the gauged reach were used as these best reflected the observed channel and floodplain roughness descriptions from photographs and land use datasets. There is very little or no data (relative spot gaugings) to base improved calibration and deviation from the observed values.
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Figure C 0.4: Comparison of Existing OPW Rating Curve and RPS Rating Curve
Min Stage Max Stage Section C a b (m) (m)
1 0.17 1.5 19.107 -0.044 1.545
2 1.5 3 5.642 0.755 2.214
Where: Q = C(h+a)b and h = stage readings (metres)
Table C 0.1: Rating equation values for gauge 09001
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LUCAN (09002)
The gauging station at Lucan (09002) is located on the Griffeen River which flows through the centre of Lucan, County Dublin. The gauging station is located 270m upstream of its confluence with the River Liffey. The staff gauge and recorder house are Located on the right hand bank of an open channel.
Figure C 0.1: Modelled Watercourse and Gauge Station Location
The model reach included within the Lucan model extends approximately 2km in the upstream direction on the Griffeen and 270m in the downstream direction from the gauge to its confluence with the Liffey. The model also includes the reach of the River Liffey adjacent to Lucan and also a small watercourse which joins the Griffeen via a culvert outlet 370m upstream of the gauging station. There is a bridge immediately upstream (20m) and another bridge downstream (75m) along the gauged reach which is channelised between the two stone arch bridges. The immediate floodplain is an area of parkland on the right bank. The bed level at the Liffey confluence is approximately 3m lower than
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the bed level at the gauge. The upstream boundary consists of a hydrograph with a peak flow of 36m3/s, in excess of an estimated 0.1% AEP event.
The channel is approximately 5 m wide with a minimum bed level of 20.65m OD Malin and bank levels of 23.92m OD Malin (left bank) and 22.74m OD Malin (right bank). The current EPA ordnance level of the gauge zero is 23.56m OD Poolbeg. The staff gauge zero level was surveyed as 20.88m OD Malin which is approximately 20mm higher than the EPA level.
Figure C 0.2: Model cross-section at gauge location
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09GRIF00027_RB - GS on right bank 13/01/2012 09GRIF00027_DN - View d/s of GS 13/01/2012
09GRIF00024_DN - Bridge d/s of GS 13/01/2012 09GRIF00027_UP - View u/s of GS 13/01/2012
Figure C 0.3: Photographs at the Gauging Station
The gauging station is operated by the EPA and was installed in 1977. A flood event which occurred on the 12/06/1993 changed the bed profile of the Griffeen which led to a significant change in the rating. There were 162 spot water level gaugings recorded between 26th August 1976 and the 26th June 2013. 49 of these were carried out after the 12th June 1993. The largest spot gauging is 3 th 3 11.92m /s recorded on 12 June 1993. Qmed for this site is estimated to be 5.3m /s. A national review under FSU classified the station at Lucan as an A1 quality rating (from 1977 to 2004), meaning the rating is good for flood flows well above Qmed with the highest gauged flow greater than 1.3 x Qmed and/or with a good confidence of extrapolation up to 2 times Qmed, bankfull or, using suitable survey data, including flows across the floodplain.
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The results of the rating review are shown below in Figure C 0.4 and Table C 0.1. The graph shows the modelled Q-h relationship and new rating along with the latest EPA rating and the spot gaugings. It is noted that the EPA rating equation is only applicable up to 2004 when it is indicated that a weir was constructed. The spot gaugings have therefore been split into pre and post 2004 and a noticeable distinction between the two periods of spot gaugings is apparent at low flows. A complete new rating has been developed as it can be shown that the EPA rating is not in line with the latest spot gaugings. The new rating is not applicable to data recorded prior to the weir being constructed in 2004.
Figure C 0.4: Comparison of EPA Rating Curve (redundant since 2004) and RPS Rating Curve
The modelled Q-h and resultant rating was found to be very well calibrated to the post 2004 spot gaugings. The modelled Q-h is within 30mm of all of the spot gaugings and is a much better fit than the redundant EPA rating although both ratings converge at around 7 m3/s. This would be expected as the weir becomes drowned out and its influence becomes negligible. Above 7.7 m3/s there are no spot gaugings upon which to calibrate the rating although there can be some confidence gained from the fact that where there is data calibration is very good. The modelled Q-h indicates a substantial change in the rating at a stage height of approximately 1m. This is the level at which the stone arch bridge downstream begins to surcharge. When surcharged there is no alternative conveyance route until flood water spill over surrounding walls which are generally between 1.7m above the bridge soffit.
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Min Max Stage Stage Equation (m) (m) C a b
1 0.278 0.768 20.274 -0.135 1.625
2 0.768 1.042 19.76 -0.139 1.548
3 1.042 2.88 11.899 0.614 0.692
4 2.88 3.06 0.141 0.571 4.28
Where: Q = C(h+a)b and h = stage readings (metres)
Table C 0.1: Rating equation values for gauge 09002
Manning's roughness values of 0.035 for the in-channel (1D) portion of the model and 0.045 for the floodplain (2D) portion of the model on the gauged reach were used as these best reflected the observed channel and floodplain roughness descriptions from photographs and land use datasets. These values resulted in very good calibration of the model to the available spot gaugings.
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KILLEEN ROAD (09035)
Gauge 09035 is located at in the Clondalkin area of Dublin on the Camac River approximately 900m upstream of its confluence with the smaller tributary called the Kingswood River. The gauge is located off the Nangor Road in the vicinity of the Toyota business off the Killeen Road 30m upstream of a footbridge in an open channel section approximately 12m wide with a minimum bed level of 44.57m OD Malin and bank levels of 46.45m OD Malin (left bank) and 46.91m OD Malin (right bank). The current ordnance level of the gauge zero is 44.169m OD Malin (as stated on the HydroNet website).
The gauge is currently active and operated by the EPA, with continuous water level and derived flow records provided from 1996 to 2011.
47.00
46.50
46.00
45.50
45.00 Elevation AD) (m
44.50
44.00 0.0 5.0 10.0 15.0 20.0 Offset (m)
Figure C3.1: Model Cross-Section at Gauge Location (Top); Photo of gauge location (Bottom)
The study reach extends approximately 650m in the upstream direction and 1km downstream of the gauge. There are three bridge structures along this reach of the Camac River, one approximately 30m upstream and one approximately 30m downstream of the gauge. The upstream and downstream approaches to the gauge (Figure C3.1) are relatively straight. The two dimensional hydraulic model
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uses information from 27 original cross sections, including the weir structure. The downstream boundary condition applied to the model was calculated as the critical flow Q-h relationship with the upstream boundary consisting of a hydrograph with a peak flow of 55.5 m3/s, equivalent to an estimated 0.1% AEP event.
The model was calibrated at lower flows by applying at the upstream boundary spot gauged flows and equivalent water levels provided by the EPA for the Killeen Road gauge. Adjustments were made to the Manning’s n values for channel and over bank roughness to reflect vegetation growth and channel roughness in order to develop a realistic model of the channel and flow conditions.
The EPA assigned a rating standard of “very good” to their latest rating review of the Killeen Road gauge. The National Review under FSU Work Package 2.1 assigned data recorded from the gauge a quality classification of B (i.e. flows can be determined up to Qmed with confidence. For the purposes of the Eastern CFRAM study, it is proposed to use flows from the Killeen Road gauge based on the lower of flow dictated by the upper limit of the current EPA ratings (i.e. Rating Curve Q/C1.1) which is 3 3 less than Qmed. Qmed for this site is estimated as 11.7m /s (FSU gauged) and 6.16m /s (FSU predicted from physical catchment descriptors), as stated on the EPA HydroNet website. The upper limit of the 3 rating curve is at a stage of 1.05m which equates to a flow of less than Qmed (approximately 8.0 m /s, based on the EPA rating curve). Therefore, for the purposes of the Eastern CFRAM study, it is proposed to use the existing EPA rating curve to calibrate the model rating up to the limits of the curve.
The results of the rating review, including a comparison with the spot gauges and the existing rating equation (which varies across two levels), are shown in Figure C3.2 and Table C3.1. Note that the first three rating equation values are taken from the existing EPA rating curve.
60
50
40
30
Q (m^3/s) Guagings 20 EPA Rating Curve 10 RPS Rating Curve
0 00.511.522.53 H (mOD)
Figure C3.2: Comparison of Existing OPW Rating Curve and RPS Rating Curve for all flows
Table C3.1: Rating equation values for gauge 09035
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Min Stage Max Stage Section C a b (m) (m)
1 0.522 0.578 136.177 0 11.3326 2 0.578 0.78 13.3693 0 7.10105 3 0.78 1.06 6.50778 0 4.20744 4 1.06 1.21 12.5404 -0.3726 0.8808 5 1.21 1.70 2.2403 0.7177 2.3875 6 1.70 1.945 1.6802 0.024 4.385 7 1.945 2.43 2.6806 2.706 1.6266 Where: Q = C(h+a)b and h = stage readings (metres)
Figure C3.2 shows that the model accurately represents the rating curve based on the lower flow gaugings up to approximately 8 m3/s The best fit rating curve was achieved with a Manning’s n value of 0.05. The weir becomes submerged between 6 and 8 m3/s, relating to gauge heights of 0.93 to 0.97m respectively. Analysis of the results show that floodwaters remain in bank at the gauged 3 section until river flow exceeds 5.5 m /s, which is less than Qmed.
The hydraulic influence of the weir structure has a significant influence on the Q-h relationship at the gauging station location. Consequently, parameters have been chosen as necessary in order to reproduce the EPA Q-h relationship up to its limit of reliability.
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CADBURY’S (09102)
Gauge 09102 is located at Bonnybrook, Dublin on the Santry River approximately 3.3km upstream of its discharge to the estuary north of the Bull Bridge to North Bull Island. The gauge is located 280m upstream of a footbridge just upstream of the Malahide Road culvert in an open channel section approximately 8m wide with a minimum bed level of 28.803m OD Malin and bank levels of 32.92m OD Malin (left bank) and 32.37m OD Malin (right bank). The current ordnance level of the gauge zero is 29.232m OD Malin (as stated on the HydroNet website).
The gauge is operated by the EPA, with continuous water level and derived flow records available from 2001 to present.
34.0
33.0
32.0
31.0 Elevation (m AD) 30.0
29.0 0.0 5.0 10.0 15.0 Offset (m)
Figure C4.1: Model Cross-Section at Gauge Location (Top); Photo of gauge location (Bottom)
The study reach extends approximately 1079m in the upstream direction and 643m downstream of the gauge. There are eight (8) bridge, four (4) culvert and three (3) weir structures along this reach of the Santry River. The nearest structures are bridges approximately 200m upstream and 280m downstream of the gauge location. The upstream and downstream approaches to the gauge (Figure C4.1) are relatively straight. The one dimensional hydraulic model uses information from 16 original cross sections, including the weir structure. The downstream boundary condition applied to the model
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was calculated as the normal flow Q-h relationship with the upstream boundary consisting of a hydrograph with a peak flow of 13.82 m3/s.
The model was calibrated by applying at the upstream boundary, lower flow gauged data, using spot gauge and the most up to date rating curve information for the Cadbury’s gauge. Adjustments were made to the Manning’s n values for channel and over bank roughness to reflect vegetation growth and channel roughness in order to develop a realistic model of the channel and flow conditions that mimics the EPA rating curve at lower flows.
The EPA assigned a rating standard of “very good” to their latest rating review of the Cadbury’s gauge. The National Review assigned data recorded from the gauge a quality classification of G (i.e. flows can be determined up to Qmed with confidence). For the purposes of the Eastern CFRAM study, it is proposed to use flows from the Cadbury’s gauge based on the lower of flow dictated by the upper limit of the current EPA ratings (i.e. Rating Curve Q/C1.1) or Qmed. Qmed for this site is estimated as 3.38m3/s (EPA observed) 2.53m3/s (FSU predicted). The upper limit of the rating curve is at a stage of 3 0.45m which equates to a flow of less than Qmed (approximately 1.43 m /s), however the rating curve equation is stated to be valid to a stage of 0.664m (approximately 2.43 m3/s) Therefore, for the purposes of the Eastern CFRAM study, it is proposed to use the existing EPA rating curve to calibrate the model rating up to this stage.
The model was calibrated by applying at the upstream boundary, lower flow gauged data, using the most up to date rating curve information for the Cadbury’s gauge. Adjustments were made to the modelled weir structure, Manning’s n values for channel and over bank roughness to reflect vegetation growth and channel roughness in order to develop a realistic model of the channel and flow conditions.
The results of the rating review, including a comparison with the spot gauges and the existing rating equation (which varies across two levels), are shown in Figures C4.2 and Table C4.1.
31.5
31
30.5
H (mOD) 30
Guagings 29.5 Existing EPA Rating Curve RPS Rating Curve 29 0 5 10 15 Q (m^3/s)
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Figure C4.2: Comparison of Existing EPA Rating Curve and RPS Rating Curve for all flows
Table C4.1: Rating equation values for gauge 09102
Min Stage Max Stage Section C a b (m) (m)
1 0.1 0.263 2.87896 0 2.6549 2 0.263 0.449 1.44324 0 1.3533 3 0.45 0.686 3.2459 0.10 1.3817 4 0.686 1.124 3.4975 0.11 1.7842 5 1.124 1.993 1.454 0.56 2.4058 Where: Q=eC*(h-a)b for Sections 1 and 2 (from EPA rating curve C1.1) and Q = C(h+a)b for Sections 3, 4 and 5 with reference to h = stage readings (metres)
Figure C4.2 shows that the model accurately represents the EPA rating curve based on the lower flow gaugings up to 1.35 m3/s. The best fit rating curve was achieved with a Manning’s n value of 0.07. Analysis of the results show that floodwaters remain in bank at the gauged section until river flow exceeds 30 m3/s.
The hydraulic influence of the weir structure has a significant influence on the Q-h relationship at the gauging station location. Consequently, parameters have been chosen as necessary in order to reproduce the EPA Q-h relationship up to its limit of reliability.
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APPENDIX D
DESIGN FLOWS FOR MODELLING INPUT
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Model 1 – Santry Flows for AEP AREA Model Node ID_CFRAMS 2 Qmed 10% 1% 0.5% 0.1% (km ) 50% (2) 20% (5) 5% (20) 2% (50) number (10) (100) (200) (1000) 09_1502_1_RPS 1.645 0.387 0.387 0.562 0.695 0.844 1.076 1.285 1.532 2.292 Model 1 09_1507_6_RPS 8.93 2.48 2.48 3.61 4.46 5.42 6.90 8.25 9.83 14.71 Model 1 Top-up between 9_1502_1_RPS 7.28 2.07 2.07 3.01 3.72 4.52 5.76 6.88 8.20 12.27 Model 1 & 09_1507_6_RPS 09102_RPS 10.90 3.245 3.25 4.72 5.83 7.08 9.02 10.78 12.85 19.23 Model 1 Top-up between 9_1507_6_RPS 1.97 0.71 0.71 1.03 1.27 1.55 1.97 2.35 2.81 4.20 Model 1 & 09102_RPS 09_1507_17_RPS 13.96 5.24 5.24 7.62 9.43 11.44 14.58 17.42 20.77 31.06 Model 1 Top-up between 09102_RPS & 3.06 2.04 2.04 2.96 3.67 4.45 5.67 6.78 8.08 12.08 Model 1 09_1507_17_RPS
MRFS Flows for AEP HEFS Flows for AEP AREA Model Node ID_CFRAMS (km2) 50% 20% 10% 5% 2% 1% 0.5% 0.1% 10% 1% 0.1% number (2) (5) (10) (20) (50) (100) (200) (1000) (10) (100) (1000) 09_1502_1_RPS 1.645 0.690 1.002 1.240 1.505 1.918 2.291 2.731 4.086 2.482 4.586 8.177 Model 1 09_1507_6_RPS 8.93 4.67 6.79 8.40 10.20 13.00 15.53 18.51 27.69 11.11 20.53 36.61 Model 1 Top-up between 09_1502_1_RPS & 7.28 3.90 5.66 7.01 8.51 10.84 12.95 15.44 23.10 9.27 17.13 30.54 Model 1 09_1507_6_RPS 09102_RPS 10.90 5.780 8.40 10.39 12.61 16.07 19.21 22.89 34.24 13.24 24.48 43.64 Model 1 Top-up between 09_1507_6_RPS & 1.97 1.26 1.83 2.27 2.75 3.51 4.19 5.00 7.48 2.89 5.34 9.53 Model 1 09102_RPS 09_1507_17_RPS 13.96 7.64 11.10 13.74 16.67 21.25 25.39 30.26 45.27 16.88 31.19 55.61 Model 1 Top-up between 09102_RPS & 3.06 2.46 3.57 4.41 5.36 6.83 8.16 9.73 14.55 4.78 8.84 15.76 Model 1 09_1507_17_RPS
Model 2A – Baldonnel Flows for AEP AREA Model Node ID_CFRAMS 2 Qmed 10% 1% 0.5% 0.1% (km ) 50% (2) 20% (5) 5% (20) 2% (50) number (10) (100) (200) (1000) 09_990_U 1.190 0.287 0.29 0.42 0.52 0.63 0.80 0.95 1.14 1.70 Model 2A 09_1156_1 1.056 0.609 0.61 0.88 1.10 1.33 1.69 2.02 2.41 3.61 Model 2A 09_1165_5 3.532 1.549 1.55 2.25 2.79 3.38 4.31 5.15 6.14 9.18 Model 2A Top-up between 09_1156_1 & 2.476 1.125 1.13 1.63 2.02 2.46 3.13 3.74 4.46 6.67 Model 2A 09_1165_5 09_Trib_Griffn_U / 0.038 0.014 0.01 0.02 0.03 0.03 0.04 0.05 0.06 0.08 Model 2A 09_Trib_Griffn_1
UN_Trib_Griff_U 1.709 0.590 0.59 0.86 1.06 1.29 1.64 1.96 2.34 3.50 Model 2A
UN_Trib_Griff_1 4.814 1.654 1.65 2.40 2.97 3.61 4.60 5.49 6.55 9.80 Model 2A Top-up between UN_Trib_Griff_U & 3.105 1.144 1.14 1.66 2.06 2.50 3.18 3.80 4.53 6.78 Model 2A UN_Trib_Griff_1 09_452_2_RPS 0.524 0.165 0.16 0.24 0.30 0.36 0.46 0.55 0.65 0.98 Model 2A 09_1120_3_RPS 30.029 6.209 6.21 8.73 10.56 12.54 15.50 18.09 21.05 29.68 Model 2A Top-up between 09_990_U & 19.931 5.101 5.10 7.17 8.68 10.30 12.73 14.86 17.29 24.39 Model 2A 09_1120_3_RPS
Input flows Top-up flows. These flows should be entered laterally Check flows. Modellers to check to ensure these flows are being reached at each HEP
MRFS Flows for AEP HEFS Flows for AEP AREA Model Node ID_CFRAMS 2 10% 1% 0.5% 0.1% 10% 0.1% (km ) 50% (2) 20% (5) 5% (20) 2% (50) 1% (100) number (10) (100) (200) (1000) (10) (1000) 09_990_U 1.190 0.358 0.52 0.64 0.78 1.00 1.19 1.42 2.12 0.79 1.461 2.605 Model 2A 09_1156_1 1.056 0.760 1.10 1.37 1.66 2.11 2.53 3.01 4.50 1.68 3.104 5.534 Model 2A 09_1165_5 3.532 3.131 4.55 5.63 6.83 8.71 10.40 12.40 18.55 7.06 13.042 23.255 Model 2A Top-up between 09_1156_1 & 2.476 2.360 3.43 4.24 5.15 6.56 7.84 9.35 13.99 6.27 11.594 20.673 Model 2A 09_1165_5 09_Trib_Griffn_U / 0.038 0.029 0.04 0.05 0.06 0.08 0.10 0.12 0.17 0.08 0.143 0.255 Model 2A 09_Trib_Griffn_1 UN_Trib_Griff_U 1.709 0.974 1.41 1.75 2.12 2.71 3.24 3.86 5.77 2.74 5.066 9.033 Model 2A UN_Trib_Griff_1 4.814 2.918 4.24 5.25 6.37 8.12 9.70 11.56 17.29 7.23 13.369 23.837 Model 2A Top-up between UN_Trib_Griff_U & 3.105 2.110 3.07 3.79 4.60 5.87 7.01 8.36 12.50 4.80 8.864 15.805 Model 2A UN_Trib_Griff_1 09_452_2_RPS 0.524 0.204 0.30 0.37 0.45 0.57 0.68 0.81 1.21 0.40 0.746 1.330 Model 2A 09_1120_3_RPS 30.029 11.668 16.40 19.85 23.56 29.12 33.99 39.55 55.78 25.75 44.093 72.367 Model 2A Top-up between 09_990_U & 19.931 8.993 12.64 15.30 18.16 22.45 26.20 30.49 43.00 21.13 36.194 59.403 Model 2A 09_1120_3_RPS
Input flows Top-up flows. These flows should be entered laterally Check flows. Modellers to check to ensure these flows are being reached at each HEP
Model 2B – Lucan to Chapelizod Flows for AEP AREA Model Node ID_CFRAMS 2 Qmed 10% 1% 0.5% 0.1% (km ) 50% (2) 20% (5) 5% (20) 2% (50) number (10) (100) (200) (1000) 09_1239_6_RPS 729.997 94.979 94.98 116.82 131.17 145.41 165.17 181.03 198.03 242.10 Model 2B 09_1131_U 0.016 0.005 0.00 0.01 0.01 0.01 0.01 0.02 0.02 0.03 Model 2B 09_475_U 0.000 0.000 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 Model 2B 09_475_3_RPS 1.737 0.239 0.24 0.35 0.43 0.52 0.66 0.79 0.95 1.41 Model 2B 09_1237_4_RPS 6.431 0.944 0.94 1.37 1.70 2.06 2.62 3.14 3.74 5.59 Model 2B Top-up between 09_1131_U & 4.678 0.767 0.77 1.11 1.38 1.67 2.13 2.55 3.04 4.55 Model 2B 09_1237_4_RPS 09_1120_3_RPS 30.029 6.209 6.21 8.73 10.56 12.54 15.50 18.09 21.05 29.68 Model 2A 09_613_U 0.076 0.023 0.02 0.03 0.04 0.05 0.06 0.08 0.09 0.14 Model 2B 09_613_3_RPS 1.313 0.501 0.50 0.73 0.90 1.09 1.39 1.66 1.98 2.97 Model 2B 09002_RPS 34.584 7.418 7.42 10.43 12.62 14.98 18.52 21.61 25.15 35.47 Model 2B Top-up between 09_1120_3_RPS & 3.242 0.947 0.95 1.33 1.61 1.91 2.36 2.76 3.21 4.53 Model 2B 09002_RPS 09_242_3_RPS 34.657 7.469 7.47 10.50 12.70 15.08 18.64 21.76 25.32 35.71 Model 2B 09_1136_U 0.198 0.068 0.07 0.10 0.12 0.15 0.19 0.23 0.27 0.40 Model 2B 09_1136_1 0.535 0.106 0.11 0.15 0.19 0.23 0.30 0.35 0.42 0.63 Model 2B Top-up between 0.337 0.054 0.05 0.08 0.10 0.12 0.15 0.18 0.21 0.32 Model 2B 09_1136_U & 09_1136_1 09_221_3 11.376 1.433 1.43 2.08 2.58 3.13 3.99 4.77 5.69 8.54 Model 2B 09_1128_U 0.018 0.008 0.01 0.01 0.01 0.02 0.02 0.03 0.03 0.05 Model 2B 09_1128_1 0.210 0.046 0.05 0.07 0.08 0.10 0.13 0.15 0.18 0.27 Model 2B Top-up between 0.192 0.040 0.04 0.06 0.07 0.09 0.11 0.13 0.16 0.24 Model 2B 09_1128_U & 09_1128_1
Flows for AEP AREA Model Node ID_CFRAMS 2 Qmed 10% 1% 0.5% 0.1% (km ) 50% (2) 20% (5) 5% (20) 2% (50) number (10) (100) (200) (1000) 09_1142_U 0.283 0.116 0.12 0.17 0.21 0.25 0.32 0.39 0.46 0.69 Model 2B 09_1142_1 0.729 0.231 0.23 0.34 0.42 0.50 0.64 0.77 0.92 1.37 Model 2B Top-up between 0.446 0.120 0.12 0.17 0.22 0.26 0.33 0.40 0.47 0.71 Model 2B 09_1142_U & 09_1142_1 09_1870_7_RPS 807.096 106.336 106.34 130.79 146.85 162.80 184.92 202.68 221.71 271.05 Model 2B Top-up between 09_1239_6_RPS & 23.161 4.420 4.42 5.44 6.10 6.77 7.69 8.43 9.22 11.27 Model 2B 09_1870_7_RPS 09_1870_8_RPS 807.577 106.401 106.40 130.87 146.94 162.90 185.03 202.80 221.85 271.22 Model 2B Top-up between 09_1870_7_RPS & 0.481 0.141 0.14 0.17 0.19 0.22 0.24 0.27 0.29 0.36 Model 2B 09_1870_8_RPS 09_1870_13_RPS 812.020 107.450 107.45 132.16 148.39 164.51 186.86 204.80 224.03 273.89 Model 2B Top-up between 09_1870_8_RPS & 4.443 1.564 1.56 1.92 2.16 2.39 2.72 2.98 3.26 3.99 Model 2B 09_1870_13_RPS
Input flows Top-up flows. These flows should be entered laterally Check flows. Modellers to check to ensure these flows are being reached at each HEP
MRFS Flows for AEP HEFS Flows for AEP AREA Model Node ID_CFRAMS 2 10% 1% 0.5% 0.1% 10% 1% 0.1% (km ) 50% (2) 20% (5) 5% (20) 2% (50) number (10) (100) (200) (1000) (10) (100) (1000) 09_1239_6_RPS 729.997 123.238 151.58 170.19 188.67 214.31 234.89 256.95 314.13 264.27 364.73 487.77 Model 2B 09_1131_U 0.016 0.000 0.02 0.02 0.02 0.02 0.03 0.03 0.05 0.03 0.07 0.10 Model 2B 09_475_U 0.000 0.000 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 Model 2B 09_475_3_RPS 1.737 0.304 0.44 0.54 0.66 0.84 1.00 1.20 1.78 0.70 1.28 2.29 Model 2B 09_1237_4_RPS 6.431 1.565 2.28 2.83 3.43 4.36 5.23 6.23 9.31 6.44 11.89 21.16 Model 2B Top-up between 09_1131_U & 4.678 1.418 2.04 2.54 3.08 3.92 4.70 5.60 8.38 4.84 8.95 15.96 Model 2B 09_1237_4_RPS 09_1120_3_RPS 30.029 11.666 16.40 19.84 23.56 29.12 33.98 39.54 55.76 28.20 48.30 79.25 Model 2B 09_613_U 0.076 0.027 0.04 0.05 0.07 0.08 0.11 0.12 0.19 0.11 0.21 0.37 Model 2B 09_613_3_RPS 1.313 0.902 1.32 1.62 1.97 2.51 2.99 3.57 5.36 2.14 3.95 7.07 Model 2B 09002_RPS 34.584 14.996 21.08 25.50 30.27 37.43 43.67 50.83 71.68 30.69 52.55 86.25 Model 2B Top-up between 09_1120_3_RPS & 3.242 1.804 2.53 3.06 3.63 4.48 5.24 6.10 8.60 3.64 6.25 10.25 Model 2B 09002_RPS 09_242_3_RPS 34.657 15.088 21.21 25.65 30.46 37.65 43.95 51.14 72.13 30.86 52.88 86.78 Model 2B 09_1136_U 0.198 0.153 0.22 0.26 0.33 0.42 0.50 0.59 0.88 0.28 0.55 0.95 Model 2B 09_1136_1 0.535 0.194 0.26 0.34 0.41 0.53 0.62 0.74 1.11 0.70 1.29 2.32 Model 2B Top-up between 09_1136_U & 0.337 0.063 0.10 0.13 0.15 0.19 0.23 0.27 0.41 0.16 0.29 0.52 Model 2B 09_1136_1 09_221_3 11.376 2.391 3.48 4.31 5.23 6.67 7.98 9.52 14.28 9.75 18.02 32.27 Model 2B 09_1128_U 0.018 0.023 0.02 0.02 0.05 0.05 0.07 0.07 0.11 0.02 0.07 0.12 Model 2B 09_1128_1 0.210 0.089 0.12 0.14 0.18 0.23 0.27 0.32 0.48 0.29 0.55 0.99 Model 2B
MRFS Flows for AEP HEFS Flows for AEP AREA Model Node ID_CFRAMS 2 10% 1% 0.5% 0.1% 10% 1% 0.1% (km ) 50% (2) 20% (5) 5% (20) 2% (50) number (10) (100) (200) (1000) (10) (100) (1000)
Top-up between 09_1128_U & 0.192 0.065 0.10 0.11 0.15 0.18 0.21 0.26 0.39 0.27 0.51 0.94 Model 2B 09_1128_1 09_1142_U 0.283 0.140 0.20 0.25 0.29 0.37 0.46 0.54 0.81 0.23 0.43 0.77 Model 2B 09_1142_1 0.729 0.299 0.44 0.55 0.65 0.83 1.00 1.19 1.78 0.54 0.99 1.77 Model 2B Top-up between 09_1142_U & 0.446 0.292 0.41 0.53 0.63 0.80 0.97 1.14 1.73 0.61 1.11 1.96 Model 2B 09_1142_1 09_1870_7_RPS 807.096 142.876 175.73 197.30 218.73 248.45 272.32 297.88 364.18 349.36 482.18 644.84 Model 2B Top-up between 09_1239_6_RPS & 23.161 6.842 8.42 9.44 10.48 11.90 13.05 14.27 17.45 20.41 28.20 37.70 Model 2B 09_1870_7_RPS 09_1870_8_RPS 807.577 143.017 175.91 197.51 218.96 248.71 272.59 298.20 364.56 350.25 483.40 646.49 Model 2B Top-up between 09_1870_7_RPS & 0.481 0.216 0.26 0.29 0.34 0.37 0.42 0.45 0.55 0.63 0.90 1.20 Model 2B 09_1870_8_RPS 09_1870_13_RPS 812.020 145.680 179.18 201.19 223.04 253.34 277.67 303.74 371.34 367.75 507.55 678.77 Model 2B Top-up between 09_1870_8_RPS & 4.443 3.132 3.86 4.34 4.80 5.46 5.98 6.55 8.01 4.70 6.48 8.68 Model 2B 09_1870_13_RPS
Input flows Top-up flows. These flows should be entered laterally Check flows. Modellers to check to ensure these flows are being reached at each HEP
Model 2C – Lower Liffey Flows for AEP AREA Node ID_CFRAMS 2 Qmed 10% 1% 0.5% 0.1% Model number (km ) 50% (2) 20% (5) 5% (20) 2% (50) (10) (100) (200) (1000) 09_1870_13_RPS 812.020 107.450 107.45 132.16 148.39 164.51 186.86 204.80 224.03 273.89 Model 2C 09_1870_14_RPS 816.377 107.602 107.60 132.35 148.60 164.74 187.12 205.09 224.35 274.28 Model 2C Top-up between 09_1870_13_RPS & 1.232 0.436 0.44 0.54 0.60 0.67 0.76 0.83 0.91 1.11 Model 2C 09_1870_14_RPS 09_1872_9_RPS 57.91 19.53 19.53 27.15 32.72 38.70 47.74 55.65 64.72 91.29 Model 2C/2D 09_1874_17_RPS 12.17 1.640 1.640 2.383 2.949 3.578 4.561 5.450 6.496 9.717 Model 2C/2E 09_587_11 112.821 52.148 52.15 72.49 87.35 103.31 127.45 148.57 172.77 243.69 Model 2C 09_631_D 1020.307 132.605 132.61 163.10 183.13 203.02 230.60 252.75 276.48 338.01 Model 2C Top-up between 09_1870_14_RPS & 21.030 5.895 5.90 7.25 8.14 9.03 10.25 11.24 12.29 15.03 Model 2C 09_631_D
MRFS Flows for AEP HEFS Flows for AEP AREA Model Node ID_CFRAMS 2 20% 10% 5% 2% 1% 0.5% 0.1% 10% 1% 0.1% (km ) 50% (2) number (5) (10) (20) (50) (100) (200) (1000) (10) (100) (1000) 09_1870_13_RPS 812.020 137.310 168.89 189.63 210.22 238.78 261.71 286.29 350.00 280.20 386.73 517.19 Model 2C 09_1870_14_RPS 816.377 137.507 169.13 189.90 210.52 239.12 262.09 286.70 350.50 280.60 387.27 517.92 Model 2C Top-up between 09_1870_13_RPS & 1.232 0.741 0.91 1.02 1.14 1.29 1.41 1.55 1.89 1.14 1.57 2.10 Model 2C 09_1870_14_RPS 09_1872_9_RPS 57.91 27.75 38.57 46.48 54.97 67.82 79.06 91.94 129.68 50.36 85.65 140.49 Model 2C/2D 09_1874_17_RPS 12.17 1.968 2.860 3.538 4.294 5.473 6.540 7.795 11.660 4.040 7.467 13.314 Model 2C/2E 09_587_11 112.821 73.842 102.64 123.68 146.28 180.47 210.37 244.64 345.06 133.99 227.91 373.82 Model 2C 09_631_D 1020.307 169.454 208.43 234.02 259.43 294.68 322.98 353.31 431.94 345.80 477.26 638.27 Model 2C Top-up between 09_1870_14_RPS & 21.030 8.363 10.29 11.55 12.80 14.54 15.94 17.44 21.32 12.51 17.27 23.09 Model 2C 09_631_D
Model 2D – Camac Flows for AEP AREA Model Node ID_CFRAMS Qmed (km2) 50% 20% 10% 5% 2% 1% 0.5% 0.1% number (2) (5) (10) (20) (50) (100) (200) (1000) 09_481_U 3.870 0.854 0.85 1.24 1.53 1.86 2.37 2.84 3.38 5.06 Model 2D 09_472_4_RPS 8.507 1.327 1.33 1.93 2.39 2.90 3.69 4.41 5.26 7.86 Model 2D Top-up between 09_481_U & 4.637 0.752 0.75 1.09 1.35 1.64 2.09 2.50 2.98 4.45 Model 2D 09_472_4_RPS 09_472_8_RPS 10.104 1.953 1.95 2.83 3.49 4.23 5.38 6.41 7.63 11.35 Model 2D Top-up between 09_472_4_RPS & 1.597 0.347 0.35 0.50 0.62 0.75 0.95 1.14 1.35 2.02 Model 2D 09_472_8_RPS 09_435_U 0.037 0.031 0.03 0.05 0.06 0.07 0.09 0.10 0.12 0.18 Model 2D 09_435_1_RPS 1.218 0.618 0.62 0.90 1.11 1.35 1.72 2.05 2.45 3.66 Model 2D Top-up between 09_435_U & 1.181 0.601 0.60 0.87 1.08 1.31 1.67 2.00 2.38 3.56 Model 2D 09_435_1_RPS 09_37_U 0.265 0.177 0.18 0.26 0.32 0.39 0.49 0.59 0.70 1.05 Model 2D 09_37_1 0.408 0.215 0.21 0.31 0.39 0.47 0.60 0.71 0.85 1.27 Model 2D Top-up between 09_37_U & 09_37_1 0.143 0.037 0.04 0.05 0.07 0.08 0.10 0.12 0.15 0.22 Model 2D 09_36_2 1.812 0.758 0.76 1.10 1.36 1.65 2.11 2.52 3.00 4.49 Model 2D Top-up between 09_435_1_RPS & 0.186 0.052 0.05 0.08 0.09 0.11 0.15 0.17 0.21 0.31 Model 2D 09_36_2 UN_Inter_Camac_1 0.099 0.025 0.03 0.04 0.05 0.05 0.07 0.08 0.10 0.15 Model 2D UN_Trib_Camac_10 0.144 0.036 0.04 0.05 0.06 0.08 0.10 0.12 0.14 0.21 Model 2D UN_Trib_Camac_20 0.233 0.073 0.07 0.11 0.13 0.16 0.20 0.24 0.29 0.43 Model 2D 09_464_1 1.014 0.681 0.68 0.99 1.23 1.49 1.90 2.26 2.70 4.04 Model 2D 09_396_U 0.250 0.142 0.14 0.21 0.26 0.31 0.40 0.47 0.56 0.84 Model 2D 09_396_1 0.857 0.254 0.25 0.37 0.46 0.55 0.71 0.84 1.01 1.51 Model 2D Top-up between 09_396_U & 0.607 0.187 0.19 0.27 0.34 0.41 0.52 0.62 0.74 1.11 Model 2D 09_396_1 09_586_3 4.066 1.443 1.44 2.10 2.59 3.15 4.01 4.79 5.71 8.55 Model 2
Flows for AEP AREA Model Node ID_CFRAMS Qmed (km2) 50% 20% 10% 5% 2% 1% 0.5% 0.1% number (2) (5) (10) (20) (50) (100) (200) (1000) Top-up between 09_464_1 & 2.195 0.750 0.75 1.09 1.35 1.64 2.09 2.49 2.97 4.45 Model 2D 09_586_3 09_1308_U 0.020 0.011 0.011 0.015 0.019 0.023 0.029 0.035 0.042 0.062 Model 2D 09_618_5 1.976 0.862 0.86 1.25 1.55 1.88 2.40 2.87 3.42 5.11 Model 2D Top-up between 09_1308_U & 1.947 0.872 0.87 1.27 1.57 1.90 2.43 2.90 3.46 5.17 Model 2D 09_618_5 09_606_U 0.000 0.000 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 Model 2D 09_606_1 0.052 0.018 0.02 0.03 0.03 0.04 0.05 0.06 0.07 0.11 Model 2D 09_39_1 1.986 1.017 1.02 1.48 1.83 2.22 2.83 3.38 4.03 6.03 Model 2D 09_360_4_RPS 3.241 1.505 1.51 2.19 2.71 3.28 4.19 5.00 5.96 8.92 Model 2D Top-up between 09_606_1 & 1.203 0.543 0.54 0.79 0.98 1.19 1.51 1.80 2.15 3.22 Model 2D 09_360_4_RPS 09_499_1_RPS 24.070 7.847 7.85 11.14 13.57 16.22 20.28 23.87 28.03 40.44 Model 2D Top-up between 09_472_8_RPS & 2.494 0.938 0.94 1.33 1.62 1.94 2.42 2.85 3.35 4.83 Model 2D 09_499_1_RPS 09_499_3_RPS 25.244 7.996 8.00 11.35 13.82 16.53 20.66 24.32 28.56 41.20 Model 2D Top-up between 09_499_1_RPS & 1.174 0.451 0.45 0.64 0.78 0.93 1.17 1.37 1.61 2.32 Model 2D 09_499_3_RPS 09_UN_T03_U 0.020 0.008 0.01 0.01 0.01 0.02 0.02 0.03 0.03 0.05 Model 2D 09_UN_T03_1 0.197 0.060 0.06 0.09 0.11 0.13 0.17 0.20 0.24 0.36 Model 2D Top-up between 09_UN_T03_U & 0.177 0.055 0.05 0.08 0.10 0.12 0.15 0.18 0.22 0.32 Model 2D 09_UN_T03_1 09_UN_T02_1 0.265 0.078 0.08 0.11 0.14 0.17 0.22 0.26 0.31 0.46 Model 2D Top-up between 09_UN_T02_U & 0.068 0.023 0.02 0.03 0.04 0.05 0.06 0.08 0.09 0.14 Model 2D 09_UN_T02_1 09_448_U 0.123 0.039 0.04 0.06 0.07 0.09 0.11 0.13 0.16 0.23 Model 2D 09_448_1 0.371 0.106 0.11 0.15 0.19 0.23 0.29 0.35 0.42 0.63 Model 2D
Flows for AEP AREA Model Node ID_CFRAMS 2 Qmed (km ) 50% 20% 10% 5% 2% 1% 0.5% 0.1% number (2) (5) (10) (20) (50) (100) (200) (1000) Top-up between 09_448_U & 0.248 0.074 0.07 0.11 0.13 0.16 0.21 0.25 0.29 0.44 Model 2D 09_448_1 09005_RPS 36.758 10.890 10.89 15.49 18.89 22.62 28.30 33.35 39.18 56.63 Model 2D Top-up between 09_499_3_RPS & 10.878 3.480 3.48 4.95 6.04 7.23 9.04 10.65 12.52 18.09 Model 2D 09005_RPS 09035_RPS 38.644 12.197 12.20 17.17 20.83 24.81 30.81 36.10 42.19 60.17 Model 2D Top-up between 09005_RPS & 1.886 0.720 0.72 1.01 1.23 1.46 1.82 2.13 2.49 3.55 Model 2D 09035_RPS 09_1252_U 0.806 0.151 0.15 0.22 0.27 0.33 0.42 0.50 0.60 0.90 Model 2D UN_Trib_Camac_U 1.475 0.685 0.68 1.00 1.23 1.49 1.90 2.28 2.71 4.06 Model 2D 09_1243_U 0.016 0.012 0.01 0.02 0.02 0.03 0.03 0.04 0.05 0.07 Model 2D UN_Trib_Camac_1 2.575 1.125 1.12 1.63 2.02 2.45 3.13 3.74 4.45 6.66 Model 2D Top-up between UN_Trib_Camac_U 1.100 0.528 0.53 0.77 0.95 1.15 1.47 1.75 2.09 3.13 Model 2D & UN_Trib_Camac_1 09_1243_1 2.742 1.189 1.19 1.73 2.14 2.60 3.31 3.95 4.71 7.05 Model 2D Top-up between 09_1243_U & 0.151 0.090 0.09 0.13 0.16 0.20 0.25 0.30 0.36 0.53 Model 2D 09_1243_1 09_1242_2_RPS 7.805 3.034 3.03 4.41 5.45 6.62 8.44 10.08 12.02 17.97 Model 2D Top-up between 09_1252_U & 4.257 1.759 1.76 2.56 3.16 3.84 4.89 5.85 6.97 10.42 Model 2D 09_1242_2_RPS 09_832_U 1.625 0.747 0.75 1.08 1.34 1.63 2.08 2.48 2.96 4.42 Model 2D 09_832_1 2.654 1.155 1.16 1.68 2.08 2.52 3.21 3.84 4.58 6.85 Model 2D Top-up between 09_832_U & 1.029 0.497 0.50 0.72 0.89 1.08 1.38 1.65 1.97 2.95 Model 2D 09_832_1 09_1872_9_RPS 57.907 19.535 19.53 27.15 32.72 38.70 47.74 55.65 64.72 91.29 Model 2D Top-up between 09035_RPS & 8.804 4.574 4.57 6.36 7.66 9.06 11.18 13.03 15.15 21.37 Model 2D 09_1872_9_RPS
MRFS Flows for AEP HEFS Flows for AEP AREA Model Node ID_CFRAMS 2 20% 10% 5% 2% 1% 0.5% 0.1% 10% 1% 0.1% (km ) 50% (2) number (5) (10) (20) (50) (100) (200) (1000) (10) (100) (1000) 09_481_U 3.870 1.025 1.49 1.84 2.24 2.85 3.40 4.06 6.07 2.00 3.69 6.58 Model 2D 09_472_4_RPS 8.507 1.592 2.31 2.86 3.47 4.43 5.29 6.31 9.44 3.10 5.73 10.22 Model 2D Top-up between 09_481_U & 4.637 0.902 1.31 1.62 1.97 2.51 3.00 3.57 5.35 1.76 3.25 5.79 Model 2D 09_472_4_RPS 09_472_8_RPS 10.104 2.414 3.50 4.32 5.23 6.64 7.92 9.43 14.03 4.80 8.80 15.59 Model 2D Top-up between 09_472_4_RPS & 1.597 0.498 0.72 0.89 1.08 1.37 1.63 1.94 2.89 1.05 1.93 3.42 Model 2D 09_472_8_RPS 09_435_U 0.037 0.037 0.05 0.07 0.08 0.10 0.12 0.15 0.22 0.07 0.13 0.24 Model 2D 09_435_1_RPS 1.218 0.808 1.17 1.45 1.76 2.25 2.68 3.20 4.79 1.59 2.93 5.22 Model 2D Top-up between 09_435_U & 1.181 0.792 1.15 1.42 1.73 2.20 2.63 3.14 4.69 1.54 2.85 5.08 Model 2D 09_435_1_RPS 09_37_U 0.265 0.212 0.31 0.38 0.46 0.59 0.70 0.84 1.26 0.41 0.76 1.36 Model 2D 09_37_1 0.408 0.279 0.41 0.50 0.61 0.78 0.93 1.10 1.65 0.57 1.06 1.89 Model 2D Top-up between 09_37_U & 0.143 0.055 0.08 0.10 0.12 0.15 0.18 0.22 0.33 0.12 0.22 0.40 Model 2D 09_37_1 09_36_2 1.812 1.002 1.46 1.80 2.19 2.79 3.33 3.97 5.94 2.08 3.84 6.84 Model 2D Top-up between 09_435_1_RPS & 0.186 0.088 0.13 0.16 0.19 0.25 0.29 0.35 0.52 0.21 0.39 0.70 Model 2D 09_36_2 UN_Inter_Camac_1 0.099 0.047 0.07 0.09 0.10 0.13 0.16 0.19 0.28 0.12 0.23 0.41 Model 2D UN_Trib_Camac_10 0.144 0.067 0.10 0.12 0.15 0.19 0.22 0.27 0.40 0.17 0.32 0.58 Model 2D UN_Trib_Camac_20 0.233 0.124 0.18 0.22 0.27 0.34 0.41 0.49 0.73 0.17 0.32 0.56 Model 2D 09_464_1 1.014 0.817 1.19 1.47 1.78 2.27 2.72 3.24 4.84 1.59 2.94 5.25 Model 2D 09_396_U 0.250 0.183 0.27 0.33 0.40 0.51 0.61 0.73 1.09 0.38 0.70 1.25 Model 2D 09_396_1 0.857 0.387 0.56 0.70 0.84 1.08 1.29 1.53 2.29 0.93 1.73 3.08 Model 2D
MRFS Flows for AEP HEFS Flows for AEP AREA Model Node ID_CFRAMS 2 20% 10% 5% 2% 1% 0.5% 0.1% 10% 1% 0.1% (km ) 50% (2) number (5) (10) (20) (50) (100) (200) (1000) (10) (100) (1000) Top-up between 09_396_U & 0.607 0.311 0.45 0.56 0.68 0.87 1.03 1.23 1.84 0.82 1.51 2.70 Model 2D 09_396_1 09_586_3 4.066 1.905 2.77 3.42 4.16 5.30 6.33 7.54 11.29 4.24 7.84 13.97 Model 2D Top-up between 09_464_1 & 2.195 1.133 1.65 2.04 2.47 3.15 3.77 4.49 6.71 2.69 4.98 8.87 Model 2D 09_586_3 09_1308_U 0.020 0.018 0.027 0.033 0.040 0.051 0.061 0.072 0.108 0.036 0.066 0.117 Model 2D 09_618_5 1.976 1.255 1.82 2.26 2.74 3.49 4.17 4.97 7.44 2.45 4.52 8.06 Model 2D Top-up between 09_1308_U & 1.947 1.252 1.82 2.25 2.73 3.48 4.16 4.96 7.42 2.44 4.51 8.04 Model 2D 09_618_5 09_606_U 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 Model 2D 09_606_1 0.052 0.028 0.04 0.05 0.06 0.08 0.09 0.11 0.17 0.07 0.13 0.24 Model 2D 09_39_1 1.986 1.292 1.88 2.32 2.82 3.59 4.29 5.12 7.65 2.52 4.65 8.29 Model 2D 09_360_4_RPS 3.241 2.519 3.66 4.53 5.50 7.01 8.37 9.98 14.92 5.03 9.30 16.58 Model 2D Top-up between 09_606_1 & 1.203 0.828 1.20 1.49 1.81 2.30 2.75 3.28 4.91 1.99 3.68 6.56 Model 2D 09_360_4_RPS 09_499_1_RPS 24.070 9.916 14.07 17.15 20.50 25.62 30.17 35.42 51.10 20.74 36.50 61.82 Model 2D Top-up between 09_472_8_RPS & 2.494 1.388 1.97 2.40 2.87 3.59 4.22 4.96 7.15 3.16 5.57 9.43 Model 2D 09_499_1_RPS 09_499_3_RPS 25.244 10.067 14.29 17.41 20.81 26.01 30.62 35.96 51.88 21.05 37.04 62.74 Model 2D Top-up between 09_499_1_RPS & 1.174 0.665 0.94 1.15 1.37 1.72 2.02 2.37 3.43 1.52 2.67 4.52 Model 2D 09_499_3_RPS 09_UN_T03_U 0.020 0.012 0.02 0.02 0.03 0.03 0.04 0.05 0.07 0.03 0.06 0.10 Model 2D 09_UN_T02_U 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 Model 2D
MRFS Flows for AEP HEFS Flows for AEP AREA Model Node ID_CFRAMS 2 20% 10% 5% 2% 1% 0.5% 0.1% 10% 1% 0.1% (km ) 50% (2) number (5) (10) (20) (50) (100) (200) (1000) (10) (100) (1000) 09_UN_T03_1 0.197 0.094 0.14 0.17 0.20 0.26 0.31 0.37 0.56 0.24 0.44 0.79 Model 2D Top-up between 09_UN_T03_U & 0.177 0.085 0.12 0.15 0.19 0.24 0.28 0.34 0.50 0.22 0.40 0.72 Model 2D 09_UN_T03_1 09_UN_T02_1 0.265 0.122 0.18 0.22 0.27 0.34 0.41 0.48 0.72 0.31 0.58 1.03 Model 2D Top-up between 09_UN_T02_U & 0.068 0.036 0.05 0.07 0.08 0.10 0.12 0.14 0.21 0.09 0.17 0.31 Model 2D 09_UN_T02_1 09_448_U 0.123 0.061 0.09 0.11 0.13 0.17 0.20 0.24 0.36 0.16 0.29 0.52 Model 2D 09_448_1 0.371 0.165 0.24 0.30 0.36 0.46 0.55 0.65 0.98 0.42 0.78 1.39 Model 2D Top-up between 09_448_U & 0.248 0.115 0.17 0.21 0.25 0.32 0.38 0.46 0.68 0.29 0.54 0.97 Model 2D 09_448_1 09005_RPS 36.758 17.279 24.57 29.98 35.89 44.91 52.91 62.17 89.85 29.94 52.84 89.73 Model 2D Top-up between 09_499_3_RPS & 10.878 5.521 7.85 9.58 11.47 14.35 16.91 19.86 28.71 11.19 19.75 33.53 Model 2D 09005_RPS 09035_RPS 38.644 19.320 27.20 33.00 39.30 48.80 57.19 66.83 95.31 27.08 46.93 78.22 Model 2D Top-up between 09005_RPS & 1.886 1.133 1.60 1.94 2.31 2.86 3.35 3.92 5.59 2.10 3.63 6.06 Model 2D 09035_RPS
09_1252_U 0.806 0.267 0.39 0.48 0.58 0.74 0.89 1.06 1.58 0.72 1.33 2.38 Model 2D UN_Trib_Camac_U 1.475 0.891 1.29 1.60 1.94 2.48 2.96 3.53 5.28 1.74 3.21 5.72 Model 2D 09_1243_U 0.016 0.015 0.02 0.03 0.03 0.04 0.05 0.06 0.09 0.03 0.06 0.10 Model 2D UN_Trib_Camac_1 2.575 1.463 2.13 2.63 3.19 4.07 4.86 5.80 8.67 2.85 5.27 9.39 Model 2D Top-up between UN_Trib_Camac_U 1.100 0.686 1.00 1.23 1.50 1.91 2.28 2.72 4.07 1.34 2.47 4.40 Model 2D & UN_Trib_Camac_1
MRFS Flows for AEP HEFS Flows for AEP AREA Model Node ID_CFRAMS 2 20% 10% 5% 2% 1% 0.5% 0.1% 10% 1% 0.1% (km ) 50% (2) number (5) (10) (20) (50) (100) (200) (1000) (10) (100) (1000) 09_1243_1 2.742 1.547 2.25 2.78 3.38 4.30 5.14 6.13 9.17 3.01 5.57 9.93 Model 2D Top-up between 09_1243_U & 0.151 0.117 0.17 0.21 0.26 0.33 0.39 0.46 0.69 0.23 0.42 0.75 Model 2D 09_1243_1 09_1242_2_RPS 7.805 3.935 5.72 7.07 8.59 10.94 13.07 15.58 23.31 7.66 14.16 25.25 Model 2D Top-up between 09_1252_U & 4.257 2.289 3.33 4.11 4.99 6.36 7.60 9.06 13.56 4.46 8.24 14.69 Model 2D 09_1242_2_RPS
09_832_U 1.625 0.971 1.41 1.75 2.12 2.70 3.23 3.85 5.75 1.89 3.50 6.23 Model 2D 09_832_1 2.654 1.503 2.18 2.70 3.28 4.18 4.99 5.95 8.90 2.93 5.41 9.64 Model 2D Top-up between 09_832_U & 1.029 0.647 0.94 1.16 1.41 1.80 2.15 2.56 3.83 1.26 2.33 4.15 Model 2D 09_832_1 09_1872_9_RPS 57.907 26.860 37.34 44.99 53.21 65.65 76.52 88.99 125.52 50.36 85.65 140.49 Model 2D Top-up between 09035_RPS & 8.804 5.489 7.63 9.19 10.87 13.41 15.64 18.18 25.65 9.96 16.94 27.79 Model 2D 09_1872_9_RPS
Input flows Top-up flows. These flows should be entered laterally Check flows. Modellers to check to ensure these flows are being reached at each HEP
Model 2E – Poddle Total Rainfall Sums – Present Day Extrapolated AEP 50% 20% 10% 5% 3.30% 2% 1% 0.67% 0.50% 0.10% RP (yrs.) 2 5 10 20 30 50 100 150 200 1000 15 mins 7.10 10.80 13.70 17.20 19.50 22.80 28.10 31.80 34.70 51.00 30 mins 9.20 13.80 17.40 21.60 24.40 28.40 34.80 39.20 42.60 64.00 1 hour 11.90 17.60 22.00 27.10 30.50 35.30 43.00 48.20 52.30 77.00 2 hour 15.50 22.50 27.90 34.10 38.20 44.00 53.20 59.30 64.10 91.00 3 hour 18.00 25.90 32.10 39.00 43.60 50.10 60.20 67.00 72.30 103.00 4 hour 20.10 28.70 35.40 42.90 47.90 54.80 65.70 73.10 78.70 112.00 6 hour 23.40 33.20 40.70 49.10 54.60 62.30 74.40 82.50 88.70 125.00 9 hour 27.20 38.30 46.70 56.10 62.30 70.90 84.30 93.20 100.10 139.00 12 hour 30.30 42.40 51.60 61.70 68.40 77.60 92.00 101.60 108.90 150.00 18 hour 35.30 48.90 59.20 70.60 78.00 88.30 104.20 114.70 122.80 168.00 1 day 38.80 53.30 64.20 76.20 83.90 94.60 111.20 122.10 130.50 179.00 2 days 46.70 62.80 74.60 87.40 95.60 106.90 124.20 135.50 144.10 194.00 3 days 53.10 70.40 83.00 96.60 105.30 117.10 135.10 146.80 155.70 207.00 4 days 58.70 77.10 90.40 104.60 113.70 126.00 144.70 156.70 165.90 218.00 6 days 68.40 88.60 103.10 118.50 128.20 141.40 161.30 174.00 183.70 249.00 8 days 76.90 98.70 114.10 130.60 140.90 154.80 175.70 189.10 199.20 257.00 10 days 84.60 107.80 124.20 141.50 152.30 166.90 188.70 202.70 213.20 272.00 12 days 91.80 116.20 133.40 151.50 162.80 178.10 200.70 215.20 226.00 288.00 16 days 105.00 131.70 150.40 169.90 182.10 198.40 222.50 237.90 249.40 314.00 20 days 117.10 145.80 165.80 186.60 199.50 216.70 242.20 258.40 270.50 349.00 25 days 131.20 162.20 183.60 205.80 219.50 237.90 264.90 282.00 294.70 368.00
Total Rainfall Sums ‐ MRFS Extrapolated AEP 50% 20% 10% 5% 3.30% 2% 1% 0.67% 0.50% 0.10% RP (yrs.) 2 5 10 20 30 50 100 150 200 1000 15 mins 8.52 12.96 16.44 20.64 23.40 27.36 33.72 38.16 41.64 61.20 30 mins 11.04 16.56 20.88 25.92 29.28 34.08 41.76 47.04 51.12 76.80 1 hour 14.28 21.12 26.40 32.52 36.60 42.36 51.60 57.84 62.76 92.40 2 hour 18.60 27.00 33.48 40.92 45.84 52.80 63.84 71.16 76.92 109.20 3 hour 21.60 31.08 38.52 46.80 52.32 60.12 72.24 80.40 86.76 123.60 4 hour 24.12 34.44 42.48 51.48 57.48 65.76 78.84 87.72 94.44 134.40 6 hour 28.08 39.84 48.84 58.92 65.52 74.76 89.28 99.00 106.44 150.00 9 hour 32.64 45.96 56.04 67.32 74.76 85.08 101.16 111.84 120.12 166.80 12 hour 36.36 50.88 61.92 74.04 82.08 93.12 110.40 121.92 130.68 180.00 18 hour 42.36 58.68 71.04 84.72 93.60 105.96 125.04 137.64 147.36 201.60 1 day 46.56 63.96 77.04 91.44 100.68 113.52 133.44 146.52 156.60 214.80 2 days 56.04 75.36 89.52 104.88 114.72 128.28 149.04 162.60 172.92 232.80 3 days 63.72 84.48 99.60 115.92 126.36 140.52 162.12 176.16 186.84 248.40 4 days 70.44 92.52 108.48 125.52 136.44 151.20 173.64 188.04 199.08 261.60 6 days 82.08 106.32 123.72 142.20 153.84 169.68 193.56 208.80 220.44 298.80 8 days 92.28 118.44 136.92 156.72 169.08 185.76 210.84 226.92 239.04 308.40 10 days 101.52 129.36 149.04 169.80 182.76 200.28 226.44 243.24 255.84 326.40 12 days 110.16 139.44 160.08 181.80 195.36 213.72 240.84 258.24 271.20 345.60 16 days 126.00 158.04 180.48 203.88 218.52 238.08 267.00 285.48 299.28 376.80 20 days 140.52 174.96 198.96 223.92 239.40 260.04 290.64 310.08 324.60 418.80 25 days 157.44 194.64 220.32 246.96 263.40 285.48 317.88 338.40 353.64 441.60
Total Rainfall Sums ‐ HEFS Extrapolated AEP 50% 20% 10% 5% 3.30% 2% 1% 0.67% 0.50% 0.10% RP (yrs.) 2 5 10 20 30 50 100 150 200 1000 15 mins 9.23 14.04 17.81 22.36 25.35 29.64 36.53 41.34 45.11 66.30 30 mins 11.96 17.94 22.62 28.08 31.72 36.92 45.24 50.96 55.38 83.20 1 hour 15.47 22.88 28.60 35.23 39.65 45.89 55.90 62.66 67.99 100.10 2 hour 20.15 29.25 36.27 44.33 49.66 57.20 69.16 77.09 83.33 118.30 3 hour 23.40 33.67 41.73 50.70 56.68 65.13 78.26 87.10 93.99 133.90 4 hour 26.13 37.31 46.02 55.77 62.27 71.24 85.41 95.03 102.31 145.60 6 hour 30.42 43.16 52.91 63.83 70.98 80.99 96.72 107.25 115.31 162.50 9 hour 35.36 49.79 60.71 72.93 80.99 92.17 109.59 121.16 130.13 180.70 12 hour 39.39 55.12 67.08 80.21 88.92 100.88 119.60 132.08 141.57 195.00 18 hour 45.89 63.57 76.96 91.78 101.40 114.79 135.46 149.11 159.64 218.40 1 day 50.44 69.29 83.46 99.06 109.07 122.98 144.56 158.73 169.65 232.70 2 days 60.71 81.64 96.98 113.62 124.28 138.97 161.46 176.15 187.33 252.20 3 days 69.03 91.52 107.90 125.58 136.89 152.23 175.63 190.84 202.41 269.10 4 days 76.31 100.23 117.52 135.98 147.81 163.80 188.11 203.71 215.67 283.40 6 days 88.92 115.18 134.03 154.05 166.66 183.82 209.69 226.20 238.81 323.70 8 days 99.97 128.31 148.33 169.78 183.17 201.24 228.41 245.83 258.96 334.10 10 days 109.98 140.14 161.46 183.95 197.99 216.97 245.31 263.51 277.16 353.60 12 days 119.34 151.06 173.42 196.95 211.64 231.53 260.91 279.76 293.80 374.40 16 days 136.50 171.21 195.52 220.87 236.73 257.92 289.25 309.27 324.22 408.20 20 days 152.23 189.54 215.54 242.58 259.35 281.71 314.86 335.92 351.65 453.70 25 days 170.56 210.86 238.68 267.54 285.35 309.27 344.37 366.60 383.11 478.40
Model 3A – Leixlip Flows for AEP AREA Model Node ID_CFRAMS 2 Qmed 10% 1% 0.5% 0.1% (km ) 50% (2) 20% (5) 5% (20) 2% (50) number (10) (100) (200) (1000)
09_284_2_RPS 502.06 62.82 62.82 77.27 86.76 96.50 110.19 121.50 133.75 166.42 Model 3A 09_1260_4_RPS 194.96 33.39 33.39 42.44 48.85 55.56 65.44 73.92 83.37 108.65 Model 3A 09_994_1 1.52 0.24 0.24 0.35 0.43 0.52 0.67 0.80 0.95 1.42 Model 3A 09_1137_1 3.62 0.59 0.59 0.85 1.06 1.28 1.63 1.95 2.32 3.48 Model 3A 09_1137_5 4.86 0.76 0.76 1.10 1.36 1.66 2.11 2.52 3.01 4.50 Model 3A Top-up flow between 09_1137_1 and 1.23 0.22 0.22 0.33 0.40 0.49 0.62 0.74 0.89 1.33 Model 3A 09_1137_5 09_1246_U 0.02 0.00 0.00 0.01 0.01 0.01 0.01 0.02 0.02 0.03 Model 3A 09_1246_1 0.56 0.11 0.11 0.16 0.20 0.24 0.31 0.37 0.44 0.65 Model 3A 09001_RPS 208.53 33.70 33.70 42.83 49.30 56.08 66.05 74.61 84.15 109.66 Model 3A Top-up between 09_1260_4_RPS & 8.15 1.55 1.55 1.97 2.27 2.58 3.04 3.43 3.87 5.04 Model 3A 09001_RPS 09_246_4_RPS 209.13 34.52 34.52 43.88 50.50 57.44 67.66 76.43 86.20 113.37 Model 3A 09022_RPS 718.68 94.01 94.01 115.63 129.83 143.93 163.48 179.18 196.01 239.63 Model 3A Top-up between 09_284_2_RPS and 5.98 1.06 1.06 1.30 1.46 1.62 1.84 2.01 2.20 2.69 Model 3A 09022_RPS 09_1050_U 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 Model 3A 09_346_3 2.37 0.40 0.40 0.58 0.72 0.87 1.11 1.32 1.58 2.36 Model 3A 09_1050_1 0.87 0.16 0.16 0.24 0.30 0.36 0.46 0.55 0.65 0.97 Model 3A 09_584_4_RPS 5.34 0.95 0.95 1.38 1.71 2.07 2.64 3.15 3.76 5.62 Model 3A Top-up between 09_346_3 and 2.10 0.41 0.41 0.60 0.74 0.90 1.15 1.38 1.64 2.45 Model 3A 09_584_4
Flows for AEP AREA Model Node ID_CFRAMS 2 Qmed 10% 1% 0.5% 0.1% (km ) 50% (2) 20% (5) 5% (20) 2% (50) number (10) (100) (200) (1000) n.a. 0.20 0.04 0.04 0.06 0.07 0.09 0.12 0.14 0.17 0.25 Model 3A 09_1239_6_RPS 730.00 94.98 94.98 116.82 131.17 145.41 165.17 181.03 198.03 242.10 Model 3A Top-up between 09022_RPS & 5.97 1.05 1.05 1.32 1.49 1.66 1.91 2.12 2.34 2.93 Model 3A 09_1239_6_RPS
Input flows Top-up flows. These flows should be entered laterally Check flows. Modellers to check to ensure these flows are being reached at each HEP
MRFS Flows for AEP HEFS Flows for AEP AREA Model Node ID_CFRAMS 2 10% 1% 0.5% 0.1% 10% 1% 0.1% (km ) 50% (2) 20% (5) 5% (20) 2% (50) number (10) (100) (200) (1000) (10) (100) (1000) 09_284_2_RPS 502.06 81.77 100.57 112.92 125.59 143.42 158.13 174.08 216.60 173.63 243.16 333.06 Model 3A 09_1260_4_RPS 194.96 41.88 53.23 61.27 69.69 82.08 92.72 104.57 136.28 82.58 124.97 183.68 Model 3A 09_994_1 1.52 0.36 0.52 0.65 0.79 1.00 1.20 1.43 2.13 1.73 3.20 5.70 Model 3A 09_1137_1 3.62 0.74 1.08 1.34 1.62 2.07 2.47 2.95 4.41 1.71 3.15 5.62 Model 3A 09_1137_5 4.86 1.20 1.74 2.16 2.62 3.34 3.99 4.75 7.11 3.02 5.57 9.94 Model 3A Top-up flow between 09_1137_1 and 1.23 0.61 0.89 1.10 1.34 1.70 2.03 2.42 3.63 1.85 3.41 6.08 Model 3A 09_1137_5 09_1246_U 0.02 0.01 0.01 0.01 0.01 0.02 0.02 0.02 0.04 0.02 0.04 0.08 Model 3A 09_1246_1 0.56 0.30 0.44 0.54 0.65 0.83 1.00 1.19 1.78 0.91 1.68 3.00 Model 3A 09001_RPS 208.53 43.33 55.07 63.39 72.10 84.93 95.94 108.20 141.00 95.00 143.77 211.30 Model 3A
MRFS Flows for AEP HEFS Flows for AEP AREA Model Node ID_CFRAMS 2 10% 1% 0.5% 0.1% 10% 1% 0.1% (km ) 50% (2) 20% (5) 5% (20) 2% (50) number (10) (100) (200) (1000) (10) (100) (1000) Top-up between 09_1260_4_RPS & 8.15 3.25 4.13 4.76 5.41 6.37 7.20 8.12 10.58 7.02 10.62 15.61 Model 3A 09001_RPS 09_246_4_RPS 209.13 44.65 56.75 65.33 74.30 87.52 98.86 111.50 146.64 100.25 151.71 225.03 Model 3A 09022_RPS 718.68 121.80 149.81 168.21 186.48 211.81 232.15 253.95 310.47 259.80 358.56 479.53 Model 3A Top-up between 09_284_2_RPS and 5.98 1.37 1.68 1.89 2.09 2.38 2.61 2.85 3.49 2.93 4.04 5.40 Model 3A 09022_RPS 09_1050_U 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 Model 3A 09_346_3 2.37 0.50 0.73 0.91 1.10 1.40 1.67 2.00 2.99 1.17 2.16 3.85 Model 3A 09_1050_1 0.87 0.20 0.30 0.37 0.45 0.57 0.68 0.81 1.21 0.47 0.86 1.54 Model 3A 09_584_4_RPS 5.34 1.43 2.07 2.57 3.12 3.97 4.75 5.66 8.46 3.81 7.04 12.56 Model 3A Top-up between 09_346_3 and 2.10 0.64 0.92 1.14 1.39 1.77 2.11 2.52 3.77 2.95 5.45 9.71 Model 3A 09_584_4 n.a. 0.20 0.05 0.08 0.10 0.12 0.16 0.19 0.23 0.34 0.14 0.27 0.49 Model 3A 09_1239_6_RPS 730.00 123.23 151.57 170.18 188.66 214.29 234.87 256.93 314.11 264.27 364.74 487.79 Model 3A Top-up between 09022_RPS & 5.97 1.37 1.71 1.94 2.16 2.49 2.75 3.04 3.81 3.00 4.26 5.90 Model 3A 09_1239_6_RPS
Input flows Top-up flows. These flows should be entered laterally Check flows. Modellers to check to ensure these flows are being reached at each HEP
Model 3B – Celbridge & Hazelhatch Flows for AEP AREA Model Node ID_CFRAMS 2 Qmed 10% 1% 0.5% 0.1% (km ) 50% (2) 20% (5) 5% (20) 2% (50) number (10) (100) (200) (1000) 09034_RPS 337.31 43.17 43.17 53.10 59.62 66.31 75.73 83.50 91.92 114.37 Model 3B 09_1627_6_RPS 98.49 20.52 20.52 27.12 31.78 36.64 43.78 49.86 56.65 75.75 Model 3B 09_426_5_RPS 12.60 1.42 1.42 2.04 2.52 3.05 3.88 4.63 5.51 8.23 Model 3B 09_1579_U 2.00 0.27 0.27 0.39 0.48 0.58 0.74 0.88 1.05 1.57 Model 3B 09_727_U 0.06 0.02 0.02 0.03 0.04 0.04 0.06 0.07 0.08 0.12 Model 3B 09_727_2_RPS 0.37 0.07 0.07 0.10 0.12 0.14 0.18 0.22 0.26 0.39 Model 3B Top-up between 09_727_U 0.31 0.05 0.05 0.07 0.09 0.11 0.14 0.17 0.20 0.30 Model 3B & 09_727_2_RPS 09_1069_2_RPS 6.52 0.78 0.78 1.13 1.40 1.70 2.16 2.58 3.08 4.61 Model 3B Top-up flow between 09_1579_U & 4.15 0.52 0.52 0.76 0.94 1.13 1.45 1.73 2.06 3.08 Model 3B 09_1069_2_RPS 09_294_1_RPS 472.81 55.73 55.73 68.55 76.96 85.60 97.75 107.78 118.65 147.63 Model 3B Top-up flow between 09034_RPS & 17.88 3.38 3.38 4.16 4.67 5.19 5.93 6.54 7.20 8.95 Model 3B 09_294_1_RPS 09_1126_U 0.26 0.04 0.04 0.06 0.08 0.09 0.12 0.14 0.17 0.26 Model 3B 09_1126_1 1.09 0.19 0.19 0.28 0.35 0.42 0.54 0.64 0.77 1.15 Model 3B Top-up between 0.83 0.16 0.16 0.24 0.29 0.35 0.45 0.54 0.64 0.96 Model 3B 09_1126_U & 09_1126_1 09_1668_2_RPS 474.37 55.90 55.90 68.76 77.20 85.87 98.05 108.12 119.02 148.09 Model 3B Top-up between 09_241_1_RPS & 0.47 0.13 0.13 0.16 0.19 0.21 0.24 0.26 0.29 0.36 Model 3B 09_1668_2_RPS 09_292_1_RPS 475.13 55.94 55.94 68.81 77.26 85.93 98.12 108.19 119.10 148.19 Model 3B Top-up between 09_1668_2_RPS & 0.76 0.20 0.20 0.25 0.28 0.31 0.36 0.39 0.43 0.54 Model 3B 09_292_1_RPS
Flows for AEP AREA Model Node ID_CFRAMS 2 Qmed 10% 1% 0.5% 0.1% (km ) 50% (2) 20% (5) 5% (20) 2% (50) number (10) (100) (200) (1000) 09_1245_U 0.76 0.14 0.14 0.21 0.26 0.31 0.40 0.47 0.56 0.84 Model 3B 09_1245_6_RPS 2.98 1.04 1.04 1.51 1.87 2.26 2.89 3.45 4.11 6.15 Model 3B Top-up between 2.22 0.80 0.80 1.16 1.44 1.74 2.22 2.66 3.17 4.73 Model 3B 09_1245_U & 09_1245_6 09006_RPS 478.58 56.49 56.49 69.49 78.02 86.77 99.09 109.26 120.27 149.65 Model 3B Top-up between 09_292_1_RPS & 0.46 0.13 0.13 0.16 0.18 0.20 0.23 0.25 0.28 0.35 Model 3B 09006_RPS UN_Trib_Liffey_U 2.12 0.36 0.36 0.52 0.64 0.78 1.00 1.19 1.42 2.12 Model 3B UN_Liffey_Inter 4.04 0.65 0.65 0.95 1.18 1.43 1.82 2.17 2.59 3.88 Model 3B Top-up between UN_Trib_Liffey_U & 1.92 0.33 0.33 0.47 0.59 0.71 0.91 1.08 1.29 1.93 Model 3B UN_Liffey_Inter Top-up at UN_Liffey_Inter N/A 0.24 0.24 0.33 0.42 0.51 0.64 0.77 0.91 1.37 Model 3B
UN_Trib_Liffey_1 5.21 1.04 1.04 1.51 1.87 2.26 2.89 3.45 4.11 6.15 Model 3B Top-up between UN_Liffey_Inter & 1.18 0.42 0.42 0.61 0.75 0.91 1.16 1.38 1.65 2.47 Model 3B UN_Trib_Liffey_1 09_299_3_RPS 484.93 56.55 56.55 69.56 78.09 86.86 99.19 109.37 120.39 149.80 Model 3B Top-up between 09006_RPS & 1.14 0.29 0.29 0.36 0.40 0.45 0.51 0.57 0.62 0.78 Model 3B 09_299_3_RPS 09_467_U 1.33 0.21 0.21 0.30 0.38 0.46 0.58 0.70 0.83 1.24 Model 3B 09_467_8 3.43 0.54 0.54 0.79 0.97 1.18 1.50 1.80 2.14 3.20 Model 3B Top-up between 09_467_U 2.10 0.35 0.35 0.51 0.63 0.76 0.97 1.16 1.38 2.07 Model 3B & 09_467_8 09_300_1_RPS 488.26 56.86 56.86 69.93 78.52 87.33 99.73 109.96 121.05 150.62 Model 3B 09_501_U 1.39 0.22 0.22 0.32 0.40 0.48 0.61 0.73 0.87 1.30 Model 3B
Flows for AEP AREA Model Node ID_CFRAMS 2 Qmed 10% 1% 0.5% 0.1% (km ) 50% (2) 20% (5) 5% (20) 2% (50) number (10) (100) (200) (1000) Overflow from Baldonnel N/A 1.28 1.28 1.40 1.45 1.55 1.64 1.75 1.78 1.92 Model 3B Canal Overflow N/A 2.32 2.32 3.28 3.97 4.72 5.86 6.86 8.00 11.36 Model 3B 09_501_Trib 0.03 0.02 0.02 0.02 0.03 0.03 0.04 0.05 0.06 0.09 Model 3B 09_501_Inter 10.31 1.44 5.04 6.76 8.01 9.42 11.52 13.43 15.55 21.97 Model 3B Top-up between 09_501_U 8.91 1.25 1.25 1.82 2.26 2.75 3.51 4.21 5.03 7.58 Model 3B & 09_501_Inter 09_501_Inter_1 11.49 1.59 5.20 6.99 8.29 9.75 11.96 13.95 16.17 22.91 Model 3B Top-up between 09_501_Inter & 1.19 0.19 0.19 0.28 0.34 0.42 0.53 0.64 0.76 1.15 Model 3B 09_501_Inter_1 09_501_7_RPS 12.76 1.78 5.39 7.19 8.48 9.90 12.00 13.88 15.93 22.01 Model 3B Top-up between 09_501_Inter_1 & 1.26 0.24 0.24 0.33 0.41 0.48 0.60 0.70 0.82 1.16 Model 3B 09_501_7_RPS 09_284_2_RPS 502.06 62.82 62.82 77.27 86.76 96.50 110.19 121.50 133.75 166.42 Model 3B Top-up between 09_300_1_RPS & 1.04 0.24 0.24 0.29 0.33 0.36 0.41 0.46 0.50 0.62 Model 3B 09_284_2_RPS
Input flows Top-up flows. These flows should be entered laterally Check flows. Modellers to check to ensure these flows are being reached at each HEP
MRFS Flows for AEP HEFS Flows for AEP AREA Model Node ID_CFRAMS 2 10% 1% 0.5% 0.1% 10% 1% 0.1% (km ) 50% (2) 20% (5) 5% (20) 2% (50) number (10) (100) (200) (1000) (10) (100) (1000) 09034_RPS 337.31 55.73 68.55 76.97 85.61 97.77 107.80 118.67 147.65 117.06 163.94 224.55 Model 3B 09_1627_6_RPS 98.49 26.35 34.83 40.81 47.06 56.23 64.03 72.75 97.28 60.82 95.42 144.96 Model 3B 09_426_5_RPS 12.60 1.79 2.58 3.18 3.85 4.90 5.85 6.96 10.40 4.09 7.51 13.35 Model 3B 09_1579_U 2.00 0.34 0.49 0.60 0.72 0.92 1.09 1.31 1.95 0.77 1.41 2.52 Model 3B 09_727_U 0.06 0.05 0.08 0.10 0.10 0.15 0.18 0.20 0.30 0.11 0.20 0.34 Model 3B 09_727_2_RPS 0.37 0.18 0.26 0.31 0.36 0.46 0.56 0.66 1.00 0.49 0.89 1.58 Model 3B Top-up between 09_727_U & 0.31 0.14 0.20 0.26 0.31 0.40 0.48 0.57 0.85 0.43 0.82 1.45 Model 3B 09_727_2_RPS 09_1069_2_RPS 6.52 1.72 2.49 3.09 3.75 4.76 5.69 6.79 10.17 6.48 11.94 21.33 Model 3B Top-up flow between 09_1579_U & 4.15 1.42 2.07 2.57 3.09 3.96 4.72 5.62 8.41 4.36 8.03 14.30 Model 3B 09_1069_2_RPS 09_294_1_RPS 472.81 71.68 88.17 98.99 110.10 125.73 138.63 152.61 189.89 148.33 207.74 284.54 Model 3B Top-up flow between 09034_RPS & 17.88 4.39 5.41 6.07 6.75 7.71 8.50 9.36 11.63 9.62 13.48 18.44 Model 3B 09_294_1_RPS 09_1126_U 0.26 0.12 0.18 0.24 0.27 0.36 0.42 0.51 0.78 0.41 0.71 1.33 Model 3B 09_1126_1 1.09 0.39 0.57 0.71 0.86 1.10 1.30 1.57 2.34 1.35 2.48 4.45 Model 3B Top-up between 09_1126_U & 0.83 0.29 0.44 0.53 0.64 0.83 0.99 1.17 1.76 1.05 1.95 3.47 Model 3B 09_1126_1 09_1668_2_RPS 474.37 71.99 88.55 99.42 110.58 126.27 139.23 153.27 190.71 149.67 209.61 287.10 Model 3B Top-up between 09_241_1_RPS & 0.47 0.17 0.21 0.26 0.28 0.32 0.35 0.39 0.48 0.41 0.56 0.77 Model 3B 09_1668_2_RPS 09_292_1_RPS 475.13 72.19 88.79 99.70 110.88 126.61 139.61 153.69 191.23 151.34 211.93 290.28 Model 3B
MRFS Flows for AEP HEFS Flows for AEP AREA Model Node ID_CFRAMS 2 10% 1% 0.5% 0.1% 10% 1% 0.1% (km ) 50% (2) 20% (5) 5% (20) 2% (50) number (10) (100) (200) (1000) (10) (100) (1000) Top-up between 09_1668_2_RPS & 0.76 0.27 0.33 0.37 0.41 0.48 0.52 0.57 0.72 0.60 0.83 1.15 Model 3B 09_292_1_RPS 09_1245_U 0.76 0.18 0.27 0.33 0.39 0.51 0.60 0.71 1.07 0.41 0.73 1.31 Model 3B 09_1245_6_RPS 2.98 1.41 2.04 2.53 3.05 3.91 4.66 5.55 8.31 2.82 5.20 9.26 Model 3B Top-up between 09_1245_U & 2.22 1.10 1.59 1.98 2.39 3.05 3.65 4.35 6.49 2.14 3.96 7.03 Model 3B 09_1245_6 09006_RPS 478.58 73.08 89.89 100.93 112.25 128.18 141.34 155.58 193.59 154.75 216.72 296.83 Model 3B Top-up between 09_292_1_RPS & 0.46 0.17 0.21 0.24 0.26 0.30 0.33 0.37 0.46 0.39 0.54 0.75 Model 3B 09006_RPS UN_Trib_Liffey_U 2.12 0.44 0.64 0.79 0.96 1.23 1.47 1.75 2.62 0.98 1.80 3.21 Model 3B UN_Liffey_Inter 4.04 0.81 1.18 1.46 1.77 2.26 2.70 3.22 4.81 1.79 3.31 5.91 Model 3B Top-up between UN_Trib_Liffey_U & 1.92 0.40 0.58 0.72 0.88 1.12 1.34 1.59 2.38 0.89 1.64 2.93 Model 3B UN_Liffey_Inter Top-up at N/A 0.29 0.40 0.51 0.62 0.78 0.93 1.11 1.66 0.55 1.01 1.80 Model 3B UN_Liffey_Inter UN_Trib_Liffey_1 5.21 1.44 2.10 2.60 3.15 4.02 4.80 5.72 8.56 5.15 9.51 16.96 Model 3B Top-up between UN_Liffey_Inter & 1.18 0.72 1.04 1.29 1.57 2.00 2.39 2.85 4.26 1.40 2.59 4.61 Model 3B UN_Trib_Liffey_1 09_299_3_RPS 484.93 73.31 90.18 101.24 112.61 128.59 141.79 156.08 194.21 156.63 219.38 300.47 Model 3B Top-up between 09006_RPS & 1.14 0.38 0.48 0.53 0.60 0.68 0.75 0.82 1.03 0.87 1.24 1.70 Model 3B 09_299_3_RPS 09_467_U 1.33 0.52 0.74 0.94 1.13 1.43 1.72 2.04 3.05 1.59 2.93 5.19 Model 3B 09_467_8 3.43 1.20 1.75 2.15 2.62 3.33 4.00 4.75 7.11 3.66 6.79 12.08 Model 3B
MRFS Flows for AEP HEFS Flows for AEP AREA Model Node ID_CFRAMS 2 10% 1% 0.5% 0.1% 10% 1% 0.1% (km ) 50% (2) 20% (5) 5% (20) 2% (50) number (10) (100) (200) (1000) (10) (100) (1000) Top-up between 09_467_U & 2.10 0.77 1.13 1.39 1.68 2.14 2.56 3.05 4.58 2.37 4.36 7.78 Model 3B 09_467_8 09_300_1_RPS 488.26 73.78 90.74 101.88 113.32 129.41 142.68 157.07 195.44 158.20 221.54 303.46 Model 3B 09_501_U 1.39 0.27 0.40 0.49 0.60 0.76 0.91 1.09 1.63 0.61 1.12 2.00 Model 3B Overflow from N/A 1.54 1.68 1.74 1.86 1.97 2.10 2.14 2.31 1.89 2.28 2.50 Model 3B Baldonnel Canal Overflow N/A 2.78 3.93 4.76 5.66 7.02 8.22 9.59 13.61 5.16 8.90 14.75 Model 3B 09_501_Trib 0.03 0.02 0.03 0.03 0.04 0.05 0.06 0.07 0.11 0.04 0.06 0.12 Model 3B 09_501_Inter 10.31 6.30 8.44 10.00 11.76 14.38 16.77 19.41 27.43 12.29 20.60 33.70 Model 3B Top-up between 09_501_U & 8.91 1.56 2.27 2.82 3.43 4.38 5.25 6.28 9.46 3.46 6.45 11.63 Model 3B 09_501_Inter 09_501_Inter_1 11.49 6.49 8.72 10.35 12.18 14.92 17.41 20.18 28.60 12.72 21.39 35.13 Model 3B Top-up between 09_501_Inter & 1.19 0.24 0.34 0.43 0.52 0.66 0.79 0.95 1.43 0.52 0.98 1.76 Model 3B 09_501_Inter_1 09_501_7_RPS 12.76 6.67 8.89 10.48 12.24 14.83 17.16 19.69 27.21 13.18 21.57 34.21 Model 3B Top-up between 09_501_Inter_1 & 1.26 0.36 0.51 0.62 0.74 0.92 1.07 1.25 1.78 1.11 1.92 3.18 Model 3B 09_501_7_RPS
09_284_2_RPS 502.06 81.41 100.14 112.44 125.06 142.80 157.46 173.33 215.67 173.65 243.18 333.08 Model 3B
Top-up between 09_300_1_RPS & 1.04 0.31 0.38 0.43 0.47 0.53 0.60 0.65 0.81 0.71 0.99 1.33 Model 3B 09_284_2_RPS
Model 4 – Maynooth Flows for AEP AREA Model Node ID_CFRAMS 2 Qmed 10% 1% 0.5% 0.1% (km ) 50% (2) 20% (5) 5% (20) 2% (50) number (10) (100) (200) (1000)
09048_RPS 59.55 16.96 16.96 23.98 29.22 34.95 43.74 51.57 60.66 87.97 Model 4 09_468_1 9.23 2.35 2.35 3.41 4.22 5.12 6.52 7.79 9.29 13.90 Model 4 09_468_3 9.57 2.51 2.51 3.65 4.51 5.48 6.98 8.34 9.94 14.87 Model 4 Top-up between 0.35 0.11 0.11 0.16 0.20 0.24 0.31 0.37 0.44 0.66 Model 4 09_468_1 & 09_468_3 09_1060_1 17.40 4.22 4.22 6.15 7.62 9.25 11.81 14.12 16.85 25.27 Model 4 09_1060_3 18.00 4.31 4.31 6.27 7.77 9.44 12.05 14.41 17.20 25.79 Model 4 Top-up between 09_1060_1 & 0.60 0.18 0.18 0.26 0.32 0.39 0.50 0.60 0.71 1.07 Model 4 09_1060_3 09_1450_U 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 Model 4 09_1452_2_RPS 49.07 7.77 7.77 11.07 13.52 16.21 20.32 23.98 28.22 40.95 Model 4 09_1464_1_RPS 13.64 2.49 2.49 3.62 4.48 5.43 6.92 8.27 9.85 14.71 Model 4 Top-up between 09_1450_U & 13.64 2.49 2.49 3.62 4.48 5.43 6.92 8.27 9.85 14.71 Model 4 09_1464_1_RPS 09_1464_2_RPS 65.23 10.49 10.49 14.64 17.68 20.97 25.94 30.33 35.36 50.18 Model 4 Top-up between 09_1452_2_RPS & 2.52 0.50 0.50 0.69 0.84 0.99 1.23 1.44 1.67 2.38 Model 4 09_1464_2_RPS 09_1464_5_RPS 66.95 10.92 10.92 15.25 18.42 21.85 27.02 31.59 36.83 52.27 Model 4 Top-up between 09_1464_2_RPS & 1.72 0.38 0.38 0.53 0.63 0.75 0.93 1.09 1.27 1.80 Model 4 09_1464_5_RPS 09_1839_7 11.29 1.49 1.49 2.16 2.68 3.25 4.14 4.95 5.90 8.82 Model 4 09_1839_12_RPS 17.91 2.83 2.83 4.11 5.08 6.16 7.84 9.37 11.16 16.66 Model 4
Flows for AEP AREA Model Node ID_CFRAMS 2 Qmed 10% 1% 0.5% 0.1% (km ) 50% (2) 20% (5) 5% (20) 2% (50) number (10) (100) (200) (1000) Top-up between 09_1839_7 & 6.62 1.61 1.61 2.34 2.89 3.51 4.47 5.34 6.36 9.49 Model 4 09_1839_12_RPS 09_1444_U 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 Model 4 09_1444_4 1.60 0.58 0.58 0.85 1.05 1.28 1.63 1.94 2.32 3.46 Model 4 09049_RPS 87.50 12.40 12.40 16.81 19.99 23.40 28.47 32.88 37.89 52.37 Model 4 Top-up between 09_1464_5_RPS & 1.03 0.19 0.19 0.26 0.31 0.37 0.44 0.51 0.59 0.82 Model 4 09049_RPS 09_611_3_RPS 87.63 12.29 12.29 16.67 19.81 23.19 28.22 32.60 37.56 51.92 Model 4 09_600_2 12.02 2.38 2.38 3.43 4.23 5.12 6.52 7.77 9.26 13.82 Model 4 09_1260_4_RPS 194.96 29.78 29.78 37.85 43.56 49.55 58.36 65.93 74.35 96.90 Model 4 Top-up between 09048_RPS & 8.19 1.53 1.53 1.94 2.24 2.54 3.00 3.38 3.82 4.97 Model 4 09_1260_4_RPS
Input flows Top-up flows. These flows should be entered laterally Check flows. Modellers to check to ensure these flows are being reached at each HEP
MRFS Flows for AEP HEFS Flows for AEP AREA Model Node ID_CFRAMS 2 10% 1% 0.5% 0.1% 10% 0.1% (km ) 50% (2) 20% (5) 5% (20) 2% (50) 1% (100) number (10) (100) (200) (1000) (10) (1000) 09048_RPS 59.55 25.10 35.50 43.25 51.74 64.74 76.34 89.80 130.21 57.14 100.8487 172.0165 Model 4 09_468_1 9.23 2.93 4.25 5.26 6.39 8.14 9.73 11.60 17.35 6.47 11.95349 21.3134 Model 4 09_468_3 9.57 3.13 4.55 5.63 6.84 8.71 10.41 12.41 18.57 6.92 12.79228 22.80898 Model 4 Top-up between 09_468_1 & 0.35 0.14 0.20 0.25 0.30 0.39 0.46 0.55 0.83 0.31 0.57 1.02 Model 4 09_468_3 09_1060_1 17.40 5.27 7.67 9.51 11.55 14.74 17.63 21.04 31.55 11.68 21.66338 38.7582 Model 4 09_1060_3 18.00 5.51 8.01 9.93 12.06 15.39 18.41 21.96 32.93 12.31 22.83007 40.84554 Model 4 Top-up between 09_1060_1 & 0.60 0.39 0.57 0.71 0.86 1.09 1.31 1.56 2.34 1.04 1.93 3.46 Model 4 09_1060_3 09_1450_U 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0 0 Model 4 09_1452_2_RPS 49.07 9.67 13.77 16.82 20.16 25.28 29.83 35.10 50.93 20.66 36.6524 62.57639 Model 4 09_1464_1_RPS 13.64 3.08 4.48 5.54 6.72 8.56 10.22 12.18 18.20 7.00 12.91524 22.9864 Model 4 Top-up between 09_1450_U & 13.64 3.08 4.48 5.54 6.72 8.56 10.22 12.18 18.20 7.00 12.92 22.99 Model 4 09_1464_1_RPS 09_1464_2_RPS 65.23 13.07 18.25 22.04 26.14 32.34 37.80 44.08 62.55 27.24 46.71747 77.29706 Model 4 Top-up between 09_1452_2_RPS & 2.52 0.62 0.86 1.04 1.24 1.53 1.79 2.08 2.96 1.28 2.19 3.63 Model 4 09_1464_2_RPS 09_1464_5_RPS 66.95 13.52 18.87 22.79 27.04 33.45 39.10 45.59 64.69 28.67 49.18221 81.37513 Model 4 Top-up between 09_1464_2_RPS & 1.72 0.54 0.75 0.91 1.08 1.34 1.56 1.82 2.58 1.86 3.19 5.28 Model 4 09_1464_5_RPS 09_1839_7 11.29 1.86 2.70 3.34 4.06 5.17 6.18 7.36 11.02 4.11 7.590421 13.53393 Model 4 09_1839_12_RPS 17.91 4.79 6.96 8.61 10.45 13.31 15.89 18.93 28.25 9.93 18.32272 32.58293 Model 4
MRFS Flows for AEP HEFS Flows for AEP AREA Model Node ID_CFRAMS 2 10% 1% 0.5% 0.1% 10% 0.1% (km ) 50% (2) 20% (5) 5% (20) 2% (50) 1% (100) number (10) (100) (200) (1000) (10) (1000) Top-up between 09_1839_7 & 6.62 3.07 4.46 5.52 6.70 8.53 10.19 12.13 18.11 5.98 11.03 19.62 Model 4 09_1839_12_RPS 09_1444_U 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.001991 0.003551 Model 4 09_1444_4 1.60 0.97 1.41 1.75 2.12 2.70 3.23 3.85 5.76 2.70 4.986674 8.891377 Model 4 09049_RPS 87.50 16.46 22.32 26.53 31.06 37.79 43.65 50.30 69.53 32.30 53.13355 84.629 Model 4 Top-up between 09_1464_5_RPS & 1.03 0.41 0.55 0.65 0.77 0.93 1.08 1.24 1.71 0.71 1.17 1.86 Model 4 09049_RPS 09_611_3_RPS 87.63 16.32 22.13 26.30 30.79 37.47 43.27 49.87 68.93 32.03 52.69172 83.92528 Model 4 09_600_2 12.02 2.97 4.29 5.29 6.40 8.13 9.71 11.56 17.25 6.50 11.92472 21.1914 Model 4 09_1260_4_RPS 194.96 41.41 52.63 60.58 68.90 81.16 91.68 103.40 134.74 76.78 116.1968 170.7788 Model 4 Top-up between 09048_RPS & 8.19 3.26 4.14 4.76 5.42 6.38 7.21 8.13 10.60 7.04 10.66 15.66 Model 4 09_1260_4_RPS
Input flows Top-up flows. These flows should be entered laterally Check flows. Modellers to check to ensure these flows are being reached at each HEP
Model 5 – Kilcock Flows for AEP AREA Model Node ID_CFRAMS 2 Qmed 10% 1% 0.5% 0.1% (km ) 50% (2) 20% (5) 5% (20) 2% (50) number (10) (100) (200) (1000)
09_181_1_RPS 19.59 6.19 6.19 8.90 10.95 13.22 16.74 19.91 23.63 34.98 Model 5 09_1251_1_RPS 0.29 0.16 0.16 0.24 0.29 0.36 0.46 0.54 0.65 0.97 Model 5 09_1251_4 1.76 0.82 0.82 1.19 1.48 1.79 2.28 2.73 3.25 4.86 Model 5 Top-up between 09_1251_1 & 1.48 0.70 0.70 1.02 1.26 1.53 1.95 2.33 2.78 4.15 Model 5 09_1251_4 09_566_U 5.55 2.52 2.52 3.66 4.53 5.49 7.00 8.37 9.97 14.92 Model 5 09_566_1 5.98 2.56 2.56 3.72 4.60 5.58 7.12 8.50 10.14 15.16 Model 5 Top-up between 0.44 0.25 0.25 0.36 0.45 0.54 0.69 0.83 0.99 1.47 Model 5 09_566_U & 09_566_1 09_1535_1_RPS 12.16 4.96 4.96 7.13 8.77 10.58 13.40 15.94 18.91 27.98 Model 5 09_1535_7_RPS 14.87 5.24 5.24 7.56 9.33 11.32 14.43 17.28 20.63 31.05 Model 5 Top-up between 09_1535_1_RPS & 2.71 1.04 1.04 1.50 1.86 2.25 2.87 3.43 4.10 6.17 Model 5 09_1535_7_RPS 09048_RPS 59.55 16.96 16.96 23.98 29.22 34.95 43.74 51.57 60.66 87.97 Model 5 Top-up between 09_181_1_RPS & 17.34 5.34 5.34 7.55 9.20 11.00 13.77 16.23 19.10 27.69 Model 5 09048_RPS
Input flows Top-up flows. These flows should be entered laterally Check flows. Modellers to check to ensure these flows are being reached at each HEP
MRFS Flows for AEP HEFS Flows for AEP AREA Model Node ID_CFRAMS 2 10% 1% 0.5% 0.1% 10% 1% 0.1% (km ) 50% (2) 20% (5) 5% (20) 2% (50) number (10) (100) (200) (1000) (10) (100) (1000) 09_181_1_RPS 19.59 7.77 11.17 13.73 16.58 21.00 24.98 29.64 43.88 17.15 31.19 54.79 Model 5 09_1251_1_RPS 0.29 0.21 0.30 0.37 0.45 0.57 0.68 0.81 1.22 0.46 0.85 1.51 Model 5 09_1251_4 1.76 1.03 1.50 1.85 2.25 2.86 3.42 4.08 6.10 2.30 4.26 7.59 Model 5 Top-up between 09_1251_1 & 1.48 0.88 1.28 1.58 1.92 2.44 2.92 3.48 5.20 1.97 3.64 6.48 Model 5 09_1251_4 09_566_U 5.55 3.16 4.58 5.67 6.89 8.78 10.49 12.50 18.70 7.07 13.07 23.31 Model 5 09_566_1 5.98 3.21 4.66 5.77 7.00 8.92 10.66 12.71 19.01 7.20 13.31 23.73 Model 5 Top-up between 0.44 0.59 0.86 1.07 1.29 1.65 1.97 2.35 3.51 1.67 3.08 5.49 Model 5 09_566_U & 09_566_1 09_1535_1_RPS 12.16 6.22 8.93 10.99 13.27 16.79 19.97 23.70 35.08 13.70 24.90 43.73 Model 5 09_1535_7_RPS 14.87 6.58 9.48 11.71 14.20 18.11 21.67 25.88 38.96 14.64 27.10 48.71 Model 5 Top-up between 09_1535_1_RPS & 2.71 1.31 1.88 2.33 2.82 3.60 4.31 5.15 7.75 2.91 5.39 9.68 Model 5 09_1535_7_RPS 09048_RPS 59.55 25.10 35.49 43.25 51.73 64.74 76.33 89.79 130.20 57.14 100.84 172.00 Model 5 Top-up between 09_181_1_RPS & 17.34 11.49 16.25 19.80 23.69 29.64 34.95 41.11 59.61 29.27 51.66 88.12 Model 5 09048_RPS
Input flows Top-up flows. These flows should be entered laterally Check flows. Modellers to check to ensure these flows are being reached at each HEP
Model 6A – Clane Flows for AEP AREA Model Node ID_CFRAMS 2 Qmed 10% 1% 0.5% 0.1% (km ) 50% (2) 20% (5) 5% (20) 2% (50) number (10) (100) (200) (1000)
09_1519_13_RPS 169.65 20.28 20.28 25.00 28.20 31.47 36.11 39.96 44.14 55.41 Model 6A 09_1519_14_RPS 170.47 20.37 20.37 25.12 28.34 31.62 36.29 40.16 44.36 55.68 Model 6A Top-up between 09_1519_13_RPS & 0.83 0.17 0.17 0.21 0.24 0.27 0.31 0.34 0.38 0.47 Model 6A 09_1519_14_RPS 09_1519_16_RPS 179.54 21.55 21.55 26.57 29.98 33.44 38.38 42.47 46.91 58.89 Model 6A Top-up between 09_1519_14_RPS & 9.07 1.44 1.44 1.78 2.01 2.24 2.57 2.84 3.14 3.94 Model 6A 09_1519_16_RPS 09_1650_9_RPS 3.57 0.61 0.61 0.88 1.09 1.32 1.68 2.01 2.40 3.59 Model 6A 09_1211_2_RPS 18.94 2.16 2.16 3.13 3.86 4.69 5.96 7.12 8.48 12.65 Model 6A 09_529_2_RPS 4.02 0.71 0.71 1.04 1.28 1.56 1.98 2.37 2.82 4.23 Model 6A 09_1490_7_RPS 1.49 0.50 0.50 0.72 0.89 1.15 1.38 1.65 1.96 2.93 Model 6A 09_1210_2_RPS 1.30 0.20 0.20 0.29 0.36 0.46 0.55 0.66 0.78 1.17 Model 6A 09_1853_7_RPS 5.69 0.75 0.75 1.09 1.34 1.73 2.08 2.48 2.96 4.43 Model 6A 09_1649_1_RPS 2.47 0.36 0.36 0.52 0.64 0.82 0.99 1.18 1.41 2.10 Model 6A 09_1649_9_RPS 5.94 0.92 0.92 1.34 1.65 2.13 2.56 3.06 3.64 5.45 Model 6A Top-up between 09_1649_1_RPS & 3.47 0.64 0.64 0.92 1.14 1.47 1.77 2.11 2.52 3.77 Model 6A 09_1649_9_RPS 09_429_1 5.39 0.88 0.88 1.27 1.57 2.03 2.43 2.91 3.47 5.19 Model 6A 09_200_2_RPS 15.40 2.07 2.07 3.01 3.72 4.79 5.75 6.88 8.20 12.27 Model 6A Top-up between 09_429_1 & 10.01 1.47 1.47 2.14 2.65 3.41 4.10 4.90 5.84 8.74 Model 6A 09_200_2_RPS
09_782_3_RPS 5.43 0.77 0.77 1.11 1.38 1.77 2.13 2.54 3.03 4.54 Model 6A 09_1601_3_RPS 336.88 43.17 43.17 53.10 59.71 66.49 76.01 83.84 92.35 115.08 Model 6A Top-up between 09_1519_16_RPS & 97.51 14.38 14.38 17.69 19.89 22.15 25.32 27.93 30.77 38.34 Model 6A 09_1601_3_RPS
Input flows Top-up flows. These flows should be entered laterally Check flows. Modellers to check to ensure these flows are being reached at each HEP
MRFS Flows for AEP HEFS Flows for AEP AREA Model Node ID_CFRAMS (km2) 50% 20% 10% 5% 2% 1% 0.5% 0.1% 10% 1% 0.1% number (2) (5) (10) (20) (50) (100) (200) (1000) (10) (100) (1000) 09_1519_13_RPS 169.65 25.49 31.43 35.45 39.56 45.39 50.24 55.49 69.66 48.25 68.36 94.79 Model 6A 09_1519_14_RPS 170.47 25.62 31.59 35.64 39.76 45.63 50.50 55.77 70.02 48.48 68.70 95.25 Model 6A Top-up between 09_1519_13_RPS & 0.83 0.22 0.27 0.30 0.34 0.38 0.43 0.47 0.59 0.43 0.61 0.85 Model 6A 09_1519_14_RPS 09_1519_16_RPS 179.54 27.10 33.41 37.69 42.05 48.26 53.41 58.99 74.05 51.21 72.56 100.62 Model 6A Top-up between 09_1519_14_RPS & 9.07 1.84 2.26 2.55 2.85 3.27 3.62 4.00 5.02 3.65 5.18 7.18 Model 6A 09_1519_16_RPS 09_1650_9_RPS 3.57 1.03 1.50 1.86 2.25 2.87 3.43 4.09 6.11 3.88 7.17 12.79 Model 6A 09_1211_2_RPS 18.94 2.68 3.88 4.80 5.82 7.40 8.84 10.53 15.71 6.15 11.34 20.15 Model 6A 09_529_2_RPS 4.02 1.50 2.18 2.70 3.27 4.17 4.98 5.94 8.89 4.44 8.21 14.63 Model 6A 09_1490_7_RPS 1.49 0.91 1.33 1.64 2.11 2.54 3.03 3.61 5.40 1.78 3.28 5.85 Model 6A 09_1210_2_RPS 1.30 0.25 0.37 0.45 0.58 0.70 0.84 1.00 1.49 0.58 1.08 1.93 Model 6A 09_1853_7_RPS 5.69 0.95 1.38 1.70 2.20 2.64 3.15 3.76 5.62 2.17 4.02 7.16 Model 6A 09_1649_1_RPS 2.47 0.44 0.65 0.80 1.03 1.23 1.48 1.76 2.63 1.03 1.90 3.39 Model 6A
MRFS Flows for AEP HEFS Flows for AEP AREA Model Node ID_CFRAMS (km2) 50% 20% 10% 5% 2% 1% 0.5% 0.1% 10% 1% 0.1% number (2) (5) (10) (20) (50) (100) (200) (1000) (10) (100) (1000) 09_1649_9_RPS 5.94 1.43 2.07 2.57 3.31 3.97 4.75 5.66 8.46 6.17 11.40 20.33 Model 6A Top-up between 09_1649_1_RPS & 3.47 1.14 1.66 2.05 2.64 3.17 3.79 4.52 6.75 3.81 7.04 12.56 Model 6A 09_1649_9_RPS 09_429_1 5.39 1.10 1.60 1.98 2.56 3.07 3.67 4.37 6.55 2.52 4.67 8.32 Model 6A 09_200_2_RPS 15.40 4.03 5.86 7.25 9.34 11.21 13.40 15.97 23.91 15.21 28.12 50.18 Model 6A Top-up between 09_429_1 & 10.01 3.47 5.04 6.23 8.03 9.64 11.52 13.74 20.56 10.37 19.18 34.22 Model 6A 09_200_2_RPS 09_782_3_RPS 5.43 1.15 1.67 2.07 2.67 3.20 3.83 4.56 6.83 5.54 10.24 18.25 Model 6A 09_1601_3_RPS 336.88 51.80 63.72 71.64 79.78 91.20 100.60 110.81 138.08 77.62 108.99 149.59 Model 6A Top-up between 09_1519_16_RPS & 97.51 19.07 23.45 26.37 29.36 33.57 37.03 40.79 50.83 40.18 56.42 77.45 Model 6A 09_1601_3_RPS
Input flows Top-up flows. These flows should be entered laterally Check flows. Modellers to check to ensure these flows are being reached at each HEP
Model 6B – Naas Flows for AEP AREA Model Node ID_CFRAMS 2 Qmed 10% 1% 0.5% 0.1% (km ) 50% (2) 20% (5) 5% (20) 2% (50) number (10) (100) (200) (1000) 09_1533_U 0.02 0.005 0.00 0.01 0.01 0.01 0.01 0.02 0.02 0.03 Model 6B 09_322_U 0.01 0.004 0.00 0.01 0.01 0.01 0.01 0.01 0.02 0.02 Model 6B 09_322_1 0.24 0.06 0.06 0.09 0.12 0.15 0.18 0.21 0.25 0.38 Model 6B
Top-up flow between 09_322_U 0.23 0.06 0.06 0.09 0.11 0.14 0.17 0.20 0.24 0.36 Model 6B & 09_322_1 09_356_U 11.96 1.57 1.57 2.29 2.84 3.68 4.43 5.32 6.37 9.64 Model 6B 09_321_1_RPS 18.63 2.41 2.41 3.46 4.25 5.44 6.49 7.71 9.13 13.48 Model 6B
Top-up flow between 09_356_U 6.66 1.02 1.02 1.46 1.80 2.30 2.74 3.26 3.86 5.69 Model 6B & 09_321_1_RPS 09_454_Inter 18.88 2.48 2.48 3.56 4.38 5.59 6.68 7.93 9.40 13.87 Model 6B
Top-up flow between 0.25 0.17 0.17 0.24 0.29 0.37 0.44 0.53 0.63 0.92 Model 6B 09_321_1_RPS & 09_454_Inter 09_454_Trib 19.17 2.54 2.54 3.64 4.48 5.72 6.83 8.11 9.61 14.19 Model 6B
Top-up flow between 0.29 0.18 0.18 0.26 0.32 0.42 0.50 0.59 0.70 1.03 Model 6B 09_454_Inter & 09_454_Trib 09_1490_1_RPS 25.32 3.50 3.50 5.09 6.29 8.11 9.73 11.63 13.86 20.74 Model 6B
Top-up flow between 09_1533_U 5.89 1.15 1.15 1.67 2.06 2.66 3.19 3.81 4.54 6.79 Model 6B & 09_1490_1_RPS 09_1490_Inter 0.37 0.20 0.20 0.29 0.35 0.45 0.55 0.65 0.78 1.16 Model 6B 09_1490_DSL 1.09 0.39 0.39 0.56 0.69 0.89 1.07 1.28 1.53 2.29 Model 6B 09_1490_7_RPS 1.49 0.50 0.50 0.72 0.89 1.15 1.38 1.65 1.96 2.93 Model 6B 09_Monread_U 1.86 1.08 1.08 1.56 1.93 2.49 2.99 3.57 4.26 6.37 Model 6B
Top-up flow between 1.86 1.08 1.08 1.56 1.93 2.49 2.99 3.57 4.26 6.37 Model 6B 09_454_Inter & 09_Monread_U 09_Monread_1 4.51 1.40 1.40 2.04 2.53 3.25 3.91 4.67 5.56 8.32 Model 6B
Flows for AEP AREA Model Node ID_CFRAMS 2 Qmed 10% 1% 0.5% 0.1% (km ) 50% (2) 20% (5) 5% (20) 2% (50) number (10) (100) (200) (1000)
Top-up flow between 2.65 0.55 0.55 0.81 1.00 1.29 1.54 1.84 2.20 3.29 Model 6B 09_Monread_U & 09_Monread_1 09_1534_U 0.00 0.005 0.01 0.01 0.01 0.01 0.01 0.02 0.02 0.03 Model 6B 09_353_U 1.16 0.22 0.22 0.32 0.39 0.48 0.61 0.73 0.87 1.30 Model 6B 09_529_1_RPS 2.31 0.44 0.44 0.64 0.79 0.96 1.22 1.46 1.74 2.61 Model 6B
Top-up flow between 09_353_U 1.15 0.24 0.24 0.35 0.43 0.52 0.67 0.80 0.95 1.42 Model 6B & 09_529_1_RPS 09042_RPS 3.79 0.68 0.68 0.98 1.22 1.48 1.88 2.25 2.68 4.01 Model 6B
Top-up flow between 09_1534_U 1.48 0.26 0.26 0.38 0.47 0.57 0.72 0.86 1.03 1.54 Model 6B & 09042_RPS 09_529_2_RPS 4.02 0.71 0.71 1.04 1.28 1.56 1.98 2.37 2.82 4.23 Model 6B
Top-up flow between 09042_RPS 0.23 0.05 0.05 0.07 0.09 0.11 0.14 0.16 0.20 0.29 Model 6B & 09_529_2_RPS 09_1650_U 0.27 0.05 0.05 0.07 0.09 0.11 0.14 0.16 0.19 0.29 Model 6B 09_1650_2 1.22 0.23 0.23 0.33 0.41 0.50 0.63 0.76 0.90 1.35 Model 6B
Top-up flow between 09_1650_U 0.95 0.19 0.19 0.28 0.35 0.42 0.53 0.64 0.76 1.14 Model 6B & 09_1650_2 09_DSL_01 2.30 0.68 0.68 0.98 1.22 1.48 1.88 2.25 2.68 4.01 Model 6B
Top-up flow between 09_1650_2 1.08 0.48 0.48 0.70 0.86 1.04 1.33 1.59 1.90 2.84 Model 6B & 09_DSL_01 09_USL_01 0.36 0.16 0.16 0.23 0.29 0.35 0.45 0.53 0.63 0.95 Model 6B 09_USL_02 0.95 0.16 0.16 0.23 0.28 0.34 0.44 0.52 0.62 0.93 Model 6B 09_10001_Trib1 0.15 0.03 0.03 0.05 0.06 0.07 0.10 0.11 0.14 0.20 Model 6B 09_1650_9_RPS 3.57 0.61 0.61 0.88 1.09 1.32 1.68 2.01 2.40 3.59 Model 6B
Top-up flow between 09_USL_01 2.11 0.46 0.46 0.66 0.82 1.00 1.27 1.52 1.81 2.71 Model 6B & 09_1650_9_RPS
MRFS Flows for AEP HEFS Flows for AEP AREA Model Node ID_CFRAMS 2 10% 5% 2% 1% 0.5% 0.1% 10% 1% 0.1% (km ) 50% (2) 20% (5) number (10) (20) (50) (100) (200) (1000) (10) (100) (1000) 09_1533_U 0.02 0.006 0.01 0.01 0.01 0.02 0.02 0.02 0.04 0.01 0.03 0.05 Model 6B 09_322_U 0.01 0.008 0.01 0.02 0.02 0.02 0.03 0.03 0.05 0.02 0.04 0.08 Model 6B 09_322_1 0.24 0.12 0.17 0.22 0.28 0.33 0.40 0.48 0.71 0.35 0.65 1.16 Model 6B Top-up flow between 0.23 0.12 0.17 0.22 0.28 0.33 0.40 0.48 0.71 0.35 0.65 1.16 Model 6B 09_322_U & 09_322_1 09_356_U 11.96 1.98 2.88 3.58 4.63 5.58 6.70 8.02 12.14 4.53 8.49 15.39 Model 6B 09_321_1_RPS 18.63 3.08 4.43 5.44 6.95 8.30 9.86 11.69 17.25 7.91 14.34 25.08 Model 6B Top-up flow between 6.66 1.42 2.03 2.50 3.19 3.81 4.53 5.37 7.92 5.16 9.35 16.36 Model 6B 09_356_U & 09_321_1_RPS 09_454_Inter 18.88 3.25 4.67 5.74 7.33 8.75 10.40 12.32 18.19 9.54 17.29 30.24 Model 6B Top-up flow between 09_321_1_RPS & 0.25 0.20 0.29 0.36 0.46 0.55 0.65 0.77 1.14 0.39 0.71 1.24 Model 6B 09_454_Inter 09_454_Trib 19.17 3.38 4.86 5.97 7.63 9.11 10.82 12.82 18.92 10.48 18.99 33.22 Model 6B Top-up flow between 0.29 0.22 0.31 0.38 0.49 0.58 0.69 0.82 1.21 0.41 0.75 1.31 Model 6B 09_454_Inter & 09_454_Trib 09_1490_1_RPS 25.32 5.18 7.53 9.32 12.01 14.42 17.23 20.53 30.72 17.72 32.74 58.38 Model 6B Top-up flow between 09_1533_U & 5.89 2.24 3.26 4.03 5.20 6.24 7.46 8.89 13.30 4.51 8.34 14.87 Model 6B 09_1490_1_RPS 09_1490_Inter 0.37 0.26 0.38 0.47 0.61 0.73 0.88 1.05 1.56 0.51 0.95 1.69 Model 6B 09_1490_DSL 1.09 0.70 1.01 1.25 1.61 1.94 2.31 2.76 4.12 1.36 2.51 4.47 Model 6B 09_1490_7_RPS 1.49 0.91 1.33 1.64 2.11 2.54 3.03 3.61 5.40 1.78 3.28 5.85 Model 6B 09_Monread_U 1.86 1.29 1.88 2.32 2.99 3.59 4.29 5.11 7.65 2.51 4.65 8.28 Model 6B Top-up flow between 09_454_Inter & 1.86 1.29 1.88 2.32 2.99 3.59 4.29 5.11 7.65 2.51 4.65 8.28 Model 6B 09_Monread_U 09_Monread_1 4.51 2.09 3.03 3.75 4.84 5.81 6.94 8.27 12.37 5.24 9.68 17.25 Model 6B
MRFS Flows for AEP HEFS Flows for AEP AREA Model Node ID_CFRAMS 2 10% 5% 2% 1% 0.5% 0.1% 10% 1% 0.1% (km ) 50% (2) 20% (5) number (10) (20) (50) (100) (200) (1000) (10) (100) (1000) Top-up flow between 09_Monread_U & 2.65 1.02 1.48 1.83 2.36 2.84 3.39 4.04 6.04 3.13 5.79 10.32 Model 6B 09_Monread_1 09_1534_U 0.00 0.006 0.01 0.01 0.01 0.02 0.02 0.02 0.04 0.01 0.02 0.04 Model 6B 09_353_U 1.16 0.47 0.68 0.84 1.02 1.30 1.56 1.85 2.77 1.40 2.59 4.62 Model 6B 09_529_1_RPS 2.31 0.92 1.34 1.66 2.02 2.57 3.07 3.66 5.47 2.71 5.01 8.93 Model 6B Top-up flow between 1.15 0.49 0.71 0.88 1.07 1.37 1.63 1.95 2.92 1.47 2.72 4.85 09_353_U & 09_529_1_RPS 09042_RPS 3.79 1.43 2.07 2.57 3.12 3.97 4.75 5.66 8.46 4.21 7.78 13.86 Model 6B Top-up flow between 1.48 0.61 0.89 1.10 1.34 1.70 2.03 2.42 3.63 1.82 3.37 6.01 Model 6B 09_1534_U & 09042_RPS 09_529_2_RPS 4.02 1.50 2.18 2.70 3.27 4.17 4.98 5.94 8.89 4.44 8.21 14.63 Model 6B Top-up flow between 09042_RPS & 0.23 0.12 0.17 0.22 0.26 0.33 0.40 0.48 0.71 0.35 0.65 1.16 Model 6B 09_529_2_RPS 09_1650_U 0.27 0.06 0.09 0.11 0.13 0.17 0.20 0.24 0.36 0.14 0.26 0.46 09_1650_2 1.22 0.50 0.73 0.91 1.10 1.40 1.67 2.00 2.99 1.50 2.76 4.93 Model 6B Top-up flow between 0.95 0.32 0.47 0.58 0.71 0.90 1.08 1.28 1.92 1.22 2.25 4.01 Model 6B 09_1650_U & 09_1650_2 09_DSL_01 2.30 1.34 1.95 2.42 2.93 3.74 4.47 5.32 7.96 2.62 4.84 8.63 Model 6B Top-up flow between 1.08 0.68 0.99 1.23 1.49 1.90 2.27 2.71 4.05 1.33 2.46 4.39 Model 6B 09_1650_2 & 09_DSL_01 09_USL_01 0.36 0.26 0.38 0.47 0.58 0.73 0.88 1.05 1.56 0.51 0.95 1.69 09_USL_02 0.95 0.40 0.58 0.71 0.86 1.10 1.32 1.57 2.35 1.19 2.20 3.93 Model 6B 09_10001_Trib1 0.15 0.07 0.10 0.13 0.16 0.20 0.24 0.29 0.43 0.23 0.43 0.77 Model 6B 09_1650_9_RPS 3.57 1.03 1.50 1.86 2.25 2.87 3.43 4.09 6.11 3.88 7.17 12.79 Model 6B Top-up flow between 09_USL_01 & 2.11 0.98 1.43 1.77 2.15 2.74 3.27 3.90 5.83 2.43 4.49 8.01 Model 6B 09_1650_9_RPS
Model 7 – Turnings / Killeenmore (Morell) Flows for AEP AREA Model Node ID_CFRAMS 2 Qmed 10% 1% 0.5% 0.1% (km ) 50% (2) 20% (5) 5% (20) 2% (50) number (10) (100) (200) (1000)
09_540_6_RPS 7.19 2.96 2.96 4.30 5.32 6.45 8.22 9.82 11.71 17.52 Model 6B 09_371_U 0.05 0.01 0.014 0.021 0.026 0.031 0.040 0.048 0.057 0.085 Model 6B 09_371_1 1.26 0.11 0.11 0.16 0.20 0.24 0.31 0.37 0.44 0.65 Model 6B Top-up flow between 1.22 0.11 0.11 0.15 0.19 0.23 0.30 0.35 0.42 0.63 Model 6B 09_371_U & 07_371_1 UN_Morrell_U 0.54 0.14 0.14 0.20 0.25 0.30 0.38 0.46 0.54 0.81 Model 6B UN_Morrell_1 2.19 0.48 0.48 0.69 0.86 1.04 1.33 1.59 1.89 2.83 Model 6B Top-up flow between UN_Morrell_U & 1.65 0.37 0.37 0.54 0.67 0.81 1.03 1.23 1.47 2.19 Model 6B UN_Morrell_1 09_1597_1 0.19 0.05 0.05 0.07 0.08 0.10 0.13 0.15 0.18 0.27 Model 6B 09_1612_1_RPS 9.55 3.15 3.15 4.56 5.64 6.85 8.75 10.47 12.51 18.83 Model 6B 09_1557_3_RPS 14.87 4.15 4.15 6.03 7.47 9.06 11.55 13.80 16.45 24.61 Model 6B Top-up between 09_1612_1_RPS & 3.13 1.04 1.04 1.50 1.85 2.24 2.85 3.40 4.05 6.04 Model 6B 09_1557_3_RPS 09_1306_1 11.92 3.40 3.40 4.85 5.93 7.14 9.00 10.67 12.63 18.57 Model 6B 09027 12.40 3.42 3.42 4.88 5.97 7.18 9.06 10.74 12.71 18.69 Model 6B Top-up between 0.48 0.19 0.19 0.27 0.33 0.40 0.50 0.59 0.70 1.03 Model 6B 09_1306_1 & 09027 09_707_U 0.18 0.06 0.06 0.08 0.10 0.12 0.15 0.18 0.22 0.33 Model 6B 09_706_1 0.35 0.11 0.11 0.16 0.20 0.24 0.31 0.37 0.44 0.66 Model 6B Top-up flow between 0.18 0.06 0.06 0.09 0.12 0.14 0.18 0.21 0.25 0.38 Model 6B 09_707_U & 09_706_1 09_1602_1_RPS 17.00 3.51 3.51 4.99 6.10 7.33 9.20 10.89 12.84 18.76 Model 6B Top-up between 09027 & 4.25 1.02 1.02 1.45 1.78 2.13 2.68 3.17 3.74 5.47 Model 6B 09_1602_1_RPS 09044_RPS 45.78 10.21 10.21 14.35 17.40 20.73 25.81 30.29 35.48 50.89 Model 6B
Flows for AEP AREA Model Node ID_CFRAMS 2 Qmed 10% 1% 0.5% 0.1% (km ) 50% (2) 20% (5) 5% (20) 2% (50) number (10) (100) (200) (1000) Top-up between 09_540_6_RPS & 5.27 1.63 1.63 2.28 2.77 3.30 4.11 4.82 5.65 8.10 Model 6B 09044_RPS 09036_RPS 47.17 10.50 10.50 14.66 17.72 21.03 26.07 30.50 35.61 50.69 Model 7 09045_RPS 47.22 10.51 10.51 14.68 17.73 21.05 26.10 30.53 35.65 50.74 Model 7 Top-up between 09044_RPS & 1.44 0.47 0.47 0.66 0.80 0.95 1.17 1.37 1.60 2.28 Model 7 09045_RPS 09_411_5_RPS 4.63 0.78 0.78 1.14 1.41 1.71 2.18 2.61 3.11 4.65 Model 7 09_1305_2_RPS 5.93 2.47 2.47 3.59 4.45 5.40 6.88 8.22 9.80 14.66 Model 7 09_1305_8_RPS 7.78 3.06 3.06 4.45 5.50 6.68 8.51 10.17 12.12 18.13 Model 7 Top-up between 09_1305_2_RPS & 1.85 0.85 0.85 1.24 1.53 1.86 2.37 2.83 3.37 5.04 Model 7 09_1305_8_RPS 09_421_1 10.50 4.80 4.80 6.93 8.55 10.36 13.18 15.74 18.76 28.05 Model 7 09_1118_6 20.78 8.12 8.12 11.73 14.48 17.54 22.32 26.65 31.76 47.49 Model 7
Top-up between 10.29 4.34 4.34 6.27 7.74 9.38 11.94 14.25 16.99 25.40 Model 7 09_421_1 & 09_1118_6 09047_RPS 41.90 13.11 13.11 18.46 22.39 26.66 33.11 38.80 45.34 64.67 Model 7 Top-up between 09_1305_8_RPS & 13.34 4.48 4.48 6.31 7.66 9.12 11.33 13.27 15.51 22.12 Model 7 09047_RPS 09_1055_3_RPS 41.96 12.98 12.98 18.27 22.16 26.39 32.78 38.41 44.88 64.01 Model 7 Top-up between 09047_RPS & 0.05 0.03 0.03 0.04 0.04 0.05 0.07 0.08 0.09 0.13 Model 7 09_1055_3_RPS 09024_RPS 98.40 20.55 20.55 27.16 31.82 36.69 43.84 49.92 56.73 75.85 Model 7
Flows for AEP AREA Model Node ID_CFRAMS 2 Qmed 10% 1% 0.5% 0.1% (km ) 50% (2) 20% (5) 5% (20) 2% (50) number (10) (100) (200) (1000)
09_1627_6_RPS 98.49 20.52 20.52 27.12 31.78 36.64 43.78 49.86 56.65 75.75 Model 7 Top-up between 09045_RPS & 4.68 1.18 1.18 1.56 1.83 2.11 2.52 2.87 3.26 4.36 Model 7 09_1627_6_RPS
Input flows Top-up flows. These flows should be entered laterally Check flows. Modellers to check to ensure these flows are being reached at each HEP
MRFS Flows for AEP HEFS Flows for AEP AREA Model Node ID_CFRAMS (km2) 50% 20% 10% 5% 2% 1% 0.5% 0.1% 10% 1% 0.1% number (2) (5) (10) (20) (50) (100) (200) (1000) (10) (100) (1000) 09_540_6_RPS 7.19 3.71 5.39 6.67 8.09 10.31 12.32 14.69 21.97 8.30 15.34 27.34 Model 6B 09_371_U 0.05 0.04 0.052 0.065 0.079 0.100 0.120 0.143 0.213 0.117 0.216 0.385 Model 6B 09_371_1 1.26 0.28 0.40 0.50 0.60 0.77 0.92 1.09 1.64 0.72 1.34 2.39 Model 6B Top-up flow between 09_371_U & 1.22 0.26 0.38 0.47 0.58 0.73 0.88 1.05 1.56 0.70 1.30 2.31 Model 6B 07_371_1 UN_Morrell_U 0.54 0.17 0.24 0.30 0.37 0.47 0.56 0.67 1.00 0.40 0.73 1.31 Model 6B UN_Morrell_1 2.19 0.60 0.87 1.08 1.31 1.67 1.99 2.38 3.56 1.36 2.51 4.47 Model 6B Top-up flow between UN_Morrell_U & 1.65 0.47 0.68 0.84 1.02 1.30 1.56 1.85 2.77 1.05 1.94 3.47 Model 6B UN_Morrell_1 09_1597_1 0.19 0.24 0.35 0.43 0.52 0.67 0.80 0.95 1.42 1.05 1.94 3.47 Model 6B 09_1612_1_RPS 9.55 3.95 5.72 7.07 8.59 10.97 13.13 15.69 23.62 8.83 16.39 29.47 Model 6B 09_1557_3_RPS 14.87 6.08 8.84 10.94 13.28 16.92 20.22 24.10 36.05 20.55 37.97 67.70 Model 6B Top-up between 3.13 2.53 3.66 4.51 5.46 6.95 8.29 9.87 14.73 7.14 13.11 23.29 Model 6B 09_1612_1_RPS &
MRFS Flows for AEP HEFS Flows for AEP AREA Model Node ID_CFRAMS (km2) 50% 20% 10% 5% 2% 1% 0.5% 0.1% 10% 1% 0.1% number (2) (5) (10) (20) (50) (100) (200) (1000) (10) (100) (1000) 09_1557_3_RPS 09_1306_1 11.92 4.25 6.06 7.42 8.93 11.25 13.34 15.79 23.22 9.17 16.50 28.71 Model 6B 09027 12.40 4.26 6.07 7.44 8.95 11.28 13.38 15.83 23.29 9.22 16.58 28.85 Model 6B Top-up between 0.48 0.24 0.34 0.42 0.50 0.64 0.75 0.89 1.31 0.50 0.90 1.56 Model 6B 09_1306_1 & 09027 09_707_U 0.18 0.14 0.21 0.26 0.31 0.40 0.48 0.57 0.85 0.40 0.73 1.31 Model 6B 09_706_1 0.35 0.25 0.37 0.45 0.55 0.70 0.84 1.00 1.49 0.75 1.38 2.46 Model 6B Top-up flow between 09_707_U & 0.18 0.13 0.19 0.24 0.29 0.37 0.44 0.52 0.78 0.40 0.73 1.31 Model 6B 09_706_1 09_1602_1_RPS 17.00 4.40 6.26 7.65 9.19 11.54 13.65 16.11 23.53 10.42 18.58 32.01 Model 6B Top-up between 09027 & 4.25 1.28 1.83 2.23 2.68 3.37 3.98 4.70 6.86 3.03 5.40 9.31 Model 6B 09_1602_1_RPS 09044_RPS 45.78 14.41 20.25 24.56 29.26 36.42 42.75 50.07 71.81 43.73 76.11 127.87 Model 6B Top-up between 09_540_6_RPS & 5.27 3.84 5.40 6.54 7.80 9.70 11.39 13.34 19.13 10.34 18.01 30.25 Model 6B 09044_RPS 09036_RPS 47.17 14.82 20.70 25.01 29.69 36.81 43.06 50.28 71.57 44.54 76.69 127.46 Model 7 09045_RPS 47.22 14.83 20.72 25.04 29.72 36.84 43.10 50.33 71.64 44.59 76.76 127.59 Model 7 Top-up between 09044_RPS & 1.44 0.59 0.82 1.00 1.18 1.46 1.71 2.00 2.85 1.31 2.26 3.75 Model 7 09045_RPS 09_411_5_RPS 4.63 0.99 1.44 1.78 2.16 2.76 3.29 3.93 5.87 2.29 4.23 7.55 Model 7 09_1305_2_RPS 5.93 4.74 6.89 8.52 10.34 13.18 15.75 18.78 28.08 13.79 25.49 45.44 Model 7 09_1305_8_RPS 7.78 5.52 8.02 9.93 12.05 15.36 18.35 21.88 32.72 17.20 31.79 56.68 Model 8 Top-up between 09_1305_2_RPS & 1.85 1.54 2.23 2.76 3.35 4.27 5.11 6.09 9.11 4.79 8.85 15.77 Model 9 09_1305_8_RPS 09_421_1 10.50 6.01 8.68 10.72 12.99 16.52 19.73 23.51 35.16 13.40 24.66 43.94 Model 7
MRFS Flows for AEP HEFS Flows for AEP AREA Model Node ID_CFRAMS 2 (km ) 50% 20% 10% 5% 2% 1% 0.5% 0.1% 10% 1% 0.1% number (2) (5) (10) (20) (50) (100) (200) (1000) (10) (100) (1000) 09_1118_6 20.78 10.19 14.72 18.17 22.01 28.00 33.45 39.86 59.60 22.76 41.90 74.65 Model 7 Top-up between 09_421_1 & 10.29 5.45 7.87 9.72 11.77 14.98 17.89 21.32 31.87 12.17 22.41 39.93 Model 7 09_1118_6 09047_RPS 41.90 17.60 24.78 30.06 35.80 44.45 52.09 60.87 86.81 53.06 91.96 153.25 Model 7 Top-up between 09_1305_8_RPS & 13.34 6.02 8.48 10.28 12.25 15.21 17.82 20.82 29.70 18.15 31.46 52.42 Model 7 09047_RPS 09_1055_3_RPS 41.96 17.42 24.52 29.75 35.42 43.99 51.55 60.24 85.91 52.47 90.93 151.54 Model 7 Top-up between 09047_RPS & 0.05 0.03 0.05 0.06 0.07 0.09 0.10 0.12 0.17 0.10 0.18 0.30 Model 7 09_1055_3_RPS 09024_RPS 98.40 26.38 34.88 40.87 47.12 56.31 64.11 72.85 97.41 60.90 95.54 145.15 Model 7 09_1627_6_RPS 98.49 28.92 38.24 44.80 51.66 61.73 70.29 79.86 106.79 82.55 129.49 196.75 Model 7 Top-up between 09045_RPS & 4.68 1.52 2.01 2.35 2.71 3.24 3.69 4.19 5.60 3.50 5.49 8.34 Model 7 09_1627_6_RPS
Input flows Top-up flows. These flows should be entered laterally Check flows. Modellers to check to ensure these flows are being reached at each HEP
Model 8 – Newbridge Flows for AEP AREA Model Node ID_CFRAMS 2 Qmed 10% 1% 0.5% 0.1% (km ) 50% (2) 20% (5) 5% (20) 2% (50) number (10) (100) (200) (1000)
Dam 09007_RPS / 58.75 58.75 77.34 88.21 98.23 110.93 120.36 129.72 151.36 Model 8 09_1007_1_RPS Control 09_1119_5_RPS 30.62 5.96 5.96 7.87 9.20 10.58 12.59 14.29 16.18 21.44 Model 8 09_1011_7 15.21 2.48 2.48 3.53 4.32 5.18 6.51 7.70 9.08 13.27 Model 8 09_1281_2_RPS 31.32 3.35 3.35 4.64 5.56 6.55 8.04 9.33 10.80 15.08 Model 8 09_1154_U 0.34 0.15 0.15 0.22 0.27 0.33 0.42 0.50 0.59 0.89 Model 8 09_588_2_RPS 2.62 0.91 0.91 1.33 1.64 2.00 2.54 3.04 3.62 5.42 Model 8 Top-up between 09_1154_U & 2.27 0.81 0.81 1.17 1.45 1.76 2.24 2.68 3.20 4.78 Model 8 09_588_2_RPS 09_1518_4_RPS 140.07 18.53 50.16 54.32 57.14 60.01 64.10 67.49 71.18 81.13 Model 8 Top-up between 09007_RPS & 53.28 7.49 7.49 9.21 10.37 11.55 13.24 14.64 16.16 20.27 Model 8 09_1518_4_RPS 09_1517_U 0.54 0.11 0.11 0.17 0.21 0.25 0.32 0.38 0.45 0.68 Model 8 09_1517_1 0.93 0.18 0.18 0.27 0.33 0.40 0.51 0.61 0.73 1.09 Model 8 Top-up between 09_1517_U & 0.38 0.08 0.08 0.12 0.15 0.18 0.23 0.28 0.33 0.50 Model 8 09_1517_1 09_1519_2_RPS 144.15 19.11 50.54 54.79 57.66 60.59 64.76 68.22 71.98 82.14 Model 8 Top-up between 09_1518_4_RPS & 3.16 0.62 0.62 0.76 0.86 0.96 1.10 1.21 1.34 1.68 Model 8 09_1519_2_RPS 09_1519_8_RPS 148.89 19.71 50.72 55.02 57.92 60.88 65.09 68.59 72.39 82.65 Model 8
Flows for AEP AREA Model Node ID_CFRAMS 2 Qmed 10% 1% 0.5% 0.1% (km ) 50% (2) 20% (5) 5% (20) 2% (50) number (10) (100) (200) (1000)
Top-up between 09_1519_2_RPS & 4.74 0.89 0.89 1.09 1.23 1.37 1.57 1.73 1.91 2.40 Model 8 09_1519_8_RPS 09_1519_13_RPS 169.65 20.28 51.27 55.75 58.79 61.90 66.30 69.96 73.93 84.64 Model 8 Top-up between 09_1519_8_RPS & 20.76 2.96 2.96 3.65 4.12 4.60 5.28 5.84 6.45 8.10 Model 8 09_1519_13_RPS 09_363_U 0.13 0.04 0.04 0.06 0.08 0.09 0.12 0.14 0.17 0.25 Model 8 09_363_2_RPS 2.00 0.59 0.59 0.85 1.06 1.28 1.63 1.95 2.33 3.48 Model 8 Top-up between 09_363_U & 1.87 0.55 0.55 0.80 1.00 1.21 1.54 1.84 2.19 3.28 Model 8 09_363_2_RPS
Input flows Top-up flows. These flows should be entered laterally Check flows. Modellers should check to make sure these flows are being reached at each HEP Denotes where on the hydrological component of Qmed is displayed. The AEP event flows denote the hydrological estimate plus the normal dam release cycle and not the peak dam release. They are intended to be used by modellers as a guide only and combination of hydrological and dam release flows can only be accurately assessed through the model.
MRFS Flows for AEP HEFS Flows for AEP AREA Model Node ID_CFRAMS 2 10% 1% 0.5% 0.1% 10% 1% 0.1% (km ) 50% (2) 20% (5) 5% (20) 2% (50) number (10) (100) (200) (1000) (10) (100) (1000) Dam 09007_RPS / 70.50 92.81 105.85 117.88 133.12 144.43 155.66 181.63 114.67 156.47 196.77 Model 8 09_1007_1_RPS Control 09_1119_5_RPS 30.62 7.15 9.45 11.04 12.70 15.11 17.15 19.42 25.74 11.96 18.58 27.88 Model 8 09_1011_7 15.21 3.12 4.44 5.43 6.52 8.19 9.69 11.42 16.69 6.84 12.20 21.02 Model 8 09_1281_2_RPS 31.32 4.18 5.79 6.94 8.18 10.04 11.65 13.49 18.83 8.53 14.32 23.14 Model 8
MRFS Flows for AEP HEFS Flows for AEP AREA Model Node ID_CFRAMS 2 10% 1% 0.5% 0.1% 10% 1% 0.1% (km ) 50% (2) 20% (5) 5% (20) 2% (50) number (10) (100) (200) (1000) (10) (100) (1000) 09_1154_U 0.34 0.25 0.37 0.45 0.55 0.70 0.84 0.99 1.49 0.49 0.91 1.61 Model 8 09_588_2_RPS 2.62 1.53 2.24 2.76 3.37 4.28 5.12 6.10 9.13 2.99 5.55 9.89 Model 8 Top-up between 09_1154_U & 2.27 1.35 1.95 2.42 2.94 3.74 4.48 5.35 7.98 2.62 4.85 8.65 Model 8 09_588_2_RPS 09_1518_4_RPS 140.07 62.74 67.95 71.47 75.06 80.17 84.41 89.03 101.47 94.88 112.07 134.72 Model 8 Top-up between 09007_RPS & 53.28 9.37 11.52 12.97 14.45 16.56 18.31 20.21 25.36 17.22 24.31 33.66 Model 8 09_1518_4_RPS 09_1517_U 0.54 0.14 0.22 0.27 0.32 0.41 0.49 0.58 0.87 0.39 0.71 1.27 Model 8 09_1517_1 0.93 0.44 0.66 0.80 0.97 1.24 1.48 1.77 2.65 1.30 2.41 4.31 Model 8 Top-up between 09_1517_U & 0.38 0.20 0.30 0.37 0.45 0.57 0.70 0.82 1.24 0.61 1.13 2.02 Model 8 09_1517_1 09_1519_2_RPS 144.15 63.68 69.03 72.65 76.34 81.60 85.96 90.70 103.50 99.76 118.04 142.13 Model 8 Top-up between 09_1518_4_RPS & 3.16 0.79 0.97 1.09 1.22 1.40 1.54 1.71 2.14 1.58 2.22 3.09 Model 8 09_1519_2_RPS 09_1519_8_RPS 148.89 63.92 69.33 72.98 76.72 82.02 86.44 91.23 104.16 100.22 118.70 143.03 Model 8 Top-up between 09_1519_2_RPS & 4.74 2.14 2.62 2.96 3.29 3.77 4.16 4.59 5.77 4.75 6.69 9.28 Model 8 09_1519_8_RPS 09_1519_13_RPS 169.65 64.45 70.08 73.91 77.81 83.35 87.95 92.94 106.40 100.54 119.65 144.75 Model 8 Top-up between 09_1519_8_RPS & 20.76 3.86 4.76 5.37 6.00 6.88 7.61 8.41 10.56 7.71 10.93 15.16 Model 8 09_1519_13_RPS 09_363_U 0.13 0.06 0.09 0.11 0.13 0.17 0.20 0.24 0.36 0.23 0.40 0.71 Model 8 09_363_2_RPS 2.00 0.84 1.21 1.51 1.83 2.33 2.78 3.33 4.97 2.35 4.32 7.70 Model 8 Top-up between 09_363_U & 1.87 0.79 1.15 1.44 1.75 2.22 2.66 3.16 4.73 2.24 4.12 7.34 Model 8 09_363_2_RPS
Model 9 – Blessington Flows for AEP AREA Model Node ID_CFRAMS 2 Qmed 10% 1% 0.5% 0.1% (km ) 50% (2) 20% (5) 5% (20) 2% (50) number (10) (100) (200) (1000) 09_581_U 0.80 0.50 0.50 0.72 0.89 1.08 1.38 1.65 1.96 2.94 Model 9 09_605_2_RPS 2.69 1.27 1.27 1.85 2.29 2.78 3.54 4.23 5.04 7.54 Model 9 Top-up between 09_581_U & 1.89 0.93 0.93 1.35 1.67 2.03 2.59 3.09 3.68 5.51 Model 9 09_605_2_RPS 09_625_U 0.54 0.35 0.35 0.50 0.62 0.75 0.96 1.15 1.37 2.05 Model 9 09_591_U 0.22 0.15 0.15 0.22 0.27 0.33 0.42 0.51 0.60 0.90 Model 9 09_591_1 0.69 0.43 0.43 0.62 0.77 0.94 1.19 1.43 1.70 2.54 Model 9 Top-up between 09_591_U & 0.48 0.31 0.31 0.45 0.55 0.67 0.86 1.03 1.22 1.83 Model 9 09_591_1 09_1876_5_RPS 8.14 2.76 2.76 4.02 4.97 6.03 7.69 9.19 10.95 16.38 Model 9 Top-up between 09_625_U & 1.66 0.59 0.59 0.85 1.06 1.28 1.63 1.95 2.33 3.48 Model 9 09_1876_5_RPS (09NWPK)
Top-up between 09_625_U & 2.55 0.90 0.90 1.31 1.62 1.97 2.51 3.00 3.58 5.35 Model 9 09_1876_5_RPS (09DPRK)
Input flows Top-up flows. These flows should be entered laterally Check flows. Modellers to check to ensure these flows are being reached at each HEP
MRFS Flows for AEP HEFS Flows for AEP AREA Model Node ID_CFRAMS (km2) 50% 20% 10% 5% 2% 1% 0.5% 0.1% 10% 1% 0.1% number (2) (5) (10) (20) (50) (100) (200) (1000) (10) (100) (1000) 09_581_U 0.80 0.62 0.90 1.11 1.35 1.72 2.06 2.45 3.67 1.37 2.53 4.50 Model 9 09_605_2_RPS 2.69 2.15 3.12 3.86 4.69 5.98 7.14 8.51 12.74 5.79 10.71 19.09 Model 9 Top-up between 09_581_U & 1.89 1.73 2.52 3.12 3.78 4.82 5.76 6.87 10.28 3.85 7.12 12.70 Model 9 09_605_2_RPS 09_625_U 0.54 0.43 0.63 0.78 0.94 1.20 1.43 1.71 2.55 1.05 1.94 3.45 Model 9 09_591_U 0.22 0.19 0.28 0.34 0.41 0.53 0.63 0.75 1.13 0.42 0.78 1.38 Model 9 09_591_1 0.69 0.57 0.83 1.03 1.25 1.59 1.90 2.27 3.39 2.34 4.32 7.71 Model 9 Top-up between 09_591_U & 0.48 0.62 0.89 1.11 1.34 1.71 2.04 2.44 3.65 1.64 3.02 5.39 Model 9 09_591_1 09_1876_5_RPS 8.14 4.81 7.00 8.66 10.51 13.39 16.00 19.07 28.53 11.28 20.84 37.16 Model 9 Top-up between 09_625_U & 1.66 1.10 1.60 1.98 2.40 3.06 3.66 4.36 6.53 2.42 4.47 7.97 Model 9 09_1876_5_RPS (09NWPK) Top-up between 09_625_U & 2.55 1.69 2.46 3.04 3.69 4.71 5.62 6.70 10.03 3.71 6.87 12.24 Model 9 09_1876_5_RPS (09DPRK)
Input flows Top-up flows. These flows should be entered laterally Check flows. Modellers to check to ensure these flows are being reached at each HEP
APPENDIX E
NAM MODELLING OUTPUTS