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DPIW – SURFACE WATER MODELS HUON, RUSSELL & LITTLE CATCHMENT

Huon River Surface Water Model Hydro Version No: FINAL 1.0

DOCUMENT INFORMATION

JOB/PROJECT TITLE Tascatch Variation 2 -Surface Water Models CLIENT ORGANISATION Department of Primary Industries and Water CLIENT CONTACT Bryce Graham

DOCUMENT ID NUMBER WR 2008/005 JOB/PROJECT MANAGER Mark Willis JOB/PROJECT NUMBER E202869/P205357 Document History and Status Revision Prepared Reviewed Approved Date Revision by by by approved type 1.0 M. Willis J. Peterson F. Ling May 2008 Final

Current Document Approval PREPARED BY M. Willis

Water Resources Mngt Sign Date

REVIEWED BY J. Peterson

Water Resources Mngt Sign Date

APPROVED FOR F. Ling SUBMISSION Water Resources Mngt Sign Date Current Document Distribution List Organisation Date Issued To DPIW May 2008 Bryce Graham

The concepts and information contained in this document are the property of Hydro Tasmania. This document may only be used for the purposes of assessing our offer of services and for inclusion in documentation for the engagement of Hydro Tasmania. Use or copying of this document in whole or in part for any other purpose without the written permission of Hydro Tasmania constitutes an infringement of copyright.

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Huon River Surface Water Model Hydro Tasmania Version No: FINAL 1.0

EXECUTIVE SUMMARY

This report is part of a series of reports which present the methodologies and results from the development and calibration of surface water hydrological models for 25 catchments (Tascatch – Variation 2) under both current and natural flow conditions. This report describes the results of a combined hydrological model developed for the Huon, Russell and Little Denison River catchments. These combined catchments are referred to within this report as the Huon catchment.

A model was developed for the Huon catchment that facilitates the modeling of flow data for three scenarios:

• Scenario 1 – No entitlements (Natural Flow);

• Scenario 2 – with Entitlements (with water entitlements extracted);

• Scenario 3 - Environmental Flows and Entitlements (Water entitlements extracted, however low priority entitlements are limited by an environmental flow threshold).

The results from the scenario modeling allow the calculation of indices of hydrological disturbance. These indices include:

• Index of Mean Annual Flow

• Index of Flow Duration Curve Difference

• Index of Seasonal Amplitude

• Index of Seasonal Periodicity

• Hydrological Disturbance Index

The indices were calculated using the formulas stated in the Natural Resource Management (NRM) Monitoring and Evaluation Framework developed by SKM for the Murray-Darling Basin (MDBC 08/04).

A user interface is also provided that allows the user to run the model under varying catchment demand scenarios. This allows the user to add further extractions to catchments and see what effect these additional extractions have on the available water in the catchment of concern. The interface provides sub-catchment summary of flow statistics, duration curves, hydrological indices and water entitlements data. For information on the use of the user interface refer to the Operating Manual for the NAP Region Hydrological Models (Hydro Tasmania 2004).

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Huon River Surface Water Model Hydro Tasmania Version No: FINAL 1.0

There were difficulties encountered during the calibration of the Huon model. The lack of observed precipitation within this catchment appears to have affected the reliability of the derived Data Drill information. The main calibration difficulty was volume balance and to obtain an acceptable volume fit, the Data Drill precipitation in the upper and middle catchments was increased by up to 30%.

There is a general lack of observed flow record within this large catchment especially in the lower, primary interest areas. The lack of any observed data in the Russell and Little Denison Rivers is a significant limitation for assessing the models performance. It is recommended that an observed gauge site be established in one of these catchments and a model calibration review is undertaken once sufficient record becomes available.

The modelled results show a change in peak winter flows around the year 2000 when compared to the observed record. A trend similar to this was also observed in the neighbouring Esperance catchment which may be related. It is recommended that a further study be undertaken to determine the source of this error, with the aim of improving the current model performance.

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Huon River Surface Water Model Hydro Tasmania Version No: FINAL 1.0

CONTENTS

EXECUTIVE SUMMARY ii 1. INTRODUCTION 1 2. CATCHMENT CHARACTERISTICS 2 3. DATA COMPILATION 5 3.1 Climate data (Precipitation & Evaporation) 5 3.2 Advantages of using climate DRILL data 5 3.3 Transposition of climate DRILL data to local catchment 6 3.4 Comparison of Data Drill precipitation and site gauges 8 3.4.1 Scaling of Data Drill Precipitation and Evaporation. 9 3.5 Streamflow data 12 3.6 Irrigation and water usage 13 3.6.1 Estimation of unlicensed (small) farm dams 20 3.7 Environmental flows 22 4. MODEL DEVELOPMENT 24 4.1 Sub-catchment delineation 24 4.2 Hydstra Model 24 4.2.1 26 4.3 AWBM Model 26 4.3.1 Channel Routing 28 4.4 Model Calibration 29 4.4.1 Factors affecting the reliability of the model calibration. 37 4.4.2 Model Accuracy - Model Fit Statistics 39 4.4.3 Model accuracy across the catchment 42 5. MODEL RESULTS 48 5.1.1 Indices of hydrological disturbance 49 6. FLOOD FREQUENCY ANALYSIS 52 7. REFERENCES 54 7.1 Personal Communications 54 8. GLOSSARY 55 APPENDIX A 57

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LIST OF FIGURES Figure 2-1 Sub-catchment boundaries 4 Figure 3-1 Climate Drill Site Locations 7 Figure 3-2 Precipitation and Data Drill Comparisons 9 Figure 3-3 WIMS Water Allocations 19 Figure 4-1 Hydstra Model Schematic 25 Figure 4-2 Two Tap Australian Water Balance Model Schematic 28 Figure 4-3 Monthly Variation of CapAve Parameter 32 Figure 4-4 Daily time series comparison (ML/d) – Huon River - Good fit. 34 Figure 4-5 Daily time series comparison (ML/d) – Huon River – Fair fit. 34 Figure 4-6 Daily time series comparison (ML/d) – Huon River – Good fit. 35 Figure 4-7 Monthly time series comparison – volume (ML) 35 Figure 4-8 Long term average monthly, seasonal and annual comparison plot 36 Figure 4-9 Duration Curve – Daily flow percentage difference 41 Figure 4-10 Duration Curve – Monthly volume percentage difference 41 Figure 4-11 Time Series of Monthly Volumes- Site 453 43 Figure 4-12 Time Series of Monthly Volumes- Site 6201 43 Figure 4-13 Time Series of Monthly Volumes- SC14_f (Area scaling) 45 Figure 4-14 Time Series of Monthly Volumes- SC14_f (Area & Rain scaling) 45 Figure 4-15 Time Series of Monthly Volumes- SC11_j (Area scaling) 46 Figure 4-16 Time Series of Monthly Volumes- SC11_j (Area & Rain scaling) 47 Figure 5-1 Daily Duration Curve 48 Figure 6-1 Modelled and Observed Flood Frequency Plot – Huon River u/s Frying Pan Creek 53 Figure A-1 Forth catchment – monthly volumes at secondary site. 59 Figure A-2 George catchment – monthly volumes at secondary site. 59 Figure A-3 Leven catchment – monthly volumes at secondary site. 60 Figure A-4 Swan catchment – monthly volumes at secondary site. 60 Figure A-5 Montagu catchment – monthly volumes at secondary site. 61

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LIST OF TABLES

Table 3.1 Data Drill Site Locations 8

Table 3.2 Data Drill Scaling 11

Table 3.2 Potential calibration sites 12

Table 3.3 Assumed Surety of Unassigned Records 13

Table 3.4 Sub Catchment High and Low Priority Entitlements 15

Table 3.5 Average capacity for dams less than 20 ML by Neal et al (2002) 21

Table 3.6 Environmental Flows 22

Table 4.2 Boughton & Chiew, AWBM surface storage parameters 27

Table 4.3 Hydstra/TSM Modelling Parameter Bounds 29

Table 4.4 Adopted Calibration Parameters 31

Table 4.5 Long term average monthly, seasonal and annual comparisons 37

Table 4.5 Model Fit Statistics 39

Table 4.7 R 2 Fit Description 40

Table 5.1 Hydrological Disturbance Indices 50

Table A-1 Model performance at secondary sites 62

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Huon River Surface Water Model Hydro Tasmania Version No: FINAL 1.0

1. INTRODUCTION

This report forms part of a larger project commissioned by the Department of Primary Industries and Water (DPIW) to provide hydrological models for 25 regional catchments (Tascatch – Variation 2).

This report covers the Huon River, Russell River and Little Denison River catchments. This combined total area is referred to within this report as the Huon catchment.

The main objectives for the individual catchments are:

• To compile relevant data required for the development and calibration of the hydrological model (Australian Water Balance Model, AWBM);

• To source over 100 years of daily time-step precipitation and streamflow data for input to the hydrologic model;

• To develop and calibrate each hydrologic model, to allow running of the model under varying catchment demand scenarios;

• To develop a User Interface for running the model under these various catchment demand scenarios;

• Prepare a report summarizing the methodology adopted, assumptions made, results of calibration and validation and description relating to the use of the developed hydrologic model and associated software.

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2. CATCHMENT CHARACTERISTICS

The Huon, Russell and Little Denison River catchments are located in Southern Tasmania. Within this report, this total area is referred to as the Huon catchment and covers the total catchment area upstream of the Mountain River junction. The Huon catchment has a total area of 2530.5 km 2, however 257.9 km 2 of this lies within the Lake Pedder catchment and this run-off is diverted through the into the . Since 1971 the headwaters of the Huon catchment effectively starts at Dam due to the diversion of these upper most catchments.

The Russell River has a catchment area of 144.1 km 2 and the Little Denison River 87.3 km 2.

The Huon catchment drains a large portion of and accordingly there are several other significant streams (tributaries) that fall within this catchment area, including the; Picton, Weld, Cracroft and Arve Rivers.

There are several significant peaks with the Huon catchment including; (1222m AHD), Mt Weld (1338m AHD), Mt Picton (1327m AHD), Mt Anne (1420m AHD) and Hartz Mt (1255m AHD).

The upper catchment is unpopulated and falls within the South West National Park and accordingly is pristine native landscape. Vegetation cover varies significantly ranging from old growth eucalypt forests through to low alpine vegetation and button grass plains.

The middle part of the catchment is also unpopulated and the predominant use is forestry. The vegetation is dominated by old growth and plantation eucalypt forest.

The lower part of the catchment contains a mixture of agriculture and smaller (life style) residential allotments, including the settlements of , Judbury and Ranelagh.

Variability in the annual precipitation total across this catchment is significant, mainly due to the changes in elevation and the varied exposure to the dominant westerly weather pattern. The lower catchment near Ranelagh receives a typical annual precipitation of around 800mm and the upper catchment near Lake Pedder around 2200mm.

There were 93 registered (current) water entitlements identified on the Water Information Management System (WIMS July 2007). Most of these extractions are concentrated in the lower sub-catchments and mainly relate to water supply and irrigation. The largest single extraction entitlement is 1750 ML (SC1_k) associated with an industrial extraction for Forestry. As expected most of the upper sub-catchments have few or no registered WIMS entitlements as this is unpopulated and utilised either for electricity generation or contained within a national park.

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For modelling purposes, the Huon catchment was divided into 60 sub areas. The delineation of these areas and the assumed stream routing network is shown in Figure 2-1.

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430000 440000 450000 460000 470000 480000 490000 500000 5275000 5275000 5270000 5270000 5265000 5265000

5260000 7-a 5260000

11-a

5255000 13-a 5255000 11-b 1-a 7-b 11-d 11-c 12-a 17-a

5250000 18-a 5250000 11-e 7-c 14-a 14-b 11-f 16-a 11-g 11-h

5245000 7-d 18-b 5245000 15-a 15-b 14-c 14-d 15-c 14-e 11-i 11-j 8-a 2-a 1-b 19-a 14-f 5240000 7-e 5240000 1-m 7-f 1-l 5-a 1-k 5235000 1-c 5235000

1-g 1-i 1-j 5230000 1-e 5230000 1-d 1-h 10-b

1-f 5225000 3-e 5225000

4-c

10-a 5220000 3-d 5220000

4-b 5215000 5215000

9-a 4-a 3-c 5210000 5210000 5205000 5205000

6-a 3-b 5200000 5200000 5195000 5195000

5190000 3-a 5190000 5185000 5185000

5180000 Legend 5180000 Gauging sites

5175000 Stream routing network 5175000 Little Dension sub-catchment boundary 03.5 7 14 21 28 Russell sub-catchment boundary 5170000 5170000 Huon sub-catchment boundary Kilometers

430000 440000 450000 460000 470000 480000 490000 500000 5165000 Figure 2-1 Sub-catchment boundaries

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3. DATA COMPILATION

3.1 Climate data (Precipitation & Evaporation) Daily time-step climate data was obtained from the Queensland Department of Natural Resources & Mines (QDNRM).

The Department provides time series climate drill data from 0.05 o x 0.05 o (about 5 km x 5 km) interpolated gridded precipitation and evaporation data based on over 6000 precipitation and evaporation stations in (see www.nrm.qld.gov.au/silo ) for further details of climate drill data.

3.2 Advantages of using climate DRILL data This data has a number of benefits over other sources of precipitation data including:

• Continuous data back to 1889 (however, further back there are less input sites available and therefore quality is reduced. The makers of the data set state that gauge numbers have been somewhat static since 1957, therefore back to 1957 distribution is considered “good” but prior to 1957 site availability may need to be checked in the study area);

• Evaporation data (along with a number of other climatic variables) is also included which can be used for the AWBM model. According to the QNRM web site, all Data Drill evaporation information combines a mixture of the following data.

1. Observed data from the Commonwealth Bureau of Meteorology (BoM).

2. Interpolated daily climate surfaces from the on-line NR&M climate archive.

3. Observed pre-1957 climate data from the CLIMARC project (LWRRDC QPI- 43). NR&M was a major research collaborator on the CLIMARC project, and these data have been integrated into the on-line NR&M climate archive.

4. Interpolated pre-1957 climate surfaces. This data set, derived mainly from the CLIMARC project data, are available in the on-line NR&M climate archive.

5. Incorporation of Automatic Weather Station (AWS) data records. Typically, an AWS is placed at a user's site to provide accurate local weather measurements.

For the Huon catchment the evaporation data was examined and it was found that prior

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to 1970 the evaporation information is based on the long term daily averages of the post 1970 data. In the absence of any reliable long term site data this is considered to be the best available evaporation data set for this catchment.

3.3 Transposition of climate DRILL data to local catchment Ten climate Data Drill sites were selected to give good coverage of the Huon catchment.

See the following Figure 3-1 for a map of the climate Data Drill sites and Table 3.1 for the location information.

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430000 440000 450000 460000 470000 480000 490000 500000 5280000 5280000 5275000 5275000 5270000 5270000

5265000 5265000

0

0

0

0

0

0

4

2

0

5260000 1 5260000

1 1 5255000 5255000 Huon_01 Huon_02 5250000 5250000 0 0 8 5245000 5245000

Huon_03 Huon_04 Huon_05 Huon_06 5240000 5240000 5235000 5235000

Huon_07 5230000 5230000

Huon_08 5225000 5225000 5220000 5220000

5215000 Huon_09 5215000 5210000 5210000

5205000 0 5205000 220 5200000 5200000 Huon_10 5195000 5195000 2000 5190000 5190000

5185000 1800 5185000

5180000 Legend 5180000 1600 Rainfall & evaporation sites

5175000 04 8 16 24 32 Rainfall Isoheytal 5175000 Sub-catchment boundary 10 Kilometers 1400 00 5170000 430000 440000 450000 460000 470000 480000 490000 500000 Figure 3-1 Climate Drill site locations

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Table 3.1 Data Drill site locations

Site Latitude Longitude Huon_01 -42:54:00 146:24:00 Huon_02 -42:54:00 146:42:00 Huon_03 -43:00:00 146:15:00 Huon_04 -43:00:00 146:33:00 Huon_05 -43:00:00 146:48:00 Huon_06 -43:00:00 146:57:00 Huon_07 -43:06:00 146:45:00 Huon_08 -43:09:00 146:27:00 Huon_09 -43:15:00 146:39:00 Huon_10 -43:24:00 146:42:00

3.4 Comparison of Data Drill precipitation and site gauges As precipitation data is a critical input to the modeling process it is important to have confidence that the Data Drill long term generated time series does in fact reflect what is being observed within the catchment. Precipitation sites in closest proximity to the Data Drill locations were sourced and compared. The visual comparison and the R 2 values indicate that there appears to be varied correlation between observed and Data Drill information across the catchment. In the lower catchment (Picton and Judbury) there appears to be good correlation. This is to be expected as the Data Drill information is derived from site data and there are a number of observed sites in this area.

However, the upper catchment is unpopulated and there are a very limited number of observed records in this area. The correlation with observed data in this area (Scotts Peak Dam) suggests a poor relationship and accordingly the Data Drill may not provide an accurate representation of precipitation temporal patterns in this area

There is no practical recommendation for addressing the lack of long term rainfall sites in the upper catchments. Information obtained from the installation of new sites would only be useful after many years and considering the low number of WIMS entitlements within this catchment it is unlikely that the expenditure for running these new stations could be justified.

In the absence of other long term records in the upper catchments, the Data Drill information was deemed the best data set available. The annual precipitation totals of selected Data Drill sites and neighboring sites for coincident periods are plotted in Figure 3-2.

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1400 Data Drill - Huon_06 Huon at Judbury - Site 14 R2 = 0.97

1200

1000

800

600 400 Annaul Annaul Rainfall (mm) 200

0

1 7 0 5 8 1 9 2 64 93 934 93 94 952 95 95 96 9 976 97 98 1925 1928 1 1 1 1 1943 1946 1949 1 1 1 1 1 1967 1970 1973 1 1 1

R2 = 0.87 2000 Data Drill - Huon_07 Picton/Tahune - Site 4125 1800 1600 1400 1200 1000 800 600

Annaul Annaul Rainfall (mm) 400 200 0

1 3 5 7 9 1 971 973 975 977 979 98 98 98 98 98 99 1970 1 1972 1 1974 1 1976 1 1978 1 1980 1 1982 1 1984 1 1986 1 1988 1 1990 1

2 3000 Data Drill - Huon_03 Scotts Peak Dam - Site 1033 R = 0.35

2500

2000

1500

1000

Annaul Annaul Rainfall (mm) 500

0

9 1 5 7 9 93 97 98 983 985 987 9 99 99 99 001 1973 1975 1977 1 1 1 1 1 1989 1991 1 1 1 1 2

Figure 3-2 Precipitation and Data Drill comparisons

3.4.1 Scaling of Data Drill Precipitation and Evaporation. As previously mentioned, due to the lack of observed precipitation sites within this catchment the derived Data Drill information data is unlikely to accurately reflect the true precipitation and evaporation across this catchment and this issue was detected

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during the model calibration process (refer to 4.4). The main issue during the model calibration was the Huon model consistently produced insufficient volume at the calibration location (Huon River a/b Frying Pan Creek). It was suspected that the Data Drill information was under representing the precipitation within the middle and upper catchments. Initial investigations indicated a discrepancy between rainfall/run-off and observed flow in the order of 20%.

To test this theory a rainfall run-off comparison between the Data Drill rainfall and observed volumes was undertaken between the neighbouring Esperance catchment (Willis March 2008) and the Huon catchment. This showed that the Esperance catchment had a rainfall run-off coefficient of approximately 0.54 whilst the Huon model had a value of 0.79. This indicates that within the Huon catchment there is significantly more observed flow per millimetre of rainfall in comparison to the Data Drill information.

To add weight to this argument, two gauge sites in the vicinity of Lake Pedder also showed a similar discrepancy between Data Drill precipitation and the corresponding observed volume at the gauge:

• Huon River at Scotts Peak, site 453, located at sub-catchment SC1_b with a rainfall run-off coefficient of approximately 0.85.

• Huon River upstream Sandfly Creek, site 6201, located at sub-catchment SC1_a with a rainfall run-off coefficient of approximately 0.70.

Utilising the modelled flows, observed flows and a considerable amount of practitioner judgment varying scaling factors were applied to the Data Drill information across the Huon catchment. This is summarised in the following table.

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Table 3.2 Data Drill Scaling

Site Scaling factor Comment

Scaling used to correct volume balance at Huon_01 – Precipitation 1.15 site 6201.

Scaling used to correct volume balance at Huon_02 – Precipitation 1.30 site 453

Scaling used to correct volume balance at Huon_03 – Precipitation 1.15 site 453

Scaling used to correct volume balance at Huon_04 - Precipitation 1.30 site 119

Low in catchment. No factor applied. Assumed that Data Drill precipitation Huon_05 - Precipitation 1.00 reflective of actual totals in this region.

Low in catchment. No factor applied. Assumed that Data Drill precipitation Huon_06 - Precipitation 1.00 reflective of actual totals in this region.

Lower in catchment. Lower factor applied. Assumed that Data Drill closer reflection of Huon_07 - Precipitation 1.27 actual totals in this region.

Scaling used to correct volume balance at Huon_08 – Precipitation 1.30 site 119

Scaling used to correct volume balance at Huon_09 – Precipitation 1.30 site 119

Scaling used to correct volume balance at Huon_10 - Precipitation 1.30 site 119

Applied within global node to all (All sites) - Evaporation 0.90 evaporation sites (EvapScaleF)

There is a general absence of observed record within this catchment to undertake detailed analysis of the precipitation/run-off volume balance within this catchment and accordingly the applied scaling factors in Table 3.2 are subjective. It is recommended that should additional information become available within this catchment, a review of these scaling factors be undertaken.

Another catchment characteristic that could be influencing the volume balance within this catchment is the extensive region of karst (limestone). Similarly, there is no observed record to analyse its affect and it is assumed that the karst is unlikely to affect overall volume balance and is more likely to only affect hydrograph shape. Some sub- catchments may experience additional loss to groundwater and others may experience additional inflow from groundwater, however it is assumed that the net loss or gain in catchment volume due to these karst formations will be minor.

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3.5 Streamflow data The selection of sites suitable for model calibration was limited for this catchment. Although there were a number of sites within this catchment there were few with significant periods of record, complete flow ratings and at a representative location in the catchment. Huon River above Frying Pan Creek (site 119) was the site identified that best met these criteria. The sites investigated as potential calibration potential sites are given in the following table.

Table 3.3 Potential calibration sites

Site Name Site Sub- Period of Record Easting Northing Comments No. catchment Location Huon River 6201 SC1_a 05/04/1977 to 445600 5249100 Very high in u/s Sandfly 19/03/1990 catchment. Creek Possible secondary comparison site. Huon River 453 SC1_b 20/02/1963 to 441500 5236350 High in at Scotts 07/06/1972 catchment. Peak Possible secondary comparison site. Huon River 119 SC1_k 02/04/1948 to 486900 5235100 Mid-low a/b Frying present catchment. Pan Creek Good long term flow record. Huon River 14 SC1_m 27/06/1990 to 494000 5239100 Low in at Judbury 18/11/1998 catchment. No Bridge reliable flow record available.

A continuous time series in ML/day was provided at the calibration site by DPIW and it is therefore assumed that this represents the best available flow record. Hence no detailed review or alteration of this data has been undertaken.

Investigations of the rating histories and qualities contained on the Hydro Tasmania’s archives at site 119, indicate that the record appears to be based on a natural control with at least 3 ratings covering the whole period of record. The data appears to be reliable during the period of interest.

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3.6 Irrigation and water usage Information on the current water entitlement allocations in the catchment was obtained from DPIW and is sourced from the Water Information Management System (WIMS July 2007). The WIMS extractions or licenses in the catchment are of a given Surety (from 1 to 8), with Surety 1-3 representing high priority extractions for modeling purposes and Surety 4-8 representing the lowest priority. The data provided by DPIW contained a number of sites which had a Surety of 0. DPIW staff advised that in these cases the Surety should be determined by the extraction “Purpose” and assigned as follows:

Table 3.4 Assumed surety of unassigned records

Purpose Surety Aesthetic 6 Aquaculture 6 Commercial 6 Domestic 1 Industrial 6 Irrigation 6 Storage 6 Other 6 Power Generation 6 Recreation 6 Stock and Domestic S & D 1 Stock 1 Water Supply 1 Fire Fighting 1 Dust Proof 6

In total there were 28 ML unassigned entitlements (Surety = 0) identified for inclusion in the surface water model, 11 of which were assigned Surety 1 and 17 were assigned Surety 6.

DPIW staff also advised that the water extraction information provided should be filtered to remove the following records:

• Extractions relating to fish farms should be omitted as this water is returned to the stream. These are identified by a Purpose name called “ fish farm ” or “ Acquacult”. There were one fish farms identified in this catchment in SC11_f with an entitlement of 9490ML which was omitted.

• The extraction data set includes a “WE_status” field where only “ current” and “existing” should be used for extractions. All other records, for example deleted, deferred, transferred, suspended and proposed, should be omitted.

• There is some uncertainty in relation to the water supply extractions. There are

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24 current entitlements within the Huon catchment for extraction totaling 70 ML. However not all these are located at the point of extraction, but at administrative buildings within towns. Additionally there are WIMS entitlements within the Nicholls catchment model (Refer Willis 2008) that relate to extractions within this catchment. Water Supply entitlements were interpreted in the following manner:

o 24 entitlements, totaling 70 ML at Judbury (SC1_m) and with stream name “Dora Creek” were moved to SC18_b.

o 24 entitlements, totaling 970 ML at (SC19_a within the Nicholls model) and with stream name “Huon River” were moved to this model and included in SC1_m.

When modeling Scenario 3 (Environmental flows and Entitlements), water will only be available for Low Priority entitlements after environmental flow requirements have been met.

There were multiple communications with DPIW staff, on allowances for extractions not yet included in the WIMS (July 2007) water license database. DPIW advised that the unlicensed extractions estimate should be three times the current Surety 5, direct extractions. This unlicensed estimate should be apportioned across the sub-catchments the same as the Surety 5 extractions. Excluding “Water Supply” there were 1471ML of direct Surety 5 extractions (current) in the WIMS database and accordingly an estimate of 4413 ML of unlicensed extractions was apportioned across the catchment, with nearly all these extractions within SC1_m. DPIW advised that these unlicensed extractions should be assigned as Surety 6 and be extracted during the months of October through to April.

In addition to the extractions detailed above, an estimate was made for small farm dam extractions currently not requiring a permit and hence not listed in the WIMS database. These extractions are referred to in this report as unlicensed (small) farm dam extractions and details of the extraction estimate are covered in Section 3.6.1.

A summary table of total entitlement volumes on a monthly basis by sub-catchment is provided below in Table 3.5 and in the Catchment User Interface. These values include the estimates of unlicensed extractions, unlicensed farm dams and WIMS database extractions. A map of the WIMS (July 2007) water allocations in the catchment are shown in Figure 3-3.

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Table 3.5 Sub Catchment high and low priority entitlements

Water Entitlements Summarised - Monthly Demand (ML) for each Subarea & Month

Subcatch Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Total

High Priority Entitlements SC1_a 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 - SC1_b 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 - SC1_c 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 - SC1_d 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 - SC1_e 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 - SC1_f 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 - SC1_g 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 - SC1_h 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 - SC1_i 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 - SC1_j 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 - SC1_k 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 - SC1_l 0.08 0.08 0.08 0.08 3.34 3.23 3.34 3.34 3.23 0.08 0.08 0.08 17 SC1_m 77.19 65.07 56.19 54.15 80.41 84.43 80.41 78.41 72.43 48.19 48.15 60.19 805 SC2_a 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 - SC3_a 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 - SC3_b 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 - SC3_c 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 - SC3_d 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 - SC3_e 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 - SC4_a 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 - SC4_b 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 - SC4_c 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 - SC5_a 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 - SC6_a 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 - SC7_a 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 - SC7_b 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 - SC7_c 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 - SC7_d 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 - SC7_e 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 - SC7_f 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 - SC8_a 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 - SC9_a 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 - SC10_a 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 - SC10_b 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 - SC11_a 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 - SC11_b 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 - SC11_c 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 - SC11_d 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 - SC11_e 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 - SC11_f 0.00 0.00 0.00 0.00 0.51 0.49 0.51 0.51 0.49 0.00 0.00 0.00 3 SC11_g 0.00 0.00 0.00 0.00 0.71 0.69 0.71 0.71 0.69 0.00 0.00 0.00 4 SC11_h 0.00 0.00 0.00 0.00 1.76 1.70 1.76 1.76 1.70 0.00 0.00 0.00 9 SC11_i 0.00 0.00 0.00 0.00 0.45 0.43 0.45 0.45 0.43 0.00 0.00 0.00 2 SC11_j 0.00 0.00 0.00 0.00 0.32 0.31 0.32 0.32 0.31 0.00 0.00 0.00 2 SC12_a 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 - SC13_a 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 - SC14_a 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 -

15

Huon River Surface Water Model Hydro Tasmania Version No: FINAL 1.0

SC14_b 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 - SC14_c 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 - SC14_d 0.00 0.00 0.00 0.00 0.28 0.27 0.28 0.28 0.27 0.00 0.00 0.00 1 SC14_e 0.00 0.00 0.00 0.00 0.41 0.39 0.41 0.41 0.39 0.00 0.00 0.00 2 SC14_f 0.00 0.00 0.00 0.00 0.96 0.93 0.96 0.96 0.93 0.00 0.00 0.00 5 SC15_a 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 - SC15_b 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 - SC15_c 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 - SC16_a 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 - SC17_a 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 - SC18_a 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 - SC18_b 5.08 5.08 4.08 4.08 7.21 6.10 6.21 6.21 6.10 3.08 4.08 4.08 61 SC19_a 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 - Total 82 70 60 58 96 99 95 93 87 51 52 64 910 Low Priority Entitlements SC1_a 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 - SC1_b 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 - SC1_c 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 - SC1_d 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 - SC1_e 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 - SC1_f 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 - SC1_g 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 - SC1_h 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 - SC1_i 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 - SC1_j 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 - SC1_k 148.63 134.25 148.63 143.84 148.63 143.84 148.63 148.63 143.84 148.63 143.84 148.63 1,750 SC1_l 304.97 275.46 304.97 295.14 0.00 0.00 0.00 0.00 0.00 219.34 295.14 304.97 2,000 SC1_m 654.05 588.43 644.05 623.18 30.75 32.56 30.75 29.75 26.56 494.33 617.55 646.05 4,418 SC2_a 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 - SC3_a 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 - SC3_b 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 - SC3_c 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 - SC3_d 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 - SC3_e 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 - SC4_a 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 - SC4_b 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 - SC4_c 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 - SC5_a 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 - SC6_a 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 - SC7_a 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 - SC7_b 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 - SC7_c 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 - SC7_d 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 - SC7_e 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 - SC7_f 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 - SC8_a 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 - SC9_a 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 - SC10_a 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 - SC10_b 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 - SC11_a 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 - SC11_b 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 - SC11_c 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 - SC11_d 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 -

16

Huon River Surface Water Model Hydro Tasmania Version No: FINAL 1.0

SC11_e 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 - SC11_f 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 - SC11_g 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 - SC11_h 0.42 0.38 0.42 0.41 0.42 0.41 0.42 0.42 0.41 0.42 0.41 0.42 5 SC11_i 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 - SC11_j 32.94 29.75 32.94 31.87 0.00 0.00 0.00 0.00 0.00 23.69 31.87 32.94 216 SC12_a 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 - SC13_a 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 - SC14_a 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 - SC14_b 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 - SC14_c 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 - SC14_d 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 - SC14_e 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 - SC14_f 29.89 27.00 29.89 28.92 0.00 0.00 0.00 0.00 0.00 21.50 28.92 29.89 196 SC15_a 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 - SC15_b 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 - SC15_c 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 - SC16_a 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 - SC17_a 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 - SC18_a 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 - SC18_b 3.00 2.00 2.00 2.00 2.00 2.00 2.00 2.00 2.00 2.00 2.00 2.00 25 SC19_a 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 - Total 1,174 1,057 1,163 1,125 182 179 182 181 173 910 1,120 1,165 8,610 All Entitlements SC1_a 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 - SC1_b 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 - SC1_c 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 - SC1_d 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 - SC1_e 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 - SC1_f 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 - SC1_g 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 - SC1_h 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 - SC1_i 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 - SC1_j 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 - SC1_k 148.63 134.25 148.63 143.84 148.63 143.84 148.63 148.63 143.84 148.63 143.84 148.63 1,750 SC1_l 305.06 275.54 305.06 295.22 3.34 3.23 3.34 3.34 3.23 219.42 295.22 305.06 2,017 SC1_m 731.24 653.51 700.24 677.33 111.15 116.99 111.15 108.15 98.99 542.52 665.70 706.24 5,223 SC2_a 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 - SC3_a 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 - SC3_b 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 - SC3_c 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 - SC3_d 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 - SC3_e 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 - SC4_a 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 - SC4_b 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 - SC4_c 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 - SC5_a 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 - SC6_a 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 - SC7_a 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 - SC7_b 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 - SC7_c 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 - SC7_d 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 - SC7_e 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 -

17

Huon River Surface Water Model Hydro Tasmania Version No: FINAL 1.0

SC7_f 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 - SC8_a 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 - SC9_a 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 - SC10_a 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 - SC10_b 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 - SC11_a 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 - SC11_b 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 - SC11_c 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 - SC11_d 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 - SC11_e 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 - SC11_f 0.00 0.00 0.00 0.00 0.51 0.49 0.51 0.51 0.49 0.00 0.00 0.00 3 SC11_g 0.00 0.00 0.00 0.00 0.71 0.69 0.71 0.71 0.69 0.00 0.00 0.00 4 SC11_h 0.42 0.38 0.42 0.41 2.18 2.11 2.18 2.18 2.11 0.42 0.41 0.42 14 SC11_i 0.00 0.00 0.00 0.00 0.45 0.43 0.45 0.45 0.43 0.00 0.00 0.00 2 SC11_j 32.94 29.75 32.94 31.87 0.32 0.31 0.32 0.32 0.31 23.69 31.87 32.94 218 SC12_a 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 - SC13_a 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 - SC14_a 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 - SC14_b 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 - SC14_c 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 - SC14_d 0.00 0.00 0.00 0.00 0.28 0.27 0.28 0.28 0.27 0.00 0.00 0.00 1 SC14_e 0.00 0.00 0.00 0.00 0.41 0.39 0.41 0.41 0.39 0.00 0.00 0.00 2 SC14_f 29.89 27.00 29.89 28.92 0.96 0.93 0.96 0.96 0.93 21.50 28.92 29.89 201 SC15_a 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 - SC15_b 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 - SC15_c 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 - SC16_a 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 - SC17_a 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 - SC18_a 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 - SC18_b 8.08 7.08 6.08 6.08 9.21 8.10 8.21 8.21 8.10 5.08 6.08 6.08 86 SC19_a 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 - Total 1,256 1,127 1,223 1,184 278 278 277 274 260 961 1,172 1,229 9,520

18

Huon River Surface Water Model Hydro Tasmania Version No: FINAL 1.0

430000 440000 450000 460000 470000 480000 490000 500000 5280000 5280000 5275000 5275000 5270000 5270000 5265000 5265000

5260000 7-a 5260000

11-a

5255000 13-a 5255000 11-b 1-a 11-d 7-b 11-c 12-a 5250000 17-a 18-a 5250000 7-c 11-e 14-a 14-b 11-f 16-a 11-g 11-h

5245000 7-d 18-b 5245000 15-a 15-b 14-c 14-d 11-j 11-i 8-a 15-c 14-e 2-a 19-a 14-f

5240000 1-b 5240000 7-e 1-m 7-f 1-l 5-a 1-k 5235000 1-c 5235000

1-g 1-i 1-j 5230000 5230000 1-d 1-e 1-h 10-b

5225000 1-f 3-e 5225000

4-c

5220000 3-d 10-a 5220000

4-b 5215000 5215000

9-a 4-a 3-c 5210000 5210000 5205000 5205000

6-a 3-b 5200000 5200000 5195000 5195000

5190000 3-a 5190000 5185000 5185000 5180000 5180000

Legend

5175000 04 8 16 24 32 WIMS allocations 5175000 Sub-catchment boundary Kilometers 5170000 430000 440000 450000 460000 470000 480000 490000 500000

Figure 3-3 WIMS water allocations

19

Huon River Surface Water Model Hydro Tasmania Version No: FINAL 1.0

3.6.1 Estimation of unlicensed (small) farm dams Under current Tasmanian law, a dam permit is not required for a dam if it is not on a watercourse and holds less than 1ML of water storages (prior to 2000 it was 2.5 ML), and only used for stock and domestic purposes. Therefore there are no records for these storages. The storage volume attributed to unlicensed dams was estimated by analysis of aerial photographs and the methodology adopted follows:

• Aerial photographs were analysed. There was fair coverage of this catchment with high resolution photography. GoogleEarth had the best photographs, which covered the majority of area of interest. The dates of these maps varied between 2006 and 2007. The total number of dams, of any size, in 2 selected sub-catchments was counted by eye. The density of dams varied across the catchment due land use which changes from intensive agriculture through to native forest. The majority of the catchment is unpopulated and therefore unlikely to contain small farm dams. The two counted sub-catchments (SC1_m & SC18_b) represent the majority of area where dams are likely to exist;

• The number of licensed dams was subtracted from the total dam count determined above. Using this information, an average ratio of unlicensed dams per km 2 of agricultural land was estimated to be 2.6. This is in the lower range of what has been estimated in other catchments such as Ansons River (2.0), George River (6.9) and Nicholls (5.2). The ratio of unlicensed dams per km 2 of agricultural land was used as an estimation tool to determine the number of unlicensed dams in each uncounted sub- catchment. In each of these sub-catchments the percentage of agricultural land was visually estimated and multiplied by the unlicensed dams per km 2 of agricultural land ratio. In total it is estimated that the catchment contains 144 unlicensed dams;

• It was assumed most of these dams would be legally unlicensed dams (less than 1 ML and not situated on a water course) however, it was assumed that there would be a proportion of illegal unlicensed dams up to 20ML in capacity. Some of these were visible on the aerial photographs;

• A frequency distribution of farm dam sizes presented by Neal et al (2002) for the Marne River Catchment in South Australia showed that the average dam capacity for dams less than 20 ML was 1.4 ML (Table 3.6);

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• Following discussions with DPIW staff, the unlicensed dam demand was assumed to be 100%. The assumption is that all unlicensed dams will be empty at the start of May and will fill over the winter months, reaching 100% capacity by the end of September;

• Assuming this dam size distribution is similar to the distribution of the study catchment in South Australia, then the total volume of unlicensed dams can be estimated as 202 ML (144 * 1.4ML). The total volume of existing permitted dams extractions in the study catchment is 58 ML. Therefore the 202 ML of unlicensed dams equates to approximately 78% of the total dam extractions from the catchment. However it should be noted that this extraction is insignificant in comparison to the total catchment yield.

There are some inherent difficulties in detecting farm dams from aerial photography by eye. Depending on the season and time of day that the aerial photograph is taken, farm dams can appear clearly or blend into the surrounding landscape. Vegetation can obscure the presence of a dam, and isolated stands of vegetation can appear as a farm dam when in fact no such dam exists. On balance, however, the number of false detections is countered by the number of missed detections and in the absence of another suitably rapid method the approach gives acceptable results.

Table 3.6 Average capacity for dams less than 20 ML by Neal et al (2002)

Average Total Size Range Volume Number of Volume (ML) (ML) Dams (ML) 0 - 0.5 0.25 126 31.5 0.5 - 2 1.25 79 98.75 2 - 5 3.5 13 45.5 5 - 10 7.5 7 52.5 10 - 20 15 6 90 27.5 231 318.25 Average Dam Volume: 1.4 ML

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3.7 Environmental flows One of the modeling scenarios (Scenario 3) was to account for environmental flows within the catchment. DPIW advised, that for the Huon catchment, they currently do not have environmental flow requirements defined. In the absence of this information it was agreed that the calibrated catchment model would be run in the Modeled – No entitlements (Natural) scenario and the environmental flow would be assumed to be:

• The 20 th percentile for each sub-catchment during the winter period (01May to 31 st Oct);

• The 30 th percentile for each sub-catchment during the summer period (01 Nov – 30 April).

The Modeled – No entitlements (Natural) flow scenario was run from 01/01/1970 to 01/01/2007.

A summary table of the environmental flows on a monthly breakdown by sub-catchment is provided in the following table and in the Catchment User Interface.

Table 3.7 Environmental Flows

Catch ment Environmental Flow (ML/d) Per Month at subcatchment Area (km2) Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Ave SC1_a 98.2 92.2 49.7 133.0 217.8 260.1 252.0 360.0 345.8 287.8 256.9 196.2 199.1 220.9 SC1_b 125.7 306.9 161.2 402.8 694.1 800.7 739.1 1072.3 1033.3 818.7 732.0 610.4 534.4 658.8 SC1_c 40.3 354.3 183.7 447.3 795.2 925.7 857.8 1225.8 1194.9 937.7 839.8 674.0 615.2 754.3 SC1_d 45.3 407.5 210.8 507.5 918.1 1086.7 992.7 1407.1 1375.5 1070.0 960.8 770.3 702.2 867.4 SC1_e 46.5 460.0 242.6 563.7 1045.6 1251.5 1136.9 1584.5 1555.2 1208.6 1078.3 867.8 790.8 982.1 SC1_f 57.9 521.4 279.3 631.1 1202.0 1440.7 1314.1 1786.2 1768.5 1385.5 1225.3 989.9 900.0 1120.3 SC1_g 40.5 647.4 346.1 795.8 1516.5 1794.2 1642.5 2220.4 2198.4 1743.0 1531.1 1259.7 1156.4 1404.3 SC1_h 56.9 941.2 497.2 1142.8 2254.2 2513.7 2497.6 3181.9 3442.3 2605.5 2325.2 1856.3 1662.0 2076.6 SC1_i 99.1 1029.1 551.9 1270.2 2498.5 2716.7 2742.3 3520.9 3788.7 2870.4 2570.4 2038.7 1835.9 2286.1 SC1_j 80.8 1636.6 857.8 2124.4 3962.3 4219.5 4382.9 5601.9 6008.7 4613.6 4177.0 3254.6 2924.5 3647.0 SC1_k 67.9 2143.1 1137.8 2751.2 5074.6 5360.3 5788.6 7423.0 7707.1 6095.3 5416.2 4243.3 4058.6 4766.6 SC1_l 43.7 2379.3 1213.9 2954.2 5668.7 5582.7 6163.0 8039.4 8211.9 6524.2 5906.8 4645.3 4575.6 5155.4 SC1_m 85.0 2460.4 1229.5 2964.9 5734.2 5545.4 6295.5 8102.4 8409.0 6589.1 6023.7 4725.3 4658.4 5228.1 SC2_a 33.9 45.5 23.1 62.6 108.5 128.0 117.3 163.8 157.8 123.9 113.3 96.9 80.5 101.8 SC3_a 64.3 94.8 50.4 110.6 216.2 233.5 280.5 308.2 386.6 257.6 236.5 249.3 161.9 215.5 SC3_b 115.7 291.2 155.9 348.2 650.3 749.4 874.5 961.7 1188.9 786.4 736.5 745.3 505.9 666.2 SC3_c 80.9 369.8 199.0 462.3 810.3 958.6 1126.0 1236.6 1499.2 990.0 912.6 854.1 671.1 840.8 SC3_d 105.1 494.4 274.2 636.2 1085.5 1246.7 1522.9 1640.4 1976.2 1293.3 1201.0 1046.5 927.7 1112.1 SC3_e 43.1 521.6 292.8 676.5 1115.5 1306.4 1618.5 1742.8 2094.2 1378.8 1282.0 1124.1 987.5 1178.4 SC4_a 74.0 68.3 37.7 88.8 164.6 209.0 224.7 249.0 291.8 197.4 184.5 144.3 131.6 166.0 SC4_b 55.8 119.5 62.8 149.9 267.5 364.9 384.8 435.5 519.3 358.2 320.1 243.8 229.0 287.9 SC4_c 87.3 197.0 109.9 273.7 478.7 638.9 643.0 764.5 875.6 617.4 549.8 404.7 396.0 495.8 SC5_a 76.5 81.2 42.1 113.0 196.9 220.0 217.4 279.9 299.1 245.1 200.9 177.2 154.6 185.6

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SC6_a 33.3 38.7 21.7 49.2 96.0 106.2 124.2 137.1 166.3 106.5 100.1 93.1 71.8 92.6 SC7_a 73.3 70.5 37.5 103.1 168.1 194.5 190.7 267.8 262.6 222.8 192.0 153.8 149.8 167.8 SC7_b 57.7 128.5 70.1 179.9 299.4 351.4 342.5 478.1 463.6 395.8 345.0 269.1 268.4 299.3 SC7_c 66.3 279.7 149.7 373.8 676.7 740.4 729.8 972.4 1013.9 883.5 742.6 621.2 568.9 646.0 SC7_d 40.0 321.2 166.5 411.3 777.4 822.7 835.4 1100.6 1158.2 1002.3 872.3 711.3 663.1 736.9 SC7_e 60.2 366.4 187.2 462.5 896.3 929.0 962.4 1282.2 1311.0 1140.6 1003.7 811.0 756.7 842.4 SC7_f 38.3 389.6 193.9 482.2 934.9 957.6 1024.9 1375.1 1414.0 1182.9 1057.3 845.8 804.2 888.5 SC8_a 74.3 79.6 41.1 110.2 204.4 207.4 200.7 266.3 294.3 238.1 225.3 187.1 164.4 184.9 SC9_a 33.3 27.4 15.5 39.1 63.1 82.9 93.3 93.9 118.7 71.7 73.3 60.9 58.9 66.6 SC10_a 56.6 34.0 19.5 46.3 70.1 85.9 107.9 118.7 142.6 90.6 82.4 68.3 62.5 77.4 SC10_b 65.0 72.5 42.1 91.0 149.3 169.6 222.4 241.7 286.5 175.6 159.5 122.9 123.7 154.7 SC11_a 12.6 13.7 6.9 16.9 35.0 27.8 32.0 41.5 46.9 36.5 37.7 33.8 26.6 29.6 SC11_b 5.8 20.3 10.5 24.5 51.1 40.1 46.6 61.1 68.3 53.4 55.5 49.6 38.7 43.3 SC11_c 17.4 68.2 35.2 80.8 169.8 132.2 155.4 205.8 227.0 178.8 186.5 166.1 130.1 144.7 SC11_d 11.7 80.2 41.0 92.9 196.1 151.7 181.2 241.5 263.2 208.5 218.3 193.4 153.7 168.5 SC11_e 13.7 88.9 45.9 103.7 218.4 168.1 205.9 272.7 298.7 235.8 246.2 216.6 174.8 189.6 SC11_f 13.6 94.8 49.8 110.9 233.4 176.7 224.2 295.4 324.0 254.5 265.3 232.3 192.8 204.5 SC11_g 4.8 101.9 53.0 118.4 248.4 184.6 240.6 325.8 347.5 270.6 284.1 246.9 210.7 219.4 SC11_h 11.8 106.3 55.1 122.5 256.3 189.0 248.9 345.2 359.8 278.2 293.4 252.4 221.6 227.4 SC11_i 6.0 108.5 56.0 124.0 259.7 190.6 252.4 355.8 365.7 281.8 298.2 254.5 228.4 231.3 SC11_j 8.7 111.9 57.4 126.9 264.1 192.7 256.4 368.7 373.1 285.7 304.3 259.4 235.7 236.4 SC12_a 16.7 17.4 8.9 21.4 44.8 35.5 41.3 53.9 60.5 47.0 48.7 43.6 33.4 38.0 SC13_a 10.3 10.7 5.5 13.0 27.4 21.3 24.7 32.8 36.3 28.5 29.6 26.4 20.4 23.0 SC14_a 8.9 8.3 4.3 10.4 21.8 17.5 21.0 27.2 30.4 23.4 23.9 21.6 16.1 18.8 SC14_b 7.4 13.6 7.3 16.8 35.2 27.6 35.5 45.6 50.3 39.0 39.9 35.0 27.6 31.1 SC14_c 5.5 36.1 19.3 44.7 93.7 72.3 101.7 137.2 140.9 104.3 103.8 88.2 78.4 85.1 SC14_d 7.5 38.6 20.5 47.2 97.0 75.0 107.8 149.9 149.3 109.4 109.3 92.1 85.7 90.2 SC14_e 5.5 44.4 22.9 52.0 104.6 80.5 118.8 171.9 162.7 118.7 119.1 99.0 98.1 99.4 SC14_f 6.4 47.0 23.8 53.9 109.8 82.2 122.8 180.1 167.4 122.3 122.9 101.1 104.2 103.1 SC15_a 6.6 4.7 2.5 6.1 12.9 10.8 14.2 17.3 19.1 14.3 13.8 11.7 9.3 11.4 SC15_b 9.6 10.4 5.6 13.6 28.1 22.7 31.7 40.4 43.0 31.6 30.9 25.5 21.6 25.4 SC15_c 8.5 13.9 7.4 17.4 35.0 27.9 41.6 56.1 56.3 39.9 39.6 32.0 29.8 33.1 SC16_a 9.8 6.8 3.7 8.7 18.3 14.6 19.4 24.8 27.2 20.3 20.5 17.3 13.8 16.3 SC17_a 11.1 4.3 2.7 6.4 11.8 7.7 12.5 18.4 17.7 11.6 12.9 8.6 9.2 10.3 SC18_a 37.2 7.3 6.2 12.7 26.0 14.3 22.6 27.6 31.3 19.2 17.3 11.6 14.0 17.5 SC18_b 39.0 11.6 11.2 21.4 45.7 24.2 33.6 43.3 52.7 37.7 24.3 19.4 24.8 29.2 SC19_a 11.7 2.2 1.7 3.9 6.6 4.2 8.9 9.5 9.8 6.0 6.2 3.8 4.4 5.6

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4. MODEL DEVELOPMENT

4.1 Sub-catchment delineation Sub-catchment delineation was performed using CatchmentSIM GIS software.

CatchmentSIM is a 3D-GIS topographic parameterisation and hydrologic analysis model. The model automatically delineates watershed and sub-catchment boundaries, generalises geophysical parameters and provides in-depth analysis tools to examine and compare the hydrologic properties of sub-catchments. The model also includes a flexible result export macro language to allow users to fully couple CatchmentSIM with any hydrologic modeling package that is based on sub-catchment networks.

For the purpose of this project, CatchmentSIM was used to delineate the catchment, break it up into numerous sub-catchments, determine their areas and provide routing lengths between them.

These outputs were manually checked to ensure they accurately represented the catchment. If any minor modifications were required these were made manually to the resulting model.

For more detailed information on CatchmentSIM see the CatchmentSIM Homepage www.toolkit.net.au/catchsim/

4.2 Hydstra Model A computer simulation model was developed using Hydstra Modelling. The sub- catchments, described in Figure 2-1, were represented by model “nodes” and connected together by “links”. A schematic of this model is displayed in Figure 4-1.

The precipitation and evaporation is calculated for each sub-catchment using inverse- distance gauge weighting. The gauge weights were automatically calculated at the start of each model run. The weighting is computed for the centroid of the sub- catchment. A quadrant system is drawn, centred on the centroid. A weight for the closest gauge in each quadrant is computed as the inverse, squared, distance between the gauge and centroid. For each time step and each node, the gauge weights are applied to the incoming precipitation and evaporation data.

The AWBM Two Tap rainfall/runoff model (Parkyn & Wilson 1997) was used to calculate the runoff for each sub-catchment separately. This was chosen over the usual method of

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a single-tap AWBM model for the whole catchment as it allows better simulation of base flow recessions.

The flow is routed between each sub-catchment, through the catchment via a channel routing function.

Figure 4-1 Hydstra Model schematic

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4.2.1 Lake Pedder Lake Pedder, a major lake operated by Hydro Tasmania, is located in the upper Huon catchment. It has a major influence on the flow regime in the Huon River because water from the upper catchment (257.9 km 2) is diverted into the Gordon River via the Gordon Power Station. Custom code was entered into the outflow node of the relevant sub-catchment (SC1_b) to account for this catchment modification. The basic rules associated with this code are:

• Scenario 1, “No Entitlements (Defines ‘Natural’ Flows)” will model the catchment with no dam or lake present for all of record.

• Both the Scenario 2 “ with Entitlements (extraction not limited by Env.Flows)” and Scenario 3, “ Environmental Flows & Entitlements (‘Low Priority Ents. Limited by Env Flows’)” scenarios will model the catchment with:

o No dam or lake present in the model prior to its construction completion date of December 1971.

o All years following the completion date, flows downstream of the this lake will be a total of the average long term monthly values, which in this case is assumed to be zero for all periods.

4.3 AWBM Model The AWBM Two Tap model (Parkyn & Wilson 1997) is a relatively simple water balance model with the following characteristics:

• it has few parameters to fit,

• the model representation is easily understood in terms of the actual outflow hydrograph,

• the parameters of the model can largely be determined by analysis of the outflow hydrograph,

• the model accounts for partial area rainfall run-off effects,

• runoff volume is relatively insensitive to the model parameters.

For these reasons parameters can more easily be transferred to ungauged catchments.

The AWBM routine used in this study is the Boughton Revised AWBM model (Boughton, 2003), which reduces the three partial areas (A1 to A3) and three surface storage

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capacities (Cap1 to Cap3) to relationships based on an average surface storage capacity.

Boughton & Chiew (2003) have shown that when using the AWBM model, the total amount of runoff is mainly affected by the average surface storage capacity and much less by how that average is spread among the three surface capacities and their partial areas. Given an average surface storage capacity (CapAve), the three partial areas and the three surface storage capacities are found by;

Table 4.1 Boughton & Chiew, AWBM surface storage parameters

Partial area of S1 A1=0.134

Partial area of S2 A2=0.433

Partial area of S3 A3=0.433

Capacity of S1 Cap1=(0.01*CapAve/A 1)=0.075*CapAve

Capacity of S2 Cap2=(0.33*CapAve/ A 2)=0.762*CapAve

Capacity of S3 Cap3=(0.66*CapAve/ A 3)=1.524*CapAve

To achieve a better fit of seasonal volumes, the normally constant store parameter CapAve has been made variable and assigned a seasonal profile. In order to avoid rapid changes in catchment characteristics between months, CapAves of consecutive months were smoothed. A CapAve of a given month was assumed to occur on the middle day of that month. It was assumed that daily CapAves occurring between consecutive monthly CapAves would fit to a straight line, and a CapAve for each day was calculated on this basis. The annual profile of CapAves for the catchment is shown in Figure 4-3.

The AWBM routine produces two outputs; direct run-off and base-flow. Direct run-off is produced after the content of any of the soil stores is exceeded and it is applied to the stream network directly. Base-flow is supplied unrouted directly to the stream network, at a rate proportional to the water depth in the ground water store. The ground water store is recharged from a proportion of excess rainfall from the three surface soil storages.

Whilst the AWBM methodology incorporates an account of baseflow, it is not intended that the baseflow prediction from the AWBM model be adopted as an accurate estimate of the baseflow contribution. The base flow in the AWBM routine is based on a simple model and does not specifically account for attributes that affect baseflow such as geology and inter-catchment ground water transfers. During the model calibration the

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baseflow infiltration and recession parameters are used to ensure a reasonable fit with the observed surface water information.

The AWBM processes are shown in the following Figure 4-2;

Figure 4-2 Two Tap Australian Water Balance Model schematic

4.3.1 Channel Routing A common method employed in nonlinear routing models is a power function storage relation.

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S = K.Q n

K is a dimensional empirical coefficient, the reach lag (time). In the case of Hydstra/TSM Modelling:

α

and

Li = Channel length (km)

α = Channel Lag Parameter

n = Non-linearity Parameter

Q = Outflow from Channel Reach (ML/day)

A reach length factor may be used in the declaration of α to account for varying reach lag for individual channel reaches. eg. α.fl where fl is a length factor.

Parameters required by Hydstra/TSM Modeling and their recommended bounds are:

Table 4.2 Hydstra/TSM Modelling Parameter Bounds

α Channel Lag Parameter Between 0.0 and 5.0

L Channel Length (km) Greater than 0.0 (km)

n Non-linearity Parameter Between 0.0 and 1.0

4.4 Model Calibration Calibration was achieved by adjusting catchment parameters so that the modeled data best replicates the record at the site selected for calibration (for information on this site, refer to Section 3.5). The best fit of parameters was achieved by comparing the monthly, seasonal and annual volumes over the entire calibration period, using regression statistics and using practitioner judgment when observing daily and monthly time series comparisons. It should be noted that during the calibration process matching of average long term monthly volumes (flows) was given the highest priority and matching of peak

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flood events and daily flows was given lower priority. Further discussion of the model calibration fit is given in 4.4.2.

The calibration process can best be understood as attempting to match the modeled calibration flow (MCF) to the observed flow record. The MCF can be described as:

MCF = MNEM - (WE x TPRF)

Where: MCF = Modeled Calibration Flow MNEM = Modeled - No Entitlements (Modified). *

WE = Water Entitlements TPRF = Time Period Reduction Factor

* Refer to Glossary for additional explanation of these terms

In the Huon catchment, data from the period 30/08/1987 to 30/08/2007 was selected at Huon River above Frying Pan Creek (site 119) for calibration.

Water entitlements were included in the calibration model and adjusted to the time period of calibration by applying a Time Period Reduction Factor (TPRF). The TPRF was calculated by a method developed in the Tasmanian State of the Environment report (1996). This states that water demand has increased by an average of 6% annually over the last 4 decades. However, following discussions with DPIW the TPRF was capped at 50% of the current extractions if the mid year of the calibration period was earlier than 1995. In the Huon catchment, data from the period 30/08/1987 to 30/08/2007 was selected for calibration and accordingly a TPRF of 56% was applied to all extractions as the mid year of the calibration period was deemed to be 1997 which is prior to the 50% capped date of 1995. In the case of the Huon River the water entitlement extractions upstream the calibration site is insignificant in relation to the observed flow, and accordingly the model calibration would be unchanged regardless of the TPRF applied.

The model was calibrated to the observed flow as stated in the formula MCF = MNEM - (WE x TPRF). Other options of calibration were considered, including adding the water entitlements to the observed flow. However, the chosen method is considered to be the better option as it preserves the observed flow and unknown quantities are not added to the observed record. The chosen method also preserves the low flow end of the calibration, as it does not assume that all water entitlements can be met at any time.

In the absence of information on daily patterns of extraction, the model assumes that

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water entitlements are extracted at a constant daily flow for each month. For each daily time step of the model if water entitlements cannot be met, the modeled outflows are restricted to a minimum value of zero and the remaining water required to meet the entitlement is lost. Therefore the MCF takes account of very low flow periods where the water entitlements demand cannot be met by the flow in the catchment.

Table 4.4 shows the monthly water entitlements (demand) used in the model calibration upstream of the calibration site.

The adopted calibrated model parameters are shown in Table 4.3. These calibration parameters are adopted for all three scenarios in the user interface. Although it is acknowledged that some catchment characteristics such as land use and vegetation will have changed over time, it is assumed that the rainfall run-off response defined by these calibration parameters has not changed significantly over time and therefore it is appropriate to apply these parameters to all three scenarios.

As detailed in Section 4.3 to achieve a better fit of seasonal volumes, the normally constant store parameter CapAve has been made variable and assigned a seasonal profile. The annual profile of CapAve for the catchment is shown in the following table and graph.

Table 4.3 Adopted Calibration parameters PARAMETER VALUE PARAMETER VALUE INFBase 0.4 CapAve Jan 12 K1 0.97 CapAve Feb 14 K2 0.89 CapAve Mar 3 GWstoreSat 30 CapAve Apr 2 GWstoreMax 50 CapAve May 23 H_GW 30 CapAve Jun 29 EvapScaleF 0.9 CapAve July 40 Alpha 2.5 CapAve Aug 55 n 0.8 CapAve Sept 46 CapAve Oct 35 CapAve Nov 28 CapAve Dec 6

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60 CapeAve 50 40 30

CapAve 20 10 0 1 2 3 4 5 6 7 8 9101112 MONTH

Figure 4-3 Monthly Variation of CapAve Parameter

Results of the calibration are shown in the plots and tables that follow in this section. In all comparisons the “Modelled Calibration Flow” (refer to previous description) has been compared against the observed flow at the calibration location.

Daily time series plots of three discrete calendar years (Figure 4-4 to Figure 4-6) have been displayed for the calibration location, showing a range of relatively low to high inflow years and a range of calibration fits. The general fit for each annual plot is described in the caption text. This indication is a visual judgement of the relative model performance for that given year compared to the entire observed record. There is also a goodness of fit statistic (R2) shown on each plot to assist in the judgement of the model performance.

Overall the daily time series comparison between observed and MCF is judged as fair. It is expected that poor precipitation and evaporation representation across the catchment is the likely cause. Although there are 10 data drill precipitation and evaporation inputs to the model these are derived from observed record which is limited in this catchment (refer section 3.4). Therefore the data drill information is unlikely to accurately represent the precipitation and evaporation across this catchment. A significant problem associated with volume balance between modelled and observed flows was encountered when using the Data Drill information. To rectify this issue, scaling factors were applied to the Data Drill precipitation and evaporation inputs. Details of these scaling factors are outlined in 3.4.1.

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The catchment average precipitation as input to the model is also displayed to provide a representation of the relative size of precipitation events through the year. Note that the precipitation trace is plotted on an offset, secondary scale.

The monthly time series, over the whole period of observed record, are plotted in Figure 4-7 and overall shows a fair comparison between Modelled Calibration Flow and observed totals at the calibration location. This plot indicates that there is a change in the peak winter volume relationship around the year 2000. Prior to the year 2000, the modelled volumes typically exceed the observed and post 2000 the modelled volumes are typically less than observed. The cause is probably due to a combination of factors, such as:

• Observed high flow errors due to an undetected high stage rating change.

• A variation in the Data Drill information as a result of a change in the observed site information used to derive this data.

A trend similar to this was also observed in the neighbouring Esperance catchment (Willis 2008) which may be related. It is therefore recommended that additional studies be undertaken to determine the source of this error and potentially improve the model performance.

The monthly, seasonal and annual volume balances for the whole period of calibration record are presented in Figure 4-8 and Table 4.4. The natural (scenario1) values are significantly higher than the MCF due to the contribution of the catchment area upstream of Scotts Peak Dam. The demand values shown represent the adopted total water entitlements upstream of the calibration location, which in this case is small and accordingly have been multiplied by 100 for plotting purposes. The demand has been included to provide a general indication of the relative amount of water being extracted from the river.

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70000 50.0 Precipitation Modelled Calibration Flow Observed R2 = 0.82

60000 30.0

50000 10.0

40000 -10.0

30000 -30.0

20000 -50.0

10000 -70.0

0 -90.0 01/97 02/97 03/97 04/97 05/97 06/97 07/97 08/97 09/97 10/97 11/97 12/97 01/98

Figure 4-4 Daily time series comparison (ML/d) – Huon River - Good fit.

45000 50.0 Precipitation Modelled Calibration Flow Observed R2 = 0.68 40000 30.0

35000 10.0 30000

25000 -10.0

20000 -30.0

15000 -50.0 10000

-70.0 5000

0 -90.0 01/98 02/98 03/98 04/98 05/98 06/98 07/98 08/98 09/98 10/98 11/98 12/98 01/99

Figure 4-5 Daily time series comparison (ML/d) – Huon River – Fair fit.

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160000 70.0 Precipitation Modelled Calibration Flow Observed R2 = 0.90 140000 50.0

120000 30.0

100000 10.0

80000 -10.0

60000 -30.0

40000 -50.0

20000 -70.0

0 -90.0 01/07 02/07 03/07 04/07 05/07 06/07 07/07 08/07 09/07

Figure 4-6 Daily time series comparison (ML/d) – Huon River – Good fit.

1200000 Observed -Huon Rv a/b Frying Pan Creek - Site 119 R2 = 0.83 Modelled Calibration Flow (MCF) 1000000

800000

600000

400000 Monthly Volume (ML) Volume Monthly

200000

0 1987 1988 1988 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007

Figure 4-7 Monthly time series comparison – volume (ML)

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18000 Observed

16000 Modelled Calibration Flow (MCF) 14000 Scenario 1 - Modelled No Entitlements (Natural) 12000 Demand x100

10000

8000

6000 Average Flow (ML/Day) AverageFlow 4000

2000

0 Jul Jun Oct Jan Apr Mar Nov Feb Aug May Sep Dec WINTER ANNUAL SUMMER Figure 4-8 Long term average monthly, seasonal and annual comparison plot

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Table 4.4 Long term average monthly, seasonal and annual comparisons 1 Modelled- Scenario 1 MONTH Observed Calibration “Modelled -- Demand 2 No Entitlements Flow (MCF) (Natural)” Jan 3264.52 3276.07 3795.46 2.68 Feb 3014.30 3193.03 3678.30 2.68 Mar 2952.89 2929.17 3442.24 2.68 Apr 4665.98 4634.31 5488.18 2.68 May 7140.58 7288.13 8576.91 2.68 Jun 8715.02 8658.85 10152.27 2.68 Jul 9932.55 10022.79 11708.05 2.68 Aug 12705.04 13574.89 15704.64 2.68 Sep 9474.53 9519.07 11150.31 2.68 Oct 9250.98 9179.53 10679.38 2.68 Nov 6143.67 6086.76 7007.49 2.68 Dec 4576.93 4408.18 5124.27 2.68 WINTER 9536.45 9707.21 11328.59 2.68 SUMMER 4103.05 4087.92 4755.99 2.68 ANNUAL 6819.75 6897.56 8042.29 2.68 WINTER from May to Oct, SUMMER from Nov - Apr.

4.4.1 Factors affecting the reliability of the model calibration.

Regardless of the effort undertaken to prepare and calibrate a model, there are always factors which will limit the accuracy of the output. In preparation of this model the most significant limitations identified, that will affect the calibration accuracy are:

1. Misrepresentation of the catchment precipitation as previously discussed in sections 3.4 and 3.4.1 is a major source of error within this model. This is due to insufficient rainfall gauge information in and around the catchment. Despite the Data DRILL’s good coverage of grid locations, the development of this grid relies considerably on the availability of measured rainfall information in the region. This is also the case with the evaporation data, which will have a smaller impact on the calibration.

2. The assumption that water entitlements are taken at a constant rate for each month. Historically the actual extraction from the river would be much more

1 The natural (Scenario 1 ) results are significantly higher than the MCF results due to the additional contribution of catchment area upstream Scotts Peak Dam. 2 The demand value includes all extraction potential upstream of calibration site with a 56% time period reduction factor applied.

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variable than this and possess too many levels of complexity to be accurately represented in a model.

3. The current quantity of water extracted from the catchment is unknown. Although DPIW have provided water licence information (WIMS July 2007) and estimates of extractions in excess of these licences, these may not represent the true quantity of water extracted. No comprehensive continuous water use data is currently available.

4. The quality of the observed flow data (ratings and water level readings) used in the calibration may not be reliable for all periods. Even for sites where reliable data and ratings has been established the actual flow may still be significantly different to the observed (recorded) data, due to the inherent difficulties in recording accurate height data and rating it to flow. These errors typically increase in periods of low and high flows.

5. The daily average timestep of the model may smooth out rainfall temporal patterns and have an effect on the peak flows. For example, intense rainfall events falling in a few hours will be represented as a daily average rainfall, accordingly reducing the peak flow.

6. The precipitation and evaporation for each sub-catchment is calculated using an inverse distance gauge weighting. The catchment topography changes significantly within this catchment and the precipitation and evaporation in some sub-catchments may not be accurately represented using the inverse distance weighting methodology. However, due to the complexities involved with accounting for localised topography effects and general lack of long term climate data within these areas, no adjustment to the current methodology has been undertaken.

7. The model does not explicitly account for changes in vegetation and terrain within individual sub-catchments. Effects due to vegetation and terrain are accounted for on catchment average basis, using the global AWBM fit parameters. Therefore individual sub-catchment run-off may not be accurately represented by the model’s global fit parameters. To account for this a much more detailed and complex model would be required.

8. Catchment freezing and snowmelt in the upper catchment, during the winter months, will affect the flow regime and this has not been specifically handled within this model.

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9. There are known effects on the flow regime due to groundwater in this catchment. The affects on ground water and inter-catchment transfers are unknown and not accounted for within the AWBM model. There is extensive karst within the Huon catchment and caves in the Mt Anne region are the deepest in Australia. A much more complex model, detailed geology and ground water monitoring would be required to account for these affects.

4.4.2 Model Accuracy - Model Fit Statistics The following section is an additional assessment of how reliably the model predicts flow at the calibration site.

One of the most common measures of comparison between two sets of data is the coefficient of determination (R 2). If two data sets are defined as x and y, R 2 is the variance in y attributable to the variance in x. A high R 2 value indicates that x and y vary evenly together – that is, the two data sets have a good correlation. In this case x and y are observed flow and modelled calibration flow. So for the catchment model, R 2 indicates how much the modelled calibration flow changes as observed flow changes. Table 4.5 shows the R 2 values between observed and modelled daily and monthly flows, as well as the proportional difference (%) between long-term (20 years) observed and modelled calibration flow.

Table 4.5 Model Fit Statistics

Measure of Fit Huon River u/s Frying Pan creek (Site 119) Daily coefficient of determination (R 2 Value) 0.67 Monthly coefficient of determination (R 2 Value) 0.83 Difference in observed and estimated long term +1.1% annual average flow

An improvement to the long term average annual flow difference could have been achieved but this would have been to the detriment to the shape of the CapAve curve (refer Figure 4-3). A minor improvement in the August volume fit would have required an unrealistically large increase in the August CapAve value and this was deemed inappropriate.

As previously mentioned the focus of the calibration process was to obtain a good correlation between monthly long term volumes (and flows) and lesser priority was given to daily correlations. However without a good simulation of daily flows, a good

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simulation of monthly flows would be difficult to achieve. A target R2 of 0.70 (or greater) was set for the daily flows and a target R2 of 0.85 (or greater) was set for monthly flows. However for this model this target was not quite achieved for the reasons discussed previously (refer to 4.4.1). A summary of comparative qualitative and statistical fit descriptions are provided in the following Table.

Table 4.6 R2 Fit Description

Qualitative Fit Description Daily R 2 Monthly R 2

Poor R2 < 0.65 R2 < 0.8

Fair 0.65 ≥ R 2 > 0.70 0.8 ≥ R 2 > 0.85

Good R2 ≥ 0.70 R2 ≥ 0.85

It should be noted that although the R2 value is a good indicator of correlation fit it was only used as a tool, to assist in visually fitting the hydrographs. One of the major limitations is that minor differences in the timing of hydrograph events can significantly affect the R2 value, although in practice a good calibration has been achieved.

Another indicator on the reliability of the calibration fit is the proportional difference between observed data and the modelled calibration flow (MCF), measured by percent (%). The proportional difference for the daily flows and monthly volumes were calculated and are presented in Figure 4-9 and Figure 4-10 in the form of a duration curve. These graphs show the percentage of time that a value is less than a specified bound. For example in Figure 4-9, for the All Record trace, 40% of the time the difference between the MCF and observed flow is less than 26%. Similarly in Figure 4-10, for the All Record trace, 50% of the time the difference between the MCF monthly volume and observed volume is less than 22%.

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200.0 All record Winter Summer 180.0

160.0

140.0

120.0

100.0

80.0 (%) - Observed vs Modelled (MCF) Observed(%) vs- Modelled 60.0

40.0 Difference

20.0

0.0 0% 5% 10% 15% 20% 25% 30% 35% 40% 45% 50% 55% 60% 65% 70% 75% 80% 85% 90% 95% 100% Percentage of time Difference is less than

Figure 4-9 Duration Curve – Daily flow percentage difference

140.0 All record Winter Summer 120.0

100.0

80.0

60.0 (MCF)

40.0 (%) - Observed - (%) vs Modelled

20.0

0.0 Difference 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Percentage of time Difference is less than

Figure 4-10 Duration Curve – Monthly volume percentage difference

Although these duration curves are an indicator of the reliability of the modelled data, they also have their limitations and should be used in conjunction with a visual assessment of the hydrograph fit in determining calibration reliability. One of the major limitations is that in periods of low flow, the percentage difference between observed and modelled can be large although the value is not significant. For example, a 1ML/day difference, would show as a 200% difference if the observed flow was 0.5

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ML/day. The duration curve graphs shows three traces, the Summer 3, the Winter 4 and All Record . The higher values, caused by the larger proportion of low flows, can be seen in the Summer trace.

4.4.3 Model accuracy across the catchment The model has been calibrated to provide a good simulation for monthly and seasonal volumes at the calibration site. Calibration sites are typically selected low in the catchment to represent as much of the catchment as possible. How the reliability of this calibration translates to other specific locations within the catchment is difficult to accurately assess, however on average it would be expected that the model calibration would translate well to other locations within the catchment. The accuracy of the model in predicting monthly volumes at other locations has been analysed for five river catchments modelled as part of this project. The results of this assessment are summarised in Appendix A. These analyses suggest that on average the models predict volumes well across the catchment.

The fit of the hydrograph shape (daily flows) is expected to be more site specific and therefore it is predicted that the calibration fit of these will deteriorate as the catchment area decreases.

In the Huon catchment there are two other gauging sites which can be used to assess the calibration fit at alternative locations. Plots of the monthly times series volumes and the corresponding R2 values are shown in Figure 4-11 and Figure 4-12. The results show that the correlation between modelled and observed volumes at these two sites compares very well with that of the calibration site. This, in some part, is due to the fact that these sites were utilised as a reference during the Data Drill factoring process (refer 3.4.1).

3 Summer period = Nov to April. 4 Winter period = May to Oct.

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Observed - Huon River at Scott's Peak - site 453 Modelled with entitlements (extracted) - SC1_b 160000.0 R2 = 0.91

140000.0

120000.0

100000.0

80000.0

60000.0 Monthly Volume (ML) Volume Monthly

40000.0

20000.0

0.0 01/63 01/64 01/65 01/66 01/67 01/68 01/69 01/70 01/71 01/72

Figure 4-11 Time Series of Monthly Volumes- Site 453

Observed - Area Scaled - Huon River u/s Sandfly Creek - site 6201 Modelled with entitlements (extracted) - SC1_a 50000.0 R2 = 0.93 45000.0

40000.0

35000.0

30000.0

25000.0

20000.0 Monthly Volume (ML) Volume Monthly 15000.0

10000.0

5000.0

0.0 11/78 11/79 11/80 11/81 11/82 11/83 11/84 11/85 11/86 11/87 11/88 11/89

Figure 4-12 Time Series of Monthly Volumes- Site 6201

In the Huon catchment there were no additional gauging sites identified in the key interest areas of the Russell and Little Denison Rivers.

In the absence of alternative observed data in these areas, the model’s ability to predict flow volumes was ascertained by extrapolating flow data recorded at the calibration site. It was assumed that streamflow volume increased by the same proportion as

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catchment area. Thus if a calibration site has a subcatchment area A and a flow volume of Q A, and another site in the catchment has a subcatchment area B and a flow volume of Q B, then

QB = Q A.(B/A)

This assumption is crude, as it ignores precipitation variability and variability in water extractions within the catchment, and therefore it will not definitively demonstrate a model’s performance throughout the catchment. However, after discussion with DPIW, the method was included as a basic overview of the model’s ability to predict flow volumes throughout other catchments.

One sub-catchments was selected in both the Little Denison and Russell River catchments.

Little Denison River - comparison of scaled calibration site and SC14_f

The area ratio of sub-catchment SC14_f to the observed data (site 119) was calculated to be 4.8%. The observed monthly volumes at the calibration site were multiplied by this ratio in order to calculate a proxy ‘observed’ record at the catchment outflow and the results are shown in Figure 4-13. These two traces do not compare well, however this is assumed due to the fact that the average precipitation contributing to SC14_f flows is significantly lower (approx 0.6) than that falling on the sub-catchments which contribute to the flow of the calibration site. Figure 4-14 show a comparison of the same two sites, however the observed site has also been scaled (approximately) for variability in annual precipitation. These two traces compare more favourably but this plot highlights the difficulties of using scaled observed data as a guide for determining flows at alternate locations or assessing model performance, especially in a large catchment with diverse topography and precipitation. The model allows for the spatial variability of precipitation over the catchment, thus the modelled flow is predicted to better estimate flow due to precipitation variability.

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Observed - Area Scaled - Huon Rv u/s frying Pan Crk - site 119 Modelled with entitlements (extracted) - SC14_f 45000.0 R2 = 0.80 40000.0

35000.0

30000.0

25000.0

20000.0

15000.0 Monthly Volume (ML) Volume Monthly

10000.0

5000.0

0.0 01/87 01/88 01/89 01/90 01/91 01/92 01/93 01/94 01/95 01/96 01/97 01/98 01/99 01/00 01/01 01/02 01/03 01/04 01/05 01/06 01/07

Figure 4-13 Time Series of Monthly Volumes- SC14_f (Area scaling)

Observed - Area & Rain Scaled - Huon Rv u/s frying Pan Crk - site 119 Modelled with entitlements (extracted) - SC14_f 35000.0 R2 = 0.80

30000.0

25000.0

20000.0

15000.0 Monthly Volume (ML) Volume Monthly 10000.0

5000.0

0.0 01/87 01/88 01/89 01/90 01/91 01/92 01/93 01/94 01/95 01/96 01/97 01/98 01/99 01/00 01/01 01/02 01/03 01/04 01/05 01/06 01/07

Figure 4-14 Time Series of Monthly Volumes- SC14_f (Area & Rain scaling)

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Russell River - comparison of scaled calibration site and SC11_j

The area ratio of sub-catchment SC11_j to the observed data (site 119) was calculated to be 7.9%. The observed monthly volumes at the calibration site were multiplied by this ratio in order to calculate a proxy ‘observed’ record at the catchment outflow and the results are shown in Figure 4-15. These two traces do not compare well, however this is assumed due to the fact that the average precipitation contributing to SC11_j flows is significantly lower (approx 0.6) than that falling on the sub-catchments which contribute to the flow of the calibration site. Figure 4-16 show a comparison of the same two sites, however the observed site has also been scaled (approximately) for variability in annual precipitation. These two traces compare more favourably but this plot highlights the difficulties of using scaled observed data as a guide for determining flows at alternate locations or assessing model performance, especially in a large catchment with diverse topography and precipitation. The model allows for the spatial variability of precipitation over the catchment, thus the modelled flow is predicted to better estimate flow due to precipitation variability.

Observed - Area Scaled - Huon Rv u/s frying Pan Crk - site 119 Modelled with entitlements (extracted) - SC11_j 70000.0 R2 = 0.80

60000.0

50000.0

40000.0

30000.0 Monthly Volume (ML) Volume Monthly 20000.0

10000.0

0.0 01/87 01/88 01/89 01/90 01/91 01/92 01/93 01/94 01/95 01/96 01/97 01/98 01/99 01/00 01/01 01/02 01/03 01/04 01/05 01/06 01/07

Figure 4-15 Time Series of Monthly Volumes- SC11_j (Area scaling)

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Observed - Area & Rain Scaled - Huon Rv u/s frying Pan Crk - site 119 Modelled with entitlements (extracted) - SC11_j 70000.0 R2 = 0.80

60000.0

50000.0

40000.0

30000.0 Monthly Volume (ML) Volume Monthly 20000.0

10000.0

0.0 01/87 01/88 01/89 01/90 01/91 01/92 01/93 01/94 01/95 01/96 01/97 01/98 01/99 01/00 01/01 01/02 01/03 01/04 01/05 01/06 01/07

Figure 4-16 Time Series of Monthly Volumes- SC11_j (Area & Rain scaling)

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5. MODEL RESULTS

The completed model and user interface allows data for three catchment demand scenarios to be generated:

• Scenario 1 – No entitlements (Natural Flow);

• Scenario 2 – with Entitlements (with water entitlements extracted);

• Scenario 3 - Environmental Flows and Entitlements (Water entitlements extracted, however low priority entitlements are limited by an environmental flow threshold).

For each of the three scenarios, daily flow sequence, daily flow duration curves, and indices of hydrological disturbance can be produced at any sub-catchment location.

For information on the use of the user interface refer to the Operating Manual for the NAP Region Hydrological Models (Hydro Tasmania 2004).

Outputs of daily flow duration curves and indices of hydrological disturbance at the model calibration sites are presented below and in the following section. The outputs are a comparison of scenario 1 (No entitlements - Natural) and scenario 3 (environmental flows and entitlements) for period 01/01/1972 to 01/01/2007. The start date of 1972 was selected as this is post completion of Lake Pedder. Results have been produced at the calibrations site, Huon River a/b Frying Pan Creek, site 119. It should be noted that for this catchment the hydro generation activities influence these results as the flow regime changes significantly between scenarios 1 & 3, overwhelming any affects that extracting entitlements may have.

100000.00

10000.00

Flow (ML/d) 1000.00 Natural Entitlements Extracted 100.00 0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100% Percent Of Time Exceeded

Figure 5-1 Daily Duration Curve

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5.1.1 Indices of hydrological disturbance The calculation of the modeled flow estimates were used to calculate indices of hydrological disturbance. These indices include:

• Index of Mean Annual Flow

• Index of Flow Duration Curve Difference

• Index of Seasonal Amplitude

• Index of Seasonal Periodicity

• Hydrological Disturbance Index

The indices were calculated using the formulas stated in the Natural Resource Management (NRM) Monitoring and Evaluation Framework developed by SKM for the Murray-Darling Basin (MDBC 08/04).

The following table shows the Hydrological Disturbance Indices at 3 locations within the catchment, comparing scenario 1 (No entitlements - Natural) and scenario 3 (environmental flows and entitlements) for period 01/01/1972 to 01/01/2007. The start date of 1972 was selected as this is post completion of Lake Pedder. Five sites in addition to the calibration site have been selected to give an indication of the variability of the indices of hydrological disturbance across the catchment.

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Table 5.1 Hydrological Disturbance Indices

Disturbance undisturbed SC1_k SC1_c SC1_m SC14_f SC11_j SC3_e Indices (natural flow) Huon u/s (high in (Low in (Low in Lt (Low in (Low in Frying Huon Huon Denison Russell Picton Pan Creek catchment) catchment) catchment) catchment) catchment) Index of Mean Annual 1.00 0.86 0.13 0.88 1.0 1.0 1.0 Flow, A Index of Flow Duration 1.00 0.84 0.12 0.86 1.0 1.0 1.0 Curve Difference, M Index of Seasonal 1.00 0.87 0.13 0.88 1.0 1.0 1.0 Amplitude, SA Index of Seasonal 1.00 1.00 1.00 1.00 1.0 1.0 1.0 Periodicity, SP Hydrological Disturbance 1.00 0.88 0.24 0.89 1.0 1.0 1.0 Index, HDI

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Hydrological Disturbance Index: This provides an indication of the hydrological disturbance to the river’s natural flow regime. A value of 1 represents no hydrological disturbance, while a value approaching 0 represents extreme hydrological disturbance.

Index of Mean Annual Flow: This provides a measure of the difference in total flow volume between current and natural conditions. It is calculated as the ratio of the current and natural mean annual flow volumes and assumes that increases and reductions in mean annual flow have equivalent impacts on habitat condition.

Index of Flow Duration Curve Difference: The difference from 1 of the proportional flow deviation. Annual flow duration curves are derived from monthly data, with the index being calculated over 100 percentile points. A measure of the overall difference between current and natural monthly flow duration curves. All flow diverted would give a score of 0.

Index of Seasonal Amplitude: This index compares the difference in magnitude between the yearly high and low flow events under current and natural conditions. It is defined as the average of two current to natural ratios. Firstly, that of the highest monthly flows, and secondly, that of the lowest monthly flows based on calendar month means.

Index of Seasonal Periodicity: This is a measure of the shift in the maximum flow month and the minimum flow month between natural and current conditions. The numerical value of the month with the highest mean monthly flow and the numerical value of the month with the lowest mean monthly flow are calculated for both current and natural conditions. Then the absolute difference between the maximum flow months and the minimum flow months are calculated. The sum of these two values is then divided by the number of months in a year to get a percentage of a year. This percentage is then subtracted from 1 to give a value range between 0 and 1. For example a shift of 12 months would have an index of zero, a shift of 6 months would have an index of 0.5 and no shift would have an index of 1.

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6. FLOOD FREQUENCY ANALYSIS

A flood frequency plot has been developed at the Huon u/s Frying Pan Creek (site 119). The plot shown below in Figure 6-1 consists of three traces:

1. Observed data. The annual maxima for this trace have been developed from continuous measured data (1972 - 2007, post Lake Pedder) at the site giving a better representation of the flood peak than the modelled daily average maxima. At the Huon u/s Frying Pan Creek site in total 35 annual maxima values were available for this flood frequency analysis. The confidence limits on the plots represent the level of certainty of this observed dataset.

2. Modelled data (Scenario 3 - Environmental Flows & Entitlements) – same period as observed data. Note that the modelled annual maxima has been determined from a daily average flow dataset and accordingly does not represent the instantaneous flood maximum.

3. Modelled data (Scenario 3 - Environmental Flows & Entitlements) – whole period of record. Note that the modelled annual maxima have been determined from a daily average flow dataset and the period of record analysed is from 1900 to 2007.

The difference between flood peak frequency derived from recorded continuous flow data and flood peak frequency derived from modelled daily average flow can be obtained by comparing the first two traces as these relate to the same time period.

However, it should be noted that during the calibration process the highest priority was to achieve the best volume match between modelled and observed. As a result, the matching of flood peaks during calibration was of a lesser priority. Also the modelled flood peaks are based on daily (total) precipitation and accordingly these lack the temporal refinement to produce peaky outputs. That is, flood events are usually based on high intensity precipitation and this is not accurately captured using models and precipitation run on a daily time step.

These two factors do affect the accuracy of the modelled flood peaks used in the development of this flood frequency curve.

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1000000

5% Confidence Limit

100000

95% Confidence Limit

Observed Data Peak Discharge (ML/Day) Peak Discharge Modelled Data - Same period as observed data Modelled Data - Whole period of record

10000 1.111 1.25 2 5 10 50 100

Annual Exceedence Probability (1:Y)

Figure 6-1 Modelled and Observed Flood Frequency Plot – Huon River u/s Frying Pan Creek

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7. REFERENCES

Boughton, W.C. and Chiew, F.,(2003) Calibrations of the AWBM for use on Ungauged Catchments

CatchmentSIM Homepage www.toolkit.net.au/catchsim/ , December 2006

QNRM Silo (Drill Data) Homepage www.nrm.qld.gov.au/silo , January 2005

SKM (2003) Estimating Available Water in Catchments in Catchments Using Sustainable Diversion Limits. Farm Dam Surface Area and Volume relationship, report to DSE, Draft B October 2003

Hydrology Theme Summary of Pilot Audit Technical Report – Sustainable Rivers Audit. MDBC Publication 08/04.

National Land and Water Resources Audit (NLWRA) www.audit.ea.gov.au/anra/water/ ; January 2005.

Hydro Tasmania (2004). Operating Manual for the NAP region Hydrological Models. Hydro Report 118783 – Report -015, 17 September 2004.

Neal B, Nathan RJ, Schreider S, & Jakeman AJ. 2002, Identifying the separate impact of farm dams and land use changes on catchment yield. Aust J of Water Resources, IEAust,; 5(2):165-176.

Parkyn R & Wilson D, (1997): Real-Time Modelling of the Tributary Inflows to ECNZ's Waikato Storages. 24th Hydrology & Water Resources Symposium Proceedings IEAust, Auckland NZ 1997.

State of the Environment Report, Tasmania, Volume 1 Conditions & Trends 1996. State of Environment Unit, Lands Information Services, DELM.

SKM (2005) Development and Application of a Flow Stress Ranking Procedure, report to Department of Sustainability and Environment, Victoria.

Willis (2008), DPIW – Surface Water Models, Esperance catchment s, March 2008.

7.1 Personal Communications Graham, B. Section Head, Ecohydrology, Water Assessment, DPIW. Dec - Feb 2008.

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8. GLOSSARY

Coefficient of determination (R 2): One of the most common measures of comparison between two sets of data is the coefficient of determination (R 2). If two data sets are defined as x and y, R 2 is the variance in y attributable to the variance in x. A high R 2 value indicates that x and y vary together – that is, the two data sets have a good correlation.

High priority entitlements: Water entitlements with an assigned Surety 1 to 3.

Low priority entitlements: Water entitlements with an assigned Surety 4 to 8.

Modelled – No entitlements (Natural) : The TimeStudio surface water model run in a natural state. That is, all references to water entitlements have been set to zero. Additionally any manmade structures such as dams, power stations and diversions have been omitted and the modelled flow is routed, uncontrolled through the catchment. This is also referred to as Scenario 1.

Modelled – No entitlements (Modified) : The TimeStudio surface water model run with no water entitlements extracted. That is, all references to water entitlements have been set to zero. Where human structures are identified that significantly affect the flow regime, such as large dams, power stations and diversions, the TimeStudio model contains custom code to estimate the flow effect on the downstream subareas. This custom code takes effect from the completion date of the structure. Where there are no significant human structures in the catchment or the model is run before the completion of these structures this model will produce the same output as “Modelled – No entitlements (Natural)”. This option is not available within the user interface and is one of several inputs used to derive a modelled flow specifically for calibration purposes. It is also referred to as MNEM in Section 4.4.

Modelled – with entitlements (extracted): The TimeStudio surface water model with water entitlements removed from the catchment flow. Where human structures are identified within a catchment that significantly affect the flow regime, such as large dams, power stations and diversions, the TimeStudio model contains custom code to estimate the flow effect on the downstream sub-catchments. This custom code takes effect from the completion date of the structure. This is also referred to as Scenario 2.

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Huon River Surface Water Model Hydro Tasmania Version No: FINAL 1.0

Modelled – environmental flows and entitlements (extracted ): The TimeStudio surface water model with water entitlements removed. However, low priority entitlements are only removed when sub-catchment flow exceeds a specified environmental threshold. Where manmade structures are identified within a catchment, such as dams, power stations and diversions the TimeStudio model contains code to estimate the flow effect on the downstream subcatchments, commencing on the completion date of the structure. This is also referred to as Scenario 3.

Time Period Reduction Factor (TPRF): A reduction factor applied to current levels of water extracted from a catchment. The TPRF was applied to satisfy the assumption that the amount of water extracted from Tasmanian catchments (e.g. for agriculture) has increased over time. The TPRF was calculated by a method developed in the Tasmanian State of the Environment report. This states that water demand has increased by an average of 6% annually over the last 4 decades. This factor is applied to current water entitlements to provide a simple estimate of water entitlements historically. However, following discussions with DPIW the TPRF was capped at 50% of the current extractions if the mid year of the calibration period was earlier than 1995.

Water entitlements: This refers generally to the potential water extraction from the catchment. Included are licensed extractions documented in WIMS (July 2007) estimates of additional unlicensed extractions and estimates of unlicensed farm dams. Unless specified otherwise, Hydro Tasmania dams and diversions are not included.

WIMS (July 2007): The Department Primary Industries and Water, Water Information Management System, updated to July 2007.

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Huon River Surface Water Model Hydro Tasmania Version No: FINAL 1.0

APPENDIX A

This appendix investigates the reliability of the catchment models at predicting river flow throughout the catchment. One of the difficulties in assessing model reliability is the lack of observed data, as there is often only one reliable gauging site within the catchment. Five catchments that do have more than one gauging site and concurrent periods of record were selected and investigated with the results presented in Table A-1. The analysis undertaken is outlined below.

• The relationship between catchment area of the calibration site (primary site) and the secondary site was determined. Good variability is represented within this selection, with the secondary site catchment area ranging between 6.6% and 41.5% of the calibration site.

• The catchment area relationship was used to derive a time series at the secondary site based on scaled observed data from the calibration site. This was used in subsequent analysis to assess the suggestion that an area scaled time series, derived from a primary site was a good representation of sub- catchment flow in the absence of a secondary gauging site.

• For concurrent periods, estimated monthly volumes (ML) were extracted at both the calibration site and the secondary site.

• R2 values were calculated on the following data sets for concurrent periods:

o Correlation A: The correlation between the calibration site observed data and calibration site modelled data . This provides a baseline value at the calibration site for comparison against the other correlations.

o Correlation B: The correlation between the calibration site observed data (which has been reduced by area) and secondary site observed data . This shows the relationship of area scaled estimates as a predictor of sub-catchment flows, in this case by comparison with a secondary gauge.

o Correlation C: The correlation between the calibration site observed data (which has been reduced by area) and secondary site modelled data . This compares modelled data with an area scaled data set derived from observed data. This has been done because in the absence of a gauging site, observed data from another site is often

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assumed as a good indication of flow within the sub-catchment (Correlation B addresses this assumption). Where this assumption is applied, this correlation provides a statistical comparison of the models ability to predict comparable volumes to that of an area scaled estimate.

o Correlation D: The correlation between the secondary site observed data and secondary site modelled data . This has been done to assess how well the calibration undertaken at the primary site directly translates to other sub-catchments within the model.

The catchment model has been calibrated to provide a good fit for monthly and seasonal volumes at the calibration site. Calibration sites are typically selected low in the catchment to represent as much of the catchment as possible. Therefore the calibration fit parameters on average are expected to translate well to other sub- catchments. However, where individual sub-catchments vary significantly in terrain or vegetation or precipitation compared to the catchment average, errors are expected to be greater. The analysis undertaken in this section appears to confirm that the models perform acceptably and the conclusions of this analysis are summarised below:

1. Four of the five catchments studied showed fair to good R2 values between observed and modelled data at the secondary site. (Correlation D).

2. The George secondary site was the worst performing in the study with a fair R2 value of 0.83. It is expected that this is due to localised changes in terrain, vegetation and/or precipitation. This is a known limitation of the model and is therefore expected in some cases.

3. Scaling the calibration site observed data by area to derive a data set at another location is not recommended. Area scaled data does not consistently outperform the model at predicting flow/volumes within catchment. It is demonstrated that the model does (in the majority of cases) a good job of directly predicting the flow/volumes within catchment.

Time Series plots of the monthly volumes in megalitres for the five catchments studied in this section are shown in Figure A-1 to Figure A-5. These plots show that generally the calibration fit at the primary site translates well as a direct model output at other locations within the catchment, when modelling monthly volumes.

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Observed - Forth a/b Lemonthyme Site 450 140000 Site 450 - Modelled - with entitlements Observed- Scaled Forth at Paloona Bdg - site 386 120000

100000

80000

60000 Monthly Volume (ML) Volume Monthly 40000

20000

0 1963 1964 1964 1965 1966 1967 1968

Figure A-1 Forth catchment – monthly volumes at secondary site.

Observed - Ransom Rv Site 2217 5000 Site 2217 Modelled - with entitlements Observed - Scaled George at WS site 2205 4500

4000

3500

3000

2500

2000

Monthly Volume (ML) Volume Monthly 1500

1000

500

0 1983 1984 1987 1989

Figure A-2 George catchment – monthly volumes at secondary site.

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Observed - Leven at Mayday Rd - Site 821 20000 Site 821 Modelled - with entitlements 18000 Observed- Scaled Leven at Bannons site 14207

16000

14000

12000

10000

8000

Monthly Volume (ML) Volume Monthly 6000

4000

2000

0 1983 1984 1987 1989 1991 1993

Figure A-3 Leven catchment – monthly volumes at secondary site.

Observed - Swan u/s Hardings F - Site 2219 Site 2219 Modelled - with entitlements 16000 Observed - Scaled Swan at Grange site 2200

14000

12000

10000

8000

6000 Monthly Volume (ML) Volume Monthly 4000

2000

0 1983 1984 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994

Figure A-4 Swan catchment – monthly volumes at secondary site.

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Observed - Montagu at Togari - Site 14216 Site 14216 Modelled - with entitlements 20000 Observed- Scaled Monatgu at Montagu Rd Brg - Site 14200

18000

16000

14000

12000

10000

8000

Monthly Volume (ML) Volume Monthly 6000

4000

2000

0 1985 1986 1987 1988 1988 1989 1990

Figure A-5 Montagu catchment – monthly volumes at secondary site.

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Table A-1 Model performance at secondary sites

Catchme Calibration Site Secondary Site Correlation A Correlation B Correlation C Correlation D nt Primary Site

Name Site Name Sub- Catchment Concurrent Site Name Sub- Catchment Catchment Monthly ML Monthly ML Monthly ML Monthly ML

& No. Catchment Area data & No. Catchment Area area factor 2 2 2 2 Location periods Location (compared with R Value R Value R Value R Value Km2 Km2 used in calibration site) Calibration site Secondary site Calibration site Secondary this observed vs observed vs observed(scale site observed analysis Calibration site Calibration site d) vs Modelled vs Modelled modelled observed (scaled) Forth Forth at SC33 1079.6 01/01/1963 SC31 310.2 0.2873 0.97 0.95 0.95 0.97 Paloona to above Bridge – 01/03/1969 Lemonthym Site 386 e – site 450 George George SC2 397.9 01/03/1983 Ransom Rv SC3 26.1 0.0656 0.91 0.96 0.86 0.83 River at SH to at Sweet WS – Site 01/10/1990 Hill – Site 2205 2217 Leven Leven at SC4 496.4 01/04/1983 Leven at SC6 37.5 0.0755 0.93 0.87 0.88 0.92 Bannons to Mayday Rd Bridge – 01/09/1994 – site 821 Site14207 Swan Swan River SC20 465.9 01/07/1983 Swan River SC4 35.6 0.0764 0.92 0.95 0.82 0.85 at Grange – to u/s Site 2200 01/10/1996 Hardings Falls – site 2219 Montagu Montagu at SC3 325.9 01/01/1985 Montagu at SC2 135.4 0.4155 0.98 0.98 0.95 0.94 Montagu to Togari – Rd Brdge – 01/01/1990 Site 14216 Site 14200

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