Catchment scale fine sediment dynamics and its implications for flood management
Sarah J Twohig
School of Architecture Building and Civil Engineering
A Doctoral Thesis Submitted in partial fulfilment of the requirements for the award of Doctor of Philosophy of Loughborough University
© by Sarah Twohig 2018
Abstract The impact of fine sediment on catchment flood risk is often neglected when designing and implementing catchment managements plans. Yet, the accumulation of fine sediment can diminish channel capacity, causing an increase in flood risk. To successfully transition away from costly and invasive sediment management methods towards an integrated Natural Flood Management (NFM) approach, the dynamics of fine sediment and its implications for flood risk management must be explored. This thesis employs a novel geomorphological, hydrological, engineering and social approach to explore the influence of fine sediment on flood risk.
Hydrological modelling of connectivity and erosion risk was conducted to determine the potential sources using SCIMAP. The model found the River Eye has relatively low connectivity, suggesting sources of sediment in- channel are likely derived from local sources such as river banks. The sub- catchments of Burton Brook and Langham Brook as the areas of highest connectivity and erosion risk indicating likely source areas. To explore patterns of spatial and temporal fine sediment transport an intensive field monitoring campaign was conducted using Time Integrated Mass Sediment samplers (TIMS) across the River Eye catchment. The suspended sediment samples found sites upstream of the silt trap had higher sediment loads than downstream, indicating the silt traps effectiveness in reducing fine sediment. Sediment yield analysis found the Burton Brook tributary is a significant contributor of fine sediments delivering 17.4 g km2 day-1. The TIMS were analysed for their relative efficiency and found sediment load between samplers to vary by 4%-171%. However, analysis of physical sediment properties was found to be consistent.
At a reach scale, three flood defences were evaluated to determine their effectiveness in terms of sediment transport. Water level monitors installed upstream of the silt trap observed flow backing-up behind the silt trap >200m in high flow events. TIMS were installed up and downstream of two silt traps and found the silt traps were effective in reducing sediment load by 59.7- 98.0% on 7/8 occasions (Burton Brook) and 32.5-71.9% on 5/8 occasions (Ham Bridge). A complementary qualitative study was undertaken to assess the non-technical barriers to changes in flood risk and sediment management. A catchment wide survey was used to investigate attitudes of awareness, resilience and responsibility. Response analysis identified potential barriers to future NFM installation such as preference to traditional engineering structures and dredging to manage sediment delivery. The outcomes from all four approaches were used to create a series of recommendations on future flood risk and fine sediment management for catchment managers in lowland catchments.
Acknowledgements
I would like to start by thanking my supervisor Dr Ian Pattison for his continued support and guidance throughout the PhD process, always having an open door to ask questions and for his valuable feedback, helping me to improve as a researcher. I would also like to thank my second supervisor Prof. Graham Sander for his advice, often whilst stood on a river bank.
This research project would not have been possible without NERC CENTA funding, gaining the approval of land owners and catchment managers within the River Eye. I would like to thank the laboratory technicians in Civil Engineering for their support in the construction of stilling wells, TIMS and laboratory assistance.
I thank Dr Philip Soar and Dr Peter Downs my undergraduate and masters supervisors for their excellent teaching, supervision and enthusiasm for rivers. Without you I would have never had the confidence or passion to embark on this journey.
To my friends, many of whom have spent cold days in rivers with me: Faye, Harry, Alan, Milly, Cardo, Jen and Kate thank you for making the last four years so enjoyable, the daily coffee trips, helping on fieldwork and being so supportive.
To my family; thank you for always believing in me and the endless love and support. My final thanks go to my husband, Mike. You are my inspiration I would not have been able to come this far without you. Contents
Table of Figures ...... viii
Table of Tables ...... xvi
1. Chapter One: Context, aims and objectives ...... 1
1.1 Research context ...... 1
1.1.1 Hydrological contributions to flood risk ...... 2
1.1.2 Geomorphological contributions to flood risk ...... 3
1.1.3 Engineering component to flood risk ...... 5
1.1.4 Social contributions to flood risk ...... 6
1.2 Research aims ...... 6
1.3 Thesis structure ...... 9
2 Chapter Two The role of fine sediment in managing catchment flood risk 11
2.1 Chapter Scope ...... 11
2.2 Fine sediment ...... 11
2.3 Fine sediment sources ...... 12
2.3.1 Geology ...... 12
2.3.2 Slope and relief...... 12
2.3.3 Climate ...... 13
2.3.4 Land cover ...... 13
2.3.5 Bank erosion ...... 15
2.4 Fine sediment detachment ...... 16
2.5 Spatial variation in suspended sediment ...... 16
2.6 Fine sediment connectivity ...... 18
2.6.1 Hydrological connectivity ...... 19
2.6.2 Geomorphological connectivity ...... 22 i
2.7 Methods of identifying fine sediment connectivity ...... 24
2.7.1 Modelling sediment connectivity ...... 24
2.7.2 Field methods for sediment connectivity ...... 27
2.8 Fine sediment delivery in river channels ...... 32
2.8.1 Hydraulic implications of sediment deposition ...... 33
2.8.2 Geomorphological implications of sediment deposition ...... 36
2.8.3 Future implications of sediment delivery in a changing climate 40
2.9 Interactions between traditional engineering techniques and hydrology ...... 41
2.9.1 Traditional engineering techniques: Dams ...... 42
2.9.2 Traditional engineering techniques: bank protection ...... 43
2.9.3 Traditional engineering techniques: dredging ...... 43
2.10 Natural Flood Management engineering: working with natural hydrological processes ...... 45
2.10.1 Instream NFM structures ...... 47
2.10.2 Silt traps ...... 47
2.10.3 Riparian buffer strips ...... 48
2.10.4 Natural Flood Management: limitations ...... 48
2.11 Social consideration in flood risk management ...... 49
2.11.1 Flood awareness ...... 51
2.11.2 Flood resilience ...... 52
2.11.3 Flood responsibility ...... 55
2.12 Chapter Summary ...... 58
3 Chapter Three Study Site ...... 60
3.1 Chapter Scope ...... 60
3.2 The River Eye Catchment ...... 60
3.2.1 Geology ...... 64 ii
3.2.2 Soil Properties ...... 65
3.2.3 Land Cover ...... 66
3.2.4 Site of Special Scientific Interest (SSSI) ...... 68
3.3 River Eye Flood Risk Problem ...... 68
3.3.1 Melton Mowbray Flood Alleviation Scheme ...... 70
3.3.2 Flood defence maintenance ...... 74
3.4 Chapter Summary ...... 76
4 Chapter Four Methodology ...... 77
4.1 Chapter Scope ...... 77
4.2 Hydrological connectivity and erosion risk modelling ...... 79
4.2.1 SCIMAP Model ...... 80
4.2.2 Model inputs ...... 83
4.2.3 Model Simulations ...... 88
4.2.4 Limitations ...... 90
4.3 Instant suspended sediment storm sample collection ...... 91
4.3.1 Sample collection ...... 92
4.4 Time integrated mass suspended sediment collection ...... 94
4.4.1 Sampler design...... 95
4.4.2 Site selection ...... 98
4.4.3 Sampler collection ...... 101
4.4.4 Sampler limitations ...... 103
4.5 Suspended sediment analysis ...... 104
4.5.1 Relative weight ...... 104
4.5.2 Organic matter content ...... 106
4.5.3 Particle size analysis ...... 107
4.6 Hydrological monitoring ...... 108
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4.6.1 Site Selection ...... 109
4.6.2 Experimental design ...... 110
4.6.3 Data compensation ...... 112
4.6.4 Morphological surveys ...... 112
4.6.5 Hydrological analysis ...... 113
4.7 Qualitative methods ...... 114
4.7.1 Preliminary unstructured interviews ...... 114
4.7.2 Questionnaire justification ...... 116
4.7.3 Questionnaire themes ...... 117
4.7.4 Questionnaire design ...... 119
4.7.5 Questions themed on awareness, resilience and responsibility 121
4.7.6 Questionnaire Analysis ...... 122
4.8 Chapter Summary ...... 123
5 Chapter Five Identifying the sources and spatial patterns of fine sediment 124
5.1 Chapter Scope ...... 124
5.2 River Eye catchment connectivity and erosion risk ...... 124
5.2.1 Spatial trends in connectivity and erosion risk ...... 129
5.2.2 Rainfall changes ...... 134
5.2.3 Land use changes ...... 136
5.2.4 SCIMAP summary ...... 142
5.3 Physical properties of suspended sediment storm samples ...... 143
5.3.1 Organic matter content method validation...... 143
5.3.2 Particle size analysis method validation ...... 144
5.3.3 Organic matter content in storm samples ...... 145
5.3.4 Particle size analysis for storm samples ...... 146 iv
5.4 Physical properties of suspended sediment TIMS ...... 147
5.4.1 Spatial mass of sediment ...... 147
5.4.2 Temporal trends in suspended sediment mass ...... 153
5.4.3 Spatial patterns in Organic matter content ...... 157
5.4.4 Temporal patterns in organic matter content ...... 160
5.4.5 Spatial trends in particle size distribution ...... 165
5.4.6 Temporal trends in particle size distribution ...... 169
5.5 Chapter summary ...... 175
6 Chapter Six Geomorphological and Hydrologic appraisal of installed flood management assets ...... 177
6.1 Chapter Scope ...... 177
6.2 Ham Bridge Silt Trap ...... 177
6.2.1 The effectiveness of Ham Bridge silt trap at retaining fine sediment ...... 178
6.2.2 Organic matter ...... 181
6.2.3 Particle Size ...... 183
6.3 Hydrological appraisal of Ham Bridge Silt Trap ...... 186
6.4 Burton Brook Silt Trap ...... 194
6.4.1 The effectiveness of Burton Brook silt trap at retaining fine sediment ...... 195
6.4.2 Organic matter ...... 198
6.4.3 Particle size analysis ...... 200
6.5 Brentingby Dam ...... 203
6.5.1 The effectiveness of Brentingby Dam at retaining fine sediment 203
6.5.2 Particle Size ...... 209
6.6 The effectiveness of the Silt Traps ...... 210
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6.7 TIMS relative efficiency ...... 212
6.8 TIMS limitations ...... 217
6.9 The geomorphic and hydrologic impact of online silt traps ...... 221
6.10 Chapter Summary ...... 223
7 Chapter Seven Social attitudes and perception of flood risk management in the River Eye Catchment...... 225
7.1 Chapter Scope ...... 225
7.2 Context ...... 225
7.2.1 Managers ...... 225
7.2.2 Farmers ...... 226
7.2.3 Residents ...... 227
7.3 Awareness to flood risk and sediment management within the River Eye Catchment ...... 229
7.3.1 Main contributors to flood risk in Melton Mowbray ...... 229
7.3.2 Exploring stakeholder awareness to flood risk management .. 233
7.3.3 Stakeholder awareness of fine sediment processes ...... 235
7.3.4 Natural Flood Management awareness ...... 242
7.4 Resilience to flooding ...... 243
7.4.1 Personal resilience to flooding ...... 244
7.4.2 Methods of reducing fine sediment deposition ...... 247
7.4.3 Attitudes towards channel dredging ...... 252
7.5 Stakeholders perception of responsibility ...... 255
7.5.1 Responsible for informing residents ...... 255
7.5.2 Responsible for implementing flood risk management ...... 256
7.5.3 Responsible to protect residential property during a flood event 258
7.6 Chapter Summary ...... 259 vi
8 Chapter Eight Conclusions ...... 262
8.1 Chapter Scope ...... 262
8.2 Objective one: Identify the sources of fine sediment within the River Eye catchment ...... 262
8.3 Objective two: Determine the spatial-temporal patterns and controls of fine sediment transport ...... 263
8.4 Objective three: Assess the impact of existing flood defences on natural sediment transport ...... 264
8.5 Objective four: Determine the non-technical barriers to sustainable natural flood risk and sediment management ...... 265
8.6 Critical evaluation of methods ...... 267
8.7 Objective five: Create a catchment management plan containing recommendations to improve sediment management within the River Eye catchment incorporating a combined hydrology, geomorphology, engineering and social science approach ...... 269
8.8 Future work ...... 273
9 References ...... 277
10 Appendix ...... 296
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Table of Figures Figure 1.1 Thesis approach used to investigate fine sediments influence on flood risk...... 1 Figure 1.2 Diagram representing the structure of the thesis...... 10 Figure 2.1 Conceptual model of sediment yield at various scales and contributing sources and sinks (De Vente and Poesen, 2005)...... 18 Figure 2.2 Conceptual model of hydrological connectivity based on Bracken and Croke (2007)...... 20 Figure 2.3 Conceptual model of fine sediment connectivity modified from Bracken et al (2015) ...... 23 Figure 2.4 Schematic diagram showing the impact of dredging on flood levels (CIWEM, 2014) ...... 45 Figure 2.5 Policy table identifying responsibility for flood risk management adapted from Brown and Damery, 2002 ...... 56 Figure 3.1 The River Soar Catchment, highlighting a primary tributary the River Wreake and River Eye...... 60 Figure 3.2 River Eye Catchment Contributing areas in Km2...... 62 Figure 3.3 2m resolution topographic map of the River Eye catchment using LiDAR data with hill shading applied...... 63 Figure 3.4 Geology of River Eye catchment. Data obtained from BGS, 2015...... 64 Figure 3.5 1km resolution soil series map of the River Eye Catchment ...... 66 Figure 3.6 Land cover of River Eye at 25m resolution from CEH ...... 67 Figure 3.7 Historic record of flood events within the River Eye Catchment 1852- 1975...... 69 Figure 3.8 Inundation of Melton Mowbray in 1998. Photographs obtained from Environment Agency ...... 70 Figure 3.9 Location of the flood defences installed during the construction of the Melton Mowbray Flood Alleviation Scheme ...... 71 Figure 3.10 a) Ham Bridge Silt trap located on the main River Eye. b) Burton Brook Silt trap located on the Burton Brook tributary. c) Ham Bridge aerial
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image. d) Burton Brook aerial image. The blue lines indicate direction of flow. Imagery taken from Google Earth...... 72 Figure 3.11 Brentingby Dam, installed in 2003 – personal photograph from June 2015 ...... 73 Figure 3.12 Channel cross sections up (depicted in blue) and downstream (depicted in orange) of Brentingby Dam ...... 73 Figure 3.13 Melton Mowbray Park 2015, shows the river laden with fine sediments after a heavy rainfall event, downstream of the Melton Mowbray Flood Alleviation Scheme...... 75 Figure 4.1 Methodology diagram outlining the methodologies in chapter 4 are discussed in results chapters...... 78 Figure 4.2 SCIMAP Model framework showing inputs(blue) and outputs (black) adapted from www.SCIMAP.com ...... 83 Figure 4.3 Spatial inputs required to run SCIMAP at 5m resolution ...... 84 Figure 4.4 1m LiDAR extent of River Eye Catchment obtained from gov.uk open source...... 86 Figure 4.5 SCIMAP model runs used to explore catchment connectivity and erosion risk...... 89 Figure 4.6 Daily average flow data for the gauging station situated at Melton Mowbray park. The two dashed lines represent the storm sample collections...... 92 Figure 4.7 Daily average water level recorded at Melton Mowbray park gauging station for 2016, with the grey lines highlighting the storm events when samples were taken...... 93 Figure 4.8 TIMS sampler design used at all locations within the River Eye. 97 Figure 4.9 Map of TIMS locations in the River Eye Catchment. TIMS in red indication installation of samplers for spatial and temporal patterns of fine sediment flux. TIMS in yellow indicate additional TIMS installed downstream of flood defences which are discussed in Chapter Six...... 99 Figure 4.10 a) position of installed TIMS at Ham Bridge Silt Trap, b) position of installed TIMS at Burton Brook Silt Trap, c) position of installed TIMS at Brentingby Dam ...... 100
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Figure 4.11 Water level at Melton Mowbray gauging station during the TIMS monitoring period. The grey dashed lines represent collections...... 102 Figure 4.12 Cross sectional data collected from each sampling site from upstream to downstream. Tributaries are marked grey and the main channel, blue...... 103 Figure 4.13 An example of a mini diver within a stilling well (Eijkelkamp: Soil and Water, 2016) ...... 109 Figure 4.14 Location of stilling wells installed upstream of Ham Bridge Silt Trap ...... 110 Figure 4.15 Design of monitoring well installed at three locations upstream of Ham Bridge Silt Trap ...... 111 Figure 4.16 Bed Elevation profile upstream of Ham Bridge silt trap ...... 113 Figure 4.17 The streets selected to send residential postal questionnaires situated in flood zones 1,2&3 or in close proximity to the River Eye ...... 121 Figure 5.1 SCIMAP catchment connectivity and erosion risk histograms. a) catchment connectivity DTM b) catchment connectivity DSM c) catchment erosion Risk DTM d) Catchment erosion risk DSM ...... 125 Figure 5.2 DTM and DSM catchment connectivity. A sub-section of the catchment has been exported to create a comparative histogram...... 128 Figure 5.3 River Eye Sub-catchment connectivity a) DTM sub-catchment connectivity b) DSM sub-catchment connectivity...... 131 Figure 5.4 River Eye Sub-catchment erosion risk a) DTM sub-catchment erosion risk b) DSM sub-catchment erosion risk...... 132 Figure 5.5 Rainfall simulations for connectivity and erosion risk in summer 2030, summer 2050, winter 2030 and winter 2050 ...... 136 Figure 5.6 Catchment erosion risk results after land cover risk weightings have been modified...... 137 Figure 5.7 a) catchment erosion risk using 2007 land cover and DTM, b) catchment erosion risk using 2007 land cover and DSM, c) catchment erosion risk using 2015 land cover and DTM, d) catchment erosion risk using 2015 land cover and DSM ...... 140
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Figure 5.8 DTM and DSM catchment connectivity using 2015 land cover. A sub-section of the catchment has been exported to create a comparative histogram...... 141 Figure 5.9 Cumulative Particle Size Distribution of suspended sediment from collected storm samples ...... 144 Figure 5.10 Suspended sediment daily load (g day-1) collected by TIMS in the River Eye catchment during monitoring period...... 148 Figure 5.11 Daily sediment yield (g km -2 day -1) ) collected by TIMS in the River Eye catchment during monitoring period...... 150 Figure 5.12 scatter plot depicting specific suspended sediment yield (SSY) over catchment contributing area of the River Eye ...... 151 Figure 5.13 scatter plot depicting weighted SCIMAP erosion risk >0.7 (%) in relation to specific sediment yield calculated by TIMS for four tributaries. . 152 Figure 5.14 Temporal trends in suspended sediment load *denotes anomalous results and site number associated. Hydrology over the time period has been shown...... 154 Figure 5.15 daily sediment load (g) at each site. Sites in blue are on the main channel and sites in grey denote tributaries. At sites where no data is presented reflects no collection during this time period. Results with numbers above them denote the daily sediment load (g) collected...... 156 Figure 5.16 Histogram displaying the organic matter content for all samples from the River Eye...... 158 Figure 5.17 Percentage of organic matter content at each location. The sites coloured in blue represent TIMS situated in the main channel...... 159 Figure 5.18 Scatter graph showing % organic matter content at each TIMS location...... 162 Figure 5.19 box plot showing percentage of organic matter content for each collection interval...... 164 Figure 5.20 Box plot indicating particle size distribution of the TIMS samples collected at each location. Box plots represent the D16, D50 and D84 particle size...... 166
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Figure 5.21 Temporal variation in particle size: indicating the D16, D50 and D84 particle sizes for each collection period. Hydrology during the sampling time period has been plotted below...... 170 Figure 5.22 Temporal changes in particle size analysis over the sampling period ...... 172 Figure 5.23 Cumulative Particle size distribution graphs for each TIMS location, depicting temporal trends in sediment sizes...... 174 Figure 6.1 Total sediment load (kg) for study period (a) and relative sediment load (g day-1 (b) collected at Ham Bridge Silt Trap ...... 178 Figure 6.2 (left) sediment mass collected (g). (right) daily sediment load (g day- 1) ...... 180 Figure 6.3 box plot depicting percentage of organic matter content collected at each location upstream and downstream of Ham Bridge silt trap. Point 5 represents the anonmoulous result of 37% organic matter calculated for the TIMS installed upstream of the silt trap on the left of the channel...... 181 Figure 6.4 scatter graph representing the calculated %organic matter content value for each collection over time. Upstream left TIMS is missing the results from August and October 2017 due to two anomalous results of 37%, previously depicted on Figure 6.3 and 92%...... 182 Figure 6.5 Particle size distribution box plots for each TIMS location at Ham Bridge. The box represents the D16, D50 and D84 values and error bars represent the range of particle sizes...... 184 Figure 6.6 Temporal variation in particle size distribution for each TIMS over time. Dark blue represents upstream left, dark green upstream right, light blue downstream left and light green downstream right...... 186 Figure 6.7 water level data collected by three divers upstream of Ham Bridge silt trap during February 17 - January 18...... 188 Figure 6.8 Surface water elevation plots for three low flow events. Bed elevation is shown in black...... 189 Figure 6.9 Hydrographs of five storm events for divers installed upstream of Ham Bridge silt trap. Dashed lines represent 3 rising limbs, the point at which each diver recorded peak water level and 3 falling limb...... 190
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Figure 6.10 Suface water elevation plots during storm events showing water level at each location in accordance to Figure 6.9 (left). Volume of water calculated within the cross section at each location (right)...... 192 Figure 6.11 Total sediment load (kg) for study period (a) and relative sediment load (g day-1 (b) collected at Burton Brook Silt Trap ...... 195 Figure 6.12 (left) sediment mass collected (g). (right) daily sediment load (g day-1) at Burton Brook ...... 197 Figure 6.13 Organic Matter content box plot for each TIMS installed at Burton Brook silt trap ...... 198 Figure 6.14 Spatial and temporal variation in organic matter content at Burton Brook silt trap ...... 199 Figure 6.15 Taken from field adjacent to Burton Brook showing the no till technique which aims at retaining nutrients in the soil ...... 200 Figure 6.16 Particle size distribution box plots for each TIMS location at Burton Brook. The box represents the D16, D50 and D84 values and the error bars depict the range in particle size...... 201 Figure 6.17 Temporal variation in particle size distribution for each TIMS over time. Dark red represents upstream left, dark orange upstream right, light red, downstream left and light oranage downstream right...... 202 Figure 6.18 Cumulative frequency graph of particle size distribution for each TIMS installed at Ham Bridge silt trap...... 203 Figure 6.19 Total sediment load (kg) for study period (a) and relative sediment load (g day-1 (b) collected at Brentingby Dam ...... 203 Figure 6.20 (left) sediment mass collected (g). (right) daily sediment load (g day-1) at Brentingby Dam ...... 206 Figure 6.21 box plots displaying the percentage organic matter content of all samples collected at Brentinby Dam ...... 207 Figure 6.22 Scatter graph depicting temporal variation in percentage organic matter content at Brentingby Dam ...... 208 Figure 6.23 box plot indicating the minimum and maximum range of particle sizes up/downstream of Brentingby Reservoir ...... 209
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Figure 6.24 Temporal variation in particle size distribution for each TIMS over time. Dark purple represents upstream left, turquiose upstream right, light purple downstream left and light turquiose downstream right...... 210 Figure 6.25 Scatter plot depicting specific suspended sediment yield over catchment contributing area of the River Eye. Blue dots indicate sites 1-11 from chapter 5. Red dots indicate downstream of silt traps and black represent upstream of silt traps which are redundant...... 212 Figure 7.1 The environmental areas catchment managers are focused on within the River Eye catchment...... 226 Figure 7.2 Map of responses at a street level to the postal survey. Purple indicates the streets that responded and red, the streets that did not reply...... 227 Figure 7.3 demographics of residential respondents. Left: homeowner status. Right: number of years in property...... 228 Figure 7.4 Likert scale displaying the results to the question “What do you think are main contributors to flood risk in this area?”...... 230 Figure 7.5: Questions asked to farmers to indicate their perception of flood risk ...... 232 Figure 7.6: Residents responses to questions regarding their personal perception of flood risk ...... 232 Figure 7.7 Awareness of current flood defences in River Eye Catchment . 234 Figure 7.8 Responses from all stakeholders on the perception of fine sediment sources in the River Eye Catchment...... 236 Figure 7.9 Responses from all stakeholders on the potential distance fine sediment can be transported downstream...... 237 Figure 7.10 Identifying areas of fine sediment within the River Eye Catchment...... 238 Figure 7.11 Likert scale showing catchment stakeholders observations of changes to the river features within their memories. Dark colours symbolise reduction and light colours an increased...... 240 Figure 7.12 Percentage of farmers willing to set aside land for flood risk management ...... 244
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Figure 7.13 Likert scale showing personal property protection residents may use to reduce flood risk...... 246 Figure 7.14 Catchment Managers barriers to work ...... 247 Figure 7.15 Likert Scale depicting the opinion of stakeholders perceived effectiveness of future flood defences ...... 248 Figure 7.16 Catchment stakeholders attitudes towards channel dredging . 252 Figure 7.17 Residents were asked to rank who was responsible for informing residents of an imminent flood event...... 256 Figure 7.18 Question asked to all stakeholders: Who is responsible for flood risk management? Where 0 is not responsible and 5 is highly responsible...... 257 Figure 7.19 Residents were asked to rank which of the following catchment stakeholders were responsible for providing protection to their properties during a flood...... 259
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Table of Tables Table 2.1 Limitations to NFM adapted from (AECOM 2017) ...... 49 Table 4.1 Land Cover weightings determined by Lane et al (2006) ...... 80 Table 4.2 Description of inputs required to run SCIMAP ...... 83 Table 4.3 Spatial differences in 2007 and 2015 in % land cover of the River Eye catchment. Blue represents an increase in land cover and red a decrease...... 88 Table 4.4 Storm samples collection time and water level ...... 93 Table 4.5 Collection dates of TIMS samplers ...... 101 Table 4.6 contributing area at each TIMS location...... 106 Table 5.1 Percentage of organic matter content from suspended sediment storm samples ...... 143 Table 5.2 percentage coefficient of variance between subsample a and subsample b ...... 145 Table 5.3 Particle size (µm) analysis for suspended sediment storm samples. %cv values in blue are statistical significant to 95%...... 146 Table 5.4 Mann-Whitney U test results for temporal changes in median values. The light blue highlight the results that are statistically significant p>0.05 with the Bonferroni correction applied...... 165 Table 5.5 D50 median mann whitney test the results in blue indicate results that were statistically significant (p <0.05) with the Bonferroni correction applied ...... 168 Table 5.6 D16 Mann Whitney. the results in blue indicate results that were statistically significant (p <0.05) ...... 168 Table 5.7 D84 Mann Whitney results. The results in blue indicate results that were statistically significant (p <0.05) with the Bonferroni correction applied...... 169 Table 6.1 The percentage increase of daily sediment load downstream of the silt traps. Percentages in red denote an increase in sediment load downstream ...... 211 Table 6.2 percentage difference between adjacent samplers...... 214
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Table 6.3 Ham Bridge silt trap adjacent TIMS comparison with Mann Whitney non parametric test ...... 214 Table 6.4 Burton Brook silt trap adjacent TIMS comparison ...... 215 Table 6.5 Brentingby Dam adjacent TIMS comparison ...... 215 Table 6.6 Comparison of particle sizes between suspended sediment collected during high flow events in Melton Mowbray and TIMS sites with adjacent samplers...... 216 Table 6.7 List of TIMS affected by changes in water level ...... 219
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Chapter One: Context, aims and objectives
1. Chapter One: Context, aims and objectives
1.1 Research context
A change in flood frequency and spatial extent of flooding can be caused by two factors 1) a change in frequency of high flows and/or 2) a change in the capacity of a channel to contain floods (Slater, 2016). Changes in sediment delivery through land use and climatic change can alter channel morphology, directly influencing the channels capacity to convey high discharges (Raven et al, 2010). Understanding the interconnection between hydrology and geomorphology is fundamental to predicting sediment transfer within the catchment (Lane et al, 2008). Artificial alterations to channel morphology through engineering can cause unnatural changes to sediment delivery within the catchment (Pinter et al, 2006). Understanding the hydrological connectivity of a catchment is vital for successful flood management. Inundation of a floodplain in the absence of humans is a hazard, where humans are affected by this process becomes risk. Understanding the potential social implications of flood risk and future management plans is vital to achieving sustainable flood management.
Figure 1.1 Thesis approach used to investigate fine sediments influence on flood risk.
1 Chapter One: Context, aims and objectives
The thesis employs a combined hydrology, geomorphology, engineering and social science approach to explore the influence of fine sediment on flood risk (Figure 1.1). In this thesis fine sediment is defined as sediment <2mm and therefore is capable of being transported in suspended load.
1.1.1 Hydrological contributions to flood risk
The British Isles has over 200 000km of river and stream networks (Marsh, 2002), with millions of inhabitants living in close proximity to water. Consequently, flood risk is the UK’s largest natural hazard, with over four million people living in areas at risk of future flooding (Wilby et al, 2008). The inception of a flood occurs when the main channel water levels exceed local bank height (Lane et al, 2007; Stover & Montgomery, 2001). Therefore, flood risk is driven by changes in the river channel stage which is influenced by changes in flow magnitude and river channel conveyance. Major flood events have resulted in significant damage to lives, homes and infrastructure (Stevens et al 2016) e.g. winter 2013/14 of Somerset Levels, December 2015 (16 000 homes), November 2016 (1000 properties), and March 2017 (800 properties).
Fluvial floods are often a result of prolonged and heavy rainfall due to atmospheric weather patterns. The magnitude and frequency of events is a result of changes in climate (Wilby et al, 2008) and can be exacerbated by alterations to land use and management (Pattison & Lane, 2012).
The frequency and severity of storms as a consequence of climate change is causing authorities to reassess the Country’s resilience to flooding. The extent of the hydrological volatility of the 21st Century being a consequence of climate change is a focus of ongoing scientific debate (Muchan et al, 2015). The intensification of the hydrological cycle as global temperatures increases (Huntington, 2006) has led to the prediction of increasing frequency of severe precipitation events (Christensen and Christensen, 2003) and precipitation totals (Palmer and Räisänen, 2002). These predictions have been supported by trends in observed rainfall and runoff data series, which indicate an increase in winter precipitation totals and intensities of extreme daily events (Wilby et al, 2008).
2 Chapter One: Context, aims and objectives
One of the most frequently cited impacts of future climate change is the potential increase in river flood hazard (Arnell & Gosling, 2016), though many studies have focused only on event frequency (Prudhomme et al, 2003). In fact, very few studies have considered the human impact of changes in flood hazard (Arnell & Gosling, 2016). Research has suggested that increased agricultural activities and artificial channel widening for navigation has caused increased volumes of sediment to enter river systems (Kondolf et al, 1997). An aggravating factor of the UK Winter 2015 floods was a reduced conveyance in many river channels caused by sedimentation, landslides and the collapse of several structures (NERC, 2016).
1.1.2 Geomorphological contributions to flood risk
Due to the dynamic nature of river systems, changes in the sediment supply and flow frequency can affect channel geometry causing alterations to the width, depth and velocity of cross-sectional flow, resulting in an insufficient channel capacity to contain flood flows (Slater, 2016). Rivers with return periods close to or exceeding bankfull conditions are the most sensitive to geometrical changes. Sediment accumulation in river channels alters the channel capacity and ultimately increases its sensitivity to flooding through its impact on stage-discharge relationships (Reid et al, 2008).
Natural sediment supply and delivery within river catchments have been severely impacted by human activities. Variations to natural sediment delivery and transport rates of sediment strongly influences flood risk within river catchments (Lane et al, 2008). Poor land management has dramatically increased silt and sand levels in England’s streams, destroying spawning sites (Walling and Amos, 1999) as well as other benthic habitats. Realignment of channels as a response would propagate the negative effects of sediment transport downstream. In areas where the channel banks are restricted to lateral adjust in response to changes in flow and sediment transport, the channel bed adjusts (Lane et al, 2007). Although geomorphic changes do not explicitly impact discharge return periods they do impact floodplain inundation,
3 Chapter One: Context, aims and objectives
leading to an increase in the magnitude/ frequency of inundation events in any river or river reach that is aggradational (Lane et al, 2007).
Lowland rivers are particularly vulnerable to fine sediment aggradation due to insufficient energy to recover to natural form (Brookes, 1995). An influx of fine sediment will deposit in the channel substantially change channel morphology (Rathburn and Wohl, 2003) causing a decrease in channel capacity and therefore the volume of water the channel is able to retain in bank.
To date, limited research has focused on sediment accumulation in channels and the catchment scale impacts of upstream land use. Past studies have focused on coarse sediment delivery in rural catchments, where inundation extents are not restricted by artificial engineering (Reid et al, 2007, Lane et al., 2008; Raven et al., 2010). In the past, studies have explored the impacts that changes in climate have on surface run-off for upland river systems and its implications for flood risk (O’Connell et al, 2004; O’Connell, 2007; Sullivan et al, 2004). There is a need to study the interactions of fine sediment delivery and its influence on flood risk in alluvial channels. Recent flooding of the Somerset Levels has widely publicised the issues surrounding insufficient channel capacity from fine sediment delivery in alluvial channels, highlighting the necessity and timeliness of further research.
Identifying the sources and transport pathways of fine sediments is critical to understand the mechanisms controlling sediment detachment, transport and delivery within river catchments (Woodward & Foster, 1997). Areas of erosion in catchments are not necessarily indicative of increased suspended sediment within the channel. The sources need connected pathways from hillslope, floodplain and channel in order to deliver sediment (Hooke, 2003).Detecting these sources can provide catchment managers with the information to calculate sediment budgets and create sustainable catchment management plans, both environmentally and economically (Carter et al,2003; Walling, 2005; Collins & Walling, 2007; Martinez- Carreras et al., 2008).
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1.1.3 Engineering component to flood risk
Traditional engineering techniques used to reduce flood risk, focused on hydrological impacts; retaining water upstream with dams and reservoirs, maintaining channel capacity through the installation of bank protection or increasing channel capacity by dredging the channel. Artificial alterations to channel morphology through engineering can cause unnatural changes to sediment delivery within the catchment (Pinter et al, 2006), due to lack of consideration of geomorphic processes. Traditional engineering measures often result in expensive maintenance to preserve a channel capacity capable of reducing flood risk. Sedimentation occurring at these sites can negatively influence adjacent areas which will then require further expensive engineering structures (Airoldi et al, 2005).
A transition in management strategy from flood defences to flood risk management in the 1990’s incorporated softer engineering defences which work in conjunction with natural processes (DEFRA, 2005). Environmental policies which drive management often have multiple purposes, such as the Water Framework Directive which is focused on maintaining and improving water quality. Consequently, river channels are being reassessed in order to meet legislative targets. Sustainable or natural flood defences are increasingly being included in management policies signalling a transition away from hard engineering techniques as a standard response. The installation of natural flood defences such as riparian buffer strips, woody debris dams and offline storage areas have been designed to increase the time taken for water and sediment to enter the river and therefore reducing the flood hydrograph peak. Measures have also been taken to reduce the volume of sediment depositing in areas of the channel where flood risk may be increased. Silt traps in agricultural fields and within the channel have been installed to encourage the deposition of fine sediment in known areas and therefore sustainably maintaining channel capacity downstream.
Engineered structures installed in river channels alter the natural sediment conveyance due to changes in discharge. The presence of flood defences
5 Chapter One: Context, aims and objectives
within a channel can reduce sediment conveyance resulting in a loss of sediment downstream (Kondolf, 1997). Maintenance is often required to maintain storage capacity and preserve protection levels (Darby & Thorne, 1995).
1.1.4 Social contributions to flood risk
The cost of UK flood risk is primarily calculated using a modelling approach that fails to incorporate several other factors such as citizen participation and involvement from other catchment experts (Hayes et al, 2014). Traditionally, flood strategies have overlooked the social element of sustainable flood defences, something which is difficult to quantify in cost-benefit analysis (Brown & Damery, 2002).Without a multi-disciplinary framework to incorporate the social implications of flood risk, management plans will inevitably favour hard engineering techniques which have proven economic merit and clear cost-benefit implications.
The Environment Agency has accepted that “risk to people, property and economy cannot be managed by simply building more and larger defence structures” (Environment Agency, 2017). Working to protect and restore the rivers natural form and processes must be considered when evaluating flood defences. (Environment Agency, 2017). Encompassing natural processes can create several other benefits including water quality and biodiversity. Due to the existing governance structure, monitoring these benefits and identifying those responsible is extremely difficult, particularly on a local delivery scale. A secondary barrier to implementing natural flood management is obtaining landowner consent. Modifying current rural land practises requires the support of landowners. Problems often occur when identifying land willing to be used for flood management and the responsibility of maintenance.
1.2 Research aims
The aim of this PhD research is:
6 Chapter One: Context, aims and objectives
To investigate the current influence of fine sediment on fluvial flood risk in the River Eye, Leicestershire.
To achieve the aim the following objectives will be answered throughout the thesis and discussed in the conclusions:
1. Identify the sources of fine sediment within the River Eye catchment
A current issue facing flood managers is understanding catchment scale processes and the potential downstream implications on flood risk. Locating the sources and transport pathways of fine sediments is critical to understand the mechanisms controlling sediment detachment, transport and delivery within river catchments (Woodward & Foster, 1997). By identifying the potential sources throughout the catchment, managers are able to account for fine sediment, installing upstream interventions, naturally maintaining channel capacity.
2. Determine the spatial-temporal patterns and controls of fine sediment transport.
Understanding the interconnection between hydrology and geomorphology is fundamental to predicting sediment transfer within the catchment (Lane et al, 2008). By identifying the spatial and temporal patterns of in-channel fine sediment connectivity it is possible to identify areas with high sediment load which could reduce the channel capacity and therefore increase flood risk. Installation of sediment samplers on key tributaries also provides an indication of which areas are delivering the most fine sediment, enabling for targeted mitigation measures on land to reduce connectivity to the main channel.
3. Assess the impact of existing flood defences on natural sediment transport.
In 2002, the River Eye flood defence scheme constructed the first two on-line silt traps to reduce downstream sedimentation. A dam was also erected downstream to reduce the volume of water at Melton Mowbray during high flows. To date, little or no research has been undertaken to determine the effectiveness of sediment traps as a method of flood defence. The results of
7 Chapter One: Context, aims and objectives
this objective will potentially be useful for informing future flood management plans in other similar alluvial catchments. Due to their relative infancy, the effectiveness of natural flood alleviation schemes such as online silt traps in reducing downstream sedimentation has yet to be assessed. By assessing the hydrological and geomorphic impact of established natural flood defences catchment managers can be better informed of the potential benefits and drawbacks of installing these structures.
4. Determine the non-technical barriers to sustainable natural flood risk and sediment management.
Identification of non-technical barriers is of equal importance to the technical barriers associated with installing NFM to ensure trust and resilience in these measures. Without stakeholder consent and clearly defined responsibilities of all relevant parties installing NFM measures will fail to be effective in reducing flood risk. Understanding the current problems associated with NFM installation will improve success in future projects. In the long term it will increase the public’s perception and trust in alternatives to hard engineered flood defences.
5. Create a series of recommendations for future sediment management within the River Eye catchment incorporating a combined hydrology, geomorphology, engineering and social science approach
The results from the previous objectives can be combined to create an overview of sediment transport and connectivity within the River Eye catchment. This data can be used to create a series of recommendations to catchment managers to improve the River Eye’s flood risk and maintain currently installed NFM measures. These recommendations will be disseminated to catchment partners including the Environment Agency, Natural England, Trent Rivers Trust and farmers who have all expressed an interest in using the results of the study to improve sediment management within the River Eye.
8 Chapter One: Context, aims and objectives
To determine the effectiveness of this novel framework, key findings from each approach will be compared to determine if the perception from stakeholders on flood risk and sediment management matches the physical data collected.
1.3 Thesis structure
The thesis is divided into eight chapters (Figure 1.2). Chapter two reviews the current literature, focusing on the hydrological and geomorphological processes influencing fine sediment connectivity and the impact of engineering structures and social attitudes to managing flood risk. Chapter three provides an overview of the study site: The River Eye, Leicestershire, a fine sediment river subjected to previous flood defences which account for excess fine sediment. Chapter four outlines the various modelling, field, laboratory and qualitative methodologies used to answer the thesis objectives. Chapter five presents the results of the catchment connectivity modelling and field data collected by sediment samplers to describe the spatial and temporal patterns of fine sediment within the catchment. Chapter six focuses on the influence of engineering structures on local hydrologic and fine sediment and provides an appraisal on the relative efficiency of sediment samplers. Chapter seven presents the findings from the qualitative study on social attitudes to flood risk. Finally, Chapter eight provides a conclusion of findings from the thesis and a series of catchment recommendations for catchment managers to improve fine sediment management in relation to flood risk.
9 Chapter One: Context, aims and objectives
Figure 1.2 Diagram representing the structure of the thesis.
10 Chapter Two: The role of fine sediment in managing catchment flood risk
2 Chapter Two The role of fine sediment in managing catchment flood risk
2.1 Chapter Scope
This chapter explores the interactions between fine sediment delivery, channel capacity and flood risk. Initially this chapter discusses the hydrological and geomorphological controls on fine sediment sources (section 2.3), detachment (section 2.4), connectivity (section 2.5), channel deposition (section 2.7) and the natural influence on flood risk. The implications of engineering (section 2.8 and 2.9) on fine sediment is then discussed followed by the social considerations in flood management (section 2.10).
2.2 Fine sediment
Fine sediment particles are those classified as those <2mm including sands (<2000 µm to >63 µm ) silts (<63 µm to >4 µm ) and clays (<4 µm ) (Church et al, 1987). The processes that transport sediment and deliver it into the channel are dependent on the size of the particles. Fine sediment are often transported in the suspended load and are an integral component of fluvial environments, particularly aquatic ecosystems (Kemp et al, 2011;Walling et al, 2008). Natural levels of fine sediment are intrinsic to habitat heterogeneity and ecological functioning (Yarnell et al, 2006).
In recent years anthropogenic activities have increased the quantity of fine sediment being delivered into the channel. Foster (2006) observed a dramatic increase in fine sediment lake deposits from 10 – 30 t km-2 year-1 to 110 t km-2 year-1 over a 20 year period.
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2.3 Fine sediment sources
Sediment sources are governed by the physical features of the catchment. The detachment of fine sediments from their sources are determined by geology, slope, land cover and soil erodibility (Nearing et al 1989). Understanding the physical properties of the catchment enables catchment managers to target those areas more vulnerable to fine sediment erosion and therefore implement methods to reduce delivery to the channel.
2.3.1 Geology
The resistance of the lithology present in the catchment dictates the erodibility and volume of fine sediment for transport. Sklar and Dietrich (2001) identify rock strength, grain size and sediment supply as the three geological factors that define the term erodibility. These components control the size and availability of fine sediment that could potentially be transported throughout the catchment. De Vente et al (2005) highlight the importance of including catchment geology within models to predict sediment yield at a regional or basin level scale. The geological zones of the catchment can act as a spatial tool to identify vulnerable areas (Gruszowski et al, 2003). In conjunction, Strand and Pemberton (1987) suggest using a combined soil and geology information factor is important for an accurate assessment of channel and bank erosion.
2.3.2 Slope and relief
Slope gradients are dictated by rock resistance and uplift rates (Sklar and Dietrich, 2001). Subtle changes in slope greatly impact the sediment supply (Montgomery et al, 1996) at local, sub catchment and catchment scales, for instance; catchments that have steep hillslopes and changes in undulating topography or relief are more likely to be connected and deliver sediment to the channel.
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2.3.3 Climate
The extent of the hydrological volatility of the 21st Century being a consequence of climate change is a focus of ongoing scientific debate (Muchan et al, 2015). The intensification of the hydrological cycle as global temperatures increases (Huntington, 2006) has led to the prediction of increasing frequency of severe precipitation events(Christensen and Christensen, 2003) and precipitation totals (Palmer and Räisänen, 2002). These predictions have been supported by trends in observed rainfall and runoff data series, which indicate an increase in winter precipitation totals and intensities of extreme daily events (Wilby et al, 2008).
One of the most frequently cited impacts of future climate change is the potential increase in river flood hazard (Arnell & Gosling, 2016), though many studies have focused only on event frequency (Prudhomme et al, 2003). Changes in climate can dictate the magnitude of peak flows; rainfall volume and intensity, and also changes to the river channel stage (Lane et al, 2007). With increasing anthropogenic forcing on channels and the impact of climate change on inundation it is necessary to investigate the impacts of channel geometry and long term sediment transport/ supply rates (Lane et al, 2007).
2.3.4 Land cover
Land cover and its subsequent use has a significant impact on the rate of sediment production and delivery (Knighton, 2014). Vegetation such as grassland and woodland provide a stabilising influence on the surface of the catchment, reducing sediment production rates and decreasing the rate of transfer within the catchment. Vegetation roots provide an anchor and method of draining saturated soils to increase landscape stability and reduce erosion (Richards, 1990). The presence of vegetation reduces rain splash directly onto the soil, increasing its stability and reducing the rate of erosion. In contrast, exposed soil areas will increase sediment production rates on hillslopes (Reid & Dunne, 1984), banks and within the channel (Montgomery and Dietrich, 1992). Modified land cover such as cultivated land, grazed grassland, channel banks and woodlands are all common land use sources of fine sediment and
13 Chapter Two: The role of fine sediment in managing catchment flood risk are capable of producing high sediment delivery rates (Heathwaite & Burt, 1990), due to a reduction in soil stability.
The need for self-sufficiency after World War Two saw a dramatic increase in agricultural activity. The demand for wheat (70 – 97%) and barley (10-65%) being sown in the winter season increased significantly during the 1960’s (O’Connell et al, 2004). Crops began to be cultivated throughout the year, even where soil conditions were unsatisfactory (Wheater and Evans, 2009). The harvesting of popular crops such as potatoes and maize in late autumn leaves many fields with bare soils at the wettest times of the year ( Holman et al, 2003; Collins and Walling, 2007). During the winters months, rilling and gullying of bare soils following seed preparation for winter cereals is likely to contribute to suspended sediment (Gruszowski et al, 2003). However, tracking the exact suspended sediment sources from agricultural lands is difficult due to vertical mixing for cultivation (Gruszowski et al., 2003).
Pastoral fields generally have a greater infiltration rate and lower runoff rates compared to arable land. However, increased stocking of animals such as sheep and cattle influences the soil compaction (Marshall et al, 2013). Similarly, machinery creating trenches (Wilkinson et al, 2013) and more pasture to accommodate increasing livestock numbers (Longfield and Macklin, 1999) increase the quantity of bare earth exposure. The compaction of land by livestock and machinery decreases the volume of soil, compressing the air from the soil structure and therefore reducing the infiltration rate. The intensity of compression is dependent on soil strength, texture and organic matter and wetness (Larson and Pierce, 1994).
Urbanisation has also had considerable influence on the availability of sediment to be transported around a catchment. The construction of impermeable surfaces such as roads and pavements has reduced the volume of land susceptible to soil erosion. However, roadside erosion is a common source of suspended sediments in river channels (Froehlich and Walling, 1992) where road surfaces act as a conveyor of fine sediment (Reid and Goss, 1981).
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2.3.5 Bank erosion
Knighton (2014) identifies hydraulic action and mass failure as the two primary types of bank erosion, both which have the ability to increase fine sediment supply to the channel. Hydraulic action often occurs at the apex of a river bend where velocity is expending energy as it hits the bank. Individual grains are then dislodged causing bank instability, which, can result in the deposition of fine sediment from the banks into the river channel (Richards, 1990). Hooke’s (1979) investigation into bank erosion found velocity; shear stress and local turbulence on banks had a significant impact on erosion by hydraulic action.
Mass failure of river banks occurs when prolonged processes have weakened the strength and cohesion of bank material, causing an overall decrease in bank stability (Thorne, 1982). Wetting and drying of river banks reduces the stability of banks resulting in slab failure (Knighton, 2014). Mass failure also results where non-cohesive materials overlie non-cohesive sands and gravels. Undercutting of the lower bank by hydraulic forcing on non-cohesive materials can create an overhang in the upper layer. The overhang will reach a critical angle where the lower bank is unable to support the weight and critical mass failure will occur (Knighton, 2014). Bank failure rates can be accelerated due to cattle trampling (Trimble and Mendel, 1995) and human disruption as they increase the downward force on the riverbank. In contrast, channel features such as bank and in-channel vegetation can reduce the rate of sediment delivery.
The presence of bank vegetation can provide lateral stability to the banks and reduce channel planform patterns (Millar, 2000). Bankside vegetation reduces near-bank velocities within the channel, reducing bank shear stress and thus bank erosion (Ikeda & Izumi, 1990). Dense vegetation such as forested catchments are likely to have narrower banks than those which are grass covered (Hey & Thorne, 1986).The roots of the vegetation improve bank stability by binding soil in their intrinsic network (Millar & Quick, 1993). Vegetation can act as a physical buffer to fine sediment delivery, reducing the wash and suspended loads through the channel. The removal of bank
15 Chapter Two: The role of fine sediment in managing catchment flood risk vegetation can cause destabilisation and channel widening causing an influx of sediment deposition into the channel (Millar, 2000).
2.4 Fine sediment detachment
The delivery of sediment into the river channel is dependent on a series of catchment processes involving the initial detachment of sediment and its connectivity to the channel. Unlike sediment transport, sediment detachment is hydrologically controlled. The physical contact of raindrops on the surface can be enough energy to dislodge fine sediment particles from the land. However, raindrop impact on heavily saturated ground can act as a sealant, reducing infiltration rates and increasing surface runoff (De Ploey, 1984). Particle cohesion, surface roughness and porosity are characteristics which can influence the soil’s vulnerability to detachment (Bryan, 2000). Anthropogenic activities such as deforestation and agricultural land intensification modify the soil-moisture-climate interactions causing more sediment detachment therefore increasing potential delivery into the channel (Seneviratne et al, 2010).
In channel, sediment detachment from the river bank is a result of bank instability, driven by energy dissipation from river flow onto the bank. Riverbanks comprised of sand and small gravels are more susceptible to erosion because less hydraulic forcing is required to break down the bank materials (Richards, 1990). Reliable information on the sources of fine sediments stored on the bed of the river channel is an essential pre requisite to develop control strategies (Walling et al., 1993; Shackle et al, 1999).
2.5 Spatial variation in suspended sediment
Understanding sediment delivery at a catchment scale remains a key challenge in sediment research (De Vente et al, 2007). Simulating all erosional and sediment transport processes requires high data inputs to accurately predict specific sediment yield (SSY) at a catchment scale (Merritt et al, 2003). Traditionally catchments have been conceptually divided into three zones which reflect the source – transport and sink continuum (Schumm, 1977). Zone
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1 refers to the headwaters of the catchment, likely to have increased erosion rates due to the present of hillslopes. Zone 2 is the transport of water and sediment into Zone 3 which reflects the floodplain or areas prone to deposition of sediments. Erosion rates in Zones 2 and 3 are thought to decrease due to decreasing hillslope gradients downstream of the catchment. These processes are suggested to have a linear relationship with area, meaning catchment area may have a significant control on specific sediment yield (Lane, 1997). Previous studies have found SSY decreases as basin area increases (Dendy & Bolton, 1976; Millman & Meade, 1983; Millman & Syvitski, 1992). Furthermore, a worldwide study into the relationship between catchment area and specific sediment yield found 877 rivers had a negative trend in relation to river basin area with R2 value of 0.02 (De Vente et al., 2007).
Due to natural variations in river catchments, the relationship between SSY- area is also likely to fluctuate. Figure 2.1 shows the non-linear relationship of SSY-area. At a small scale (m2) sources of sediment are likely to be generated from splash and sheet erosion (Osterkamp & Toy, 1997). Whereas at larger scales (km2) additional processes such as rill, gully and channel erosion can increase SSY (Poesen, et al, 1996). Local catchment characteristics such as topography, climate, land use and vegetation are likely to determine the availability of sediment for transport, thus the SSY-area relationship. For instance, the presence of a large floodplain created by low topography and slope can create a sediment sink resulting in an inversion of the SSY-area relationship (Figure 2.1).
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Figure 2.1 Conceptual model of sediment yield at various scales and contributing sources and sinks (De Vente and Poesen, 2005). In contrast, if channel erosion dominates, SSY shows a positive relationship with area (Vente & Poesen, 2005). Walling & Webb (1996) discovered that inverse relationships are likely to occur in catchments where geology in upland areas (Zone 1) is resistant to erosion but softer more erodible rocks downstream (Zone 2 & 3) are present. Catchments which contain readily available sediment sources are also likely to have an inverse relationship (M Church & Slaymaker, 1989). Understanding the varying relationships between SSY-area can provide an insight into sediment delivery at a range of spatial scales. This section highlights the importance of understanding the physical catchment characteristics and connectivity of sediment in determining catchment processes.
2.6 Fine sediment connectivity
Once the sediment has been detached from the source it is available for transportation within the catchment. In hydrology and geomorphology there are three identified types of connectivity 1) Landscape connectivity which is the coupling of landforms such as hillslope-floodplain, floodplain-channel; 2)
18 Chapter Two: The role of fine sediment in managing catchment flood risk hydrological connectivity, the movement of water through the landscape and 3) sediment connectivity which refers to the transfer of sediment through the landscape. The focus of this study is to investigate the influence of fine sediment on flood risk and therefore focus’ on both hydrological and sediment connectivity.
2.6.1 Hydrological connectivity
Source areas may be ineffectual in delivery if they do not have established pathways to transport the eroded material to the channel. When pathways become hydrologically connected, fine sediment can be transported in the suspended load. Hydrological connectivity is initiated at local scales during low intensity rainfall events, but for catchment scale connectivity to be achieved high intensity events are required (Bracken and Croke, 2007), those most likely to result in flooding.
The efficacy of rainfall intensity to mobilise fine sediments depends on the availability of sediment sources and nature of connections. Persistent erosion and weathering creates more sediment available for transport (Collins et al, 1998; Gruszowski et al., 2003). Antecedent conditions can create low soil moisture levels and therefore increase runoff creating a pathway of sediment delivery. Increased storminess as frequency in more heavy rainfall events could create flash runoff and increases in peak magnitudes (Huntingford, 2003), causing slope failure and increased inundation levels.
The temporal patterns of precipitation are important when considering connectivity and ultimately flood risk (Pitlick, 1994). For instance, light rainfall preceded by an intense rainfall event will dramatically increase hydrologic connectivity and surface runoff than a single high intensity rainfall event. This is due to the infiltration rate of the land surface being already saturated resulting in surface and sediment transport (Bracken and Croke, 2007).
The catchments climate is the greatest influence on the rate of fine sediment transport as it determines the hydrological connectivity through the magnitude, intensity and distribution of precipitation throughout the catchment (Bracken and Croke, 2007). Climatic controls on local weather are responsible for the
19 Chapter Two: The role of fine sediment in managing catchment flood risk spatial and temporal rainfall events and therefore which pathways within the catchment are fully connected and have sufficient energy to transport fine sediment to the channel.
In addition to climate, Bracken and Croke’s (2007) conceptual model of hydrological connectivity identifies four other major components that influence catchment connectivity (Figure 2.2).
Figure 2.2 Conceptual model of hydrological connectivity based on Bracken and Croke (2007).
Runoff potential refers to the catchments characteristics that can impact hydrological connectivity as runoff is a non-linear process. Physical features such as hillslopes can increase runoff potential as it reduces the time taken for water to connect with the channel. Infiltration and vegetation are also likely to determine runoff potential. For example, dense soils which are slow to infiltrate can increase surface hydrological connectivity and therefore sediment delivery from the land. Land use alterations such as urbanisation and loss of vegetation can also increase runoff potential due to alterations in delivery pathways (Bracken and Croke, 2007).
Delivery pathway refers to the individual routes and pathways taken by water and suspended sediment to hydrologically connect the catchment. Each runoff source has its own network depending on its position in the catchment, the physical and management characteristics. Overground runoff is usually
20 Chapter Two: The role of fine sediment in managing catchment flood risk identified by the presence of rills and gullies. The establishment of incisional rills and gullies on the landscape are an effective method of coupling the hillslope to the channel, this is a common feature in agricultural lands (Bracken and Croke, 2007). Gully erosion is the term used to describe the accumulation of runoff water in narrow channels, removing soil from the channel. The removal of vegetation for cultivation causes mass soil erosion and rill development (Walling et al., 1999). Permeant gullies are a frequent feature on agricultural lands as the process of ploughing encourages surface sealing which increases surface runoff (Moussa et al, 2002). Topography, manmade interventions such as tracks, roads and ditches alter the delivery pathway and can increase or decrease hydrological connectivity depending on their landscape positioning.
Small scale disintegration and swelling of the soil can cause the formation of micro-rills establishing a network of pathways (Bennett, 1999). Water erosion processes such as interill splash, caused by raindrops and the velocity of water travelling overland are affected by the nature of the topsoil (Savat, 1977). Surface roughness, size, pore space and flow depth are vital to the geology’s resistance to erosion, thus highlighting the critical importance of soil properties in determining spatial and temporal patterns of sediment transport on hillslopes (Bryan, 2000).
Landscape position within the conceptual model refers to the probability the source location has in being hydrologically connected throughout the catchment. For example, the probability of hydrological connectivity is increased if the location is near the channel (Bracken and Croke, 2007). The further the transport distance between source and channel the less likely the pathway will be fully hydrologically connected.
Lateral buffering refers to the connectivity experienced between landscapes such as the floodplain and channel during inundation (Pringle, 2001). Lateral buffering in these areas controls the volume of organic matter and sediment delivery to the channel (Bracken and Croke, 2007). Features such as riparian buffer strips can reduce the hydrological connectivity due to obscuring flow paths and porous soil structure. In contrast, agricultural drainage in these
21 Chapter Two: The role of fine sediment in managing catchment flood risk locations can increase hydrological connectivity and thus sediment delivery (Burt & Pinay, 2005).
2.6.2 Geomorphological connectivity
Sediment connectivity refers to the physical movement of particles from one zone to another and the potential of the individual particle to move throughout the channel system (Hooke, 2003). The movement of sediment from source to receptor as a result of detachment and sediment transport over a range of spatial and temporal scales describes a catchment experiencing sediment connectivity (Bracken et al, 2015). Fine sediment connectivity is intrinsically linked to hydrological connectivity as they are often transported suspended in the water column. The degree of sediment connectivity within a river catchment is entirely specific to the landscape characteristics (Hooke, 2003). It is not dependent on individual processes but all factors of the geomorphic systems which control sediment flux such as detachment, transport and entrainment (Sandercock & Hooke, 2011). Conversely, stable channel morphology reflects a stable net sediment budget with annual aggradation or degradation suggesting an imbalance or change to connectivity. A high degree of connectivity is usually assumed for fine sediments (Hooke, 2003) due to their ability to travel suspended in water flow.
Coupling within the catchment can be divided into reaches, occasionally referred to as compartment connectivity. The compartments (hillslope, floodplain and channel) have different connectivity characteristics that are often identifiable when exploring processes at a scale such as, hillslope- floodplain, floodplain- channel, upstream-downstream (Brierley et al, 2006; Fryirs et al, 2007; Fryirs, 2013). Fryirs et al (2007) identifies two common causes of sediment disconnectivity within sub catchments; landforms which impede sediment movement into the river channel network are termed ‘buffers’ (walls, roads, drainage, hedgerows) and those that impede connectivity within channels are called ‘barriers’ (weirs, dams, vegetation). Individual stones and soil aggregates can act as local barriers to connectivity if the water depth is lower than the structures. The identification of buffers and barriers within catchments can help predict how different land forms would respond to
22 Chapter Two: The role of fine sediment in managing catchment flood risk disturbances within the catchment. Dividing the catchment based on its connectivity enables a processed based understanding (Brierley et al, 2006).
The degree of connectivity within catchments influences the probability of local scale impacts propagating downstream (Borselli etal,, 2008). Patterns of sediment source, transfer and accumulation zones and their connectivity may differ when considering the location within the catchment (Schumm, 1977). Sediment routing is often impeded where reaches appear to become disconnected, causing sediment to enter temporary storage (Hooke, 2003). The impacts of indirect and direct interference on the river channel or catchment can interrupt the morphology and channel dynamics, (Hooke, 2003) potentially worsening the problem.
The proposed sediment connectivity framework (Bracken et al, 2015) identifies the three elements essential to identifying relevant processes and variables influencing sediment detachment and transfer through geomorphic systems. Understanding the connections between these elements is essential to understanding sediment connectivity and the mechanisms regulating the scale (Figure 2.3).
Figure 2.3 Conceptual model of fine sediment connectivity modified from Bracken et al (2015)
The magnitude of force applied by geomorphic processes can be measured relative to the amount of work done on a landscape. The frequency of that
23 Chapter Two: The role of fine sediment in managing catchment flood risk force being applied will also affect the sediment detachment and transport in the catchment (Bracken et al, 2015). The spatial position in which these geomorphic processes are occurring will also affect the magnitude and frequency. For example, sediment transport events on hillslopes have different frequency-magnitude distributions to sediment transport within river channels. High magnitude events can impact sediment connectivity in three ways. 1) The event can result in sediment detachment and transport causing full catchment hydrological connectivity over the event duration. During a study identifying connectivity on the River Wharfe, Yorkshire Reid et al (2007) observed increased hillslope connectivity in major events, causing greater volumes of sediment to be transported. 2) Sediment detachment may occur but not enough hydrological energy to initiate sediment transport, resulting in the creation of sediment barriers inhibiting future connectivity. 3) The high magnitude event can cause large geomorphic changes to landscape such as loss of floodplains, increasing sediment connectivity.
Spatial and temporal feedbacks can be both positive and negative and refer to the morphological processes that affect erosion, sediment transport which have implications for sediment connectivity and sediment yield. Finally, the mechanisms of sediment detachment and transport refer to those processes influenced by hydrological controls.
2.7 Methods of identifying fine sediment connectivity
Modelling and field methods are commonly used to identify sediment connectivity and therefore potential sediment sources.
2.7.1 Modelling sediment connectivity
Reid et al (2007) focused on the implications of hydrological disconnection for the delivery of failed sediment to the drainage network on the River Wharfe, Yorkshire. A reduced complexity model (SEDMAP) was developed in response to the observed river management problem; channel instability and flood risk. SEDMAP, a modified version of SHALSTAB and TOPMODEL captures this process using a simplified representation of the surface
24 Chapter Two: The role of fine sediment in managing catchment flood risk hydrological connection and a series of associated assumptions (Reid et al, 2007). SEDMAP was used to identify both hillslope and channel bank sources and to estimate if the delivery of failed sediment to the drainage network be improved by requiring failure to occur with a hydrologically connected flow path.
The model indicated that only the largest event (21st August 2003) had both the storm intensity and duration to generate coarse sediment from channel banks, bed or hillslopes and delivery it into the channel network. SEDMAP observed hydrological connectivity 150m from the river channel during such storm events. In contrast, moderate storm events such as 2nd November 2003 identified hydrological connectivity at 12m from the channel network, indicating the majority of sediment is generated through mass failures of channel banks or failure initiated by basal cutting as channels eroded into a hillslope (Reid et al, 2007). However, during high magnitude events, the hillslopes can become a significant source area (Reid et al, 2007). These results provide an explanation for the presence of coarse sediment at Buckden Beck where the reach does not have significant channel bed sources. The volume of sediment present is a result of sediment delivery from the deeply incised headwaters upstream.
Physics based models such as The Watershed Erosion Prediction Project (WEPP) and CEASAR and are also referred to as numerical simulation models that use standard equations for flow calculations based on first principles and therefore allow predictions of sediment routing to be made using fundamental catchment processes in a controlled landscape (Bennett, 1974). Inputs for these models are often data intensive and again must be calibrated against observed data within the catchment (Beck et al, 1995). WEPP is a physics- based model used to assess erosion by water on American slopes, including anthropogenic impacts (Merrit et al, 2003). A WEPP output is able to estimate spatial and temporal sediment yield, soil losses and run off volumes. To achieve this however, WEPP requires numerous model inputs such as soil characteristics, canopy cover, hydraulic processes occurring, meaning extensive observational work is also required.
25 Chapter Two: The role of fine sediment in managing catchment flood risk
CAESAR is a physically based numerical model which accounts for hydrological and geomorphological processes such as flow routing, sediment transport, sediment suspension and lateral erosion (Coulthard et al, 2002; Coulthard et al, 2007). CAESAR uses initial inputs of topography, sediment distribution, vegetation patterns and roughness and forcing inputs such as rainfall, inflow hydrograph and sediment inflows to simulate fluvial and hillslope processes. These processes identify areas of sediment erosion and deposition and the topography layer is adjusted accordingly to run the model again. CAESAR outputs flow and sediment hydrographs, topography, inundation, grainsize and erosional maps. The model can simulate suspended and bed load transport due to its calculation on each sediment fraction, making it suitable for simulating both coarse and fine sediment particles.
The model was applied a 4.2km reach of the River Teifi, Wales and successfully simulated processes such as incision, bed armouring and meander migration indicating the models ability to simulate long-term landscape evolution on a catchment scale. Detailed model outputs such as these indicate the models complexity and the data requirements needed to simulate both geomorphological and hydrological processes over time. However, too many assumptions in a model can divert away from reality, rendering the models outputs redundant (Merrit et al, 2003).
Sensitive Catchment Integrated Modelling and Analysis Platform (SCIMAP) is one example of a process-based risk model focused on representing fine sediment delivery in terms of risk. SCIMAP perceives the catchment as a series of flow connections that accumulate distributed sources of pollution from the surrounding landscape into the river channel (Reaney et al, 2011). The model was designed and calibrated on large rural catchments in the UK, recognising the importance of representing processes occurring at both the catchment and sub-field scale (Reaney et al., 2011). SCIMAP analyses risk at one location relative to all over locations within the landscape. SCIMAP was used to model the impacts of land use changes on salmon in the River Eden catchment, UK. The study successfully identified locations where salmon spawning sites would be most vulnerable to increases in fine sediment loading and the associated pollutants from arable fields (Reaney et al., 2011).
26 Chapter Two: The role of fine sediment in managing catchment flood risk
SCIMAP requires three datasets to successfully run the model: rainfall, topography and land cover. Reaney et al (2011) used SCIMAP within the Eden River catchment to determine potential sources of fine sediment phosphorous pollution and its impact on fish. Spatial rainfall pattern data was obtained from the Met Office and interpolated onto the topographic dataset. This data was then used alongside the nearest neighbour algorithm to determine the relationship between abundance levels and fry concentration. SCIMAP produces a risk map displaying the predictions of risk concentration.
Due to the complex and diverse nature of river landscapes, Van de Weil et al (2011) believe that most catchment scale models are unsuitable for accurately representing sediment routing throughout an entire catchment. Field methods offer an alternative, particularly in catchments where data input for models are limited.
2.7.2 Field methods for sediment connectivity
When investigating fine sediment’s influence on water quality, flood risk and sediment flux it is vital to obtain a representative sample to conduct research and make statistically significant assumptions. Phillips et al (2000) believes there are four key limitations to collecting such samples. The first is fine sediments often travel in the suspended load which is highly episodic and therefore difficult to obtain a representative temporal sample. Secondly, sampling of suspended sediment is often labour intensive and expensive. Thirdly, the collection of point samples as means of representing the sediment movement around a catchment can cause severe under or over estimation of sediment flux. Finally, the sample collected must contain enough fine sediment in order to conduct chemical analysis (Phillips et al, 2000).
In response, Phillips et al (2000) designed an inexpensive time-integrated suspended sediment sampler which enables the collection of time-integrated composite sediment samples to be continuously collected over the period of operation. The device can collect a composite sample representative of geochemical properties which can aid the identification of sediment sources. The simplistic design is advantageous to traditional suspended sediment field
27 Chapter Two: The role of fine sediment in managing catchment flood risk techniques as it requires less labour, costs and manual measurements, little to no maintenance and no power supply.
The design was initially tested by Phillips et al (2000) in a UK flume and in two catchments, including the Gilwiskaw Brook, located near Ashby-de-la-Zouch Leicestershire. This 2.6km2 lowland catchment is predominately agricultural with a blue lias mudstone geology. Point samples were additionally collected within the reach to compare the efficiency of the TIMS devices. The samples were analysed for grain size distribution and nutrient concentrations. Results found in field conditions the sediment sampler collected a statistically representative sample. However, minor differences were detected between particle size distributions of the point samples and those from the TIMS. The study concluded that the method was most representative on smaller streams (Phillips et al., 2000).
The flume tests indicated a mass retention of suspended sediment in the TIMS devices ranging between 31-71% with a bias towards coarser sediment particles as finer particles remained in suspension through the TIMS cylinder. Phillips also identified turbulence from the flume as a possible cause of coarse sediment bias. Phillips et al, (2000) conclude that the mass efficiency of the device is dependent on the particle size characteristics of the suspended sediment.
TIMS have been successfully deployed in numerous countries including; Australia (Olley et al, 2013), France (Poulenard et al., 2009), United States (Fox & Papanicolaou, 2008), Canada (Mcdonald et al, 2010;Koiter et al, 2013;Smith & Owens, 2014) and UK (Hatfield & Maher, 2008; Collins et al, 2010; Perks et al, 2014).
In Australia, Olley et al (2013) installed TIMS in 21 locations across the Laura- Normandy catchment in Northern Australia as part of a sediment source ascription study. The samples were collected after 2009/10 and 2010/11 wet seasons varying in mass from 5 – 1200g in each TIMS. The samples were successfully analysed using radionuclide tracers to determine the sources of suspended sediment. Similarly, in the Albenche catchment, France TIMS were successfully installed to collect a representative suspended sediment sample
28 Chapter Two: The role of fine sediment in managing catchment flood risk for sediment fingerprinting studies using spectroscopy analysis (Poulenard et al., 2009).
McDonald et al (2010) used a modified TIMS design to assess the effectiveness of a modified TIMS to collect a representative sample of suspended sediment, during snowmelt in the High Artic. Suspended sediment in artic regions have spatial and temporal variability due to snow, sediment accessibility and channel dynamics (Mcdonald et al., 2010). Two TIMS were deployed adjacent in a small stream on Melville Island, Nunavut, Canada and modified to accommodate a frozen bed and dynamic river stage. The sampler tubes were shortened from 1000mm to 228mm with a 2mm inlet tube which extended 20cm into the TIMS. Both TIMS were sealed with a plastic cap and outlet re-located to the top of the devise. One of the TIMS was static in the channel whilst the other placed on parallel pivoting arms to maintain 60% water depth without manual adjustment.
Potential capture rates were calculated from the ratio of the cross-sectional area of the inlet tube and the cross-sectional area of the river, multiplied by the daily suspended discharge. These results were compared actual suspended sediment collected and found to both over and underestimate suspended sediment load throughout the season. The fixed TIMS actual sediment load exceeded the potential by 150%.
McDonald et al (2010) found the ambient sediment analysed was not proportionate to the sampler sediment, as the sampler sediment was found to be significantly coarser. However, temporal variability in sediment capture was similar to variations in discharge and velocity. Though the TIMS proved successful in collecting enough suspended sediment for geochemical analysis it was not thought to be representative of ambient suspended sediment due to its overestimation of particle size.
Smith and Owen’s (2014) study in Canada investigated the efficiency of TIMS samplers at collecting a sample representative of ambient conditions both in mass, particle size and geochemical structure. The mass efficiency was analysed using two methods. The first was a temporal calculation of sediment retained by Phillips sampler assuming an initial ambient suspended sediment
29 Chapter Two: The role of fine sediment in managing catchment flood risk concentration for the reach. The second method compared a grab sample from the flume and comparing it to sediment collected by the sampler. The results showed there was little difference between the sediment in the sampler and the bed, with no significant difference in sediment types but a large variation in D50 values. The sampler retained 43-87% of the mass expected if it was 100% efficient (Smith & Owens, 2014). The study found the TIMS sampler capable of collected a representative sediment sample and reasonably efficient at collecting sediment mass which could be used as an indicator of relative sediment transport (Smith & Owens, 2014).
Perk’s et al (2014), conducted an extensive field campaign using TIMS on two lowland river catchments in North Yorkshire, UK. The investigation included 39 sampling sites to be installed in the Rivers’ Esk and Upper Derwent for two hydrological years between 2008-2010 creating a long term suspended sediment dataset using TIMS. The data was used to determine the suitability of TIMS as a method of characterising fine sediment flux and collecting a representative sample of physical, mineral and magnetic properties. The multiple sample analysis from the devices indicated that TIMS have the potential to provide a fully composite sample (Perks, 2014). However, as the properties were not compared to ambient sediment samples it could be argued that the true representativeness of the samplers remains uncertain (Smith & Owens, 2014). Two methods of analysis were undertaken to determine the effectiveness of TIMS. The first, directly compare the estimated flux from the sampler with reference sediment loads calculated from high frequency suspended sediment concentration and flow measurements. The second method compares the physical and chemical properties of samples collected from adjacent TIMS installed in the Rivers at four locations. The results of both methods enabled investigation into the absolute and relative efficiency of the TIMS (Perks et al., 2014).
The reference loads calculated for the monitoring period were found to underestimate the absolute sediment load by 66.38-96.31%. These results suggested that TIMS are not an efficient indicator of absolute total suspended sediment load and should not be used as a means of independent quantification of suspended sediment load (Perks et al., 2014). The results
30 Chapter Two: The role of fine sediment in managing catchment flood risk from the samplers that were installed adjacent at each location were statistically analysed to determine their relative efficiency. In 4/7 samples relations between TIMS A and TIMS B were statistically significant at the 99% level with two further at 95% confidence level, indicating TIMS have relative efficiency. The analysis also indicated an inherent sampling bias of larger particles. The chemical and physical particle analysis between TIMS A and TIMS B at adjacent sites showed statistically significant median grain size. The largest variations in median grain size were found where the coarsest sediment is present. Small deviations (1.58%) in organic matter content were also found, indicating chemical analysis of the adjacent samplers were statistically similar. From these results Perks et al (2014) concluded the TIMS provide a statistically significant relative load indicator which is capable of being deployed over prolonged periods of time. However, the absolute sediment flux will be underestimated but consistently with the magnitude of change of ambient flux.
The same dataset was successfully compared with SCIMAP modelling software to provide information on suspended sediment water quality and composition (Perks et al., 2017). The method of using TIMS and SCIMAP successfully identified areas of fine sediment risk which could be used to inform catchment scale management interventions. TIMS were found to provide consistent spatial and temporal patterns of sediment flux and argued to be a preferred sampling method compared to current monthly sampling which was found to have a bias of 13% (Perks et al., 2017). The unison of TIMS and SCIMAP through the plotting of channel erosion risk against specific sediment yield, has the potential to further understanding of fine sediment risk through the identification of critical source areas in UK catchments (Perks et al., 2017).
The use of TIMS to discover the relative quantity of suspended sediment within the catchment and its chemical properties have been used as part of sediment fingerprinting methods to determine potential sources and connectivity of fine sediment. Sediment fingerprinting is a popular method used to identify sediment sources within a catchment and allocate the amount of sediment contributed by each source through the use of natural tracer technology (Davis
31 Chapter Two: The role of fine sediment in managing catchment flood risk and Fox, 2009). This method uses a combination of field and laboratory techniques to identify the origins of fine sediments from reach to catchment scale (Fox and Papanicolaou, 2008; Davis and Fox, 2009; Collins et al, 2010;Martínez-Carreras et al., 2010; Wilkinson et al, 2013).
This technique makes use of chemical and physical properties of sediment to differentiate potential source materials from the suspended sediments (Walling et al, 1993; Collins et al., 2010). Though relatively simplistic in design, there are a number of potential problems such as identifying a unique property that can conclusively determine the source. Several fingerprint tracers have been used in the past such as; radionuclide concentrations, magnetic parameters, sediment chemistry, physical particle size but Walling et al, (1993) identify the importance of using a multi-parameter approach as no single parameter can conclusively identify sediment sources.
The sediment fingerprinting methodology has been successful in the UK at identifying sediment sources (Walling et al., 1993; Collins, et al, 1997; Collins et al., 1998; Mukundan et al, 1999; Walling et al., 1999; Jenkins et al, 2002; Carter et al., 2003; Walling et al, 2003); Collins and Walling, 2007; Martínez- Carreras et al., 2010), although there are some limitations associated with the technique. The common classification of suspended sediment as a discrete source overlooks the potential for this source to be a temporary store as well as a permanent one. In addition, obtaining reliable results which are representative of the source soil, sediment fingerprinting is a labour and laboratory intensive procedure requiring instrumentation to measure a variety of properties. Furthermore, for significant differences to be identified by tracers there needs to be distinct chemical or physical characteristics between source types. This is particularly difficult in areas with homogenous geology and land cover types such as the River Eye catchment (see section 3.2.3).
2.8 Fine sediment delivery in river channels
The processes which govern fine sediment delivery are intrinsically linked through a series of feedback mechanisms within the river catchment. Primarily, fine sediment delivery into the channel relies on three areas; 1) the availability
32 Chapter Two: The role of fine sediment in managing catchment flood risk of sediment to be transported, dictated by physical catchment characteristics, 2) the presence of hydrological connectivity, determined by discharge/ runoff, 3) and the inclusion of artificial flood defences which reduce natural flow and create barriers to sediment connectivity. Alterations to physical features such as land use changes and climate through climate change may alter the current natural levels of sediment being transported throughout the catchment.
Excess fine sediments in the water column increase turbidity, limiting light penetration thus reducing primary productivity (Davies-Colley & Smith, 2001), diminishing habitat quality. Sedimentation reduces fish spawning sites (Acornley & Sear, 1999) macrophyte and invertebrate populations (Ward & Bretschko, 1998; Collins & Walling, 2007) causing an overall degradation in habitat and water quality.
Fluvial flooding is not only dependent on climatic conditions that dictate the magnitude of peak flows; rainfall volume and intensity, but also changes to the river channel stage (Lane et al, 2007). Investigating the impact channel morphology has on flood risk is often overlooked (Stover & Montgomery, 2001) but with increasing anthropogenic forcing on channels and the impact of climate change on inundation it is necessary to investigate the impacts of channel geometry and long term sediment transport/ supply rates (Lane et al, 2007).
2.8.1 Hydraulic implications of sediment deposition
Alterations in channel flow conveyance can be quantified using a time series of gauging measurements. Specific gauge analysis utilises long time series of systematically measured stage and discharge data to test for changes in the stage-discharge relationship at a given cross section (Pinter & Heine, 2005). This type of measurement can be used to illustrate changes in channel geometry and flow conditions over time. Using stage trends for consistent discharges excludes basin processes that may alter the discharge-frequency distribution over time. Specific gauge analysis excludes climatic and land use changes and focuses on modifications to the channel and floodplain. A fixed- discharge analysis is applied to measured channel parameters such as width,
33 Chapter Two: The role of fine sediment in managing catchment flood risk velocity, depth and bed elevation. By regressing each of these parameters against discharge at the measured cross sections the hydraulic geometry can be calculated (Pinter & Heine, 2005).
The Missouri river has been subjected to straightening and constriction to maintain channel depths and prevent lateral erosion to maintain navigational courses. Systematic measured hydrologic data including stage-discharge, cross sectional area, channel width and average depth was recorded over a 70 year period. The results indicate that the impact of engineering modifications to the channel have been abrupt and episodic, indicating large rivers can take several years or decades to reach equilibrium. Two clear trends were discovered during this investigation rising velocities tend to lower stage over time and declining flow velocities tend to increase stage over time. The reduction in cross sectional area within the channel provides one explanation to increased magnification of flood stages (Pinter & Heine, 2005). Similarly, James et al’s (1999) study into stage-discharge changes in the Sierra Nevada region California found that sediment aggradation, a legacy from mining was responsible for shifts in stage-discharge and an increase in flood inundation to the area.
Stage-discharge analysis was also used to test the hypothesis that flooding has increased in magnitude and or frequency in the Mississippi River, US and the Rhine, Germany (Pinter et al, 2006). Maximum annual stage discharges and flood frequencies from 14 gaging stations on the Mississippi and 8 from the Rhine, provided 75 years of continuous flow measurement data. This data was subjected to continuity and quality checks so stage data could be corrected to a uniform vertical datum at every stage location (Pinter et al, 2006). The data was examined for trends in flood heights using least square regression and time series analysis. Trends in flood frequency were also explored within the time series data. The results showed no trend hypothesis for flood stage was rejected by 10 of 14 Mississippi sites and 1 of 8 Rhine. Whereas trends in flood frequency saw no trend hypothesis rejected for 10 of 14 sites on the Mississippi and 2 of 8 on the Rhine. The statistical method showed statistically significant increases in flood levels can be found within the Mississippi but only once within the Rhine. However, specific-stage changes
34 Chapter Two: The role of fine sediment in managing catchment flood risk with smaller discharges reflected bed incision or aggradation at or nearby that gaging station location suggesting a decline in flow conveyance at these sites. The results from both rivers discovered that trends in flood stages represent the cumulative effect of several simultaneous mechanisms including, channel modifications, changes in precipitation, land use, and artificial flood defences (Pinter et al., 2006).
Remo et al (2009) combined stage-discharge analysis with a 1D unsteady flow model using HEC-RAS to quantify the effects of levee construction upon flow conveyance and flood stage. The model used historic hydrological and geospatial data to run a series of scenarios at given locations. The results indicated that changes in channel geometry and roughness were largely responsible for changes in flood stage. Changes in land cover within the flood was found to have minimal effect (Remo et al., 2009).
The impact of changes in channel capacity on flood frequency has been explored in the USA and UK (Slater, 2016; Slater et al, 2015). Using secondary stage-discharge and geomorphic data from the USGS, Slater (2015) applied a method for measuring long-term trends in channel capacity on 401 gauged rivers to determine the affect on flood frequency. The network of channels over the USA were categorised into “least”, “intermediate” and “most” modified to reflect the anthropogenic influence. The study measured the effect of flow frequency and the effect of channel capacity to calculate the total change in flood hazard. The results showed 227/401 rivers with channel capacity or flow frequency changes had statistically significant impact on flood hazard, suggesting channel capacity may be important in attenuating the impacts of climate on flood frequency. The results demonstrate nonstationarity in flood frequency is common and is a result of hydrologic and geomorphic influences (Slater et al., 2015). The same methodology was applied to 41 UK rivers with results indicating that geomorphic trends attributed to changes in sediment delivery, flow frequency and vegetation growth in channels can be directly related to estimated changes in flood hazards (Slater, 2016). The work also identified flow frequency trends outweigh the effect of channel capacity on flood hazard in many locations. However Slater (2016) believes this result may
35 Chapter Two: The role of fine sediment in managing catchment flood risk be overemphasised due gauging station locations often installed in areas that are geomorphically stable.
2.8.2 Geomorphological implications of sediment deposition
Erosion or deposition within channels is an indication of active sediment transport and can be used to predict morphological changes to the channel (Wilcock et al, 2009). Where flows are unable to effectively transport sediment, temporary storage occurs (Collins and Walling, 2007) causing the formation of channel bars and loss of channel capacity. Calculating incipient motion for different sediment sizes within a channel reach can determine the transport rate of sediment through a reach. The rate at which it moves through a calculated cross section is known as the transport capacity (Wilcock et al, 2009). The balance between sediment supply and transport capacity determines downstream impacts such as channel topography, bed scour and aggradation as well as the construction or erosion and river banks (Wilcock et al, 2001).
Determining sediment transport rates in various reaches throughout the catchment gives an insight into the channels capability to move sediment downstream and therefore its degree of connectivity. Longitudinal, lateral and vertical linkages can alter over time, connecting or disconnecting sediment connectivity within the catchment (Ward et al, 1989). When material is no longer being transported through a reach it is assumed the material is broken down or the channel morphology adjusts until it can be transported downstream.
Reid et al’s (2007) study of the River Wharfe predicted that future sediment delivery would happen throughout the year with the majority of sediment transported to the channel during the summer months as a result of convective rainfall events. This would result in a temporary increase in bed aggradation as a result of insufficient discharge to transport the sediment downstream (Reid et al, 2007). Similarly, abrupt sediment releases may cause pool infilling, fining of channel substrate, formation of lateral bars, aggradation and loss of conveyance (Antony, 1987, Schmidt, 1990 Montgomery 1999; Rathburn &
36 Chapter Two: The role of fine sediment in managing catchment flood risk
Wohl, 2003). If the transport of sediment throughout a catchment and river channel is continuous, the effects of disturbance can be propagated downstream (Kondolf, 1997). Re-adjustment towards equilibrium after a disturbance may only occur in areas where the channel is not being artificially restricted. Raven et al (2011) used a quasi-2D conceptual model to determine lateral and vertical migration for gravel bed rivers that simulated sediment aggradation, degradation and downstream fining. The model divided the channel in two, allowing for the left and right banks to be treated separately. Bed material transport rates used the Wilcock and Crowe 2003 equations combined with local shear stress (Raven et al, 2011). The model successfully simulated reach coupling, calculating the annual bed load input into Hubberholme as 9000m3 from March 2003 – March 2004 (Raven et al, 2011). The model simulates natural process widening in response to deposition (Raven et al, 2011).
To date, there is limited literature available on the impacts of fine sediment on channel capacity and subsequent flood risk. An investigation on high fine sediment delivery rates in the Waitangitaona and Poerua Rivers in New Zealand determined that recent landslide activity within the catchment caused an increase in river stage during higher discharges as the river had insufficient stream power to transport the sediment downstream (Korup et al, 2004).
There has been significant studies investigating the connectivity of coarse sediment throughout the catchment and its influence on flood risk in response to catchment changes in climate and land use on the River Wharfe ( Reid et al, 2007; Reid et al, 2007; Lane et al., 2007; Lane et al, 2008; Raven et al,2009; Raven et al, 2010; Raven et al, 2010; Raven et al, 2011).
Lane et al, (2008) investigated the potential influence of future channel change on the River Wharfe catchment by trialling a series of tools that can predict the medium term response of riverbeds in order to assess flood risk impacts. To conceptualise the entire 72km2 catchment, data from sediment impact sensors and the channel surveys assessed the linkage between sediment delivery and channel change. Lane et al’s (2008) results indicated sediment transfer within the tributaries occurred in smaller magnitude flows and for a shorter duration.
37 Chapter Two: The role of fine sediment in managing catchment flood risk
Therefore the tributaries are most effective at transferring sediment in the summer flows (64%) than winter flows (26%) (Lane et al, 2008). In addition, variations between tributaries determined the forested tributary had the lowest recording of sediment transport, indicating that the reduced production of coarse sediment from the hillslope has a significant impact (Lane et al, 2008). In contrast, the tributaries that recorded the most sediment transport were incising into past glacial deposits, supporting Reid et al’s (2007) results (Lane et al, 2008).
Recent morphological investigations have focused on the coarse sediment sources and transport within a 3km reach of the River Wharfe between Hubberholme and Starbotton (Reid et al, 2007; Lane et al, 2007). This was extended downstream by 2.6km to Cam Gill Beck in 2006 by Raven et al (2009, 2010, 2011). The 5.6km reach begins at Hubberholme, where flow travels from a steep confined valley into a relatively flat, u-shaped valley. From here, the river becomes meandering with some straight sections causing the channel width to vary between 10-20m until it reaches Cam Gill Beck (Raven et al., 2011, 2010; Raven et al., 2009). Over a 16 month period (December 2002 – March 2004) extensive morphological surveys were conducted on a 3km reach of the River Wharfe compiling the raw data for several investigations (Reid et al, 2007; Lane et al, 2007, 2008; Raven et al, 2009,2010,2011). Bi-annual surveys (April and December) were taken over an 18 month period to assess the linkage between sediment delivery and channel change. 57 cross sectional surveys using a differential GPS and a further 3 using a total station due to dense canopy cover were recorded at each survey. The cross sections were spaced closely on the meander bends with an average distance of 48.5m and further apart on the straightened sections (115.5m) due to geomorphic heterogeneity.
The upper study reach was found to be aggradational, though seasonality and volume of rainfall greatly affected the extent of aggradation (Lane et al, 2007), causing average bankfull discharge to reduce from 30.6 – 28.7 m3 s-1. Winter discharges in winter 2003 were a responsible for a significant reduction in channel cross sectional area observed in spring 2004 channel survey (Lane et al, 2007). Significant sediment delivery was observed between Hubberholme
38 Chapter Two: The role of fine sediment in managing catchment flood risk and Starbotton due to a decrease in channel gradient in this area (Lane et al, 2007).
The channel cross section surveys identified two reaches of sedimentation: approximately 1500m from Hubberholme and 3000m – 6000m downstream respectively. Both locations of aggradation are areas of relatively flat channel slope after significantly steeper upstream gradients, creating a natural zone of sedimentation. The latter zone of sedimentation is the result of major historical flood event (Coulthard et al, 2002) that has caused an elevated bed level and thus a continuous zone of deposition. During the survey period bed aggradation was calculated at 0.12m +/- 0.014m.
Seasonal fluctuations were found to impact the spatial sedimentation of coarse sediment in the Wharfe catchment and therefore increase flood risk. In the winter, sediment is more likely to be delivered from the hillslope into Hubberholme where its shallow gradient has insufficient energy to transport sediment downstream, resulting in scouring and bed. An increase in sedimentation in this area during the winter months increases the inundation time during high flows. However, convective summer rainfall events were found to be effective at transporting sediment downstream and thus reducing the mean bed level (Raven et al, 2009).
Temporal patterns within the Wharfe catchment were also found to be highly variable. Raven et al (2009) discuss the overall trend variation depending on the length of survey. For instance: Using the data from 2001-2007 the results indicate a predominately-degrading channel. However, if the trend is taken from 2003 onwards the channel appears to be stable or slightly aggrading (Raven et al, 2009). The importance of seasonal surveys is emphasised by the major aggradation period recorded between December 2004- April 2005. Without bi-annual surveys this trend would have been missed (Raven et al, 2009). Given flows closest to bankfull discharge are the most sensitive to geometrical change prolonged aggradation could result in reduced partitioning of flows between channel and floodplain (Lane et al, 2008). Overall, the sedimentation rate of the River Wharfe has increased the frequency of flood events by 2.7 and the water above bankfull by 12.8 hours (Raven et al, 2009).
39 Chapter Two: The role of fine sediment in managing catchment flood risk
The extended surveys showed an increase in mean bed level by 0.17m ± 0.029 with aggradational zones increasing by 0.67m ± 0.031m. In particular the upper zone of the catchment has experienced a 4.5 times mean bed level rise between December 2002 and July 2007 (Raven et al, 2010). The results of this seven year investigation highlighted the importance of monitoring the feedback of short term aggradation in reference to flood risk and implementing river management methods that allow for channel migration to allow for readjustment (Raven et al, 2009; 2011).
Raven et al’s (2010) morphological study of the River Wharfe found bed elevation levels increased by a rate of 0.12m during the survey period as a result of sediment aggradation. A reduction in channel capacity was observed to due the River Wharfe having insufficient energy to transport the delivered sediment downstream. This resulted in localised bank erosion to adjust to changes in channel depth (Raven et al, 2010).
2.8.3 Future implications of sediment delivery in a changing climate
The exact impacts of climate change on sediment delivery are unknown but past studies have tried to predict the influence of hydrologic drivers on the detachment and transport of sediment.
Lane et al (2007) combined observed rates of sedimentation over an 18 month monitoring period of the River Wharfe with Climate Change Scenarios to determine the changes in sedimentation. The results indicated a 38.2% increase in inundation for the 2050 climate scenario and a 52.1% increase in the 2080’s scenario. The results indicate that drivers influencing flooding are non-linear. The joint impacts of climate change and bed aggradation emphasise the non-linear nature of system responses and potentially the severe synergistic that result from the combined influence of climate change and sediment delivery. The increase in inundation extents are not a result of increased return periods but represent inundation occurring at lower return periods due to a reduction in channel capacity. However, the results are governed by the lateral inundation extent controlled by the number of channel cross sections experiencing out of bank flow and the magnitude duration of the
40 Chapter Two: The role of fine sediment in managing catchment flood risk out of bank flows (Lane et al, 2007). Further results from climate change scenarios on the results generated by SEDMAP suggest the number of sediment generating events will increase in both 2050’s and 2080’s and the proportionate increase in volume is greater than the proportional increase in the number of events. These results confirmed that the magnitude of extreme precipitation events dominates sediment delivery (Lane et al, 2008). The peak inundation rate was predicated for the future climate change scenarios, increasing to 12.2% in 2050’s and 21.6% in 2080’s, indicating a non-linear trend. In light of this, Lane et al (2008) explain the importance of future catchment management adapting to allow for climate change, emphasising a reduction in sediment delivery rates to the channel is the optimal management option.
In summary, the studies conducted both in the UK and USA highlight the importance of maintaining channel capacity when managing flood risk. Geomorphic drivers such as increased sediment delivery from changes in land use can decrease the capacity of the channel and therefore increase flood risk. Identifying potential areas of sediment sources and understanding the spatial and temporal patterns of sediment transport can help catchment managers sustainably manage flood risk.
2.9 Interactions between traditional engineering techniques and hydrology
When a river system is no longer adequately meeting the needs of its inhabitants, it is often subjected to modification (Plate, 2002). River engineering, particularly flood defence has evolved largely from industrial studies of fluid mechanics, hydraulics and regime theory (Chang, 1988; Chow, 1959). But rivers by their nature are unique, irregular and difficult to anticipate (James & Kiersch, 1991) meaning consideration and understanding of fluvial processes is paramount to constructing sustainable flood defences (James, 1999).
A transition in management strategy from flood defences to flood risk management in the 1990’s incorporated softer engineering defences which work in conjunction with natural processes (DEFRA, 2005). Traditionally, flood
41 Chapter Two: The role of fine sediment in managing catchment flood risk strategies have overlooked the social element of sustainable flood defences, something which is difficult to quantify in cost-benefit analysis (Brown & Damery, 2002).
2.9.1 Traditional engineering techniques: Dams
Dams are often constructed to store water to sustain water supply across the UK, by reducing the volume of water that flows downstream. Many dams alter flood hydrographs and natural seasonal distributions in discharge. In addition, to some degree, all dams restrict the longitudinal connectivity of sediment transport (Kondolf, 1997). Upstream of the dam, all sediment travelling as bedload and part of the suspended load will be deposited in the slower deeper waters before the dam. This is a result of increased depth and a reduction in velocity causing deposition to occur (Kondolf, 1997). Prolonged deposition behind a dam will cause a reduction in its storage capacity, resulting in expensive maintenance.
Downstream, the flow transports less sediment and therefore dissipates its energy on the banks. The construction of dams reduce natural flow variations, the excess energy can result in channel erosion downstream (Pinter & Heine, 2005). If the discharge has been significantly reduced, riparian vegetation can encroach due to a reduction in scour (James, 1999; Kondolf, 1997). If stream power is insufficient, fine sediment accumulation will result (Williams & Wolman, 1984). The disruption of sediment transport (Phillips et al, 2004; Phillips, 2003, 2005) and modification of flow regime by dam construction can cause diminished channel capacity downstream, resulting in an increase to flood risk (Batalla et al, 2004).
The re-routing of sediment around dams have been mostly implemented in Japan as a measure to prevent deposition (Kantoush & Sumi, 2010). Bypass tunnels come at a high cost but can be added to existing dam structures without losing storage capacity. The presence of hydraulic jets at the base of the upstream dam causes turbulence and the remobilisation of sediment laden water, which can then be transported downstream. This technique can be used
42 Chapter Two: The role of fine sediment in managing catchment flood risk to maintain storage depths, providing a long term sustainable solution to dam infilling (Jenzer, 2009).
2.9.2 Traditional engineering techniques: bank protection
Bank protection in the form of concrete, riprap and gabions are often used to reduce sediment erosion and natural channel adjustment in response to high discharges. Bank protection is often located around important channel infrastructure such as dams, bridges and weirs to reduce erosion in those areas. The presence of which can cause deposition in those areas and therefore progressive narrowing of the channel at these sites (James, 1999).
2.9.3 Traditional engineering techniques: dredging
A previously popular management method of flood defence is to dredge the riverbeds to remove sediment and lower the channel bed. The impacts of dredging are not well documented in the literature, particularly when considering the catchment scale impacts to morphology, vegetation and ecology. The act of dredging involves the artificial widening and deepening of channels to increase the capacity of those channels, alleviating flooding and/ or drainage (CIWEM, 2014).
The Environment Agency (EA) conducts routine gravel extraction operations throughout the UK to maintain and improve channel capacity as one method of reducing flood risk (Wishart et al, 2008). Lowering of the river bed through gravel extraction can affect both immediate and long term channel stability (Wishart et al, 2008). The lowering of the channel bed disrupts the armoured layer (Rinaldi et al, 2005), causing the bed to become vulnerable to fluvial erosion (Mossa and Mclean, 1997). Bank instability often results as the bank height is increased interrupting the sediment transport system (Wishart et al, 2008) through mass failure or knick-point migration (Kondolf, 1997). The magnitude of effects caused by dredging is determined by the speed of volume of sediment removal (Rinaldi et al, 2005). Monitoring after extraction on the Southern French Alps found an increase in shear stress and decreased resistance of gravel bars to erosion.
43 Chapter Two: The role of fine sediment in managing catchment flood risk
Wishart et al (2008) investigated the impacts of gravel extraction at two separate 3km sites; Haperly Park and Wolsingham on the River Wear, County Durham. Both sites had an absence of direct slope-channel coupling and an influence of fine sediments on channel morphology. The removal of sediment temporarily increased sediment storage due morphological changes to the width and reduction in channel gradient. At Wolsingham, localised failure of pre-exisiting bank protection structure occurred indicating the importance of investigating downstream impacts of artificial sediment removal (Wishart et al, 2008). At Haperley Park, after becoming unstable, the channel was straightened and vegetated bars removed causing sedimentation further downstream. Disrupting the natural bed exacerbates sedimentation downstream and disturbed bed sediments are once again mobile (Gob et al, 2005). Aerial photographs were used to identify sedimentation after extraction, the medial bars became well vegetated and secondary channels were abandoned as channel incised through the deposits (Wishart et al, 2008).
By artificially increasing the channel capacity to an unnatural geomorphic design to alleviate flood risk can cause adverse impacts for sediment transport, bank stability, flora and fauna. These local scale impacts are likely to propagate downstream, increasing the vulnerability of those areas. Currently limited research exists directly looking into impacts of dredging, particularly at the temporal impacts of dredging as well as the spatial scale. Such management techniques require a catchment based approach that accounts for the geomorphic processes present within the area.
In the wake of the 2014 floods, the decision to dredge the Somerset Levels, a practise that had not been conducted in the area for over 20 years, created a deep controversary between academics, governments and stakeholders. The process requires heavy machine access to waterways, which is often destructive to bank stability and local flora and fauna. Due to the unnatural morphology, sediment deposition in those areas can be exacerbated, resulting in expensive maintenance £20 000 per kilometre (SDBC, 2014). The Environment Agency initiated a number of pilot schemes to investigate the impact of dredging on flood risk. At Hinksey, Oxfordshire the dredged channel
44 Chapter Two: The role of fine sediment in managing catchment flood risk was found to reduce water level by 120mm when flows remain in the channel but only 40mm when the water enters the floodplain (Figure 2.4).
Figure 2.4 Schematic diagram showing the impact of dredging on flood levels (CIWEM, 2014)
Dredging practises require fluvial maintenance to preserve flood capacity and geomorphic stability, using in the form of channel and bank vegetation removal as well as sediment. These practises are often costly and damaging to ecology (Darby & Thorne, 1995). To limit the environmental and economic impacts of dredging in the UK and USA Darby and Thorne (1995) suggest the intensity of maintenance can be reduced without losing channel capacity and furthermore incorporating an integrated catchment-based approach can reduce the need for fluvial maintenance.
2.10 Natural Flood Management engineering: working with natural hydrological processes
River engineers must account for the natural variations in channels in order to create sustainable flood defences (James, 1999; Kondolf, 1997; Plate, 2002). Current UK policy and legislation have placed emphasis on working with natural processes in order to create cost effect, efficient and sustainable flood defences (See section 2.9) in order to combat the increasing challenges from increasing population, building on floodplains and climate changes. Government and industry are in agreement that traditional flood defences are not the sole answer to flood risk to people, property and the economy. A multi- functional strategy is required to protect, restore and match the natural
45 Chapter Two: The role of fine sediment in managing catchment flood risk functions of river catchments, often termed Natural Flood Management (NFM) (Environment Agency, 2017). The Environment Agency defined NFM as “working with natural processes to retain water in areas where it poses less of a hazard to commercial and residential property” (Environment Agency, 2017). This approach relies on three mechanisms increasing infiltration, storing water and slowing flows. The principle is to offer low cost, multi beneficial schemes supported by experts in geomorphology, hydrology, ecology and engineering to sustainably alleviate flood risk. Understanding the natural processes causing flood risk areas enables catchment managers to install measures targeted at maintaining natural sediment supply and channel capacity and thus alleviating problems downstream, reducing invasive costly measures that were previously required.
The town of Pickering, North Yorkshire suffered from significant flooding in June 2007, causing 48 properties to be inundated (Lane et al., 2011). This was the 4th flood event in a decade to hit the 66km2 catchment which is naturally prone to flashy summer flows due to its steep topography. (Environment Agency, 2017). Land cover in the catchment consists of arable crops, improved grassland, forestry woodland and heather. Poor land management decisions such as overgrazing, overstocking and poor drainage resulted in increased flood risk (Forestry Commission, 2015). In order to reduce flood risk to the town, a collaboration was created by DEFRA to install low cost resilient solutions at the cost of £4.2 million. Bunds were installed to increase flood storage, 167 large woody debris dams were placed to slow the channel flow. Moorland drains were blocked and buffer zones installed alongside streams to delay run off. The diverse scheme provided additional benefits to water quality, habitats, carbon sequestration and tourism (Environment Agency, 2017). Optimisation models were used to identify areas where NFM installation would be most beneficial based on 2000 and 2007 flood events. The results indicated that the interventions would be most effective in the upper reaches of the catchment, with installations in the main beck being more effective than the smaller streams.
The scheme received positive press attention in December 2015, where the scheme was estimated to reduce river peak by 15-20% thus preventing the
46 Chapter Two: The role of fine sediment in managing catchment flood risk town from flooding (BBC News, 2015). However, the effect of NFM was brought into question by the media who believed the reduced volume of rainfall compared to 2007 was responsible for the absence of flooding and the installation of natural measures would have very little impact at reducing flooding caused by large flood events (The Guardian, 2016).
The Pickering scheme provides a case study for UK NFM measures effective in small catchments. Recent research has yet to ascertain the effectiveness of NFM at large scales which holds a more complex scale of physical features such as land us and topography (Environment Agency, 2017).
2.10.1 Instream NFM structures
Though the majority of NFM measures are designed to be installed out of channel, some in channel measures have been designed to slow instream flow and potentially direct water into offline storage areas (Environment Agency, 2017). The installation of woody debris dams into the channel can increase surface roughness and encourage out of bank flow enabling reconnection of river and floodplain, reducing the volume of water being transported downstream (AECOM, 2017). Woody debris dams can accrete fine sediments behind, affecting channel capacity and thus river stage. Maintenance is required to maintain effectiveness (Woodland Trust, 2016), highlighting the importance of accounting for fine sediment delivery.
Sediment yield reductions are a catchment based approach to reducing sediment delivery to the river channel. This approach is an effective catchment tool to reduce flood risk (Kantoush & Sumi, 2010). The reestablishment of vegetation as a riparian buffer can dramatically reduce the rate of sediment delivery to the channel (Kantoush & Sumi, 2010). Online mechanisms such as establishment of weirs can encourage deposition of suspended sediments to reduce downstream aggradation (Kantoush & Bollaert, 2005).
2.10.2 Silt traps
A relatively new technique has been implemented in UK Rivers to reduce fine sediment delivery downstream in the form of online sediment traps. Sediment
47 Chapter Two: The role of fine sediment in managing catchment flood risk traps above dams are starting to be used to reduce sediment deposition at the site of a dam or downstream of it (Kondolf et al., 2014). Online sediment traps are an artificially widened and deepened part of the channel that encourages natural sediment deposition of suspended and wash load sediments. These sites are located in areas where the deposited material can be easily excavated (Kantoush & Sumi, 2010) and the enriched soil can be redistributed over fields to prevent financial costs incurred through soil erosion. Runoff attenuation features such as offline diversion ponds were installed in the Belford catchment, Northumbria to reduce flood peak and increase lag time to the main channel (Nicholson et al, 2012). The inclusion of these features within a catchment can also reduce the volume of soil being delivered to the channel.
2.10.3 Riparian buffer strips
Riparian buffer zones are often considered as an optimal measure in improving water quality of rivers as they reduce the volume of pollutants and fine sediment entering the river system. The installation of vegetated strips made from grasses, hedges or wood under cultivated fields have been found to reduce sedimentation by 70-90% (Wilson, 1967). Field studies have successfully shown reductions in fine sediment delivery through the installation of buffer strips (Barton, et al, 1985; Verstraeten et al, 2006), though it is argued that the efficiency of buffer strips is dependent on the design and location of the feature. Buffer strips must be designed based upon fine sediment characteristics such as particle size distribution and soil type. Environmental factors such as slope and sub-surface drainage, should be considered when designing the density and size of macro and micro vegetation in the buffer strip (Hickey, & Doran, 2004). Buffer strip efficiency is also dependent on its spatial location within the catchment. Coleman & Scatena (1986) found buffer zones installed next to a water course are most effective at reducing sediment.
2.10.4 Natural Flood Management: limitations
With NFM in relative infancy compared to traditional engineering techniques there are several barriers to its installation (Table 2.1). Many barriers are due to a lack of empirical evidence, emphasising the importance of monitoring and
48 Chapter Two: The role of fine sediment in managing catchment flood risk appraising current installed NFM measures. Lack of awareness or trust from the public and key stakeholders into the potential benefits of NFM is also outlined as a potential barrier.
Table 2.1 Limitations to NFM adapted from (AECOM 2017)
Barrier Details
Funding Funding is required for the installation of measures, compensation for land take and maintenance of measures. It is currently unclear who is responsible for the payment of NFM Evidence gap There is a lack of empirical, measured evidence to support the impact of NFM on reducing downstream evidence, reducing stakeholder uptake. Modelling has been used to predict likely outcomes. Land Take Many NFM measures require loss of land to create storage areas or woodlands. Currently there is not a strong incentive for land owners or farms to engage with these schemes. Land Ownership NFM is most effective when deployed at a catchment scale, this requires engagement from multiple land owners.
Public The benefits of NFM are not as tangible as hard engineering perception structures resulting in a lack of awareness and confidence in NFM from stakeholder communities. Maintenance Maintenance may be required for some NFM measures such as silt traps and offline storage areas in order to remain effective. The responsibility of maintenance has not been identified. Environmental Sites designated for the preservation of flora and fauna such Constraints as SSSI’s dictate how land is managed and therefore create a barrier to NFM installation in these areas.
2.11 Social consideration in flood risk management
The reversal of current policy’s presents future challenges to flood managers attempting to install soft engineering approaches. Hard engineered solutions may provide the desired result in the short term but undermining expert advice and policy for political gain is an expensive cost. Emery and Hannah (2014) suggest the problem derives from soft engineered approaches being longer term investments and sustainable methods need further development but not at the detriment to local communities. Smith et al’s (2014) study demonstrated local communities capacity and willingness to be involved with flood risk
49 Chapter Two: The role of fine sediment in managing catchment flood risk management whilst highlighting the vulnerability to government decisions in order to secure and maintain the funding they desire to protect themselves. Execution of future flood management plans require sensitivity and a responsibility to communities affected by hydrological processes and subsequent political and economic consequence (Emery and Hannah 2014).
Successful NFM also requires stakeholder engagement between key groups such as: farmers, rivers trusts, Environment Agency, Local Authorities, Water Companies, consultants and community groups. Stakeholder engagement though vital to NFM is often impeded by fragmentation between agencies who are without a platform to knowledge transfer. In addition, no agency has been identified as responsible for guidance of funding NFM projects causing difficulties in the planning, design and implementing processes. The Environment Agency has created a seven-step framework to plan and deliver NFM which includes data collection, management and monitoring to determine the scheme’s success (Environment Agency, 2017). These institutional barriers are just as important to overcome as community engagement if NFM is to become a sustainable flood defence option. The emotional strain on citizens experiencing flood events is often overlooked. The acceptance of flood waters in the home combined with a lengthy recovery process of repairs, cleaning, insurance claims can cause intense stress to residents (Walker & Burningham, 2011), particularly vulnerable communities such as the elderly (Tapsell et al,1999).
With increasing challenges to catchment managers from climate change, land cover alternations and political uncertainty it is imperative that flood risk strategies are sustainably managed. This has caused a shift in governance from flood extents to those citizens vulnerable to flood risk and questions over responsibility. Changes in the thought process from floods being considered an external threat into a human activity that can be governed (Butler & Pidgeon, 2011) have led to perceived risk to society being integral to future success of flood management policy (Brown & Damery, 2002).
50 Chapter Two: The role of fine sediment in managing catchment flood risk
For flood risk management to be truly successful a clear structure of responsibility is required to maintain awareness and increase resilience to vulnerable flood communities.
2.11.1 Flood awareness
Public engagement is supported by FCRM policy as its strives to achieve a fully integrated sustainable agenda through public consultation, engagement and co-delivery which are essential to meeting integrated river basin planning objectives. Engaging with local residents provides the benefit of local knowledge which has become increasingly recognised (Brown & Damery, 2002). It is important to ascertain the extent of the public’s comprehension of their perceived flood risk and the information they are given. Where possible, technical jargon should be removed when educating the public on vulnerability (Brown & Damery, 2002).
For public engagement to be successful the public need a coherent voice from management that correlates with the technical assessments and is intelligible for them to make informed decisions on their vulnerability (Brown & Damery, 2002). Whitmarsh (2008) argues that the public do not automatically make the linkage between climate change and flood events. The shift to risk management is regularly justified on this contextual basis.
A popular method of engagement used by the Environment Agency is to empower citizens at risk of flooding to interact with them through online forums, and targeted awareness activities. These activities provide a sense of community, creating a support network. Successful examples of flood resilient communities include the Town’s of Bourton and Ryedale in Northern England where community led efforts have led to the planning, funding or building of structural flood defences (Nye et al, 2011).
Early efforts to engage public in flooding can be traced back to the 1980’s and 1990’s where the public were asked to review management schemes (Tunstall et al, 1994). There has been a marked increase in the uptake of public engagement regarding flooding. Issues such as managed realignment of
51 Chapter Two: The role of fine sediment in managing catchment flood risk coastal flood defences, flood warning awareness and the promotion of community resilience in the event of a flood.
Recent efforts have been made to incorporate social implications into flood risk maps and flood warning systems and the inclusion in principle planning projects such as catchment management plans (Nye et al, 2011). The transition from top down management to emphasis placed on the individual is supported by the transition from hard engineering responses of stopping the water to living with flood risk. The Environment Agency have begun to include public engagement in flood risk strategies, to raise awareness of likely risk and educate those in flood risk areas. This shift in public awareness prepares citizens expectations to live with flood risk, enabling the government to govern from a distance (Butler & Pidgeon, 2011).
2.11.2 Flood resilience
Recent messages to flood risk communities from the Government have been one of resilience (McEwen et al, 2017). The term resilience in this context is thought to refer to the time taken to return to normal or improved conditions after a disruptive event. The quicker the recovery time, the greater its resilience (McEwen et al, 2017). Miller et al (2010) suggest the term resilience is a concept associated with values, capacity, power, temporal processes of risk, vulnerability, response and recovery. Community resilience can be used to refer to local responses to emergencies that complement overarching policy objectives. Complementary working between local and government communities should improve resilience and the ability to adapt. Stark and Taylor (2014) argue that successful community resilience will enable local communities to assist governments in crisis response and recovery, not replace. To achieve successful community resilience, each community must be treated as unique, owing to each locations ability to deal with extreme hazards and is dependent on several factors including; economic, social, cultural, and demographic (Mcewen et al, 2017).
McEwen et al’s (2017) study into the use of flood memories to develop communication and increase communities capacity for resilience was
52 Chapter Two: The role of fine sediment in managing catchment flood risk conducted through interviews in the aftermath of the 2007 flood events. Flood memories provide an opportunity to include emotion and behavioural responses, often absent from decision making. The results indicate that implementing this technique as part of increasing community resilience is difficult in areas where flood memories are difficult to obtain (McEwen et al, 2017). The results have the potential to be used create a platform for stakeholder awareness, though, limited attempts made by local flood risk management groups to obtain lay knowledge (McEwen et al, 2017).
Community action groups are often cited as an example of improving local resilience. McEwen et al (2017) investigated the feasibility of creating new community groups in areas without recent flood experiences and reduced social capital. Though found to be possible, the absence of detailed flood knowledge at a local scale is a large barrier to successful resilience (Mcewen et al., 2017). For community action groups to become successful they need to encourage knowledge transfer and be flexible in the skills required to obtain the information. There also needs to be further acceptance from the wider flood risk management community of the importance of community knowledge and its benefits in assisting decision making (McEwen et al., 2017).
The return to hard engineered methods of flood defence shows a contradiction to current flood policy. Governments are compelled to react to flood events using methods that show immediate, local and quantitative improvements (Emery & Hannah, 2014) even if the actions could increase flood risk downstream. NFM and other sustainable measures are unable to withstand the pressures mounted by the public and catchment stakeholders, which can lead to loss of confidence in the transition to soft engineering solutions (Emery & Hannah, 2014).
The use of dredging to reduce flood risk is perceived as good practise by the farming community (Gray, 1996) and was welcomed as a response to flood risk in the Somerset Levels. Recent policy movements have isolated the farming community, portraying farmers, once stewards of the land as environmentally damaging and heavily subsidised (Emery & Hannah, 2014). In light of this, rural communities have frequently been ignored and
53 Chapter Two: The role of fine sediment in managing catchment flood risk marginalised in favour of protecting urban settlements from flood risk. Emery and Hannah (2014) argue that very little attention has been given to the resulting flooding that is likely to occur as a result of NFM installation. In light of this policies need to protect farming practises and involve rural communities in flood risk measures.
The extensive coverage of the Somerset Levels flooding demonstrates the power the media has to influence and shape flood management. Local and national press provides a platform for communication between individuals, action groups and politicians (Demeritt, 2014). The Flooding on the Levels Action Group (FLAG) are a successful example of community engagement petitioning the government for their flood risk needs. Community members united under the clear message “Stop the Flooding! Dredge the rivers!”, receiving considerable social media attention capitalising on sensitivities (Smith et al, 2014) which resulted in their desired outcome. Smith et al (2014) conducted a study on national and local newspaper coverage as well as stakeholder interviews to analyse the shift in policy towards dredging. Newspaper articles from 1994-2014 were collected using key word search criteria and categorised into three groups 1. Dredging was neither argued for or against, 2. Dredging was discussed negatively as a flood management method, 3. Dredging was discussed positivity as a flood management method. In total, 275 articles on dredging were identified, 53% positive towards dredging practises and 33% opposed. Smith et al (2014) identified dredging as a low priority topic to the media initially with 0 articles appearing in local papers between 1994-2009, even with the area being flooded in 2000. In the aftermath of the 2012 summer floods and 2013 winter floods 26 news articles appeared, 5% raising concerns over the practise and 81% strongly in favour. All of the articles contained reference to the Environment Agency being under pressure to act. Between 15th December 2013 – 31st January 2014 120 news articles were generated on the Somerset Level flooding. Of the 35 local articles published after 7th January 60% made explicit reference to dredging. 66 National press articles were also published on the floods, 68% of those questioning why dredging had not yet occurred and its potential merits. Only 15% flagged concern (Smith et al, 2014).
54 Chapter Two: The role of fine sediment in managing catchment flood risk
The portrayal of community resilience by the media is critical to its acceptance by the public. Flooding is portrayed by the media as a human story of natural disaster with the aftermath of flood events often debated in the media, providing a platform for stakeholders to communicate. Garde-Hansen et al (2017) explore the media’s representations on flooding and the role of the communities in enhancing resilience. Four areas were selected that had been affected in the 2007 floods to be interviewed on their flood memories. The results indicated the settlement with an established community and history of flooding was the most resilient, as it was the most prepared community than actively took ownership (Garde-Hansen et al, 2017). The most successful flood communication campaigns are often found on flood awareness in local areas, directly relating to one campaign. Here, the media can provide a coherent narrative.
In order to achieve sustainable resilient communities social, cultural, economic institutional and planning considerations need to be networked together to create a feasible framework at both the local and national level (Cutter et al 2010) (McEwen et al, 2017). This framework would support the transition of risk managements inclusion of citizen participation, not the transition into community led risk management (Stark & Taylor, 2014).
The successful NFM scheme installed in Pickering, North Yorkshire consulted with local stakeholders and members of the public to raise awareness of the scheme. A research collaboration between members of the public, stakeholder, academics and flood modellers was created for participatory engagement. The inclusion of stakeholders enabled a new flood model to be created which incorporated local knowledge, successfully raising awareness (Landstrom et al., 2011).
2.11.3 Flood responsibility
UK policy and agenda has included phrases such as “learning to live with water” indicative of shared community responsibility. This transition in viewpoint, follows the principle that central government authorities should have a
55 Chapter Two: The role of fine sediment in managing catchment flood risk subsidiary function, only interacting in tasks unable to be performed at a local level (Stark & Taylor, 2014).
To successfully manage flood hazards there needs to be integration between technical impacts a hazard poses and the subsequent social vulnerabilities. A clear structure of responsibility is required to successfully mitigate against flood hazards (Brown & Damery, 2002).
Flood management in England and Wales is conducted and financed by multiple organisations. The Department of (DEFRA) maintains overall responsibility for flood and coastal defence. It is responsible for informing policies and creating targets for flood mitigation. The Environment Agency is the principle operating authority for delivering flood risk policy in addition to drainage, maintenance and flood defences on main water bodies (Butler & Pidgeon, 2011). Local councils are responsible for maintaining flood defences on the water bodies not considered main channel within their jurisdictions (Brown & Damery, 2002; Donaldson, 2013) (Figure 2.5).
Figure 2.5 Policy table identifying responsibility for flood risk management adapted from Brown and Damery, 2002
56 Chapter Two: The role of fine sediment in managing catchment flood risk
During a flood event, the time taken to process an emergency response is often used as a benchmark of success. The interaction between organisations such as EA, local councils, emergency services and the military with the public and media to share information, coordinate and execute management responsibilities is vital (Brown & Damery, 2002).
Butler & Pidgeon (2011) conducted a total of 44 interviews with professional groups and flood victims to determine where perceived responsibility for flood risk stood. Citizens were found to act on communications about their specific responsibilities and felt the need to know and accept flood risk. Butler & Pidgeon (2011) also argue that responsibility may not be the correct term for current communication. They perceive flood risk to be a blame game where assumptions of contributing factors and accountability are often given without critique of progress (Beck, 2009).
The difficulty in identifying political responsibility is creating a framework that means some individuals are responsible for their individual choices and which individuals are given allegiance (Butler & Pidgeon, 2011). Flood risk is primarily assessed using economic factors, providing a quantifiable baseline. This technique however often fails to include the social associated problems. New policies have redistributed responsibilities to wider communities including public and private organisations, communities as well as individuals.
The Environment Agency’s approach to public engagement is to first engage with consultancy’s and other official partners, then involve a wider range of professionals such as the professional stakeholders and independent experts. The third stage of engagement with the public usually occurs during an appraisal stage (Cornell, 2006).
A consequence of highly publicised flood events is that policy can be quickly altered in response (Nye et al, 2011). The Easter 1998 floods provide a supportive case study. Following the devastating impact, the flooding had on over 4200 properties (Environment Agency, 2018b) the government commissioned an independent report to make future flood recommendations, resulting in the formal establishment of the flooding overview role held by the Environment Agency. Further changes in flood governance began to occur due
57 Chapter Two: The role of fine sediment in managing catchment flood risk to the publication of the Pitt review 2008, commissioned after the 2007 flood. The 2010 flood and water management act provided local authorities a lead role in managing local flood risk, whilst the Environment Agency maintained a strategic overview. For public to take more responsibility it is vital that a clear distribution of knowledge and hierarchy of responsibility is present (Butler & Pidgeon, 2011).
The transition from flood defence to flood risk management is often attributed to developing scientific insight and economic factors and the inclusion of the social element is often overlooked. Without successful public engagement and clear framework the desire for empowered communities, acceptance of soft engineering measures and tolerance to living with water will fail (Nye et al, 2011). This is particularly difficult in communities where difficult management decisions have to be made regarding defences (Nye et al, 2011).
The social risk based approach considered how flood affect individuals and their interaction between technical systems such as flood warnings (Evans et al, 2004). Consideration is now incorporated into planning, prioritisation and delivery of flood management (Nye et al, 2011). The inclusion of social risk into management plans has highlighted the importance of better flood warnings and raising awareness (Johnson et al, 2006).
2.12 Chapter Summary
Changes in catchment hydrology and geomorphic processes such as climate and land use changes can impact the sources, detachment and delivery of fine sediment into river channels. Excess sediment entering river systems can increase flood risk by reducing channel capacity causing an increase in flood frequency. Understanding the potential sources and spatial/ temporal patterns of fine sediment dynamics can help to target areas of excess fine sediment and therefore improve both flood risk and water quality. Traditional engineering methods of flood defence have neglected to account for fine sediments sustainably, resulting in costly maintenance of their removal. New NFM methods have started to incorporate geomorphology into hydrological and engineering planning, though the effectiveness of these features has yet to be
58 Chapter Two: The role of fine sediment in managing catchment flood risk assessed. The potential limitations of installing NFM measures has been discussed and highlighted the importance of involving key stakeholders and the public into the decision-making processes to increase awareness and resilience and responsibility within catchment flood risk planning.
59 Chapter Three: Study site
3 Chapter Three Study Site
3.1 Chapter Scope
This chapter describes the physical, social and management attributes of the selected study site; the River Eye. Section 3.2 discusses the physical catchment characteristics of the River Eye. Section 3.3 outlines the current flood risk problem and management strategies which have been implemented to reduce sedimentation and flood risk downstream in Melton Mowbray.
3.2 The River Eye Catchment
The River Eye has a catchment size of 218.3 km2. Its headwaters are located in Bescaby, the Vale of Belvoir near the Lincolnshire/ Leicestershire border. The river flows southwest towards the town of Melton Mowbray which was established at the confluence of the River Eye, Scalfold Brook and Thorpe Brook, forming the River Wreake. The River Wreake is a primary tributary of the River Soar, from Melton Mowbray it travels 24km West to the confluence at Cossington, North of the City of Leicester (Figure 3.1).
Figure 3.1 The River Soar Catchment, highlighting a primary tributary the River Wreake and River Eye.
60 Chapter Three: Study site
Rural Leicestershire is predominately arable farming and pasture, generating a rapid runoff into the River Soar and its tributaries. The rural market town of Melton Mowbray in the catchment has a population of 26,100. As well as two major industrial factories (i.e. Pedigree and Mars) its economy is centred on rural food markets and tourism (Melton Borough Council, 2016).
Though flood risk the River Eye catchment is considered low with 30 properties upstream of Melton Mowbray at risk of a 1% flood (Environment Agency, 2010), the River Soar’s tributaries are part of the Environment Agency’s long term vision to provide a sustainable flood defence schemes which considers the natural function of the river channel, reducing soil runoff and improving habitats within the watershed.
Upstream of Melton Mowbray, The River Eye has a catchment size of 218.3km2 (Figure 3.2), consisting of nine sub-catchments. The catchment is extensively low lying with a topographical range of 200m (Figure 3.3). The steepest slopes are located at the south of the catchment, delivering run-off into the Burton Brook tributary (Figure 3.2 Figure 3.3). The Burton Brook and Whissendine Brook have been identified by Natural England as two tributaries which contribute large volumes of fine sediment into the catchment.
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Figure 3.2 River Eye Catchment Contributing areas in Km2.
62 Chapter Three: Study site
Figure 3.3 2m resolution topographic map of the River Eye catchment using LiDAR data with hill shading applied.
63 Chapter Three: Study site
3.2.1 Geology
The geology of the River Eye catchment is predominately the Lias group formation which is comprised of limestone, mudstone, siltstone and sandstone (BGS, 2015) (Figure 3.4). These sedimentary rocks were formed in shallow seas 172 to 204 million years ago in the Jurassic and Triassic periods, covering an area of 1297 km2 throughout Lincolnshire, Northamptonshire and Leicestershire (Cranfield University, 2017). Within the parent group much of the geology is Blue Lias formation, a mudstone group. Smaller areas such as the area above Melton Mowbray are formed of Charmouth Mudstone Formation, a sedimentary rock formed 183- 197 million years ago during the Jurassic period (BGS,2015).
Figure 3.4 Geology of River Eye catchment. Data obtained from BGS, 2015.
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3.2.2 Soil Properties
Soil in the River Wreake catchment consists primarily of two series: Ragdale and Hanslope (Land Research Associates Ltd, 2005) with areas of river alluvium in the floodplain of the River Eye. The Ragdale series is a common soil in Leicestershire which was first defined in the Melton Mowbray area (Thomasson, 1971) (Figure 3.5). The parent material is comprised of dense grey clay or silty clay that is mixed with Jurassic limestone, flint, bunter pebbles to form the matrix. The Ragdale series upper subsoil is heavily mottled and due to its low calcium carbonate composition, it is slowly permeable below the plough layer, resulting in severe seasonal waterlogging (Thomasson, 1971). Cultivation on waterlogged clay soils can cause loss in soil structure and increase in surface runoff. Spring cultivations are particularly hazardous for this reason (Cranfield University, 2017). The Hanslope series has a marginally improved drainage capacity but there is a very small difference between the two soil types. Some soils present on the slopes in the catchment have calcareous topsoil’s providing a stronger and more stable substrate (Land Research Associates Ltd, 2005). These geological characteristics of the catchment make it susceptible to groundwater flooding (Environment Agency, 1998).
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Figure 3.5 1km resolution soil series map of the River Eye Catchment 3.2.3 Land Cover
Land use is dominated by agriculture (69%), the soil is favourable to arable farming and provides good fattening pasture (Figure 3.6). As well as many small to medium size farms there are three major agricultural estates within the catchment that own 70% of the agricultural land; Freeby, Stapleford and Buckminster.
Due to the area’s heavy soil texture autumn sown crops such as oilseed rape and winter wheat dominate the landscape. Animals are prone to poach the land if left to graze during late October- late April. Many fields are left fallow in winter months to aid soil recovery. There is evidence within the catchment of agricultural practises improving drainage through tilling and ploughing orientation, to enable spring crop cultivation. The presence of ridge and furrow
66 Chapter Three: Study site in the landscape are indicative of historic attempts to improve drainage through ploughing (Land Research Associates Ltd, 2005).
Small areas of historic woodland are preserved within the catchment, particularly on the Stapleford estate. The Eye Catchment has several smaller settlements situated at Brentingby, Whissendine and Scalford within the catchment in addition to the town of Melton Mowbray with a population of 25,000 (Environment Agency, 2010).
Figure 3.6 Land cover of River Eye at 25m resolution from CEH
The relatively homogenous geology and soil structure of the River Eye catchment increases the likelihood of water retention in the catchment. Loss
67 Chapter Three: Study site of soil structure through intensive cultivation near the headwaters can result in reduced soil capacity to retain water, increasing runoff. These factors can result in increased flood risk if the land is not correctly managed.
3.2.4 Site of Special Scientific Interest (SSSI)
Due to its Jurassic limestone geology the River Eye is an excellent example of a typical lowland chalk stream in Central and Southern England. Natural river features such as riffles, pools and meander bends provide an abundance of habitat for native flora and fauna. Rarer invertebrate species such as white clawed crayfish (Austropotamobius pallipes) and white-legged damselfly (Platycnemis pennipes) have been recorded in the catchment (Camelo et al, 2015). In order to preserve and protect the semi lowland river a 7.5km reach was designated a Site of Special Scientific Interest (SSSI). To maintain and preserve the area surrounding the River Eye, Natural England insist physical features are maintained as well as spawning habitats, bankside vegetation and water quality. To ensure habitat quality is preserved it is vital to manage the volume of fine sediment delivery into the River Wreake Catchment (Natural England, 2014).
3.3 River Eye Flood Risk Problem
Flooding in the town of Melton Mowbray has been observed since 1828, in floods on average occurring every six years (Entec, 2008). Historic out-of-bank flows of the River Eye have caused significant flooding in Melton Mowbray, particularly in 1875 and 1922 where reports of water levels through the town exceeded 3m. Flooding was also a considerable problem for Scalford Brook, who’s confluence with the River Eye forms the River Wreake. Significant flooding occurred upstream of Melton Mowbray in 1947, 1969 and 1975 (Environment Agency, 1998) (Figure 3.7).
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Figure 3.7 Historic record of flood events within the River Eye Catchment 1852-1975.
In 1990, the Scalford brook flood alleviation scheme was sanctioned to reduce the volume of water entering the River Wreake at its confluence with the River Eye. Scalford Dam was erected to the North of Melton Mowbray, creating three stretches of open water; a large central lake upstream of the dam, a smaller upstream lake above a weir and a downstream lake behind the dam. The dam has increased water levels upstream by 2.5m and in doing so, created an ecologically diverse wetland reserve within 140 acre parkland (Melton Borough Council, 2015).
Recent floods in the town of Melton Mowbray include 1998, 1999 and 2001.The Easter floods of 1998 occurred on 10th April causing widespread flooding throughout the River Eye and Wreake catchments. The rain gauge at Whissendine recorded 56mm of rainfall in 24 hours resulting in a 1-in-4 year event. Though this volume of water was not exceptional, antecedent conditions and already saturated soils resulted in a 1-in-100 year flood event (Environment Agency, 1998). Upstream of Melton Mowbray, the River Eye rose rapidly, filling upstream storage, within the SSSI reach, over spilling onto agricultural floodplains. As a result, water in Thorpe Brook and Scalford Brook
69 Chapter Three: Study site backed-up and caused bank overtopping. Floodwater in the town exceeded 1m and was greatly exacerbated at the River Eye/ Wreake confluence due to a blockage at the railway bridge (Figure 3.8). 164 properties were affected during the flood event as well as public facilities such as the leisure centre, library and Melton Mowbray park and industry (the Pedigree foods factory). Downstream of Melton Mowbray, Frisby on-the-Wreake, Ratcliffe on- the- Wreake and Ashforby had less extensive damage to property which is thought to be a result of previous dredging of the channel and the absence of blockages (Environment Agency, 1998). Flood warning systems were not installed in the town, the nearest was 10 miles downstream at Syston.
Figure 3.8 Inundation of Melton Mowbray in 1998. Photographs obtained from Environment Agency
3.3.1 Melton Mowbray Flood Alleviation Scheme
Previous flood defence schemes within the River Eye and Wreake catchments have included tree clearance (1970’s), channel dredging and offline storage areas (1980’s) (Environment Agency, 2003). In the aftermath of the 1998 flood, which inundation <2000 hectares of the Midlands (Williams & Archer, 2002) the Environment Agency devised an updated flood management plan; the Melton Mowbray Flood Alleviation Scheme in collaboration with DEFRA, Melton Mowbray Council and private funding. Initial consultations were conducted in collaboration with government agencies, landowners, utility companies, wildlife groups and members of the public to assess the feasibility of an alleviation scheme. The flood risk assessment identified 400 residential, commercial and industrial properties that would benefit from upstream flood defences. The collaborative approach designed a scheme which would also
70 Chapter Three: Study site benefit water quality, pollution, erosion and siltation. A two-phase construction scheme was approved by Melton Borough Council in 2002 (Environment Agency, 2003) (Figure 3.9).
Figure 3.9 Location of the flood defences installed during the construction of the Melton Mowbray Flood Alleviation Scheme
Phase one included the installation of two online silt traps at Ham Bridge and Burton Brook. This involved the artificial widening and deepening of the channel to encourage fine sediment deposition upstream of Melton Mowbray and the SSSI. The silt trap dimensions at either location were not specifically designed in advance of construction. Aerial imagery from 2011 (Google Earth, 2018) shows the established silt traps and a ground survey provided an indication of the surface area (Ham Bridge 1180m2 Burton Brook 1537m2) (Figure 3.10).
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Figure 3.10 a) Ham Bridge Silt trap located on the main River Eye. b) Burton Brook Silt trap located on the Burton Brook tributary. c) Ham Bridge aerial image. d) Burton Brook aerial image. The blue lines indicate direction of flow. Imagery taken from Google Earth. As the water enters the silt trap, the energy is dissipated over a larger area, reducing the velocity. This process results in a reduction of fine sediment being transported in the suspended load and depositing within the silt trap. Willow and reed beds were established at Ham Bridge to provide a second method of sediment deposition (Environment Agency, 2003). Reducing the volume of fine sediment entering downstream reaches has multiple benefits. Firstly, it reduces fine sediment transport downstream and therefore naturally maintains channel capacity. In addition, the absence of silt in the channel improves water quality and habitat diversity in the SSSI reach of the River Eye. This was the first time in the UK green engineering techniques had been installed to control flooding (Environment Agency, 2003). Gabions were installed at both Ham Bridge and Burton Brook to maintain bank stability and reduce erosion.
During the second phase of the project 13 000m3 of material was removed and reused to construct an online storage reservoir at Brentingby, 2km upstream of Melton Mowbray (Figure 3.9). Brentingby dam is 650m in length and designed to retain 3.7 million cubic meters of water to protect against up to 1 in 100 year floods (Environment Agency, 2003) (Figure 3.11). It has three independently operated sluice gates. Gabions were installed to protect the bank from scour, limit upstream and downstream erosion and subsequent geomorphological impact. The Leicester to Peterborough railway line was an important consideration when designing the dam. The railway bridge nearest
72 Chapter Three: Study site to Brentingby was reinforced to protect against erosion and three culverts were installed upstream to direct water away from the tracks.
Figure 3.11 Brentingby Dam, installed in 2003 – personal photograph from June 2015
Although the morphological impacts of Brentingby Dam have not been investigated, river channel cross sections upstream and downstream have been recorded for use in the study (see section 4.3) provide an insight into current longitudinal morphology (Figure 3.12).
Width (m) 0 2 4 6 8 10 12 0
0.2
0.4
0.6
Depth(m) 0.8
1
1.2
Upstream Downstream
Figure 3.12 Channel cross sections up (depicted in blue) and downstream (depicted in orange) of Brentingby Dam The upstream cross section is shown to be wider and shallower than the channel downstream of Brentingby Dam. These profiles reflect the literature discussed in section 2.8.1 where upstream areas are prone to in-filling and deposition due to slowing of water (Kondolf, 1997). Whereas, downstream reaches are deeper as a result of bed and bank erosion due to dissipation of energy (Pinter & Heine, 2005). Without cross section data existing before the
73 Chapter Three: Study site construction of the dam, it is difficult to determine the full morphological impact the installation has had, but current results indicate Brentingby Dam has an influence on sediment transport which may impact the relationship between specific sediment yield and catchment contributing area.
In 2014, as part of a capital scheme for the River Eye, Natural England have incorporated flood management strategies into their current management plans for farmers (Natural England, 2014). The three aims of the project are: i) reduce and manage soil erosion and loss, ii) reduce the volume of sediments and nutrients entering the river system and iii) improve field drainage. These aims suggest a sediment transport in the catchment is an ongoing concern for both farmers and managing authorities.
3.3.2 Flood defence maintenance
Since the installation of flood alleviation scheme, the town Melton Mowbray has not experienced any out of channel flows. The dam has been effective at reducing the volume of water flowing through the town and at the confluence of the River Wreake during high flow events. During high flow events the three independent penstocks reduce the volume of water following into the centre of Melton Mowbray, storing the excess water upstream within the flood storage reservoir. This can be safely released by lifting the penstocks once water levels begin to recede (Environment Agency, 2003). Success at reducing fine sediment within the catchment to maintain channel capacity and improve water quality through the installation of silt traps has yet to be determined. In fact, the 2016 dredging of Egerton Park to remove fine sediment deposits from the channel to maintain channel capacity suggests either the silt traps are not efficient at reducing downstream sedimentation, or there are further sources of fine sediment entering the channel downstream of these alleviation measures (personal communication with Environment Agency Asset Performance Advisor, Kevin Coleman). Additional reconnaissance studies in Melton Mowbray 2015 indicated a high volume of suspended fine sediments present in the River Eye (Figure 3.13).
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Figure 3.13 Melton Mowbray Park 2015, shows the river laden with fine sediments after a heavy rainfall event, downstream of the Melton Mowbray Flood Alleviation Scheme. For natural flood management measures to remain effective at reducing flood risk they must remain at their optimal design specification. Furthermore, assessing the effectiveness of the installed NFM is vital to determine their success and future use as a viable flood defence. Minimal analysis was undertaken post installation of the silt traps. Twice year representatives from the Environment Agency would visit the sites and use a pole to determine the depth (personal communication with Environment Agency Asset Performance Advisor, Kevin Coleman). In 2011, the silt trap at Ham Bridge was considered “full” and the silt trap was dredged. The process cost over £100 000, including compensation to the neighbouring land owners to return the silt back onto their land. Specific dimensions for the depth were not given, and no record of deposition rate has been kept. Therefore, continual monitoring of the silt trap would be highly valuable to catchment managers planning to install similar NFM measures.
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3.4 Chapter Summary
This chapter has described the River Eye’s viability as a suitable study site to determine the thesis aim; to investigate the influence of fine sediment flood risk. The River Eye catchment has been shown to have a flood rich history resulting from physical characteristics such as geology, soil and land cover. The predominately agricultural land established on dense clay soils has led to poor soil infiltration and consequently surface water runoff. Flooding downstream in the town of Melton Mowbray prompted a response from catchment managers to reduce flood risk, identifying excess fine sediment as a contributor to flood risk. The installation of silt traps to reduce fine sediment volume downstream provides a unique opportunity to evaluate the success of natural flood management measures in an established catchment.
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4 Chapter Four Methodology
4.1 Chapter Scope
This chapter will explore the modelling, field, laboratory and social methods used to answer the objectives set in chapter one. The methods used enable sediment transport within the River Eye to be studied at a range of spatial scales to determine the influence of fine sediment on catchment, sub- catchment and reach scale flood risk.
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Figure 4.1 Methodology diagram outlining the methodologies in chapter 4 are discussed in results chapters.
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4.2 Hydrological connectivity and erosion risk modelling
In order to identify potential sources of fine sediment (objective one) and interpret the River Eye catchment’s spatial sediment transfer (objective two) the hydrological connectivity must be understood (see section 2.5.1).
By using a risk based model that has been developed to assess the risk of surface and shallow sub-surface hydrological connectivity, potential erosion risk can be mapped at a catchment scale. SCIMAP was used to model the impacts of land use changes on salmon in the River Eden catchment, UK. The study successfully identified locations where salmon spawning sites would be most vulnerable to increases in fine sediment loading and the associated pollutants from arable fields (Reaney et al., 2011).
SCIMAP is an example of an environmental model which assess relative risk of diffuse fine sediment in catchments within a probabilistic framework. The model uses hydrological delivery mechanisms to connect the sources of fine sediment to the channel under the assumption that catchments’ have unique flow paths which accumulate and transport contaminants from sources to water bodies, where they may become pollutants (Lane, et al, 2006). SCIMAP is based on the probability of a unit of land producing a risk and then of that risk reaching the drainage network, indicating its connectivity. It is therefore an effective tool to locate the potential sources and pathways of fine sediment within a catchment for targeted management, which is particularly beneficial where resources are limited. SCIMAP has been successfully used to map hydrological connectivity in rural catchments (Lane et al, 2009; Perks et al, 2017; Porter et al, 2017; Reaney et al, 2011; Shore et al., 2013) and therefore was selected to identify spatial sediment connectivity for the River Eye through the network index and erosion risk outputs.
By comparing SCIMAP outputs to field data collected provides a greater level of understanding to sediment processes within the River Eye. This combined approach was successfully demonstrated by Perks et al, (2017) who found the hybrid approach increased the rigour of analysis and positively assist decision making for targeting fine sediment source areas. In this study the results of the
79 Chapter Four: Methodology field and modelling data will be used to discuss fine sediment connectivity within the catchment, achieving objects one and two and enable recommendations to catchment managers in chapter 8 (objective five).
4.2.1 SCIMAP Model
The first stage in the SCIMAP framework is to identify the risk of contaminants (fine sediment) being generated and exported at any given point in the landscape (Heathwaite et al, 2005). To calculate this each point within the catchment is assigned a risk value based on topographic controls such as slope and upslope contributing area. The initial calculation of erosion risk is then combined with a land cover risk This value is combined with a risk weighting for each land cover type to generate an overall risk weighting. Each land cover type has a default risk weighting scaled between 0-1 parameterised by expert judgement of SCIMAP developers (Lane et al., 2006) (Table 4.1). The weightings concentrate of the risk of soil erosion and fine sediment generation.
Table 4.1 Land Cover weightings determined by Lane et al (2006)
Land Cover Category Risk Weighting Broadleaf Woodland 1 0.05 Coniferous Woodland 2 0.05 Arable and Horticulture 3 1 Improved grassland 4 0.3 Rough grassland 5 0.15 Neutral grassland 6 0.15 Calcareous grassland 7 0.15 Acid grassland 8 0.15 Fen marsh and swamp 9 0.05 Heather 10 0.05 Heather grassland 11 0.05 Bog 12 0.05 Montane 13 0.05 Inland rock 14 0
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Freshwater 16 0 Urban 22 0.01 suburban 23 0.01
The determined risk weightings are then combined with the risk of there being enough potential energy to erode material and generate transport. SCIMAP assumes this from the upslope contributing areas at any point within the catchment and combined stream power (calculated by the upstream contributing area) and topography to estimate the potential energy available to
g transport fine sediment (equation 4.1). Where Pi is the risk generation
h parameter, Pi is the risk of there being sufficient energy to erode the material
e and Pi is the risk of the material being susceptible to erosion. For instance, if the material is highly erodible but the is insufficient forcing, the risk generation parameter will be lowered. Similarly, if the material is subjected to extensive external pressure to erode but its physical properties are highly resistant, the risk parameter will be low. To obtain a high risk generation parameter result, the physical properties of the material must be susceptible to erosion and those processes which cause erosion must be present.
g h e Pi = Pi . Pi Equation 4.1
The second stage of SCIMAP is determining the ability of the risk within the catchment to connect to the channel network. The risk of fine sediment delivery is based upon the topography and hydrological connectivity of flow paths. The degree of connectivity between points will determine whether the risk is transported from its source to the channel or become disconnected within the catchment (Reaney et al, 2011). Flow paths are calculated using the deterministic flow routing algorithm (Wilson et al, 2008), which uses the nearest neighbour approach to determine the relationship between the central cell and its eight neighbouring cells, moving from the steepest gradient into the next cell. SCIMAP calculates the topographic wetness index (Equation 4.2) to measure the tendency to saturation and overland flow. Where K is the
81 Chapter Four: Methodology topographic wetness index, β is the topographic slope and a is the rainfall weighed upslope contributing area.
K = ln (a/ tanβ) Equation 4.2
Not all areas of saturated land within the catchment will connect or deliver fine sediment to the channel, and the connectivity of many areas to water channels is dependant on the connection of critical cells along the flow path. SCIMAP determines that for a point to export risk through hydrological connectivity, every other point along the flow path must be capable of transporting that risk. To account for on-slope deposition, SCIMAP uses a modified topographic index, the network index that is based upon the lowest value of the topographic index along a given flow path from the point of interest to the drainage network (Reaney et al ,2011). Assuming that topography is the primary driver of surface flow and all other runoff influencing factors are homogenous, (i.e. soil type and vegetation) the network index controls the delivery along the flow path. Points with low network index require more rainfall to connect the waterways and therefore connect less frequently than areas with high network index. SCIMAP then calculates the relative risk of connection at each point in relation to the rest of the catchment by using a probability density function on the network index, scales 0 (low connectivity probability) to 1 (high connection probability)(Figure 4.2).
The third stage of SCIMAP is to create an erosion risk weighting through the accumulation of connected fine sediment sources along flow paths and integrate them into the drainage network.
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Figure 4.2 SCIMAP Model framework showing inputs(blue) and outputs (black) adapted from www.SCIMAP.com 4.2.2 Model inputs
Three physical datasets are required to run SCIMAP: topography, rainfall and land cover (Figure 4.3). The resolution of the model relies on the resolution of the raw datasets. The finest resolution data with complete coverage of the catchment (5m) was selected (Table 4.2).
Table 4.2 Description of inputs required to run SCIMAP
Input Data Resolution Data Digital Terrain Model 5m 5m NEXTMAP DTM Digital Surface Model 5m 5m NEXTMAP DSM Rainfall 1km BADC annual average rainfall data 1971-2000.
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Land Cover 25m Centre of Ecology and Hydrology 2007 Land Cover Map of the UK
Figure 4.3 Spatial inputs required to run SCIMAP at 5m resolution
Two topography layers were downloaded at 5m resolution; a Digital Terrain Model (DTM) and a Digital Surface Model (DSM). Previous studies have found 5m resolution successful for identifying risk areas (Porter et al, 2017; Shore et al., 2013). A DTM is traditionally used in SCIMAP modelling, simulates bare earth that is absent of land form features. Though it represents topographic changes within the catchment, the absence of features such as hedges, walls, roads buildings may overpredict hydrological connectivity as no barriers are represented. The inclusion of the DSM is a novel approach to using SCIMAP to determine if the model can simulate connectivity and erosion risk in a landscape which includes natural and built features on the Earth’s surface. SCIMAP’s connectivity mapping was used by Shore et al (2013) to predict surface connectivity in agricultural catchments that included representation of surface ditches and difference spatial scales for phosphorus management. The study found SCIMAP modelled surfaced connectivity at a sub-catchment scale in accordance to observations, despite variability in soil type (Shore et al., 2013a). It was also found to work on the field scale, identifying fields that
84 Chapter Four: Methodology were most and least connected which is important for phosphorus management. Porter et al (2017) used SCIMAP which is optimised for diffuse fine sediment (Reaney et al., 2011) and nutrient pollution (Milledge et al, 2012) and applied it to faecal indictor organisms (FIO) to trace an alternative pollutant in agricultural land. The model was performed on two catchments and found to process reasonable results for the River Yealm, Devon but poor outputs for the River Wyre, Yorkshire.
An attempt was made to run SCIMAP at a greater spatial resolution using 1m and 2m resolution LiDAR data, downloaded from the Environment Agency. The LiDAR extents did not sufficiently cover the catchment extent (Figure 4.4). The LiDAR data was then stamped into the 5m DTM and together resampled to 2m resolution. The grid was added to the input data and ran in SAGA. Though visually the new DTM appeared to successfully join, SCIMAP failed to generate an output, due to grid-misalignment and processing capacity. A further attempt was made to run SCIMAP at a 2m resolution for two sub- catchments (Burton Brook and Somerby Brook), but the joins in topography caused connectivity and erosion risk to fail. Though a 5m DTM has been successfully used in previous studies to identify connectivity and erosion risk (Milledge et al., 2012; Perks et al., 2017, Reaney et al., 2011) a 2m DTM would have provided a higher resolution which unlike the 5m grid would require less smoothing. The potential consequence of using a coarser resolution terrain layer is an underprediction in connectivity and erosion risk as smaller slopes may not be visible. However, given the results are discussed at the sub- catchment scale, the 5m DTM and DSM is suitable for this study. Future studies, investigating within sub-catchment scales may benefit from using a stochastic subgrid parameterization methodology (Passalacqua et al, 2006).
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Figure 4.4 1m LiDAR extent of River Eye Catchment obtained from gov.uk open source. Rainfall data is required to calculate the potential runoff and connectivity of fine sediment within the catchment. As SCIMAP is focused on investigating spatial distribution of risk a long term integrated dataset of spatial rainfall distribution is required. The 1961-2000 based on the mean annual precipitation was used at 5km resolution was selected due to its availability and GIS compatible format.
To explore the impact future climate change predictions may have on hydrological connectivity and erosion risk, the annual average rainfall map was modified to simulate predicted drier summers and wetter winters (IPCC, 2007). Rainfall values were increased by 20% and 30% to simulate 2030 and 2050 winter predictions and decreased by 10% and 20% to simulate summer predictions (IPCC, 2007). These modelling scenarios provide an indication of future catchment connectivity in light of changing hydrological inputs.
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Land Cover information was obtained from the Centre for Ecology and Hydrology’s Land Cover Map 2007 at 25m resolution (Table 4.2). The dataset was resampled in ArcGIS to 5m resolution and then loaded into SAGA GIS to use the “reclass” function to produce a spatial layer of relative erosion risk (Table 4.1).
Land cover changes were also explored by changing the risk weighting automatically given to land cover types. The three classes (arable and horticulture, broadleaf woodland and improved grassland) which account for over 90% of the catchment land cover were modified to explore the relationship each has on hydrological connectivity and erosion risk. The three classes were given risk weightings of 0, 0.5 and 1 to determine the impact of connectivity and erosion risk. Alteration of default risk weighting also provide the opportunity to reflect a change in geology or soil type within the catchment that would otherwise be excluded by SCIMAP. Though land cover and slope provide a strong indication of potential connectivity and erosion risk, and the underlying geology and soil type often dictate the land cover options. Risk weightings had successfully been modified by Porter et al (2017) who ran Monte Carlo simulations of 25 000 variations in land cover risk weightings across 10 catchments to simulate which land cover classes were optimum for the catchments to detect connectivity of faecal indicator organisms (FIO). Porter et al, (2017) found that all land cover types excluding woodland in both catchments and improved grassland in the River Yealm were found to be uncertain after running multiple risk weighting scenarios. The aim of this study is to consider the potential sensitivity in assigned risk weightings of land cover when identifying the potential sources and spatial pathways of fine sediment. It is beyond the scope of the current study to identify the optimum risk weightings to use within SCIMAP.
In light of the newly available CEH 2015 land cover map, made available in summer 2017 an additional SCIMAP model was run using the new spatial extent of land cover for both DTM and DSM, using the default risk weightings. Catchment differences in land cover between 2007 and 2015 are observed in Table 4.3.
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Table 4.3 Spatial differences in 2007 and 2015 in % land cover of the River Eye catchment. Blue represents an increase in land cover and red a decrease.
Land Use 2007 2015 Percentage (%) (%) change (%) Broadleaf Woodland 2.79 3.00 0.21 Coniferous woodland 0.01 0.04 0.03 Arable and Horticulture 68.85 65.61 3.24 Improved Grassland 22.26 Rough Grassland 2.98 27.76 1.75 Natural Grassland 0.77 Heath and Bog 0.05 0.01 0.04 Inland Rock 0.07 0.06 0.01 Freshwater 0.07 0.15 0.08 Urban 0.32 0.39 0.07 Suburban 1.83 2.97 1.14
4.2.3 Model Simulations
The data was initially downloaded from the sources identified in Table 4.2 and uploaded and transformed into shapefiles. The files were loaded into ArcGIS where they were resampled to create three input layers all at 5m resolution. The terrain layers were used calculate hydrological parameters in ArcGIS such as flow direction, and flow accumulation within the River Eye catchment. The upstream contributing area was then calculated for the catchment and sub- catchments. The newly created raster layers were clipped to the catchment extent to ensure each layer contained equal grid cells and then converted to ASCII files, to ensure they were compatible with the SCIMAP model. Each layer was loaded into SAGA, a free GIS software package. Here, the land cover data was converted into a land cover risk map based on values previously created by Lane et al (2011) (Table 4.1). All of the model runs are displayed in Figure 4.5 and the outputs provide an insight into the sensitivity of SCIMAP to independent users.
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Figure 4.5 SCIMAP model runs used to explore catchment connectivity and erosion risk. The calculated connectivity (network index) and erosion risk maps were exported as ASCII files from SAGA and loaded into ArcGIS to display the spatial extents. The ASCII files were also loaded into Microsoft Excel where each 5m cell was represented by a connectivity or erosion risk value between 0-1. The results were used to create histograms which allow the comparison of connectivity and erosion risk. Initial analysis was conducted on catchment DTM and DSM, followed by sub-catchment analysis to determine the potential sources and spatial patterns of fine sediment. Further analysis was then conducted to explore the sensitivity of SCIMAP and the catchment to changes in rainfall and land cover alterations. The decision not to compute the channel risk using SCIMAP was taken as the study was focused on identifying the potential sources of fine sediment at a sub-catchment scale of the River Eye
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(Objective One), not within the channel. The identification of potential fine sediment at the source can prohibit connectivity and prevent sediment entering the channel, causing increased flood risk or a reduction in water quality.
4.2.4 Limitations
There is uncertainty associated to any model prediction (Bracken & Croke, 2007) and SCIMAP is no exception. The SCIMAP framework has several potential limitations. SCIMAP cannot simulate non-topographic controls on connectivity that are not represented within the topography layer, such as absent structure features in DTM’s. Shore et al’s (2013) study found that though SCIMAP was able to map the ditches in the land, the future inclusion of subsurface drainage features would improve the model accuracy. The inclusion of theses and additional information on ditches would enable a more accurate prediction of critical source areas. The impacts of these features on hydrological connectivity is a key question arising from the framework. This study seeks a novel approach to overcome the DTM limitations by including structural landscape features through the use of DSM topography layer.
SCIMAP assumes that for material to reach a water channel every cell between the source and outlet is capable of transporting overland flow (Reaney et al., 2011). The model then uses this assumption for the topographic wetness index to describe the propensity of a given area to generate overland flow, assuming that the higher the network index, the greater the propensity for overland flow generation. SCIMAP assumes that areas in the top 5% of the network index are constantly connected and those in the bottom 5% are never connected, those in between have a linear relationship. This may cause problems when attempting to map connectivity (network index) into connection cycles within SCIMAP.
SCIMAP does not include groundwater input or storage into the catchment. In areas with low lying topography, water that infiltrates the topsoil will flow through the zone of saturation to the main stream (Morrice et al, 1997). Though this is a potential problem when investigating diffuse pollution sources as
90 Chapter Four: Methodology groundwater may dilute pollutant levels it is not a concern of this study as fine sediment is not transferred via groundwater systems. However, SCIMAP’s inability to differentiate between areas of geology or soil type may significantly alter connectivity dynamics (Ward & Robinson, 2000). In areas with sandy soils, which are known to have large pore spaces, overland flow may be reduced as infiltration increases. Similarly, alterations in sediment particle sizes are important when calculating the erodibility of soil and the energy required to transport the sediment thus affecting connectivity. SCIMAP attempts to map connectivity pathways based on data available, though the simplicity of risk loading into risk concentration has been identified as a potential area of concern within the framework (Reaney et al., 2011).
Though attempts could have been made to incorporate soil risk into the land cover layer to create a combined risk layer it was not deemed necessary for this study as soil within the catchment is relatively homogenous. In addition, the dense Clay Ragdale soils reduce the risk of over predicting overland flow as infiltration is minimal (see section 3.2.2). Although the absence of representative field drains may cause an underestimation of sediment delivery to the channel.
SCIMAP is currently unable to include temporal variations due to land cover map representing one point in time. Therefore, SCIMAP is not able to include seasonal variation in agriculture or vegetation cover. However, the inclusion of running 2007 and 2015 land cover maps will provide an insight into how temporal land cover changes affect connectivity and erosion risk. The results of SCIMAP are reported in Chapter Five (section 5.2) and achieves objective one.
4.3 Instant suspended sediment storm sample collection
Suspended sediment samples were collected in Melton Mowbray park as part of a pilot study to refine the laboratory methodology and provide an insight into fine sediment transport downstream in the town of Melton Mowbray. The samples collected were collected during high flow events to determine whether
91 Chapter Four: Methodology a representative sample of fine sediment suspended in the flow. The sample of native sediment was used to refine the methodology for relative weights, organic matter content and particle size analysis. The location of Melton Mowbray park was selected due to the availability of flow data from the only Environment Agency gauge within the catchment and the bridge enabled collection of samples from the middle of the channel. Figure 4.6 shows the two high flow events where suspended sediment samples were collected are representative of high flow events within the catchment as similar water levels have been observed within a five-year period.
Figure 4.6 Daily average flow data for the gauging station situated at Melton Mowbray park. The two dashed lines represent the storm sample collections.
4.3.1 Sample collection
Suspended sediment samples were collected during two storm events in the winter of 2016; 8-9th February and 9th March from Melton Mowbray park bridge into the River Wreake (Figure 4.7). When the gauging station located in Melton Mowbray park indicated the water level of the River Wreake was forecast to exceed 2m in the town of Melton Mowbray, storm samples were taken on the rising and falling limb of both storm events (Table 4.4).
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Table 4.4 Storm samples collection time and water level
Storm Sample Time Water level (m) 8th February rising limb 14:40-14:53 1.53 8th February peak 16:00-16:05 2.04 9th February falling limb 09:19-09:25 1.50 9th March peak 14:27-14:33 2.01
Figure 4.7 Daily average water level recorded at Melton Mowbray park gauging station for 2016, with the grey lines highlighting the storm events when samples were taken.
Suspended sediment samples of 10L were collected using a bucket vertically inserted through the water column and removed. The method was successfully deployed by Hillier (2001) on the River Don, Aberdeenshire to collect representative samples for particulate composition of suspended sediment sample analysis. The samples were then decanted into 10L sealable containers and stored in the laboratory cold room for a minimum of 72 hours for the sediment to settle out from the water. The water was then siphoned off and the sediment samples were used for laboratory analysis (see section 4.5.)
To determine the robustness of the methodology each suspended sediment sample was sub-sampled in twice to determine if the sub-sample was representative of the whole sample. This provided a comparison of two results for both organic matter content and particle size, where, each sub-sample was
93 Chapter Four: Methodology measured 7 times using the mastersizer to determine the particle size distribution.
4.4 Time integrated mass suspended sediment collection
Time integrated mass suspended sediment samplers (TIMS) are an inexpensive method of collecting representative sample of fine suspended sediment which can be used for physical and chemical analysis. The deployment of multiple TIMS has been successful in calculating the relative suspended sediment flux of river catchments (Perks et al, 2014), identify sediment sources (Collins et al, 2010; Fox & Papanicolaou, 2008), physical and chemical property analysis (Hatfield & Maher, 2008; Phillips et al, 2000) and identifying areas of relative high suspended sediment yield, the results of which can be used by catchment managers to target areas of risk (Bolland et al, 2010; Perks et al., 2017).
TIMS are designed for the inlet tube to face into the flow, allowing suspended sediment to enter the inlet and travel into the larger pipe. The sudden increase in pipe area causes the velocity to decrease, encouraging the sedimentation of fine sediment into the sampler pipe. The water can continuously flow out of the outlet tube. The original streamlined TIMS design by Phillips et al, (2000) was shown to minimise disruption to the flow and be capable of suspended sediment mass retention between 31-71%. The design has been successfully used and modified for a range of river environments including lowland rivers (Collins et al., 2010; Phillips et al., 2000), upland rivers (Fox & Papanicolaou, 2007; Perks et al., 2014) the arctic (Mcdonald et al, 2010), and lakes (Hatfield & Maher, 2008).
A critical assessment of the TIMS was undertaken by Perks et al (2014), investigating the absolute and relative efficiency of the samplers. Absolute sampling efficiency refers to comparing the calculated sediment load from the TIMS to secondary sediment data such as turbidity sensors, to determine whether the samplers are under or overpredicting absolute sediment load. Previously absolute efficiency has been calculated in in two upland catchments Yorkshire, UK over a two-year extensive monitoring period. The absolute
94 Chapter Four: Methodology efficient was calculated by comparing the estimated suspended sediment flux of the sampler to installed turbidity sensors which were used to calculate suspended sediment concentration. The results found the TIMS underpredicted sediment flux by 66.38-96.31% (Perks et al, 2014) which supports findings on the Gilwiskaw Brook (Phillips et al, 2000). Due to the absence of secondary suspended sediment data on the River Eye, the absolute efficiency of the samplers cannot be calculated, meaning the results cannot verify whether the TIMS installed in the catchment are under or over predicating the actual sediment load. Similarly, in the absence of discharge data the sediment yield is also unable to be calculated. However, the results are still able to determine the spatial and temporal pattern of suspended fine sediment relative to each location to determine which areas are likely to be responsible for fine sediment delivery.
Relative sampler efficiency refers to the difference in suspended sediment collected by two TIMS installed in the same spatial location. The decision was made to explore the relative efficiency of TIMS samplers by installing two TIMS adjacent in the river channel at six locations to provide a comprehensive insight into the effectiveness of TIMS as a method of determining suspended sediment transport and its physical and chemical properties. Perks et al (2014) undertook this method at four locations and found that at all locations the organic matter content and particle size analysis results for adjacent TIMS were statistically similar, suggesting the TIMS are efficient relative to each other, allowing for cross catchment comparisons of suspended sediment load (Perks et al, 2014). Measuring the relative efficiency is a low-cost method of identifying spatial and temporal fine sediment transport which can be deployed in any catchment as is it not reliant on secondary data.
4.4.1 Sampler design
The TIMS were designed using the same specification as Phillips et al (2000) and Fox & Papanicolaou (2007) following successful deployment and representative sample collection. The inlet tube was designed to remain at 4mm, in keeping with the original design due to the similarities in the geology and physical catchment characteristics between the River Eye and Gilwiskaw
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Brook, both lowland river catchments in Leicestershire (Phillips et al., 2000). Laboratory experiments conducted by Phillips et al (2000) found a strong correlation (r2 0.99) between ambient flow velocity and inlet velocity for the inlet design. Experiments measuring the ambient flows and inlet velocities determined the sampler was not isokinetic, suggesting the TIMS may oversample coarser sediments. However, as Phillips et al (2000) designed the sampler for lowland streams where silt is likely to consist of silt and clay sized material the effect on the particle size distribution is reduced.
Consideration was made to decrease the expansion chamber to from 98mm to 90mm and increase the sample inlet size from 4mm to 8mm after Perks et al (2014) identified these adaptations can produce necessary conditions for sedimentation to occur. A smaller diameter chamber of 86mm instead of 98mm was used due to materials availability. The internal cross-sectional area of the TIMS used by Phillips et al (2000) was 7543 mm2 and was calculated to reduce flow velocities within the chamber by a factor of 600. Owing to a smaller internal cross-sectional area of 5808 mm2 there is a 23% reduction in chamber size, resulting in a decrease of flow velocities within this study to be by a factor of 462. The reduction in the chamber size may result in a reduction of sedimentation in finer particles and sediment retention to vary from 31-71%. (Phillips et al, 2000).
During the laboratory study, Phillips et al (2000) substituted the TIMS for a Perspex tube (71mm diameter, 1.2m length) and surmised it is highly unlikely that a small reduction in cylinder diameter would alter the fundamental flow structure and mixing dynamics, but there may be some contracts in the scale of the flow structure. Further studies conducted by McDonald et al (2010) deployed a highly modified TIMS sampler into Artic steams. The deployed sampler had an inlet diameter of 2mm, length of chamber 228mm and diameter 63.5mm and was suspended from the bank due to a frozen channel bed. The study results found the sampler had a bias to coarser sediment where 40% of ambient sediment samples consisted of sands whereas the TIMS sample consisted of 80%.
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Figure 4.8 TIMS sampler design used at all locations within the River Eye. PVC downpipe was used to construct the main body of the TIMS. The material is inert, and robust to withstand high flows. The pipes were cut into 1m lengths, 86mm diameter and a 90mm funnel attached with sealant to the upstream end (Figure 4.8). A 4mm diameter tube was placed inside the funnel and sealed using watertight silicone sealant to create the inlet. A 4mm pipe was also inserted through a PVC cap and sealed to create the sampler outlet. Two reinforced steel bars were attached to the tube using cable ties and jubilee clips. The addition of two bricks were included in the modified design to help maintain stability in high prolonged flows.
The samplers were filled with native water and submerged in the channel. The reinforced rods were hammered into the river bed in the centre of the channel at approximately 0.6 mean depth (see section 4.4.4 for limitations associated with this procedure). The streamline design was found to minimise flow intrusion (Fox & Papanicolaou, 2008). Upon entering the inlet, the waters velocity is reduced, Phillips et al (2000) to encourage sedimentation of particles in the chamber. Due to its robust design the sampler can endure all flow conditions within the catchment for the entire sampling period, providing a continuous record of flux that incorporates all flow events (Walling et al, 2008). The range of velocities the sampler is subjected to would also influence the efficiency of the TIMS. McDonald et al’s (2010) study recorded ambient velocities during sampling of >1 ms-1 which is consistently higher than the
97 Chapter Four: Methodology velocities Phillips et al (2000) designed the samplers for in lowland, low order streams. Consistently higher flows result in an increased flow velocity through the TIMS chamber, reducing sedimentation in the sampler.
4.4.2 Site selection
To understand patterns of fine suspended sediment transport across the River Eye catchment to achieve objective two (see chapter 1.1), TIMS were installed near the confluences of tributaries and the main River Eye (Figure 4.9). Permission was granted to install 23 TIMS into the River Eye. However, due to unforeseen dredging in Melton Mowbray park by Melton Mowbray Council the two TIMS situated downstream were lost. In addition, the installed TIMS located in Freeby Brook was lost due to restricted access, resulting in 20 TIMS installed (Figure 4.9). The unavoidable loss of access to a substantial tributary such as the Freeby Brook means that the study cannot determine how much sediment is being delivered to the main channel relative to the other tributaries. However, TIMS have been installed upstream (site 7) and downstream (site 8) of the confluence and the mass of sediment collected in both samplers will provide an indication of sediment delivery and whether there is a large increase in mass between sites. The results of these key questions will be reflected in Chapter Six. The loss of TIMS at Melton Mowbray Park resulted in the loss of study area incorporating Melton Mowbray town, limiting it to upstream rural reaches. Although TIMS installed within the town could have provided an insight into suspended sediment on the River Wreake, the absence of TIMS on Scalford Brook and Thorpe Brook (the two tributaries which merge with the River Eye to form the River Wreake) would have made any conclusions speculative.
To assess the morphological impact of the existing flood defences to achieve object three (see chapter 1.1), additional samplers were installed upstream and downstream at Ham Bridge, Burton Brook and Brentingby Dam, depicted in yellow on Figure 4.9. At these locations two TIMS were installed adjacent, approximately 0.3m apart, to calculate the relative efficiency of the samplers. Due to restrictions in channel width Burton Brook samplers were installed 0.1m
98 Chapter Four: Methodology apart. In total of 20 TIMS devices being installed for a period of 21 months January 2016- October 2017.
Figure 4.9 Map of TIMS locations in the River Eye Catchment. TIMS in red indication installation of samplers for spatial and temporal patterns of fine sediment flux. TIMS in yellow indicate additional TIMS installed downstream of flood defences which are discussed in Chapter Six. Figure 4.9 shows the TIMS locations where sites 1-11 indicate the TIMS used to discover the spatial pattern of fine sediment. Upstream of the flood defences at site 8, 10 and 11 the sampler installed to the left of the channel was selected to be used in Chapter Five, as it was placed in the dominant flow path analysis to determine the catchment spatial and temporal fine sediment patterns. TIMS positions at each of these locations is shown in Figure 4.10.
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Figure 4.10 a) position of installed TIMS at Ham Bridge Silt Trap, b) position of installed TIMS at Burton Brook Silt Trap, c) position of installed TIMS at Brentingby Dam
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4.4.3 Sampler collection
Sample collections were conducted over two days over the monitoring period, with sites 1-8 collected on day 1 and sites 9-11 on day 2 (Table 4.5). Dates between TIMS collections varied, after collection 4 (Table 4.5) when the river became inaccessible due to period of prolonged high flows (Figure 4.11). During the study, the samplers were left insitu for longer periods of time than previous studies (Mcdonald et al., 2010; Perks, 2014; Phillips et al., 2000). Over collection periods sedimentation within the chamber will reduce the internal cross-sectional area of the sampler which may impact further sedimentation. However, during collection of the sampler the TIMS were never found to be full, the spread was even across the length of the chamber, therefore causing minimal effect on the flow through the TIMS. Furthermore, the samplers were all collected on each occasion within a 2 day period, meaning any effect of longer time periods is consistent across all installed TIMS.
Table 4.5 Collection dates of TIMS samplers
Day 1 Day 2 Sample days Start 27/01/16 28/01/16 Collection 1 01/06/16 02/06/16 126 Collection 2 06/07/16 07/07/16 35 Collection 3 10/08/16 12/08/16 35 Collection 4 30/10/16 31/10/16 38 Collection 5 01/03/17 02/03/17 131 Collection 6 05/05/17 06/05/17 66 Collection 7 08/08/17 09/08/17 95 Collection 8 06/10/17 07/10/17 59
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Figure 4.11 Water level at Melton Mowbray gauging station during the TIMS monitoring period. The grey dashed lines represent collections.
At each location the TIMS was lifted out of the water, ensuring that both the nose and the cap ends were blocked. The cap was removed, and the contents poured into a sealable 10L bucket. The tube was rinsed with water to ensure the whole sample was collected. The cap was then replaced and secured. The TIMS were returned to the same location in the centre of the channel and hammered into the bed until stable and at approximate 0.6 water depth. The sample was taken back to the laboratory and stored in the cold room for a minimum of 72 hours to settle.
During the 21-month period in which the TIMS were submerged in the water some maintenance was required. After sustained high flows, debris, such as branches and leaves were removed from the TIMS that had become caught on the poles and cable ties. During the summer months, algal growth in the inlet pipe was removed to maintain function, as were any macroinvertebrates inside the pipe. Though the TIMS chambers were always found with 8 litres of water and sediment, indicating a full capacity, during the summer season when water levels dropped in the tributaries there may have been occasions where the inlet was above the water level.
Channel cross sectional areas at each TIMS location were recorded during a morphological survey at each site. A traditional manual survey was conducted
102 Chapter Four: Methodology using a theodolite and survey pole to measure the bankfull channel cross section (Figure 4.12). The graph shows the tributaries within the catchment have a similar cross-sectional area, whereas the main channel fluctuates throughout the catchment. There is a general increase in cross-sectional area downstream in the River Eye, with the exception of site 9 which is situated within the SSSI. This location was the only site with exposed gravels and minimal fine sediment deposition observed due to its wide but shallow cross section. The sites recorded in the upper reaches (e.g. sites 2 and 4) were deeper and narrower than those located within the floodplain (e.g. sites 8 and 11), this is reflected in the topographic map (Figure 3.3) and Appendix 1.1. Water levels reaching bankfull are a regular occurrence within the catchment due to the morphology of the cross sectional areas.
8
7 ) 2 6
5
4
3
2
Cross Cross sectional area (m 1
0 0 2 4 6 8 10 12 Sites downstream
Figure 4.12 Cross sectional data collected from each sampling site from upstream to downstream. Tributaries are marked grey and the main channel, blue.
4.4.4 Sampler limitations
Though becoming an increasingly popular method of collecting representative suspended sediment samples, TIMS samplers are found to have some limitations:
1. Due to fluctuations in river stage over sampling intervals and the static TIMS the sampler cannot remain at 0.6 water depth. This can result in
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the TIMS being above the water level for unknown duration, particularly in the spring when winter levels recede. 2. Over prolonged periods whilst the TIMS is situated in the river channel, organic detritus can block the inlet tube, reducing the volume of water entering the inlet and thus the quantity of sediment captured (Mcdonald et al, 2010). 3. Previous studies which have deployed TIMS have found a sampling bias to coarser particles (Phillips et al, 2000). This may be a result of finer particulates remaining in suspension throughout the samplers’ chamber and exiting in the outlet. However, Smith & Owens, (2014) argue that in rivers where suspended load is primarily composed of silts and clays and fine sands the particles will travel in the suspended loads as flocculants, thus promoting settling in the sampler. 4. Absence of additional secondary data such as turbidity sensors or suspended sediment concentration instrumentation to calculate the absolute efficiency of the TIMS (Perks et al, 2014) and provide a benchmark for data comparison. 5. The mass of suspended sediment collected by the TIMS does not represent a precise composite sample, only an indicator of sediment flux at one specific point over the sampling period. To calculate a suspended sediment yield, the flux must be multiplied by channel cross sectional area and discharge at the time when the sediment sample was collected (Perks et al, 2014). 6. Suspended sediment concentration is not considered to be consistent throughout the channel cross section (Wass and Leeks, 1999).
4.5 Suspended sediment analysis
This section describes the laboratory and statistical analysis of the suspended sediment collected by the TIMS devices.
4.5.1 Relative weight
Samples were stored in the laboratory cold room for sediment to settle. The excess water was then removed using a siphon pump. Although the removal
104 Chapter Four: Methodology of the excess water may have removed some sediment still in suspension, previous studies using this technique have found the sediment lost accounted for 0.12% of the total sediment collected (Perks, 2013). A needle tipped syringe was used to remove the water in close proximity to the suspended sediment sample, increasing precision and reducing the associated errors of a siphon can inhibit close to the sediment sample. The samples were transferred to pre- weighed oven dishes and placed in the oven at 400C for 24 hours to ensure the water had evaporated and the sediment was dry. This oven temperature complements the temperature cited in similar studies (Mcdonald et al., 2010; Perks et al., 2014). However other TIMS samples have been subjected to freeze-drying (Ankers et al, 2003), suggesting the absence of a standardised method. The samples were then left to cool and weighed twice to four decimal places, ensuring accuracy in results, to determine the mass of sediment from each TIMS sampler.
The mass of dry sediment collected at each location was compared against all TIMS locations to determine which sites had the highest mass of sediment, indicating a high delivery rate. To overcome the temporal differences between collection dates (Table 4.5) the sediment load (g day-1) was calculated to standardise the data.
The mass of sediment each TIMS collects reflects the cumulative fine sediment flux for 12.56cm2 (inlet diameter) cross section of flow which enters the sampler through the inlet nozzle. Material must be scaled to represent that cross-sectional area during the monitoring period (equation 4.3):
rSSL = K · M · ScE Equation 4.3
Where relative suspended sediment load rSSL (g day-1) equals K = unit conversion factor M = total mass of sediment (g) ScE = scaling component (m2)
Like Perks (2014) a static scaling component of bank-full cross sectional area was used (equation 4.4):
ScE = CSA/ ID Equation 4.4
Where CSA = cross sectional area (m2) ID = inlet diameter (m2)
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The results shown in Chapter 5 and Chapter 6 will display sediment load (g day-1) values, which have been calculated with the scaling component. To account for the contributing area to each site the daily yield (g km-2 day-1) (Equation 4.5) will also be calculated to identify key fine sediment contributors within the catchment (Table 4.6). rSSY = rSSL · CCA Equation 4.5 rSSY = Relative suspended sediment yield (g km-2 day-1), rSSL = relative suspended sediment load (g day-1) and CCA = Catchment Contributing Area (km2).
Table 4.6 contributing area at each TIMS location.
Site Location of TIMS device Contributing Area (km2) 1 Whissendine brook 14.2 2 Eye main Stapleford farmland 76.3 3 Wymondham tributary 15.2 4 Stapleford Golf Course 92.0 5 Stapleford Woods 92.9 6 Eye main tributary 32.9 7 Eye Stapleford bridge 126.9 8 Ham bridge (below) 144.3 9 Eye at Burton Woods 150.9 10 Burton brook silt trap (above) 16.3 11 Above Brentingby dam 175.4
4.5.2 Organic matter content
The sediment was disaggregated and sieved at 2mm with care to ensure the process did not reduce the natural particle size by crushing sediment particles. The remaining sample was weighed and a 0.5g sub-sample was taken. Each sub-sample was treated with 20ml of 40% Hydrogen Peroxide to remove organic matter. This process was repeated to ensure the sample had fully digested the acid. The sample was then placed in the oven for 1 hour at 1050C to evaporate the acid and weighed once cooled. The reduction of mass between the pre-treated and post-treated subsample equated to the
106 Chapter Four: Methodology percentage of organic matter content present in the sample. The same method of organic matter removal was used by Phillips et al (2000) and Ankers et al (2003) during their analysis of suspended sediment samples collected by TIMS.
4.5.3 Particle size analysis
2ml of sodium hexametaphosphate was added to the sub-sample to encourage deflocculation and the sample was left covered for 24 hours. This method was previously applied to samples from TIMS collected by Smith & Owens, (2014).The sub-sample was placed in suspension within 700ml of purite water for particle size analysis using a Malvern Mastersizer. The same method has been successfully used to analysis particle size in fluvial sediments for both TIMS and fingerprinting studies (Ankers et al., 2003; Collins et al, 1998; Phillips et al., 2000; Poulenard et al., 2009; Walling et al, 2003).
The mastersizer passed a laser beam through the dispersed suspended sediment sample and measured the angular variation in intensity of the scattered light (Malvern, 2018) also known as laser diffraction. Large particles scatter the light at small angles whilst smaller particles scatter the light at larger angles, relative to the laser beam. The angle of scatter is then calculated to determine the size of the particle which created the scatter (Malvern, 2018).
A blank sample of 700ml of purite water initially ran through the mastersizer to create a baseline and ensure the system was clean of sediment. A pipette was used to draw up the suspended sediment solution and add it to the purite water. The sample was added until the obscuration level was between 10-15%. The sample was then run through the mastersizer a minimum of seven times or until five similar particle size distributions were created. This was determined in real time where the live calculations of the D16 D50 and D84 analysed by the mastersizer on the attached monitor. In the event where results appeared erratic, repeats using the sub-sample were run, this is most commonly due to the introduction of air into the system causing irregularities in the results (Malvern, 2018). The five results were then used to create an average particle size distribution curve. Between each sample, the mastersizer was cleaned
107 Chapter Four: Methodology with purite water and a blank sample was run to prevent cross contamination and thus ensure the scanning of a representative sample.
4.6 Hydrological monitoring
To successfully answer objective two (see chapter 1.1), hydrological monitoring of the River Eye was conducted to determine the influence of current flood defences on water level. As NFM is still in its relative infancy, monitoring of established features such as online silt traps have yet to be examined for their impact on local hydrology, both upstream and downstream. Similar channel changes monitored after dredging of a channel suggest water level can artificially increase upstream of the dredged reach due to a reduction in flow velocity as the water enters the widened and deepened section, causing a backing up effect (CIWEM, 2014). To determine whether this effect was occurring in the River Eye and propagate upstream, water level monitoring equipment was installed on the larger silt trap located at Ham Bridge.
Due to the absence of gauging stations in the River Eye catchment, water level monitoring required the installation of equipment. Pressure transducers developed by Van Walt instruments were used to record water level at specified time interval resolution (five minutes) at Ham Bridge silt trap.
Mini divers are a small autonomous datalogger, designed to record temperature and water pressure and store the data in its internal memory. The diver measures absolute pressure, meaning that the pressure sensor records water pressure and the pressure exerted on the water’s surface (Eijkelkamp: Soil and Water, 2016).
When a diver is submerged the built in pressure sensor measures water pressure. A barometer (baro-diver) is usually installed nearby to measure the variation in atmospheric pressure and calibrate the pressure transducer underwater. Mini-divers measure and record the water temperature using a semiconductor sensor. This sensor measures temperature whilst simultaneously using the data to compensate the pressure.
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Divers are designed to be installed in stilling wells when measuring surface flow or groundwater. Figure 4.13 shows the design recommended by Eijkelkamp, the manufacturing company. The top of the casing (TOC) is measured in relation to the vertical reference datumn. The diver is then suspended with a rigid cable. The barometer diver on land (Pbaro) measures atmospheric pressure and the diver measures the pressure exerted by the water column (WC) and the atmospheric pressure below the surface (Pdiver).
Figure 4.13 An example of a mini diver within a stilling well (Eijkelkamp: Soil and Water, 2016) 4.6.1 Site Selection
To determine if the hydrological effects of the silt trap were propagating upstream, three divers were installed at three locations at varying distances upstream of Ham Bridge silt trap (Figure 4.14). A walk over survey was initially conducted to identify suitable locations to secure stilling wells. Identifying reaches where (i)water level was sufficient all year for data collection, (ii) vertical or near vertical banks to safely secure monitoring wells and enable access to download data without entering the river and (iii) areas of river representative of the reach i.e locations which have a morphology and water level consistent with the majority of the reach, avoiding morphological features such as pools.
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Figure 4.14 Location of stilling wells installed upstream of Ham Bridge Silt Trap
4.6.2 Experimental design
The stilling wells comprised of PVC tubes suspended in the flow, attached to three reinforced steel rods installed into the bed for stability. The divers were attached to cable and placed through the centre of the stilling well cap to suspend the diver in the centre of the stilling well (Figure 4.15).
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Figure 4.15 Design of monitoring well installed at three locations upstream of Ham Bridge Silt Trap
The barometer was installed in a secure open field, 3.5km Southeast to the silt trap due to lack of open space unimpeded by vegetation near to the silt traps and for security as the site is often used by the public. The proximity of the barometer should not affect results as there was no significant changes in elevation or spatial distance which may alter air pressure. All three monitoring wells were installed on 20th February 2017 and divers at site 1 and site 2 and the barometer began recording at 9:00am. The third diver at site 3 was installed on 1st March 2017 and all divers were reset to begin recording on the same day. The divers continuously recorded water depth at five minute intervals for 11 months until 20th January 2018. All three diver sites and the barometer data was downloaded onto a field laptop on 31st March, 25th May, 8th August and 24th October 2017. During these collections, the diver was removed from the stilling well, cleaned and the data downloaded. The diver was then re-secured into the stilling well at the same depth.
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4.6.3 Data compensation
The length of the diver cable was measured and maintained throughout the monitoring period, in addition the water inside and outside of the monitoring well was checked to ensure the monitoring wells were representative of the water level. The downloaded data from each collection was merged to create a single dataset and manually checked for the times of data downloading to ensure the level before and after were accurate and adjusted accordingly. The diver data was then combined with the barometer to deduct the atmospheric pressure from the pressure recorded at each five minute time interval by the divers to determine the water level in each stilling well. The compensated results from each collection were then combined to create one continuous dataset for each diver, removing the data recorded during collection times where the water level was measuring the air pressure.
4.6.4 Morphological surveys
Two morphological surveys were conducted upstream of Ham Bridge silt trap. The first, in depth cross sectional surveys using a Trimble total station at each diver location to create a morphological profile of the channel. The survey has conducted at a high resolution to record changes in bed elevation. A second survey using a theodolite and survey pole was conducted to calculate the bed surface elevation relative to each monitoring well. The bed height was recorded at each monitoring well in relation to site 1 (0m) (Figure 4.16).
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Figure 4.16 Bed Elevation profile upstream of Ham Bridge silt trap 4.6.5 Hydrological analysis
Figure 6.1 shows the daily hydrograph, upstream of Ham Bridge silt traps at 0m (diver 1), 76m (diver 2) and 157m (diver 3) respectively. Diver 1 and diver 2 collected water level data from 20th February 2017 and diver 3 on 1st March 2017. The graph shows similar hydrograph shapes for the monitoring period, with the largest flow events occurring in the winter (February 17 and January 18). The hydrograph also shows during high flow events, the water levels recorded at diver 3 are lower than at diver 1 and diver 2, which is in keeping with the channel cross sectional survey conducted at each location. To determine the influence of the silt trap on upstream river stage five storm events of different magnitudes throughout the monitoring period were selected to explore the relationship between surface bed elevation at the different locations over time (Event 1 17th-23rd May 17, event 2 22nd-30th July 17,event 3 13-18th December 17, event 4 25th-29th December 17, event 5 29th-1st January 2018). A further three monitoring points were selected during periods of sustained low flow to investigate the influence of the silt trap on stage in the absence of a rainfall event (3rd March, 20th June 28th October 17).
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4.7 Qualitative methods
This section describes the methods used to collect qualitative data from three key social groups; catchment managers, farmers and residents within the River Eye Catchment, to determine the non-technical barriers to sustainable sediment management (objective four) .
Qualitative data was collected to assess three themes surrounding fine sediment transport and its impact on flood risk; awareness, resilience and responsibility. Identifying the social attitudes within the catchment can create a robust catchment management plan that not only accounts for the physical catchment processes but includes the restrictions and limitations from those directly impacted within the catchment. For NFM to become a sustainable future option, the social paradigm must be included (AECOM, 2017).
However, it is the responsibility of the researcher to interpret the subjective perceptions within the social context the data was collected in (Crouch & Mckenzie, 2006). Social experiences from those directly engaged with the research area provide an insight into the current views and attitudes of the affected population. Identifying knowledge gaps, reluctance and awareness from the community, enable realistic recommendations to be made to improve risk mitigation and adaptation strategies (Bird, 2009).
4.7.1 Preliminary unstructured interviews
During reconnaissance studies in the catchment, unstructured, informal interviews were conducted with land owners, tenant farmers, catchment managers and the public. The interviews focused on current flood management methods and awareness of fine sediment origins or hot spots within the catchment. These preliminary discussions identified a disparity in knowledge and opinion on flood risk from the different groups, particularly when discussing current management measures.
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Through discussions with managers within the catchment, analysis of the predominant land cover and consulting historic flood extents (see section 3.2.3), three key stakeholder groups emerged as having a stake in flood risk management; catchment managers, farmers and residents. Catchment managers incorporates public sector organisations such as Environment Agency, Natural England and local councils, as well as charities and organisations including; Trent Rivers Trust, Canal and Rivers Trust, Wildlife Trust. These groups are responsible for driving the direction of flood risk planning and mitigation and must complement catchment managers working within associated fluvial roles such as biodiversity, fisheries, navigation and water quality. The catchment managers contacted in this study are members of the Soar Catchment Partnership, a consortium of catchment mangers that enables a collaborative approach to management across the River Soar Catchment. It is important to assess the understanding catchment managers have regarding sediments influence on flooding and future flood risk paradigms such as NFM to identify potential barriers to future flood management planning. The consequences of catchment managers decision making directly impacts farmers and residents within the River Eye catchment. As arable and improved grassland equates to over 90% of land use within the Eye catchment, farming practises and rural land management may have a large influence on flood risk. In addition, many NFM techniques, including currently installed silt traps are designed for implementation in rural areas and therefore it is important to identify the levels of awareness and responsibility felt by farmers and landowners in relation to flood risk. The third community, the residents of a flood risk town, Melton Mowbray provide an opportunity to gather public opinion on awareness of fine sediment and perception of flood risk. Due to the installation of the dam at Brentingby, Melton Mowbray has not flooded for 16 years causing a possible detachment of flood risk within the town. This provides a unique opportunity to explore resilience and awareness in towns that have previously experienced flooding but since been subjected to mitigation measures. By exploring the resilience and awareness of the residents, larger recommendations can be made to catchment managers on how to manage flooding and incorporate sediment strategies. A secondary
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Chapter Four: Methodology focus of the qualitative study is exploring the potential barriers to the installation of NFM within lowland river catchments.
Building upon unstructured interviews, the decision was taken to formally record these opinions on a wider, more representative platform. Though semi- structured interviews provided an initial insight, this method would be difficult to expand multiple detailed interviews due to time constraints, and availability of the catchment managers and farming stakeholders. The decision was made to use questionnaires as a method of recording multiple viewpoints across the catchment in an unbiased way.
4.7.2 Questionnaire justification
Questionnaires are widely used in social studies to collect qualitative information and have been a successful tool in natural hazard studies, such as flooding as they provide an opportunity to gather evidence on public attitudes, knowledge, experience and levels of preparedness for future hazards (Bird, 2009).
Questionnaires were chosen as the qualitative methodology for the following reasons:
• Allows for direct comparisons between stakeholders responses (Heitz et al, 2009), which can often be quantified by statistical analysis. • Using a postal or online service eliminates responder bias that may occur with interviews or door-to-door research surveys (Crouch & Mckenzie, 2006) due to the absence of the researcher who may influence responder opinion. • Enables the inclusion of open and closed questions, limiting the bias incurred through predefined answers associated with purely closed questions (Bird, 2009).
Questionnaires have been successfully used in previous studies to target similar stakeholder groups. Structured questionnaires were disseminated to farmers of the Beckingham Marshes near the River Trent, Nottingham to generate a database of current farming systems, land use, farm inputs and
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Chapter Four: Methodology outputs and field drainage. The qualitative data was complemented with ecological surveys to create a sustainable ecosystem services management plan (Posthumus et al, 2010).
Alternative qualitative methods such as focus groups and semi-structured interviews were considered as part of the study. These two alternatives enable comprehensive responses to be obtained from participants (Adams et al, 2008) as questions can be developed thoroughly and misinterpretation can be avoided. Both techniques are used to interview smaller study groups, with focus groups recommended between 4-6 participants and semi-structured interviews 1 on 1 (Adams et al, 2008). However, both techniques provide the opportunity for the interviewer to influence the responses given through unconscious leading of questions (Adams and Sasse, 2001). Similarly, focus groups can lead to bias, as collaborative experiences can become the focus of discussion and individual viewpoints can be lost, resulting in a false consensus (Lunt and Livingstone, 1996).
Conducting these methods requires participants to be willing to attend meetings. Participants for this study, particularly farmers are restricted to availability, dependant of time of year and agricultural activity. By using questionnaires, the respondents have flexibility to reply when convenient, increasing the likelihood of response. Furthermore, individual responses reduce social bias and enable a wider audience to be assessed.
4.7.3 Questionnaire themes
The themes of awareness, resilience and responsibility, explored in section 2.10, provide a framework to structure the questionnaire. Previous studies have explored similar themes. A study investigating risk perception of muddy floods in North West France identified three key catchment stakeholders; local council, farmers and inhabitants of the area to test the following hypotheses; (1) Are key stakeholders willing to adapt current behaviours to mitigate risk, (2) does risk perception vary with proximity to natural disasters, (3) does risk need to be identified for effective communication of information? (Heitz et al, 2009). In total, 33 questions were devised for the stakeholders with a further 10
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Chapter Four: Methodology additional questions for farmers and 8 for local council. By designing the questionnaire to be divided into general questions asked to all respondents and stakeholder specific questions the study ensured all relevant background data was collected to interrupt the comparable results.
Similarly, Brilly & Polic, (2005) investigated residents in Celje, Solvenia’s perceived awareness of flood frequency and concerns in current warning systems in the event of flooding from Savinja River. The aim of the study was to collect general attitudes towards floods, not personal experiences from specific flood events, providing an insight into resident resilience to flood risk. Closed questions were used to record personal details such as location, and time in residence. In Lincolnshire, the survey was used to comprehend perception of risk, awareness and acceptance towards the planned managed realignment of Freiston Shore (Myatt & Lester, 2003). Whereas residents across Illinois were asked to give their preferences on riparian buffer strips in urban and rural waterways to address sediment and soil runoff due to agricultural intensification in the area. Photographs of tree buffers, grass buffers and no buffers were used in a postal survey over 8 regions (Kenwick et al, 2009) to determine which measures are aesthetically pleasing to residents.
Response rates for qualitative studies researching floods and risk have been positively discussed in the literature, particularly when disseminated to members of the public. Heitz et al (2009) qualitative study had 34 respondents; 14 within the erosion area and 20 situated in the sedimentation area of the catchment. The high response rate collected identified the perception of risk in relation to location of risk as a key finding (Heitz et al, 2009). A larger number of recipients was received in Celje, Solvenia when investigating flood frequency awareness. Here, two questionnaires were disseminated in 1997, 7 years after the 1990 flood event and 2003, 5 years after the 1998 flood event. The questions from both questionnaires were similar, focusing on awareness and attitudes to new flood management practises, enabling comparisons to be made. The surveys were conducted by researchers door-to-door to increase sampling, resulting in 157 in 1997 and 208 in 2003 responses to be collected
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(Brilly & Polic, 2005). A similar response rate was returned in a questionnaire conducted by the Environment Agency to residents of Freiston Shore, South Lincolnshire on resilience to future flood defences. Here a postal survey returned 262 responses yielding a response rate of 34% (Myatt & Lester, 2003). In addition, a postal survey in Illinois to farmers had a response rate of 40% (Kenwick et al, 2009).
4.7.4 Questionnaire design
Questionnaires were designed in two-sections. The first, contained questions directly relating to the stakeholder group to provide context to responses and target specific topics valued by the group (Questions 1-7 catchment mangers survey; Questions 1-10 farmers survey; Questions 1-6 residential survey). The second section is focused on exploring the themes of awareness, resilience and responsibility for fine sediment and flood risk management. These questions were asked to all three stakeholder groups to enable direct unbiased comparisons to occur. The questionnaires were disseminated using the methods most appropriate for each stakeholder group. All three questionnaires were designed using Bristol Online Survey (BOS).
The managers have a variety of environmental roles within the River Eye catchment and therefore were asked an additional 7 questions to determine their responsibility within the catchment, their understanding of the popular ‘NFM’ and ‘catchment based approach’ terms and their perception of what is limiting their management goals. The full questionnaire can be found in appendix 1.1
The questionnaire was disseminated to catchment managers using two methods. The first was to email the questionnaire to the relevant river managers from the Soar Catchment Partnership’s mailing list. This yielded a small return and the decision was taken to distribute hard copies of the questionnaire during a River Soar catchment management meeting to increase the number of potential respondents to 20.
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An additional 10 questions were added to the survey to determine the type and size of farm (Q1, Q4, Q5) as well as the length of time farming within the catchment (Q2). Further questions regarding current stewardship schemes (Q6) were asked to determine their level of engagement with the environment and environmental managers. The full questionnaire can be found in appendix 1.2.
The farming community in the River Eye received the questionnaire through email via Natural England. The decision to electronically contact farmers was made due to previous successful communication using this method to ask for land access when installing field equipment and to prevent intrusion onto the farm at busy periods, enabling recipients to respond at a convenient time. The questionnaire was sent to 40 farmers within the catchment, via email from Natural England to maintain confidentiality of respondents.
An additional eight questions were asked to residents to provide context to the comparable responses e.g. home ownership, length of time in property and flood history (Q1, Q2, Q5). Residents were also asked further questions on the theme of resilience and responsibility to identify which personal measures they are likely to implement to avoid flooding and which organisations they believe are accountable for informing residents of flood warnings and in the event of a fluvial flood.
The population of Melton Mowbray Borough was measured at 50,376 residents in the 2011 Census (Melton Borough Council, 2016). To reduce the sample size from the entire population, the Environment Agency’s flood map was used to identify residents addresses that were in close proximity to the River Eye and risk of fluvial inundation. A database of 663 houses was created from the properties located in the flood risk zones 1,2 and 3 or in close proximity to the River Eye but not deemed at risk of flooding (Figure 4.17). The decision was made to target residents in close proximity to the River Eye as they are the most likely to be directly affected by fluvial flooding. Random sampling was used to select which houses on the street should receive questionnaires. In total, 200 properties received questionnaires via a postal survey. The questionnaires were sent in 4 batches of 50 surveys over a 4 week
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Figure 4.17 The streets selected to send residential postal questionnaires situated in flood zones 1,2&3 or in close proximity to the River Eye 4.7.5 Questions themed on awareness, resilience and responsibility
The majority of questions asked to all three stakeholder groups, concerned awareness themed questions as they are the most translational across the stakeholder communities. A series of open and closed questions were used to discover stakeholders perception of flood risk, attitudes towards flood mitigation measures and awareness of sediment and soil transport within the catchment. Closed questions including multiple choice options were used to identify the main contributors to flood risk, and ranking questions to determine preferred management measures and awareness of changes within and close to the River Eye, which may be indicative of sediment deposition or transport. Closed questions can be easily coded and quantified providing easy comparisons between stakeholder groups. Open questions were used to ascertain opinions on contentious mitigation measures such as dredging,
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Chapter Four: Methodology providing respondents the opportunity to answer with freedom to discuss wider ideas which stakeholder groups may associate with mitigation measures that cannot be pre-empted in advance. The questions asked to determine stakeholder awareness can be found in Appendix 1 (catchment managers Q 8-13, 15, 16, Farmers Q11-18,19, Residents Q7-11,13-14) an example of which is “Have you noticed any changes to the following river features since living in this area?”
Resilience questions were concerned with identifying how those who previously experienced flooding coped and what mitigation measures individuals would be willing to take to protect their properties from flood damage. Similarly, questions of large scale mitigation measures were asked to determine the levels of acceptance of NFM measures compared to traditional flood defences. Questions ask such as “which of the following measures would you prepared to do to reduce flood risk to your property?” are presented in Appendix 1 (catchment mangers Q14,Q5, farmers Q10, Q18, residents Q6, Q12).
Closed questions were also asked to stakeholders to rank perceived responsibility of flood risk management. This question can determine how closely aligned stakeholders views are in terms of who they believe is accountable. These results can be compared to flood risk management literature detailing who is responsible for flood risk to identify areas of perception which may need adjustment. Residents were additionally asked to identify who they believe is responsible of informing residents of an impending flood and who is responsible for the protection of residential property. The questions asked to each stakeholder group are shown in Appendix 1 (catchment managers Q17, farmers Q20, residents Q15-17).
4.7.6 Questionnaire Analysis
The questionnaire responses received online were automatically uploaded to BOS website and all manual responses were manually added to the database. The results for each question were downloaded to enable data analysis. Bar and pie charts were created to visually display some of the closed questions
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Chapter Four: Methodology asked. Likert scales, were used to display the results from ranking questions. Likert scales provide scaled or ranked responses, measuring attitudes and opinions to a greater depth than simple yes/no question. Studies have previously found them to be the most accessible form of displaying ranking questions (Van Laerhoven et al, 2004).
The results from the contextual questions asked to each stakeholder group will be analysed first to provide social background to the subsequent themed questionnaire responses (Crouch & Mckenzie, 2006). The remaining responses will be discussed individually and then compared with the results from the other stakeholder groups. The analysis will focus on the awareness, resilience and responsibility perceptions felt by each stakeholder group to identify possible options and barriers to future flood risk management strategies within the River Eye catchment.
4.8 Chapter Summary
The overreaching themes and perceptions of sediment transport within the catchment will be compared with connectivity modelling and field data discussed in chapter 5 and chapter 6, to discuss if the reality of risk modelling and physical data capture matches the perception felt by the River Eye inhabitants. Finally, the combined analysis from all methodologies will be used to achieve objective 5 and produce a series of recommendations to catchment managers on the future of flood risk management in the River Eye
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Chapter Five: Identifying the sources and spatial patterns of fine sediment
5 Chapter Five Identifying the sources and spatial patterns of fine sediment
5.1 Chapter Scope
This chapter seeks to use the modelling (4.2), field (4.3, 4.4) and laboratory (4.5) methods outlined in Chapter Four to investigate potential sources and spatial patterns of fine sediment. Chapter Five begins exploring the results of the SCIMAP model (section 5.2) which has been used at a catchment and sub- catchment scale to identify fine sediment source areas based on connectivity and erosion risk using traditional DTM and a novel DSM at both catchment and sub-catchment scale. Section 5.2 then goes on to explore the effects of changes in future climates and land use may affect sediment connectivity and erosion risk at the catchment scale.
Section 5.3 explores the storm samples taken in Melton Mowbray park during two high flow events to validate the laboratory methods using native sediment (section 5.3.1-5.3.2) before investigating changes in organic matter content and particle size during different stages of the storm event (section 5.3.3-5.3.4). These results are then used to inform the spatial and temporal patterns in mass (section 5.4.1-5.4.2), organic matter (section 5.4.3-5.4.4) and particle size (section 5.4.5-5.4.6) collected from installed TIMS samplers throughout the catchment.
5.2 River Eye catchment connectivity and erosion risk
The SCIMAP model was run at 5m resolution for the River Eye catchment using DTM and DSM to calculate catchment connectivity and erosion risk (network index) (Figure 5.1). Figure 5.1a shows the histogram created from the DTM topography layer in SCIMAP has a normal distribution from 0-0.9 with
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Chapter Five: Identifying the sources and spatial patterns of fine sediment an increase in the tail at 0.91-1. The median connectivity value is 0.35, suggesting the catchment has a degree of connectivity during average rainfall under current land cover conditions. 5.4% of the catchment is completely disconnected (0) and 7.2% is fully connected (1) suggesting fine sediment is likely to be transported via overland flow in these locations.
The SCIMAP network index output for the DSM (Figure 5.1b) which includes surface structures such as buildings and roads, shows a similar histogram normal distribution with an increased tail. The median value is 0.1 lower than DTM results at 0.25 which is indicative of less connection with the catchment due to the addition of surface features. However, the percentage of the River Eye catchment that is completely disconnected (0) remains unchanged (5.4%) between the DTM and DSM, whilst the percentage of connected areas increases by 0.5% (7.7%). This result is surprising as the outlined limitations of SCIMAP is the use of a DTM would over predict connectivity due to the absence of land structures which could inhibit connected pathways (Reaney et al, 2011). One potential reason may be the inclusion of surface features, such as roads and footpaths can increase hydrological connectivity and thus the potential of sediment delivery (Bracken & Croke, 2007).
Figure 5.1 SCIMAP catchment connectivity and erosion risk histograms. a) catchment connectivity DTM b) catchment connectivity DSM c) catchment erosion Risk DTM d) Catchment erosion risk DSM
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Using a DSM or DTM where landscape features such as roads, drainage and surface features such as hedgerows were stamped into the raster layer may decrease connectivity and erosion risk.
Figure 5.2 provides a visual representation of differences between the DTM and DSM connectivity. At a catchment scale, the DTM shows larger areas of connected catchment whilst the DSM appears to be less connected (Figure 5.2). The SCIMAP spatial coverage reflects the results found in the River Eye catchment where areas of high connectivity could be located across the catchment and not limited to one area (Lane et al, 2009). A sample section of the catchment shows the DSM visually depicts field boundaries, and roads resulting in a more intricate spatial representation of connectivity, compared to the traditional DTM topography layer which displays larger spatial areas of connectivity (Figure 5.2). The subsequent histograms calculated for the sample sections show that DTM predicts a higher degree of connectivity with 15.6% of the area fully connected which is 7.3% greater than DSM predictions (Figure 5.2). The left skewed distribution of the DSM indicates that overall connectivity in this area is lower than predicted by the normal distribution DTM due to the inclusion of surface features, complementing the predictions made in the literature (Reaney et al, 2011). The sub-section used is a rural area with field boundaries which may inhibit connectivity (Shore et al., 2013b).
Figure 5.1c shows the catchment distribution of erosion risk using a DTM. The distribution is skewed to the left, indicating that risk of erosion is low within the catchment. The band 0.01-0.1 represents 47.3% of the catchments erosion risk and only 1.9% has been calculated as high erosion risk (0.91-1), suggesting that although the catchment is moderately connected (Figure 5.1a) the potential erosion risk is considered low. The DSM erosion risk histogram (Figure 5.1d) shows a further decrease in areas of erosion risk observed in the DTM (Figure 5.1c). The area of catchment calculated to have zero risk is 24.9% higher in the DSM (Figure 5.1c). In contrast, the DSM predicts areas of erosion risk with value of 1 as 3.2%, 1.4% higher than predicted DTM values, suggesting that DSM layer has predicted a higher erosion risk for the
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Chapter Five: Identifying the sources and spatial patterns of fine sediment catchment. This may be indicative of increased catchment connectivity resulting in areas of increased erosion risk. Secondly, erosion risk calculated by both the DTM and DSM may be superficially lowered due to the resolution of the elevation input layer. A 5m DTM and DSM may be to coarse to identify smaller slopes and landscape features that intrinsically increase erosion risk. However, as the results are discussed at the sub-catchment level, using the same input values this is a consistent limitation within the study.
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Figure 5.2 DTM and DSM catchment connectivity. A sub-section of the catchment has been exported to create a comparative histogram.
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5.2.1 Spatial trends in connectivity and erosion risk
The DTM and DSM SCIMAP models were clipped in ArcGIS to each sub- catchment extent and exported into excel to calculate histograms for catchment connectivity (Figure 5.3) and erosion risk (Figure 5.4) to determine the potential sources and spatial patterns of fine sediment.
SCIMAP’s DTM connectivity map (Figure 5.3a) shows areas within Burton Brook and Langham Brook sub-catchments as having the largest spatial areas of connectivity, indicated by the presence of red areas. This is supported by the representative sub-catchment histograms which indicate Burton Brook has highest percentage of fully connected spatial area (8.6%). Similarly, Langham Brook and Eye tributary are both the second highest with 7.9% of the sub- catchment’s fully connected. The results indicate that these sub-catchments are most likely to transport fine sediment to the river channel and become significant contributors to fine sediment within the channel. These sub- catchments represent potential sources of fine sediment as SCIMAP recognises these areas with the greatest variation in topography therefore increasing connectivity.
In contrast, the Whissendine Book has the smallest spatial area of fully connected pathways (3.6%), suggesting that any sediment being transported within the channel is likely to be a local source due to poor sub-catchment connectivity. The DTM map indicates an area of increased connectivity downstream of the confluence of the Whissendine Brook, suggesting a potential source of fine sediment, as it appears connected to the channel (Figure 5.3a). Another notable area of high connectivity outside of the sub- catchment is downstream of Freeby Brook, indicated on Figure 5.3a by red and orange connectivity coverage. This result is similar to Lane et al’s (2009) SCIMAP study that found areas of high connectivity were located to main channel as opposed to smaller streams and tributaries in the upper Eye Catchment.
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6/7 sub-catchment histograms reflect the normal distribution trend of the catchment histogram with the median observed at 0.35. Lane et al's, (2009) study using SCIMAP also found sub-catchments of the River Rye, Yorkshire has similar connectivity distributions across the catchment. The Wymondham Brook is an exception to this, where, the median network index is 0.55, suggesting this sub-catchment has a greater number of partially connected areas. However, the DSM histograms do not appear similar to the catchment histogram with 5/7 sub-catchments showing an 0.1 increase in median network index to 0.45. The median values of the DTM and DSM suggest that the DSM predicts higher level of connectivity within the sub-catchments, suggesting the catchment may be more connected than traditional DTM layers suggest. The DSM histogram (Figure 5.3b) reflects that of the DTM histograms by identifying Burton Brook and Freeby Brook as the sub-catchments that have the highest percentage of fully connected spatial area 14.3% (Burton Brook) and 10.3% (Langham Brook), and thus the sub-catchments identified as having the greatest potential to deliver fine sediment to the channel. In addition, it also identifies Whissendine Brook as the sub catchment with the least areas of connectivity (9.6% with network index 0). The similar results displayed by the DSM to the DTM indicate the inclusion of surface features create more intricate, potentially more realistic topography, which is governed by changes in terrain relief.
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a) b)
Figure 5.3 River Eye Sub-catchment connectivity a) DTM sub-catchment connectivity b) DSM sub-catchment connectivity.
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a) b)
Figure 5.4 River Eye Sub-catchment erosion risk a) DTM sub-catchment erosion risk b) DSM sub-catchment erosion risk.
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Figure 5.4a shows the erosion risk output for SCIMAP using a DTM topography. Due to the intrinsic link with connectivity, the Burton Brook is the sub catchment identified as having the highest erosion risk score (4.8%). However, it is also the sub-catchment with the highest spatial coverage of 0 erosion risk (38.2%). This result appears an anomaly of the sub-catchment histograms with the remaining six sub-catchments having 0 erosion risk ratings between (16.3- 21.1%). The result may reflect the slopes present within the Burton Brook catchment in the uplands and the subsequent low lying area around the floodplain, resulting in areas of high erosion risk and 0 erosion risk.
The DTM erosion risk map indicates sites close to the confluences of Somerby’s brook and River Eye tributary as having higher erosion risk, shown by the yellow and red areas close to the channel. SCIMAP identifies these areas are potentially high in erosion risk, suggesting a potential fine sediment source for the River Eye (Figure 5.4). In contrast, the Freeby Brook tributary is identified as the lowest sub-catchment for erosion risk with 53.2% of the spatial area measured 0.01-0.1 erosion risk reflected in the absence of yellow and red erosion risk spatial areas close to the channel (Figure 5.4).
The DSM erosion risk output (Figure 5.4b) indicates Wymondham Brook has the highest percentage erosion risk with 4.03% of the sub-catchment is rated 1. Burton Brook is the second largest sub-catchment with 3.49% rated 1 or high erosion risk. Although these areas have been identified as potential sources of fine sediment, the DSM output predicts 43.2% of Wymondham and 42.4% of Burton Brook sub-catchments are at 0 erosion risk, suggesting that much of the River Eye catchment is not at risk of erosion. The inclusion of surface features within the DSM layer appear to have calculated the erosion risk as 0 for most of the catchment, compared to the DTM which measures the highest frequency from 0.01-0.1 reflecting the results (Figure 5.1). These consistent results suggest the cause of partial connectivity and low erosion risk may be a consequence of the relatively small changes in topography within the catchment. As SCIMAP calculation of connectivity relies on slope and contributing area, it is likely many of the potential sources of fine sediment entering the channel are in close spatial proximity to the channel and derive
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Chapter Five: Identifying the sources and spatial patterns of fine sediment from sources such as banks or runoff from floodplains. However, Lane et al (2009) highlight a potential limitation of SCIMAP by identifying contributing area is not the sole factor which governs connectivity. A study by Aryal et al, (2003) found the impact of evaporation on surface flow paths can prevent the development of saturation areas at the base of hillslopes, suggesting other factors of hydrological and by extension fine sediment connectivity are neglected, potentially resulting in sources of fine sediment to remain undetected.
5.2.2 Rainfall changes
Climate change has been hypothesised to create a greater disparity in season with summers set to become drier and winters to increase in storminess (Wilby et al, 2008). SCIMAP simulated summer and winter rainfall changes to identify potential alterations in catchment connectivity and erosion risk.
The summer rainfall simulations for 2030 and 2050 saw a decrease in 10% and 20% of annual average rainfall grid. Comparing the original model output to these 2030 and 2050 results indicate there is no difference in catchment connectivity between the summer scenarios, suggesting that a reduction in rainfall between 10-20% does not impede connectivity (Figure 5.5a Figure 5.5b), However, there is a 4% decrease in areas of the catchment that are fully connected (1) between the original rainfall simulation (Figure 5.1a) and the 2030/2050 climate scenarios (Figure 5.5a Figure 5.5b), suggesting the initial 10% decrease in rainfall does impact connectivity.
The erosion risk histogram for summer 2030 is identical to the original model output (Figure 5.1c), suggesting a 10% decrease in rainfall does not impact computed erosion risk. However the 2050 results show a 0.3% decrease in erosion risk and a 5% increase in areas with 0 erosion risk, suggesting a 20% reduction in rainfall is the required threshold to impact the SCIMAP model. This may be result of points within the catchment with low network index score now have less rainfall to connect cells and create a flow pathway (Lane et al, 2006). The results indicate that under future climate predictions, connectivity will marginally decrease in summer, due to less rainfall to connect flow pathways,
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Chapter Five: Identifying the sources and spatial patterns of fine sediment suggesting any fine sediment delivery and transport within the channel is likely to derive from local sources such as river banks.
The Winter 2030 connectivity results show no change in catchment connectivity (Figure 5.5c) from the original rainfall simulation for the DTM layer (Figure 5.1a Figure 5.1c), suggesting no change in spatial extent with a 20% increase in rainfall and the potential sources and pathways identified in Figure 5.3a and Figure 5.4a remain unchanged. However the 2050 results show an increase in areas within the catchment that are fully connected by 0.5% (7.7% winter 2050), indicating a 30% increase in annual average rainfall supplied a sufficient volume of water to cells to increase the spatial connectivity extent. The increase in fully connected areas are concentrated around areas of existing connecting observed from spatial extents. In addition, there is an observed reduction of 1.4% in areas with minimal connectivity (0.01-0.1) from 6.5% of the catchment (Figure 5.1a Figure 5.5a) to 5.1% and a 5% increase in cells with 0.3 connectivity suggesting connectivity within the catchment is increasing. These findings are reflected in the erosion risk results (Figure 5.5g and Figure 5.5h) where an increase in rainfall from the original (Figure 5.1c) shows an increase of 0.17% of erosion risk scores of 1. However, there is no differences between 2030 and 2050 scenarios, suggesting the threshold for change is between 0-20% increase in rainfall, not 20-30%.
The changes simulated by increasing rainfall suggest that catchment managers must consider increased connectivity during winter periods, causing a higher volume of fine sediment delivery. The results highlight the importance of working at a catchment scale to reduce the delivery of fine sediment to the channel as the sources may be connected to the channel from a greater distance.
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Figure 5.5 Rainfall simulations for connectivity and erosion risk in summer 2030, summer 2050, winter 2030 and winter 2050 5.2.3 Land use changes
Risk weightings were parametrised by Lane et al (2006) based on expert judgement for the potential risk of that source generating fine sediment pollution. Risk weightings were altered to determine the potential user influence on predicted connectivity and erosion risk for the three largest land cover types within the River Eye catchment; arable, broadleaf woodland and
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Chapter Five: Identifying the sources and spatial patterns of fine sediment improved grassland. For all SCIMAP simulations, connectivity remained the same, due to land cover not being incorporated into the network index calculations.
As arable has an assigned risk weighting of 1 (Table 4.1) SCIMAP was re-run changing the parameter to 0 and 0.5. The risk weighting refers to the potential vulnerability of soil run off from agricultural fields. By altering the risk weightings the results may reflect changes in land management practises; such as crop coverage throughout the year or the inclusion of buffer strips on field boundaries which reduce the risk of soil run off within the catchment.
Figure 5.6 Catchment erosion risk results after land cover risk weightings have been modified. Figure 5.6a and Figure 5.6d show the erosion risk results for the River Eye catchment with an arable risk weighting of 0 and 0.5. With a risk weighting of 0 applied to arable sites the erosion risk for the catchment ranges between 0- 0.3 indicating erosion risk is very low (Figure 5.6a). Similarly, with a risk
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Chapter Five: Identifying the sources and spatial patterns of fine sediment weighting of 0.5 the catchment erosion risk values range 0-0.5 suggesting no areas within the catchment are of high risk (1) to erosion. The results suggest that arable fields are a potential fine sediment source within the River Eye catchment, as a reduction in risk weighting for these locations eliminates catchment erosion risk (Figure 5.6a). Furthermore, the SCIMAP scenario indicates that a reduction reduced risk weighting, symbolising a reduction in runoff, through the use of winter crop coverage or field buffer strips may reduce erosion risk within the River Eye catchment. The results reflect findings by Porter et al (2017) who highlighted the importance of selecting the correct risk weighting for land cover units which occupy a large spatial area within the catchment (Porter et al, 2017). Furthermore, spatial dominance of one land cover type has been was found by Davies and Neal, (2007) to affect the variability of results.
Broadleaf woodland equates to 2.79% of the land cover within the catchment and has default risk weighting of 0.05 (S. . Lane et al., 2006), resulting in changes to erosion risk weighting for this land cover group to be relatively minor. Reducing the risk weighting to 0 resulted in a 5.7% increase in areas with 0 erosion risk (default settings 21.7% = 0, 0 weighting 27.4%=0). However, it only decreased locations of erosion risk with a value of 1 to decrease by 0.29% suggesting broadleaf woodland are not areas of high sediment delivery. Increasing the risk weighing to 1 (Figure 5.6h) shows an erosion risk with a value of 1 of 1.85% matching the erosion risk observed with the default settings (Figure 5.4c), suggesting an alteration in risk weighting in broadleaf woodland does not impact overall catchment erosion risk.
Improved grassland, referring to land which is commonly grazed and classified as highly productive grassland (CEH, 2017) has a default risk weighting of 0.3. By decreasing the assigned risk weighting to 0 (Figure 5.6c), areas of the catchment with 0 erosion risk increase by 20.4% (0 weighting= 41.2% 0.3 weighting 21.68%). Similarly, there is a 10% decrease in areas of erosion risk 0.01-0.1, suggesting an overall reduction in catchment erosion risk with a shift in risk weighting to 0. Increasing the risk weighting to 0.5 and 1 reduces the areas of 0 erosion risk to 24.98% and 24.02% respectively. Furthermore, with
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Chapter Five: Identifying the sources and spatial patterns of fine sediment an applied risk weighting of 1, areas within the catchment that are rated erosion risk 1 increase by 0.05% to 1.9% from the original (0.3, Figure 5.1c) and 0.5 risk weighting (Figure 5.6e) suggesting, the locations of improved grassland do influence catchment erosion risk. Porter et al’s (2017) study using Monte Carlo simulations to identify optimum risk weightings for FIO’s determined improved grassland should be increased to 0.78 to account for cattle poaching and compaction which increases surface runoff. This result suggests that traditional SCIMAP models may under predict catchment erosion risk due to risk weighting associated with improved grassland.
Milledge et al 2012 applied an inverse approach to determining risk weigtings assigned to different land classes to explain spatial pattersn of instream nutrient concentrations. Using a Monte Carlo approach to run 5000 model simulations to randomly selected weightings between 0-1 for a series of scenarios across 11 River catchments in England and Wales. The results determined optimal risk weightings are not consistent between catchments highlighting the need to apply SCIMAP risk weightings on a catchment by catchment basis (Milledge et al, 2012). Given the River Eye Catchment has land cover of 69% agriculture, and the default score is 1 in these areas the majority of the catchment has a high-risk weighting. One potential area where the default score may have underestimated connectivity in within cultivated grassland category which has a risk weighting of 0.3. Given these cultivated areas are likely to subjected to compaction and erosion, the risk weighting may need to be increased to reflect a potential increase in erosion risk.
Finally, SCIMAP was run using the CEH 2015 land cover new extent using default risk weightings to determine if changes in land cover have affected catchment connectivity and erosion risk (Figure 5.7). The histograms for connectivity DTM and DSM (Figure 5.7a and b) are identical to the previous histograms for catchment connectivity (Figure 5.1a and b) suggesting subtle changes in land cover (Table 4.3) have not influenced the connectivity of the catchment, confirming SCIMAP connectivity is a function of topography, as expected. To authenticate no observed changes in 2007 and 2015 land cover connectivity extents the same sub-section was exported for both DSM and
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DTM and the histograms (Figure 5.8). The histograms and spatial maps of Figure 5.2 and Figure 5.8 were identical, suggesting the potential sources of fine sediment identified in section 5.2.1 remain unchanged.
Figure 5.7 a) catchment erosion risk using 2007 land cover and DTM, b) catchment erosion risk using 2007 land cover and DSM, c) catchment erosion risk using 2015 land cover and DTM, d) catchment erosion risk using 2015 land cover and DSM Figure 5.7c shows the 2015 land cover extent has increased the area of 0 erosion risk by 1.02% from 2007 (Figure 5.7a) and decreased the area of 1 erosion risk by 0.07%, suggesting the erosion risk within the River Eye catchment has marginally reduced. Similarly, the DSM 2015 land cover extent Figure 5.7d shows an 0.83% increase in 0 erosion risk and a 0.11% decrease in area of 1 erosion risk from 2007 extent (Figure 5.7b). This result are likely to reflect the 3.24% loss in arable land cover (Table 4.3) in 2015, causing a reduction in land cover with the highest risk weighting.
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Figure 5.8 DTM and DSM catchment connectivity using 2015 land cover. A sub-section of the catchment has been exported to create a comparative histogram.
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5.2.4 SCIMAP summary
SCIMAP model has successfully identified areas of connectivity and erosion risk within the River Eye catchment and shown to identify potential fine sediment sources. Overall catchment connectivity and erosion risk appeared low due to small topographical changes suggesting the River Eye in-channel fine sediment may be a result of local sources within close proximity to the channel such as banks and neighbouring arable fields which, were found to influence erosion risk. The results identified the sub-catchments of Burton Brook and Langham Brook as areas of highest connectivity and erosion risk, suggesting these areas are potential sources of fine sediment within the River Eye. In addition, areas of high erosion risk on the main River Eye channel downstream of Somerby Brook and Eye tributary were identified as potential contributors to fine sediment delivery. The additional of a DSM layer provided a more realistic spatial representation of catchment connectivity, suggesting that the inclusion of surface features such as roads and footpaths may increase spatial patterns of connectivity. The SCIMAP simulations of climate change found a decrease in connectivity and erosion risk for Summer 2050 but no change in Summer 2030 suggesting a decrease of 20% of rainfall is the required threshold for changes to catchment scale fine sediment connectivity. Similarly, a 20% increase in rainfall simulating 2030’s climate scenarios saw an increase in sediment connectivity and erosion risk but the 2050’s scenario (30% increase in rainfall) remained unchanged. The results suggest that predicted future climate changes are likely to impact sediment connectivity and erosion risk within the River Eye catchment, resulting in catchment managers to extend current areas of management in winter months to ensure there isn’t an increase in fine sediment entering watercourses.
SCIMAP has successfully fulfilled objective one of the thesis by identifying sources of fine sediment within the catchment. The results of spatial patterns of fine sediment identified by SCIMAP will be further explored and compared with suspended sediment analysis.
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5.3 Physical properties of suspended sediment storm samples
The instant suspended storm samples were used in a preliminary experiment for three reasons. 1. To validate the laboratory methodology before conducting analysis on TIMS samples. 2. To investigate the change in organic matter and particle size during a storm event. 3. To provide an indication of the physical properties of the suspended sediment travelling through Melton Mowbray, discussed in section 5.3.
5.3.1 Organic matter content method validation.
The samples collected at the peak of the storm hydrograph on 9th February 2016 and 9th March 2016 have similar water levels (2.01m and 2.04m) and 2.92% variation in organic matter content within the sub-samples, indicating a degree of consistency in the storm samples collected during high flow events.
Table 5.1 Percentage of organic matter content from suspended sediment storm samples
Percentage of Organic matter Water Collection Date content (%) Percentage Level Sub-sample A Sub-sample B Difference (m) (%) 8th Feb 2016 2:50pm 1.53 11.33 12.62 1.29 8th Feb 2016 4:05pm 2.01 12.41 12.39 0.02 9th Feb 2016 9:20 am 1.5 11.98 9.33 2.65 9th Mar 2016 2:27pm 2.04 11.71 14.63 2.92
The ranges of organic matter content range between 9.33-14.63% (Table 5.1) indicating 7 of the 8 samples lie within the 10-30% organic matter content typical for British Rivers (Walling & Webb, 1987). Differences between sub- sampled organic matter content values are shown in (Table 5.1). The differences in organic matter content calculated between sub-samples have a small variation of 0.02-2.92%. Each sub-sample was treated twice with hydrogen peroxide and weighed to ensure the sample was fully oxidised,
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5.3.2 Particle size analysis method validation
Particle size analysis was also conducted on the suspended sediment storm samples. Each sub-sample was run through the mastersizer a minimum of 7 times and then an average of five runs was taken to create a particle size distribution curve (Figure 5.9).
100 90 80 70 60
% 50 40 30 20 10
0
0.16 0.21 0.28 0.36 0.48 0.63 0.83 1.10 1.45 1.91 2.51 3.31 4.37 5.75 7.59
10.00 13.18 17.38 22.91 30.20 39.81 52.48 69.18 91.20
158.49 208.93 275.42 363.08 478.63 630.96 831.76 Particle Size (µm) 120.23 8th Feb 2:50pm 8th Feb 2:50pm 8th Feb 4:05pm 8th Feb 4:05pm 9th Feb 9:20am 9th Feb 9:20am 9th March 2:27pm 9th March 2:27pm
Figure 5.9 Cumulative Particle Size Distribution of suspended sediment from collected storm samples Percentage coefficient of variance (%cv) was calculated to determine the inter- sample variability recorded by the mastersizers multiple readings for each sample (Table 5.2). Results indicate the mastersizer is consistent in calculating the D16 and D50 readings for each sample, indicated by the low %CV values (<20%) for all samples. However, the D84 showed the most variance with only 1 storm sample rising limb at 2:50pm on 8th February being significant 12.7%.
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Table 5.2 percentage coefficient of variance between subsample a and subsample b
%cv D16 %cv D50 %cv D84 8th Feb 2:50pm 3.67 2.72 12.79 8th Feb 4:05pm 5.68 16.27 53.89 9th Feb 9:20am 1.99 5.00 24.99 9th March 2:27pm 3.58 5.43 37.58
The remaining samples showed greater variation between each mastersizer run for both sub-samples 53.8%, 24.9% and 37.6% respectively (Table 5.2). The mastersizer, does incur a high level of variance in the D84 which is indicative of the mastersizer failing to record consistent larger sediment sizes to the same level of precision. The increase in variance may occur due to:
• The sample not being fully de-floculated resulting in several smaller particles being clustered together and subsequently being recorded as a larger particle • Inclusion of air bubbles in the mastersizer which can be recorded by the laser as a particle. • Singular larger particles, particularly in sites which are naturally coarser sediment may skew the distribution and cause a high %CV.
5.3.3 Organic matter content in storm samples
Table 5.1 displays the organic matter content collected during two storm events; on the 8th-9th February 2016 and 9th March 2016. In February, three collections were made during the rising limb, the peak of the hydrograph and the falling limb, with the water levels were obtained from the Melton Mowbray Park monitoring station installed approximately 40m upstream of the sampling location (Table 5.1). The results indicate similar levels of organic matter are travelling within the suspended sediment load during the rising limb the peak and the falling limb in the hydrograph (9.33-12.41% range). The results suggest similar levels of organic matter are travelling within the suspended load of sediment throughout the high flow event.
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5.3.4 Particle size analysis for storm samples
The particle size distribution shows the rising limb on 8th February (2:50pm) to have to smallest D50 and D84 values of all samples taken, 2.7µm and 11.7µm respectively (Table 5.3). The results recorded on the rising limb are more likely to reflect regular flow conditions due to water levels being only slightly elevated when the measurement was taken. During the receding water level on 9th February (9:20am), the D16 values recorded are similar to those of the rising limb 0.66µm and 0.69µm respectively, indicating a return to suspended sediment transport rates before the storm peak. However, the D84 remains at similar levels to the peak samples (45.39 µm and 45.66 µm) collected suggesting sediment being transported during this time is over a much greater range (Table 5.3).
Table 5.3 Particle size (µm) analysis for suspended sediment storm samples. %cv values in blue are statistical significant to 95%.
D16 (µm) %CV D50 (µm) %CV D84 (µm) %CV 8th Feb 2:50pm 0.61 1.10 2.64 1.65 10.48 9.71 8th Feb 2:50pm 0.63 1.22 2.76 1.93 11.26 15.36 8th Feb 4:05pm 0.56 3.80 4.06 11.42 65.37 58.77 8th Feb 4:05pm 0.59 5.10 5.63 14.96 92.75 49.01 9th Feb 9:20am 1.23 1.87 5.00 5.03 45.39 27.28 9th Feb 9:20am 1.22 2.22 5.76 4.53 45.66 25.02 9th March 2:27pm 1.30 3.95 6.30 5.89 75.42 43.61 9th March 2:27pm 1.31 3.42 6.48 5.09 61.08 23.61
Finally, Figure 5.9 shows the samples collected at the peak of both storm events on 8th February and 9th March to be very similar in there particle size distribution. The second peak recorded is marginally smaller at D16, D50 &D84 values which may reflect the water level on March 9th was lower than that on February 8th. The similarities in particle size distribution curves for both storm events provides an indication of sediment transport which may benefit future catchment managers when installing sediment reducing measures in the River Eye at Melton Mowbray.
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5.4 Physical properties of suspended sediment TIMS
The suspended sediment samples collected over a 19-month period from the River Eye will be analysed in terms of both spatial and temporal patterns for mass, organic matter content and particle size analysis.
5.4.1 Spatial mass of sediment
Spatial variability of suspended sediment throughout the River Eye catchment has been expressed as sediment load (g day-1) and sediment yield (g km -2 day -1) at a daily rate to account for the period of time TIMS were installed within the catchment (Figure 4.9). The daily load has been extrapolated to the cross-section area using the scaling factor in Equation 4.3.
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Figure 5.10 Suspended sediment daily load (g day-1) collected by TIMS in the River Eye catchment during monitoring period. Figure 5.10 shows the daily load (g) from the TIMS samplers during the monitoring period of January 16- October 17. The mean suspended sediment load is 516.4g day-1, with the minimum load at site 9 Burton woods (51.4 g day- 1) and the maximum recorded at site 5 Stapleford woods (1148.6 g day-1). The catchment map suggests as sites progress downstream the daily load reduces. This result contradicts spatial patterns found by TIMS samplers on the River Esk where a positive correlation was found between increasing catchment contributing area and increased suspended sediment load for the 2007/8 and 2008/9 hydrological years (Perks et al, 2017). The result observed on the main River Eye channel shows a high daily load ranging from 154.8 g day-1 (site 1)
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Chapter Five: Identifying the sources and spatial patterns of fine sediment to 1148.6 g day-1 (site 5) up to Ham Bridge silt trap, located downstream of site 8. Downstream of this location, the daily load is reduced to 51.4 g day-1 (site 9) – 405.7 g day-1 (site 11). The results suggest that the silt trap at Ham Bridge is effective at reducing the mass volume of suspended sediment downstream and may explain why there is an inversed correlation to expected trends.
The four tributaries with installed TIMS show the Whissendine (site 1) and Wymondham (site 3) Brooks to contribute a relatively small sediment load to the main channel (154.8 g day-1 and 117.6 g day-1 respectively). The main Eye tributary (Site 6) has the largest suspended sediment load of the tributaries of 499.8g, which is in keeping with its proximity to sites 5-8 which are the highest sediment loads observed on the main River Eye channel. SCIMAP did not identify the main Eye tributary (site 6) as a tributary with high erosion risk, suggesting the sources of fine sediment in these areas may be in-channel or from banks. Bank erosion was observed on the banks due to the steep profile (see cross sectional area in Appendix 1).
When the sediment load is converted to area specific suspended sediment yield (g km -2 day -1) to account for the catchment contributing area, the results show a TIMS installed within smaller sub-catchments are generating a greater mass of suspended sediment per unit area than TIMS located on the main channel (Figure 5.11). Results are in keeping with previous research which found suspended sediment yields within catchment peak over 0.1-20km2 scale (Chaplot & Poesen, 2006; Perks, 2013; Poesen, et al, 1996).
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Figure 5.11 Daily sediment yield (g km -2 day -1) ) collected by TIMS in the River Eye catchment during monitoring period. Figure 5.11 shows site 10 located on the Burton Brook tributary as having the largest daily sediment yield of 17.4 g km -2 day -1. Similarly, site 6 on the Eye tributary has the second largest yeild of 15.2 g km -2 day -1. Smaller tributaries such as site 3 located on the Wymondham Brook show a relatively small sediment yield of 7.7 g km -2 day -1 which is 56% smaller than Burton Brook in terms of sediment yield. The results reflect the sub-catchment identification of connectivity and erosion risk which identified the Burton Brook as the sub- catchment with the highest percentage of connected areas (8.6% >0.91 network index). Sites located on the main River Eye channel have a daily suspended sediment yield ranging 0.35-15.2 g km -2 day -1.
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20
) 1
- 10 18
day 6 2 2
- 16 14 5 12 1 7 10 3 2 8 4 8 6 4 11
2 9 Specific Specific sediment yieldkm (g 0 0 20 40 60 80 100 120 140 160 180 200 catchment contributing area (km2)
Figure 5.12 scatter plot depicting specific suspended sediment yield (SSY) over catchment contributing area of the River Eye Specific sediment yield from each location was plotted in relation to catchment contributing area to determine the SSY-area relationship. Figure 5.12 shows an inverse relationship between SSY-area, with an R2 0.54, indicating as catchment contributing area increases specific sediment yield decreases. This trend has been generally reported in the literature (Dedkov, 2004; Dendy & Bolton, 1976; Millman & Meade, 1983; Millman & Syvitski, 1992; Schumm, 1977; Walling & Webb, 1996) and a positive relationship considered a deviation from the norm (M Church & Slaymaker, 1989).
The result is likely a reflection of the topography of the catchment with steeper slopes identified in the upper reaches of the catchment to the North where the River Eye main tributary has its source (site 6) and the South where the source of Burton Brook (site 10) originates. The result for Burton Brook (site 10) suggest the hillslope and channel flow paths are well connected to deliver high volume of fine sediment. This is supported by the SCIMAP model which identified Burton Brook to have the highest connectivity and erosion risk due to topographical changes which increase hydrological connectivity to the channel. In these upper reaches splash and sheet erosion are likely to be the main processes generating fine sediments (Osterkamp & Toy, 1997). The results also support previous findings in agricultural catchments where hillslope erosion is often the dominant process for sediment generation,
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Chapter Five: Identifying the sources and spatial patterns of fine sediment compared to river channel erosion. This is reflected by a decrease in SSY in sites located in floodplains compared to upper reaches of the catchment (Walling, 1983; Dedkov and Moszherin, 1992; Osterkamp and Toy, 1997; Church et al., 1999; Slaymaker et al., 2003; Dedkov, 2004).
Sites within the large floodplain of the River Eye (sites 8,9 and 11) reflect literature findings that SSY is decreased assumed to be a result of sediment sinks, storage areas and decreased energy to transport fine sediments in these areas (De Vente & Poesen, 2005). This idea is further explored in chapter six (section 6.7.1) when evaluating the influence of the silt traps.
Perks et al, (2017) compared SCIMAP outputs for in-channel risk to spatial variability in specific sediment yields owing to both datasets providing data at per unit area. The results found a positive correlation with SCIMAP predicting increased sediment delivery in areas of increased specific sediment yield from TIMS results. In the absence of channel risk from the study, the specific sediment yield for the tributaries has been correlated with SCIMAP erosion risk for the corresponding sub-catchments. The results indicate a general positive correlation between the predicted areas of erosion risk and calculated suspended sediment yield for TIMS, though this analysis is only based on four tributaries and therefore is limited in its significance (Figure 5.13).
6 Burton Brook 5
4
Wymondham 3 Eye Trib Whissendine
2
SCIMAP SCIMAP Erosion Risk >0.7 % 1
0 0 2 4 6 8 10 12 14 16 18 20 Specific sediment yield (g day km2)
Figure 5.13 scatter plot depicting weighted SCIMAP erosion risk >0.7 (%) in relation to specific sediment yield calculated by TIMS for four tributaries.
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5.4.2 Temporal trends in suspended sediment mass
To determine the temporal trends in sediment mass transport the daily sediment load (g) was calculated for each collection period (Figure 5.14). The greatest daily load collected by the TIMS was June 16 (sediment collected from January-June 16), which has a median of 553.9g and an interquartile range of 73.3-692g day. In contrast, October 16 collection, covering a sampling period of 35 days had the lowest mass of suspended sediment within the samplers ranging spatially from 18.1-491.5 g day.
The winter/ spring collection in March 17 (sediment collected from October 16- March 17) shows the median daily sediment load of 292.9 g day lower than sampling period of Winter/spring 16 (January-June16) with interquartile range of 54.3-975.0g. The 2017 winter period is considerably lower than previous winter/spring collected in June 16 and may reflect the high water levels changing the position of the TIMS in the water column for prolonged periods of time, though both periods are shown to have low sediment flux. The largest range in sediment flux is observed in May 17 (covering a collection period between March-May) (Figure 5.14). This contrasts results found by Perks et al (2014) who found the largest range of sediment flux during 3rd-30th August 2008 in the River Esk catchment, which consequently in the River Eye is the smallest interquartile range (18.2-491.3g day).
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Figure 5.14 Temporal trends in suspended sediment load *denotes anomalous results and site number associated. Hydrology over the time period has been shown.
Figure 5.15 shows the temporal trend in sediment load for each site indicating which locations are most affected by changes in seasonality. The results in October 16 (sampling period August- October 16) show site 2 at Stapleford farmland and site 5 at Stapleford Woods as collecting a much greater sediment
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Chapter Five: Identifying the sources and spatial patterns of fine sediment yield during Autumn period 2572g day and 5534 g day respectively. During collections at these locations in Autumn 16 bare earth from changes in bank vegetation (site 2) and woodland (site 5) were observed which may explain the elevated results compared to other collection periods. The seasonal trend is also reflected in 2017. In contrast, the main Eye tributary (site 6) shows an increase in sediment load during August 17 (collection from May-August 17) and October 17 (collection from August- October17) collections from an average of 242.2g day for the previous collections to 1156.9g day (August 17) and 1183.3g day (October 17). During these collections the removal of bank vegetation could be observed upstream, and the channel was visibly more turbid suggesting the elevated results reflect the removal of vegetation from the banks. This result highlights a potential hot spot of fine sediment which may need to be explored by catchment managers.
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Figure 5.15 daily sediment load (g) at each site. Sites in blue are on the main channel and sites in grey denote tributaries. At sites where no data is presented reflects no collection during this time period. Results with numbers above them denote the daily sediment load (g) collected.
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5.4.3 Spatial patterns in Organic matter content
The mean organic matter content of the River Eye Catchment is 7.31% (CV76.3%), indicated by the left-skewed distribution (Figure 5.16). The minimum organic matter content 0.11% was recorded at Brentingby Dam in July 16, on the main River Eye. Similarly, the maximum organic matter content was recorded on the main channel at Ham Bridge 37.51% in October 17. Figure 5.16 shows the frequency distribution of percentage organic matter content calculated across the River Eye catchment with 25% of the results falling within 2.5-7.5%. Of the 153 samples collected, 45 (29%) fall between 10-30% the typical range identified by Walling and Webb (1987) for British rivers. 3 (2%) results exceeding the range and the remaining 105 (69%) samples recorded >10%. However, during Clarke & Wharton's, (2001) study of the variability of sediment nutrient characteristics in 17 lowland river catchments in Southern England found organic matter content to range between 2-21%, with 16 rivers recording organic matter contents >10%, suggesting that organic matter represents a smaller component of sediment by weight. Similarly, a study of 60 catchments in Southwest England which used the same methodology to calculate organic matter, found levels to range between 4.5-12.2% (Ankers et al, 2003). The difference in TIMS samplers to suspended storm sediment organic matter content ranges may have results for the following reasons. 1) the storm samples were collected downstream of all TIMS sites where there may be an increase in organic matter. 2) The TIMS may be underestimating the quantity of organic matter due to the chamber being too large to decrease velocity and encourage sedimentation of organic matter within the sampler (6.8). 3) Agricultural practises within the catchment may have an impact on the variation in organic matter content.
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Figure 5.16 Histogram displaying the organic matter content for all samples from the River Eye.
Figure 5.17 shows the range of organic matter content across the catchment. Of the TIMS located on tributaries, Site 1, Whissendine Brook had the largest median value of organic matter content 8.1% (CV48%) even though it has the smallest catchment contributing area 14.2km2. An increased organic matter content suggests the sources of fine sediment are derived locally (Walling & Amos, 1999). The result reflects observations from SCIMAP which identified the Whissendine Brook as having low connectivity, thus sediment within the sources is likely to be locally sourced. Though organic matter usually equates to less than 30% of the total suspended load (Hillier, 2001), its presence can be used to determine the transport of pollutants which can have adverse effects for water quality, suggesting the Whissendine Brook may be a future target of catchment managers for water quality.
Similarly, Site 10, Burton Brook which is regarded by catchment managers and SCIMAP as a tributary with a high sediment delivery has the lowest mean organic matter content of all locations (5.11%). However, the CV value for this
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Figure 5.17 Percentage of organic matter content at each location. The sites coloured in blue represent TIMS situated in the main channel.
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A Mann-Whitney non-parametric test was conducted to determine if there was a statistical difference between the median site values, which ranged between 3.6% (site 10) – 8.8% (site 4). The results showed no statistically significant differences between medians at any location at the 95% confidence level. No further trend was observed in relation to catchment contributing area and organic matter content. The relatively small variation in organic matter content between sites may be a result of the homogenous soil types and agricultural land cover within the catchment. Dense clay soils limit the variation in crops and livestock are reared across the catchment and thus not providing a strong signature in organic matter content. Furthermore, the practise of tilling, a dominant practise in the River Eye catchment, has been found to reduce organic matter content as organic matter is re-ploughed into the soil structure and unavailable for transport (Balesdent et al, 2000).
5.4.4 Temporal patterns in organic matter content
The variation observed at each location of the installed TIMS throughout the sampling period suggests significant temporal fluctuation in organic matter content (Figure 5.17). Figure 5.18, depicts variation during sample collection times temporally at each location, reflecting the ranges shown by the whiskers in Figure 5.17. The results from each collection period show a relatively consistent value of organic matter at each spatial location, indicating the variation occurring at each site is a result of temporal variation in organic matter content. For instance; the organic matter results for March 17 range by 4.3% (9.1-13.4%) across all sites (Figure 5.19). The graph highlights some anomalous results for each temporal collection which are not in keeping with the natural fluctuation observed at most sites (Figure 5.18). For instance, the May 17 collection indicates an increased level of organic matter at site 4 on the main River Eye at Stapleford Golf Course. During this sampling period, the TIMS was surrounded by aquatic vegetation in the channel at this location which may have increased the percentage organic matter content within the sub-sample. A similar result was found in the River Frome, Dorset by Cotton
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August 17’s collection shows an elevated recording at site 6 on the main River Eye tributary. During this sampling period the channel experienced removal of riparian vegetation upstream of the TIMS device, resulting in bare earth banks, which may have led to an increase in increased levels of organic matter entering the tributary. Similarly, the elevated reading at Site 8, Ham Bridge in October 17 may reflect the surrounding bare fields as a result of harvesting in the fields owned by Freeby Estates during this time.
The box plots show a small variation in the D50 between sites; 5.1% (CV79%)– 11.4% (CV 62%). The large CV values at each site are indicated by the whiskers present on the box plot, that highlight the large variation in organic matter content collected at each location during the field campaign.
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Figure 5.18 Scatter graph showing % organic matter content at each TIMS location.
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Figure 5.6 shows an increase in organic matter content during the summer of 2016 with July 16 and August 16 readings higher than the initial collection in June 16. This is in keeping with findings by Perks et al, (2014) who found organic matter levels were highest in the summer during a two year monitoring period in the River Esk catchment. The highest organic matter content readings were observed in October 2017 (collection period August-October 17) which is in keeping with Ankers et al., (2003) who found the highest concentrations of organic carbon were recorded in summer and early autumn. An increase in summer concentrations may reflect the increase in aquatic and riparian vegetation observed within the River Eye catchment, which is complementary to the suggestion that it is a result of increased productivity due to increase daylight hours and rises in temperature during this season (Ankers et al, 2003). The anomalous result observed on main Eye tributary (site 6) during August 17 is synonymous with the daily sediment load data (Figure 5.15) which identified an increase in sediment load due to increased localised bank erosion upstream. The elevated organic matter content during this time period supports the source of organic matter may be local.
However, the observed increase in organic matter 10.7% (CV66%) in March 17 is not in keeping with the expected results of lower organic matter content in the winter months. Collection of sediment samples during the Winter of 2017 were hindered by consistently high water levels, in some locations such as site 11, Brentingby Dam the water level exceeded 2m during the dam closure. The suspended sediment collected during this period may have originated from a source higher in organic content (i.e. fields within the floodplain) as a result of increased hydrological connectivity.
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Figure 5.19 box plot showing percentage of organic matter content for each collection interval.
To determine if the seasonal fluctuations observed in the data were statistically significant a Mann-Whitney U test was conducted on the median values of organic matter content. Unlike the statistical test on the observed spatial differences, the temporal differences did have some statistical significance at the 95% confidence (Table 5.4). Collections occurring in March 17, August 17, and October 17, were identified as statistically significant in collections, with March 17and October 16 significantly higher than average and August 17 significantly lower, indicating a seasonal trend in sediment collections.
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Table 5.4 Mann-Whitney U test results for temporal changes in median values. The light blue highlight the results that are statistically significant p>0.05 with the Bonferroni correction applied.
June July August October March May August October 16 16 16 16 17 17 17 17
June 16 0.026 0.057 0.131 0.000 0.131 0.084 0.000
July 16 0.658 0.061 0.363 0.168 0.038 0.061
August 16 0.418 0.000 0.395 0.002 0.000
October 16 0.000 0.968 0.006 0.000
March 17 0.002 0.004 0.016
May 17 0.002 0.001
August 17 0.001 October 17
The seasonal trend in organic matter content is difficult to discern over a short sampling period of 18 months, particularly when the sampling dates are not consistent in time interval (Table 4.5). To determine if the mass of sediment the sub-sample of organic matter content was derived from influenced the results a regression analysis was conducted to identify any statistically significant differences between sites owing to fluctuations in collection times. Results found no statistically significant relationship indicating the lack of variation between sites was not a function of sampling period, suggesting it refers to seasonal variations.
5.4.5 Spatial trends in particle size distribution
The particle size analysis of samples collected by TIMS samplers showed a diverse range in absolute particle sizes from 0.31 – 954.99µm across the catchment. The range between the D16 – D84 particle size is 1.7 – 279.5 µm, with D50 values ranging between 6.9 - 22.7µm over all TIMS locations. The range of particle sizes indicate a combination of clays (<2 µm) silts >2 - 63 µm) and sands (>63 - 200 µm) and greater sediment sizes are being transported within the catchment. The D50 range is larger than the D50 of 6.2-8.3 µm found
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Chapter Five: Identifying the sources and spatial patterns of fine sediment by Ankers et al (2003) who collected approximately monthly samples from TIMS over a 14 month period.
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Figure 5.20 Box plot indicating particle size distribution of the TIMS samples collected at each location. Box plots represent the D16, D50 and D84 particle size.
The median D16, D50 and D84 particle sizes for each location over the entire study period were calculated to investigate the spatial variation (Figure 5.20). The particle size distribution of each site over the study period had a median range of D16 2.5-3.5µm, D50 8.7 – 15.5µm and D84 34.4-64.8µm values, indicating the main body of suspended sediment travelling within the catchment is a combination of fine and coarse silt and fine sands. Figure 5.20, shows no evidence of downstream fining within the catchment over the study period, emphasised by site 11, the furthest downstream location at Brentingby
Dam having the highest D16 (3.59µm), D50 (15.57µm) and D84 (64.82µm). These results suggest site 11 is transporting locally sourced sediment due to its increase in particle size distribution. Bank erosion from sheep grazing was observed at this location, suggesting a potential sediment source. In addition, the sites proximity to Brentingby Dam may contribute (see section 6).
Site 4, located on the main channel was observed to have the smallest D50 (8.7 µm) and D84 (34.4 µm) values (Figure 5.20), suggesting the suspended sediment transport at this location was the smallest in the catchment. This may
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Chapter Five: Identifying the sources and spatial patterns of fine sediment be a result of river reach being surrounded by dense aquatic vegetation, which would cause a reduction in local flow velocity and therefore its capacity to transport larger particles (Cotton et al., 2006). This result supports Walling et al’s (2005) sediment fingerprinting study using TIMS which found a positive trend in organic matter content increasing as particle size decreased. Similarly, site 11 Burton Brook was identified as the tributary with the smallest D16 and D50 values, which was a location with a small catchment contributing area, small channel and very low velocities. In contrast, site 1 Whissendine Brook tributary has the highest D16 and D84 (11.9µm and 64.7µm Figure 5.20) values of the tributaries, suggesting it is a source of coarse sediment. A non parametric Mann-Whitney U test was used to determine if the differences between sites for D16, D50 and D84 were statistically significant. Whilst the majority of results between sites were found not to be statistically significant (Table 5.5 Table 5.6,Table 5.7) Whissendine Brook (Site 1) was found to be statistically different from sites at, Stapleford golf course (site 4) and Burton Brook (site 10) at D50 and sites 4,5,6 and10 in D84 suggesting this site is significantly coarser than these locations. In contrast, Burton Brook tributary was found to be statistically different from site 1 in D50 and D84 suggesting this tributary is significantly finer than the Whissendine Brook sediments. The results are in keeping with observations made in potential sediment sources during SCIMAP modelling where, Whissendine Brook was found to be poorly connected and sediment sources locally derived which is in keeping with larger particle sizes as downstream fining has not occurred. Similarly, Burton Brook which was identified as highly connected has some of the smallest particle sizes recorded, which is in keeping with the SCIMAP results. The relatively homogenous geology, soil type and land cover variation within the catchment may explain the absence of statistically significant Mann Whitney tests between sites.
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Table 5.5 D50 median mann whitney test the results in blue indicate results that were statistically significant (p <0.05) with the Bonferroni correction applied
Sites 1 2 3 4 5 6 7 8 9 10 11 1 0.02 0.68 0.01 0.27 0.09 0.42 0.95 0.52 0.01 0.77 2 0.22 0.87 0.27 0.87 0.17 0.1 0.08 0.37 0.49 3 0.08 0.37 0.22 0.56 0.87 0.84 0.06 0.49 4 0.05 0.42 0.03 0.04 0.033 0.96 0.155 5 0.42 0.65 0.27 0.95 0.05 0.79 6 0.27 0.08 0.4 0.42 0.27 7 0.4 0.57 0.04 0.95 8 0.47 0.03 0.87 9 0.08 0.95 10 0.27
11
Table 5.6 D16 Mann Whitney. the results in blue indicate results that were statistically significant (p <0.05)
Sites 1 2 3 4 5 6 7 8 9 10 11
1 0.27 0.87 0.06 0.95 0.95 0.72 0.33 0.72 0.02 0.87
2 0.32 0.96 0.27 0.16 0.14 0.08 0.48 0.71 0.27
3 0.19 0.96 0.96 0.75 0.43 0.85 0.08 0.50
4 0.04 0.19 0.01 0.02 0.14 0.50 0.23
5 0.87 0.95 0.27 0.95 0.02 0.71
6 0.65 0.43 0.65 0.05 0.96
7 0.27 0.69 0.00 0.95
8 0.33 0.01 0.71
9 0.17 0.65
10 0.27 11
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Table 5.7 D84 Mann Whitney results. The results in blue indicate results that were statistically significant (p <0.05) with the Bonferroni correction applied.
Sites 1 2 3 4 5 6 7 8 9 10 11
1 0.07 0.27 0.00 0.00 0.00 0.04 0.68 0.43 0.01 0.77
2 0.37 0.23 0.56 0.37 0.85 0.32 0.48 0.64 0.43
3 0.02 0.06 0.07 0.33 0.96 0.85 0.07 0.87
4 0.23 0.37 0.11 0.05 0.06 0.43 0.05
5 0.71 0.33 0.13 0.14 0.96 0.16
6 0.40 0.10 0.14 0.96 0.16
7 0.27 0.69 0.40 0.48
8 0.95 0.16 0.96
9 0.22 0.95
10 0.23 11
5.4.6 Temporal trends in particle size distribution
The median D16, D50 and D84 values have been calculated for each collection period to explore the temporal trends in particle size (Figure 5.21). The median D16 values across the sampling period vary by 1.5µm, from 1.9- 3.4µm. Similarly, the D50 has a small variation of 4.8µm ranging from 7.9-12.7µm, whereas the D84 has a much larger variation of 36.6µm from 24.0µm-60.6µm. The ranges observed in D16, D50 and D84 are all from the same time periods, with the smallest occurring in March 17 (representing the winter period from October16-March17) and the largest values in October 17 (representing the winter period of August-October 17).
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Figure 5.21 Temporal variation in particle size: indicating the D16, D50 and D84 particle sizes for each collection period. Hydrology during the sampling time period has been plotted below. Figure 5.21 indicates that samples from summer periods such as August 16 (July-August 16) and August 17 (May-August 17) D50 11.5 have higher D50 (12.1µm and 11.5µm) and D84 (54.6µm and 59.8µm) values than those observed during winter periods in March 17 (October16-March 17). This trend differs to temporal trends identified by Perks (2014) in the Esk Catchment where winter sample collections in January 2008 and 2009 were observed to have the highest D50 values, due to an increase in winter high flows during these periods. Though the temporal trend observed by TIMS samplers is unusual the suspended storm samples taken in Feburuary and March 2016 (Table 5.3) are in keeping with similarly observed particle size ranges.
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Figure 5.22 displays the spatial variation in particle size distribution (laterally) and the temporal variation (longitudinally) for each TIMS location. Results for collection 1-2 (June 16 and July 16) show a relatively consistent D50 particle size range across all sites of 9.1-14.3µm (June 16) and 8.6-11.2µm (July 16). The early summer collections also suggest evidence of downstream fining in these locations with site 11 having the smallest D50 values recorded within the catchment. Collections in August and October 16 show sites 8, 9 and 11 to have an increased D50 and D84 values, indicative of coarsening during autumn periods. Site 8 and 11 are located upstream of Ham Bridge silt trap and Brentingby Dam and further analysis in chapter six will discuss these results (see section). Site 9, located within SSSI recorded a D84 value of 255µm in August 16. Comparison with other collection from the same TIMS at this location (Figure 5.23) suggest this result is an anomaly potentially caused by the sample not being fully deflocculated before measuring particle size in the mastersizer.
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Figure 5.22 Temporal changes in particle size analysis over the sampling period
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Figure 5.23 shows the variation in particle size distribution over the 21 month study period. Samples analysed from sites 3,4,5,6,7 show a consistently similar particle size distribution, depicted by the overlapping collection samples, suggesting that these locations do not vary widely in season. Site 7 located at on the main river eye by Stapleford cottages has a small D16 2.7-3.2µm and D50 9.4-13.0µm range though the D84 range is greater 35-66 depicted by the divergence at the top of the graph. However, this may be a result of variance in D84 (see 5.3.2). The sites identified above are situated on or around Stapleford Estate which is predominately cultivated grassland and therefore physical catchment features such as land cover and geology are unlikely to alter sediment delivery seasonally. Consistency in particle size would suggest either sediment sources which are physically similar throughout the catchment, or no additional sediment sources which may increase particle size distribution.
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Figure 5.23 Cumulative Particle size distribution graphs for each TIMS location, depicting temporal trends in sediment sizes.
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5.5 Chapter summary
This chapter sought to identify the potential sources of fine sediment and the spatial patterns of in-channel transport within the River Eye catchment. The suspended storm samples collected during high flow events in February and March 2016 have successfully been used to validate the laboratory methodology using native sediment from the River Eye. The SCIMAP results identified the sub-catchments of Burton Brook and Langham Brook as areas of high sediment connectivity and erosion risk suggesting these are likely areas of sediment sources. This result was supported by sediment yield calculations from installed TIMS devices which found Burton Brook is the highest contributor of fine sediment per km2 of 17.4g km2 day.
The TIMS sediment load calculations identified the Eye main tributary as the tributary with the highest sediment load of 499.9g day, which reflected hot spots of connectivity observed during the SCIMAP model. Further temporal analysis of sediment load observed the high sediment load is a result of increased fine sediment delivery in August and October 17 due to removal of bank vegetation. An elevation of organic matter content to 13.5% supported the observation of local bank erosion being a likely source of fine sediment throughout the catchment. Changes in land cover risk weightings identified arable land as having the largest impact on erosion risk, suggesting management of fine sediment on these fields is vital to reducing connectivity to the River Eye.
The SCIMAP model successfully identified areas of catchment connectivity and erosion risk for the catchment and sub-catchment scale. Overall, connectivity and erosion risk in the catchment was low due to small changes in topography, suggesting the sediment collected by TIMS in channel is a result of local sources such as bank erosion. The addition of a DSM layer which included surface features such as roads and footpaths was shown to increase catchment connectivity as did increased rainfall predictions for future climate scenarios. The addition of in-channel TIMS data provided an indication of suspended sediment spatial patterns identifying sites on the main channel,
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Chapter Five: Identifying the sources and spatial patterns of fine sediment particularly Stapleford woods (site 5) upstream of Ham Bridge silt trap, as having significantly higher fine sediment loads than downstream, which is indicative of the silt traps effectiveness.
The spatial particle size analysis from TIMS indicates limited evidence of downstream fining, suggesting that spatial patterns of fine sediment transfer are not throughout the catchment and in-channel sediment is likely attributed from local sources. This result contradicts the specific sediment yield analysis which identified a negative trend in yield as catchment contributing area increased, suggesting sediment sources were limited to the upper reaches of the catchment and tributaries such as the Burton Brook. Alternatively, the particle size analysis results may reflect the sources throughout the catchment have the same physical attributes owing to the similar geology and soil type, which would coincide with the SSY-area results. To fully determine the spatial patterns of fine sediment the influence of the silt traps must be examined to determine its impact on downstream fine sediment transport and verify the results in this chapter which suggest they are effective.
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Chapter Six: Geomorphological and Hydrological appraisal of installed flood management assets 6 Chapter Six Geomorphological and Hydrologic appraisal of installed flood management assets
6.1 Chapter Scope
This chapter explores the efficiency of two features: the current flood defences installed within the River Eye catchment and the use of TIMS as a method of collecting representative suspended sediment samples. The chapter is divided into four main sections: The first refers to sections 6.2, 6.4 and 6.5 which evaluates the suspended mass, organic matter and particle size of suspended sediment upstream and downstream of the silt traps located at Ham Bridge and Burton Brook and the Dam installed at Brentingby to determine their geomorphic efficiency. The second section 6.3 investigates the hydrological implications of established NFM silt traps on water level. The third section 6.6 determines whether the silt traps are effective at reducing sediment load. Section 6.7 discusses the relative efficiency of adjacent samplers installed up/downstream of these features and section 6.8 the limitations associated with this sampling technique. The final section 6.9 evaluates the hydrologic and geomorphic effect of the flood defences and its implications for flood management.
6.2 Ham Bridge Silt Trap
Ham Bridge silt trap is located on the main River Eye channel is the upstream NFM flood defence for the catchment (Figure 3.7). Over a 21 month period 4 TIMS were installed, 2 upstream and 2 downstream of the silt trap, though the TIMS installed on the left downstream was damaged and unable to collect sediment during August 16- March 17.
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Chapter Six: Geomorphological and Hydrological appraisal of installed flood management assets 6.2.1 The effectiveness of Ham Bridge silt trap at retaining fine sediment
a) b)
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200 Load( 200 TotalLoad ( 100
0 0 Upstream Upstream DownstreamDownstream Upstream Upstream Downstream Downstream Left Right Left Right Left Right Left Right
Figure 6.1 Total sediment load (kg) for study period (a) and relative sediment load (g day-1 (b) collected at Ham Bridge Silt Trap The total mass of dried suspended sediment collected from each TIMS during the monitoring period was used to calculate the sediment load (g) for each sampler. Figure 6.1a shows the toal sediment load (kg) for the sampling period for each TIMS. The upstream TIMS are shown to have a higher sediment load (622.2 kg and 384.8 kg) than the downstream TIMS (206.2 kg and 363.9 kg) suggesting the silt trap is effective at reducing the suspended sediment load. This result reflects the sediment load findings in chapter five where sediment daily load was seen to decrease by 95% (Figure 5.10). However, the results of the upstream and downstream TIMS do not reflect the same reduction in sediment load (54% on left side of channel, 5% on right side of the channel). Due to significant period of time the downstream left sampler was absent, it does not provide a direct comparison for the study, though the daily suspended load is shown in (Figure 6.1b).
The daily load results indicate from upstream right to downstream right 5% decrease in sediment. The differences observed between adjacent samplers may reflect a variation in flow rate through the sampler. Velocity measurements taken across the channel in October 2017 showed an average variation of 0.02 and 0.026 m/s-1 at the positions of the upstream right and left
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Chapter Six: Geomorphological and Hydrological appraisal of installed flood management assets TIMS samplers respectively. The differences measured suggest that the flow rate through the sampler may also have varied, causing the left TIMS to collect more sediment than the right. Variation in adjacent TIMS was observed by (Schindler Wildhaber et al, 2012) who installed six samplers in one location and found a variation of 12-100% in mass retention over a weekly period.
Figure 6.2 shows the temporal variation in the sediment load throughout the monitoring period. Figure 6.2a shows the silt trap is successful at reducing the suspended sediment load downstream (in all TIMS) in 5/8 collections (June16, August 16, March 17, May17 and October 17). Collections which occurred during the winter/ spring such as June 16 (January-June 2016) and March 17 (October-March 2017) contain the largest suspended sediment load upstream of the silt trap measured at 431.7 g day-1 (left) and 213.0 g day-1 (right) in June 2016 and 115.5 g day-1 (left) 116.1g (right) March 2017. In contrast, the collections occurring over the summer had considerably less suspended sediment load. Collections from both July and August 2016 have a daily deposition in July 16 of 0.1 g day-1 (left) and 0.1 g day-1 (right) (Figure 6.2b). These results are 97% smaller compared to June 2016 3.4 g day-1 (left) and 1.7 g day-1 (right). The reduction in general sediment load during summer collections may also explain why the silt trap at Ham Bridge appears less effective.
In July 16 and August 17, the collections show downstream TIMS collecting a greater sediment load upstream. For instance, in July 16 87% more sediment in left sampler and 99% more sediment in the right sampler, suggesting the silt traps at Ham Bridge is not reducing the suspended sediment load downstream. TIMS have been shown to directly correlate sampling efficiency with increasing flow velocities (Hatfield & Maher, 2008; Perks et al, 2014; Russell et al, 2000), providing a more representative sample during higher flow velocities. This may also explain the potential reason for the silt traps appearing less effective in the summer months when flows are lower.
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Figure 6.2 (left) sediment mass collected (g). (right) daily sediment load (g day-1)
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Chapter Six: Geomorphological and Hydrological appraisal of installed flood management assets 6.2.2 Organic matter
The percentage organic matter recorded at each TIMS location at Ham Bridge shows a narrow range in 25th percentile between 2.01 – 4.37%, and 75th percentile 13.38-15.90% indicating a consistency in the levels of organic matter collected by the TIMS. The greatest variation observed in the median organic matter content which was calculated as higher upstream (7.01% and 7.48%) on average than downstream of the silt trap (6.93% and 3.57%), suggesting that the silt trap does encourage the deposition of sediments which carry organic matter. The reduction in sediment load suggests less sediment is downstream of the silt trap and these results suggest the sample contains less organic matter see 6.2.1.
Figure 6.3 box plot depicting percentage of organic matter content collected at each location upstream and downstream of Ham Bridge silt trap. Point 5 represents the anonmoulous result of 37% organic matter calculated for the TIMS installed upstream of the silt trap on the left of the channel. The percentage coefficient of variance in organic matter was calculated for each TIMS location: upstream of the silt trap: 62.7% (left) 70.9% (right) and downstream of the silt trap 67.7% (left) and 96.2% (right). The results suggest
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Chapter Six: Geomorphological and Hydrological appraisal of installed flood management assets a large degree of variation in organic matter content which is likely to be result of seasonal fluctuations. Figure 6.4 shows the temporal variation in organic matter content over the monitoring period and temporal spacing between sample collections.
20 18 16 14 12 10 8
% organic % matter 6 4 2 0 Jan-16 May-16 Aug-16 Nov-16 Mar-17 Jun-17 Sep-17 Dec-17
Upstream Left Upstream Right Downstream Left Downstream Right
Figure 6.4 scatter graph representing the calculated %organic matter content value for each collection over time. Upstream left TIMS is missing the results from August and October 2017 due to two anomalous results of 37%, previously depicted on Figure 6.3 and 92%. The organic matter results from October 16 – October 17 show less up/downstream variation in percentage organic matter content in each collection than results in June-October 16. Furthermore, the collections in March 17 and October 17 represent winter and autumn collections and are shown to have a higher organic matter content than samples collected in the spring (May 17) and summer (August 17), which are in keeping with the sediment mass results.
Summer collections in June, July and August 2016 show the largest up/downstream range in organic matter content (Figure 6.4) with June 16 showing an 3.9% (left) and 16.6% (right) increase in organic matter content downstream of the silt trap. In contrast, July 16 results show a decrease of 2.4% (left) and 12.7% (right) of organic matter content downstream of the silt trap. In 5/8 collections the downstream TIMS are observed to have a greater organic matter content than upstream, which may indicate a reactivation of sediment deposited within the silt trap.
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Chapter Six: Geomorphological and Hydrological appraisal of installed flood management assets Many of the organic matter content results are below the expected observed levels in UK rivers 10-30% (Walling et al, 2008), particularly in the summer months. However, a study on lowland catchment in southeast of England found organic carbon content of suspended sediment to range between 4.5- 12.2% (Ankers et al, 2003) which reflects a similar range found in this study of 0.77- 18.56%. The observed difference in organic matter content may be a result the TIMS are failing to comprehensively capture the finest component of the suspended sediment load (see section 6.2.3). However, the silt traps may not be an effective method of increasing water quality if many flocculants remain in suspended flow.
Upstream of the silt trap the samples collected by the adjacent TIMS show consistent results. Of the samples collected 6 of 8 samples are within 1% of each other for percentage of organic matter, indicating the TIMS successfully collected a consistent sample. However, in August 16 and October 17 there are considerable differences of 8.1% and 24.5% respectively, this may be a result of the sub-sampling methodology. The adjacent samplers downstream of the silt trap recorded percentage organic matter content differences for the sample collections in June, July and August 2016 of 12.2%, 10.3% and 4.6% respectively, indicating that the samplers were not collecting chemically similar samples. After the removal of the left TIMS due to damage, the replacement sampler installed in March 2017, recorded percentage organic matter content differences in May, August and October 2017 as 1.16%, 1.21% and 1.5% respectively. During this time period the newly installed TIMS collected more sediment that its adjacent TIMS situated on the right side of the channel (Figure 6.2). The results show the TIMS are sensitive to their position within the reach, particularly where morphological features such as silt traps can affect suspended sediment transport and local flow velocities.
6.2.3 Particle Size
The particle size analysis for Ham Bridge silt trap shows a consistent range of sediment 0.36-724µm for every TIMS device (Figure 6.5). There is also a minimal observed difference in D16 values upstream (3.3 µm) and
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Chapter Six: Geomorphological and Hydrological appraisal of installed flood management assets downstream (2.7 µm). These results contrast the organic matter content results as the observed decreased in organic matter downstream of the silt trap is not reflected in the D16 values, where organic matter is likely to travel. The D50 average of all four samplers ranged between 10.1-12.6 µm and were found not to be statistically significant from each other. However, the D84 values show a fining downstream of the silt trap where the D84 particle size has reduced on the left and right TIMS by 18.9µm and 13.0µm respectively. The reduction in the coarser component of the samples collected suggest the silt trap encourages deposition of larger particles due to the decrease in velocity within the silt trap, though this result was not statistically significant. However, due to the consistent overall range above and below the silt trap it does not remove the largest component entirely. The reduction in coarser fine sediments may indicate the silt traps are also reducing the transport of coarse sediment downstream. The preferred reduction in coarse sediment transport downstream may impact the availability of spawning sites for fish, which is a concern for the SSSI situated 0.1km downstream.
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1 Ham Bridge US L Ham Bridge US R Ham Bridge DS L Ham Bridge DS R
Figure 6.5 Particle size distribution box plots for each TIMS location at Ham Bridge. The box represents the D16, D50 and D84 values and error bars represent the range of particle sizes.
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Chapter Six: Geomorphological and Hydrological appraisal of installed flood management assets Downstream of the silt trap the adjacent TIMS installed showed greater differences in particle size than upstream samplers, the right TIMS particle size distribution was found to be coarser, particularly for the D84 (38.4µm left and 46.0 µm right). Temporal fluctuations show that left side TIMS is consistently smaller than right (Figure 6.6) which may reflect the results found insection 6.2.1 where sediment load in the left TIMS was lower than the right due to it being installed in the centre of the channel but outside of the dominant flow path where water has more energy to transport larger suspended sediment particles (Slattery & Burt, 1997). The results complement the study conducted Stone and Walling, (1997) who found statistically significant differences in median particle sizes between autumn and winter seasons to those measured in spring and summer. The results suggest that coarsening of median sediment in spring/summer is indicative of sediment source availability being responsible for sediment size, not the flow of water.
Temporal fluctuations depict that the particle size distribution recorded for each sub-sample is not consistent between samplers. For instance, in August 2016 the TIMS upstream left has a D50 23.9 µm and D84 208.4 µm higher than upstream right and in comparison, the upstream right TIMS has D50 of 8.2 µm and D84 of 54.44 µm greater than upstream right TIMS in March 2017 (Figure 6.5). The observed differences in adjacent particle size during different sampling periods may reflect a limitation in TIMS deployment. Though care was taken to ensure TIMS were reinstalled after each collection to the same channel depth, changes in D50 and D84 samples may be a result of sampling in different depths of the water column.
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Figure 6.6 Temporal variation in particle size distribution for each TIMS over time. Dark blue represents upstream left, dark green upstream right, light blue downstream left and light green downstream right. The temporal variation in particle size distribution (Figure 6.6) does not conclusively show particle size distribution decreasing downstream of the silt trap. On 4/8 occasions (July 16, August 16, October 16 and October 17) the D16, D50 and D84 are smaller downstream from both adjacent samplers than the equivalent TIMS upstream, suggesting during summer/autumn sampling periods the silt trap encourages the deposition of larger particles. However, This may be a result of the TIMS chamber not reducing the velocity of the water through the inlet enough to encourage maximum deposition of the finest particles of suspended sediments. However, if these particles are remaining in suspension within the TIMS then it is likely that they will deposit downstream, reducing channel capacity and therefore increasing flood risk.
6.3 Hydrological appraisal of Ham Bridge Silt Trap
To determine the hydrologic implications of installed online silt traps three divers were installed to measure water level upstream of Ham Bridge silt trap. (Figure 6.7) shows the flow data collected during March 17 – January 18 and the five events that were selected to determine the silt traps influence on water level at low flows and during the five high flow events (Figure 6.7). The peak of the hydrograph for each diver location was recorded in addition to 6
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Chapter Six: Geomorphological and Hydrological appraisal of installed flood management assets randomly selected time intervals; 3 on the rising limb and 3 on the falling limb (Figure 6.9). The storm events selected reflect a spring (event 1), summer (event 2) and winter (events 3,4,5) hydrographs.
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Figure 6.7 water level data collected by three divers upstream of Ham Bridge silt trap during February 17 - January 18.
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Chapter Six: Geomorphological and Hydrological appraisal of installed flood management assets During the low flow events three time intervals were chosen to compared water surface elevation upstream of the silt trap (Figure 6.8). A bed elevation survey of the river bed at each location determined a 2cm increase in elevation between site 1 (0m) and site 2 (57m) a further 26cm increase was recorded at site 3 (167m). The small difference in bed elevation between site 1 and site 2 may be indicative of deposition at site1 due to the influence of the silt trap. Ham Bridge silt trap is an artificially widened and deepened area of channel and thus can be assumed to have similar upstream impacts as dredging where increased cross sectional area and roughness reduce velocities through the dredged areas. Deposition upstream of the dredged site is a common channel adjustment as water velocities reduce and sediment is encouraged to deposit as the river attempts to re-establish a stable gradient (CIWEM, 2014). Figure 6.8 indicates that during periods of sustained water level throughout the year, the surface water mimics the shape of the bed profile, suggesting the silt trap has no impact on upstream river stage.
Figure 6.8 Surface water elevation plots for three low flow events. Bed elevation is shown in black.
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Figure 6.9 Hydrographs of five storm events for divers installed upstream of Ham Bridge silt trap. Dashed lines represent 3 rising limbs, the point at which each diver recorded peak water level and 3 falling limb.
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Chapter Six: Geomorphological and Hydrological appraisal of installed flood management assets The silt trap can also be seen to influence water level in similar trends during events 1,3 and 4 which took place in May and December 2017 (Figure 6.10). The steep rising limbs depicted in (Figure 6.9) show a decrease in surface water elevation from site 1 to site 2 which is not represented in the bed elevation (Figure 6.10). The dipped curves suggest an artificial increase in water level occurring at site 1 (silt trap) due to the backing up of water as velocities decrease in response to the sudden channel morphological change (Fisher, 1992; Gob et al, 2005). Similar results where upstream water level was increased due to lowering of velocities was observed during the installation of a weir on the River Stour (Fisher, 1992). Studies investigating the impact of dredging on water level have found the reduction of water level during a flood is minimal (Gob et al, 2005), suggesting water levels within the silt trap may also be minimally effected.
During the peak of events 1 and 4 the hydrograph shows similar water levels at site 1 (1.32m event 1 & 2.35m event 4) and site 2 (1.26m event 1 % 2.27m event 4), suggesting the impact of the silt trap is propagating upstream to site 2 during the flood peak(Figure 6.10). The similar water levels recorded during event 3 show the same change in rising limb surface water elevation and the peak. The results are supported by the volume table displayed (Figure 6.10) for event 4 where the volume of water at site two increases by 8.44m3 and site one 6.15m3 in the same time scale (7hours 26mins). In contrast, event 4 shows the peak event to have negative gradient, indicating that at higher flows the effect of the silt trap can propagate further upstream causing water level to be higher downstream than upstream due to the backing up of water from the silt trap. However, during a pilot scheme for channel dredging at Hinksey Oxford water levels were observed to decrease by 120mm in usual flows but only 40mm in high flow events. The reduced water level in the dredged area was determined to be result of external controls such as bridges and floodplain restrictions as opposed to the channel capacity and morphology. Owing to Ham Bridge’s proximity approximately 10m downstream of the silt trap, potential observed backing up in high flows may also be related to the bridge structure (CIWEM, 2014).
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Chapter Six: Geomorphological and Hydrological appraisal of installed flood management assets Bed Elevation Rising Limb Falling Limb Peak
Figure 6.10 Suface water elevation plots during storm events showing water level at each location in accordance to Figure 6.9 (left). Volume of water calculated within the cross section at each location (right).
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Chapter Six: Geomorphological and Hydrological appraisal of installed flood management assets The surface water elevation measured on the falling limbs for all events show a similar trend; a flatter elevation gradient (depicted by the straightened blue lines) compared to the rising limbs (curved orange lines). Event 3 provides a clear example where similar water levels for the rising and falling limbs were selected (Figure 6.9) but the surface water elevations are different (Figure 6.10), for example the water level at site 2 is 4cm different on the rising limb 3 (event 3) to falling limb 1 (event 3) but the surface water elevation shows 28cm difference, suggesting a greater backing- up effect on the receding limb. The increase in water level on the falling limb at site 2 suggests the backing-up effect due to the silt trap is present at this location. This is supported by the cross-sectional volumes recorded at site 2 for the similar water levels observed at site 1 and site 3. There is an increased volume of water of 1.93m3 between rising limb 3 and falling limb 1 and 0.87m3 between rising limb 2 and falling limb 2, indicative of a rise in water level at this location. The same effect is observed during event 4 where the higher water levels show the water level being impacted 167m upstream at site 3.
During the largest water stage levels which occurred in event 5 (29th-1st January) the rising limb for the first two measurements located on the steepest gradient of the hydrograph (Figure 6.10) show a similar shape to those recorded in events 1,3 &4 where the exaggerated dip at site 2 suggests a backing up of water artificially increasing water level at site 1. During the peak flow where water levels recorded 2.44m at site 1 the water surface elevation shows a flat line indicative of water level propagating upstream. The falling limb shows an inversion to the bed elevation indicative of the artificial water level propagating upstream, reflected in the smaller distance between flow lines in the hydrograph (Figure 6.9). The final water level measured approximately 27 hours later shows a return to similar surface water conditions, suggesting the influence of the silt trap may be limited to this shorter time period.
The impact of the silt trap is diminished during lower rainfall events such as event 2 (22nd-28th July 2017), where all surface water elevations measured (figure) mimic the bed elevation. The results suggest that low rainfall events
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Chapter Six: Geomorphological and Hydrological appraisal of installed flood management assets such as event 2 where maximum surface elevation is 0.78m have no artificial elevations from the silt trap. This result is supported by the calculated volumes for each location which show no evidence of prolonged water levels.
The evidence presented by the water surface elevation plots and calculated channel volumes for each site suggest the silt trap does have the capability to artificially increase river level upstream during all the selected events. However, during largest events such as event 5 the effects are seen to propagate further upstream and remain for a longer period of time.
The suspended sediment data collected by the TIMS devices for May 17, August 17 and October 17 reflect the findings of the surface water level analysis. Samples collected in May 17 reflect the hydrograph period between March- May 17 where a series of higher flows can be identified (Figure 6.7). Increased water levels upstream of the silt trap can cause aggradation (Fisher, 1992)(Environment Agency, 2014), reflected by the increased suspended sediment load (Figure 6.1). Similarly, the hydrographs and selected events covering the August (May-August 17) and October (August-October 17) collections show a lower sediment load, indicating minimal deposition upstream as the influence of the silt trap is diminished.
6.4 Burton Brook Silt Trap
Burton Brook silt trap is located on a tributary in the South East of the River Eye catchment. 4 TIMS were installed at this location, 2 upstream and 2 downstream of the silt trap located at Burton Lazars (Figure 4.9).
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a) b)
200 350 180 300 160
140 ) 250
1 - 120 200 100 80 150 60 (Load g day 100 40 TotalLoad (Kg) 50 20 0 0 Upstream Upstream Downstream Downstream Upstream Upstream Downstream Downstream Left Right Left Right Left Right Left Right
Figure 6.11 Total sediment load (kg) for study period (a) and relative sediment load (g day-1 (b) collected at Burton Brook Silt Trap The TIMS situated upstream of Burton Brook silt trap had a greater suspended sediment load than downstream (Figure 6.11a). The results indicate that the silt trap in this location is effective at reducing the sediment load from 175.8kg and 158.3kg to 79.9kg and 91.7kg. This equates to a 54.6% (left) and 42.2% (right) reduction of suspended sediment load downstream of Burton Brook (Figure 6.11a). A Mann Whitney U test determined the upstream and downstream TIMS results were statistically significant at 95% confidence, suggesting the Burton Brook silt trap is effective at reducing suspended sediment load downstream.
The results from each collection period shows that the one or both of the TIMS situated upstream of Burton Brook silt trap consistently collected more suspended sediment than the TIMS situated downstream (Figure 6.12). The largest sediment load from a single collection was from January -June 16 where the upstream samplers collected 69.8g and 39.7g of suspended sediment and the downstream samplers recorded 36.9g and 19.6g. The large volume reflects the winter and spring collection which was also the highest observed sediment load at Ham Bridge silt trap, potentially as a result of the samplers being installed for the longest period (126 days). The daily yield (Figure 6.11b) standardises the temporal variability in sample collections to a
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Chapter Six: Geomorphological and Hydrological appraisal of installed flood management assets comparable daily rate to all sample collections. The results shows that July 16 has the highest sediment yield upstream of the silt trap.0.6 g day-1 (left) and 0.9 g day-1 (right). The collections which cover the Winter (June 16 and March 17) have the 2nd and 3rd highest sediment daily yields upstream 0.5 day-1 (left) ,0.28 g day-1 (right) and 0.24 0.9 g day-1 (left) and 0.4 g day-1 (right), suggesting winter seasons that winter collections carry a higher volume of suspended sediment. However, a Mann Whitney U test found no statistically significant temporal trends in suspended sediment load.
During collections in August 17 (sampling between May- August 95 days) and October 17 (sampling between August- October 59 days) the TIMS located on the right of the channel downstream of the silt trap showed a 146.1% and 5.17% increase in the mass of suspended sediment captured compared to the adjacent sampler on the left. This may be a result of observed bank erosion on the right hand bank during these collection times which occurred when accessing the channel to empty TIMS.
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Figure 6.12 (left) sediment mass collected (g). (right) daily sediment load (g day-1) at Burton Brook
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6.4.2 Organic matter
The organic matter content at Burton Brook has a range across all samplers from 1.1-24.9%. The median organic matter content values are all below 10% (Figure 6.13), suggesting that the stream is not within the typical range of organic matter for UK rivers (10-30%) (Walling et al, 1998) for much of the year. The interquartile range for each TIMS indicates that organic matter is sensitive to seasonality, supported by high coefficient of variation scores upstream left (79.2%), upstream right (82.9%), downstream left (69.6%) and downstream right (71.6%).
Figure 6.13 Organic Matter content box plot for each TIMS installed at Burton Brook silt trap
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15 % 10
5
0 Jan-16 May-16 Aug-16 Nov-16 Mar-17 Jun-17 Sep-17 Dec-17
Upstream Left Upstream Right Downstream Left Downstream Right
Figure 6.14 Spatial and temporal variation in organic matter content at Burton Brook silt trap Figure 6.14 shows the spatial and temporal variation in percentage organic matter content up and downstream of Burton Brook silt trap. The results indicate a temporal fluctuation in organic matter where summer collections in July 16, May 17 and August 17 are comparatively lower than winter and autumn collections in March17 and October 17. These results reflect observations made in March and October 17 where bank vegetation was greatly reduced and riverbanks showed signs of active erosion. In addition, surrounding fields were left ploughed with no crop coverage, increasing the potential for surface water runoff delivering topsoil to the channel.
Most of samples collected for each time interval have similar values across the four TIMS, resulting in the values appearing grouped together in the scatter graph (Figure 6.14). However, in August 16, October 16 and October 17 the TIMS situated downstream of the silt trap on the left showed spikes in organic matter content of 14.1%, 23.8% and 17.7% respectively (Figure 6.14). These increases in organic matter content in late summer and autumn reflect the findings of Ankers (2003) who observed organic (carbon) matter peaked due to increased leaf litter vegetation from increased vegetation growth occurring during summer. In addition, Perks et al (2014) found a peak in organic matter content in both hydrological years of the study period. The same increase in organic matter was not reflected in the downstream right TIMS device suggesting that the organic matter content travelling in the suspended load
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Chapter Six: Geomorphological and Hydrological appraisal of installed flood management assets was not uniform across the channel. Both upstream and downstream locations were heavily vegetated which may have resulted in increased organic matter content within the TIMS. There appear to be no conclusive trends regarding upstream and downstream of the silt traps indicating silt traps do not encourage the deposition of organic matter content. This may be a result of organic matter representing one of the finest components of fine sediment and therefore are able to remain in suspended load at low velocities such as those created by the silt trap. Changes in agricultural practises, for instance the introduction of no tillage ploughing to the area upstream of the silt trap (Figure 6.15) which is used to retain nutrients on the land may also explain why the organic matter values are low for this tributary.
Figure 6.15 Taken from field adjacent to Burton Brook showing the no till technique which aims at retaining nutrients in the soil 6.4.3 Particle size analysis
The range of absolute particle sizes detected in the Burton Brook is 0.32- 724.4µm and was found to be consistent with all four installed TIMS sub- samples (Figure 6.16). This result suggests the silt trap does not change the particle size distribution such as the largest particle sizes. In addition, the result
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Chapter Six: Geomorphological and Hydrological appraisal of installed flood management assets suggests the adjacent TIMS are manufactured to collect the same range of sediment sizes, indicating that any algae growth or potential blockages did not prevent a representative sample from being captured. The D16 average values show a small decrease in particle size of 0.9µm (left) and 0.5µm (right) from upstream to downstream of the silt trap. However, a Mann-Whitney U non- parametric test found no statistically significant differences in the upstream and downstream values. A greater difference can be observed in the D50 (-12.0µm left -7.1µm right) and D84 (11.9µm left + 5.9µm right). These results are in keeping with those found at Ham Bridge silt trap that the larger fine sediment particles are being deposited within the silt trap. Statistical analysis between upstream and downstream D84 values show no statistical significance at the 95% confidence level (p>0.05).
1000
100 µm)
Particle Particle ( Size 10
1 Burton Brook US L Burton Brook US R Burton Brook DS L Burton Brook DS R
Figure 6.16 Particle size distribution box plots for each TIMS location at Burton Brook. The box represents the D16, D50 and D84 values and the error bars depict the range in particle size.
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Figure 6.17 Temporal variation in particle size distribution for each TIMS over time. Dark red represents upstream left, dark orange upstream right, light red, downstream left and light oranage downstream right. Figure 6.17 shows the temporal fluctuations in samples collected over the study period. The D16 and D50 values have a narrow range of 1.3-2.8µm and 6.3-12.2µm respectively with largest particle sizes observed in August and October 2016. The results reflect the findings of Slattery and Burt, (1997) who found during low flows (such as those observed in August and October) a greater proportion of sand-sized particles are transported and as flows increase in winter, the size of particles within the load diminish due to increased turbulence and greater aggregate breakdown. Similarly to Ham Bridge the D84 values shows the largest temporal range in particle size 21.3- 91.6µm (Figure 6.18). The result reflects the storm sample analysis (see section 5.3.4) where the coarsest component of the sediment sample was found to have the most variance. Downstream of the Burton Brook silt trap the left sampler appears to show a greater temporal variation which has been reflected in the organic matter data and may be a result of increased sediment load observed in August and October 2016 as discussed in 6.4.1.
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Figure 6.18 Cumulative frequency graph of particle size distribution for each TIMS installed at Ham Bridge silt trap. 6.5 Brentingby Dam
Finally, TIMS were installed up/downstream of Brentingby Dam to determine its geomorphological impact on suspended sediment and whether it influenced sediment load, organic matter or particle size.
6.5.1 The effectiveness of Brentingby Dam at retaining fine sediment
a) b)
400 700
350 600 300
500
) 1 250 - 400 200 300 150 (Load g day (Load 200 Total Load (Kg)Load Total 100 50 100 0 0 Upstream Upstream Downstream Downstream Upstream Upstream DownstreamDownstream Left Right Left Right Left Right Left Right
Figure 6.19 Total sediment load (kg) for study period (a) and relative sediment load (g day-1 (b) collected at Brentingby Dam
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Chapter Six: Geomorphological and Hydrological appraisal of installed flood management assets In contrast to the results at Ham Bridge and Burton Brook silt traps, the suspended sediment load at Brentingby Dam does not appear to decrease downstream. Sediment load appears relatively similarly with a sediment load of 251.2 kg (left) and 351.5 kg (right) upstream and 281.1 kg (left) and 270.3 kg (right) downstream, indicating an increase of 11% downstream to the left of the channel and 23% decrease on the right (Figure 6.19). A Mann Whitney U non parametric test determined these results are no statistically significant.
Adjacent TIMS downstream of Brentingby Dam have a difference in total sediment load 3.7% (11g), suggesting TIMS provide relative efficiency over the study period. In contrast, the adjacent TIMS upstream have a 33.2% difference of collected sediment mass indicating the samplers in this location are not collecting similar sediment loads. Figure 6.20 indicates the collection in June 16 (covering a period of January – June 16) is the period of greatest difference between upstream TIMS, where, the left TIMS collected 56.1g less than the right TIMS. During the collection for this sampling period the TIMS installed on the left of the channel was found above water level (Table 6.7) by over 15cm due to installation occurring in winter flows.
The second largest collection of fine sediment from the upstream samplers occurring in March 17 following a winter sampling period (October 16- March 17). The upstream TIMS had a sediment load of 127.7g (left) 104.3g (right) compared to 50.0g (left) and 50.3g (right) in the downstream samplers, indicating Brentingby Dam reduces the transport of suspended sediment during this period by 52-61%. The high sediment yield of 0.9 g day-1 (left) 0.3 g day-1 (right) (Figure 6.20) upstream of Brentingby Dam may reflect the activity of the dam during the sampling period. During the Winter 2016/2017 Brentingby Dam closed for several days to protect the town from flooding, in response to several rainfall events which caused a period of high flows (Figure 6.7). During this time samplers were subjected to water levels of >2m (Personal Communication Environment Agency, 2017), which took approximately six weeks to recede. The closure of the dam caused a backing up of water upstream of the dam and a reduction in velocity, which would encourage the deposition of fine sediment (Brandt, 2000).
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Chapter Six: Geomorphological and Hydrological appraisal of installed flood management assets Downstream of Brentingby Dam shows the right TIMS consistently collected a greater mass than the left TIMS in Summer/Autumn periods (July 16, August 16, October 16, August 17, October 17) (Figure 6.20). During these time periods cattle were grazing in the left bank field downstream of the dam. Evidence of bank erosion from cattle poaching was evident on the left bank and during collection of TIMS cattle were witnessed in the river, creating a potential source of fine sediment that may explain the increase in suspended sediment mass present in the left side TIMS. Similar findings were observed by Walling and Amos, (1999) in sites located in close proximity to cattle trampling which increased fine sediment delivery to the channel on the River Piddle.
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Figure 6.20 (left) sediment mass collected (g). (right) daily sediment load (g day-1) at Brentingby Dam
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Chapter Six: Geomorphological and Hydrological appraisal of installed flood management assets Figure 6.21 shows the percentage organic matter content for the monitoring period at Brentingby Dam. The median organic matter content has a narrow range of 4.3-5.5%, with the lower quartile ranging from 2.1-3.01% and the upper quartile 10.5-11.6% indicating all four installed TIMS have similar levels of organic matter present. The lower than expected range in values, reflects findings both at Ham Bridge and Burton Brook silt traps and catchment wide as discussed in chapter five.
Figure 6.21 box plots displaying the percentage organic matter content of all samples collected at Brentinby Dam
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0 Jan-16 May-16 Aug-16 Nov-16 Mar-17 Jun-17 Sep-17 Dec-17
Upstream Left Upstream Right Downstream Left Downstream Right
Figure 6.22 Scatter graph depicting temporal variation in percentage organic matter content at Brentingby Dam The narrow percentage organic matter range displayed in Figure 6.21 is reflected in Figure 6.22 which shows organic matter values from the TIMS locations for each collection. The graph shows the values are similar at all four locations for 7/8 collections. During the final collection in October 17, the TIMS installed downstream on the left has a higher organic matter content of 29.2%, which has been recorded as an outlier (Figure 6.22).
Collections which occur in the summer (July16, August 16, October 16, August 17) as low in organic matter content with all values collected in these time periods <5.8%. The highest values in organic matter content were observed in March 17 (October16- March 17) and October 17 (August 17-October 17). The spike in organic matter content during this autumn and winter period may reflect the high rainfall events connecting the channel to the floodplain, increasing sediment delivery and thus organic matter content from the agricultural fields. The results from October 17 reflect findings at Ham Bridge and Burton Brook silt traps and a study by Ankers et al (2003) who found late summer and autumn to have the highest organic matter content due to an increase in vegetation during this season.
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The total range of particle size at Brentingby Dam is 0.34-839.7µm. The average D50 range between 12.53-14.4µm, D16 (3.58-3.83µm) and D84 (53.2-97.0µm) (Figure 6.23). A Mann-Whitney statistical test was conducted between adjacent samplers and found the D16 differences in the upstream sampler installed on the left and the upstream right sampler were significant for the monitoring period, but not for the D50 or D84 values.
Temporal changes in particle size appear to be more pronounced than observed at Ham Bridge and Burton Brook silt traps (Figure 6.24). D50 particle sizes analysed from samples collected in June16, July 16 and March 17 and May 17 show a D50 range of 7.1-14.2µm compared to those in August16 and October 16 and 17 of 22.3-35.6µm. This apparent coarsening of D50 sediment reflect the findings of Stone and Walling, (1997) who found statistically significant differences in D50 particle sizes between spring/summer and autumn/winter with the former observed to be coarser.
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1 Upstream Left Upstream Right Downstream Left Downstream Right
Figure 6.23 box plot indicating the minimum and maximum range of particle sizes up/downstream of Brentingby Reservoir
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Figure 6.24 Temporal variation in particle size distribution for each TIMS over time. Dark purple represents upstream left, turquiose upstream right, light purple downstream left and light turquiose downstream right.
6.6 The effectiveness of the Silt Traps
Table 6.1 shows the average daily sediment load, calculated from the adjacent TIMS for each collection to determine whether the silt traps are an effective method in reducing fine sediment downstream. Ham Bridge silt trap is shown to reduce the sediment load downstream on 5/8 collection periods, effectively reducing the fine sediment downstream by 32.5-71.9%. Burton Brook is shown to effectively reduce fine sediment downstream of 7/8 collections by 59.7-98.0% indicting that this silt trap is more effective at reducing fine sediments than the silt trap installed at Ham Bridge.
The results suggest the silt traps are most effective when the water levels are moderately high such as spring (May 17 -71.9%Ham Bridge and -67.6%Burton Brook and Autumn (October 17 -52.4% Ham Bridge and -58.8% Burton Brook). Water levels during these periods are likely to be affected by sudden change in channel morphology which will reduce stream power and encourage deposition (Environment Agency, 2003). During larger flows experienced in winter, the impact of the silt trap may be diminished due increased stream
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Chapter Six: Geomorphological and Hydrological appraisal of installed flood management assets power maintaining fine sediment in suspension and transporting it downstream. This may explain the reduced effectiveness observed at Ham Bridge silt trap during winter collection March 17 -32.5%.
The silt traps were shown to be ineffective at reducing silt in July16, October 16 and August 17 at Ham Bridge and October 16 at Burton Brook. These results indicate the silt trap is less consistent at Ham Bridge, particularly in low summer flows. The cross sectional area of the channel at Ham Bridge is much greater (3.9m2) compared to Burton Brook (1.3m2) though the silt traps are relatively equal size (Figure 3.10) which may indicate the silt trap at Ham Bridge needs to be increased in order to trap more fine sediment.
Table 6.1 The percentage increase of daily sediment load downstream of the silt traps. Percentages in red denote an increase in sediment load downstream
Ham Bridge daily load (g) Burton Brook daily load (g) Upstream Downstream % increase Upstream Downstream % increase Jun-16 4263.7 2136.3 -49.9 710.9 257.8 -63.7 Jul-16 136.7 261.7 91.5 1135.5 22.4 -98.0 Aug-16 329.1 186.9 -43.2 172.9 69.6 -59.7 Oct-16 187.4 495.6 164.4 87.8 376.3 328.6 Mar-17 857.5 578.4 -32.5 483.6 82.4 -83.0 May-17 1955.8 550.1 -71.9 306.7 99.2 -67.6 Aug-17 51.7 175.0 238.3 282.6 99.2 -64.9 Oct-17 128.8 61.3 -52.4 98.5 40.5 -58.8
To determine the influence of the silt traps at a catchment scale the sediment yield was calculated for the sites downstream of the flood defences (Figure 6.25). The results show a reduction in suspended sediment yield of 9.6-8.5 g km-2 day-1 at Burton Brook and 3.9-2.9 g km-2 day-1 at Ham Bridge, showing a positive impact their installation has on suspended sediment yield within the catchment. Furthermore, the larger reduction per km2 at Ham Bridge indicates the effectiveness of installing sediment management measures on smaller tributaries, supporting the sediment load data (Table 6.1).
The impact of the silt traps alters the SSY-area relationship in the upper reaches, with the results now reflected De Vente et al’s (2007) conceptual diagram (Figure 6.25) where a peak of specific sediment yield as catchment
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Chapter Six: Geomorphological and Hydrological appraisal of installed flood management assets contributing area increases enabling the inclusion of erosional processes such a rill and gully creation. Though the silt traps were installed 12 years prior the full impact of them on the SSY-area and other works to improve soil conservation may take many years to impact (Trimble, 1999). The results for Brentingby Dam show an increase in suspended sediment yield downstream of 1.42 g km-2 day-1, suggesting a potential additional source of sediment, such as the local erosion observed downstream. The dampened negative trend may also echo findings by Perks (2013) who determined the lack of negative relationship between area and suspended sediment yield suggests the system is in receipt of a steady supply of material likely to be from in-stream sources or within close proximity to the channel.
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) 1 - 18
day 16
2 2 - 14 12 10 8 6 4 2
Specific Specific sediment yieldkm (g 0 0 20 40 60 80 100 120 140 160 180 200 Catchment contributing area (km2)
Figure 6.25 Scatter plot depicting specific suspended sediment yield over catchment contributing area of the River Eye. Blue dots indicate sites 1-11 from chapter 5. Red dots indicate downstream of silt traps and black represent upstream of silt traps which are redundant.
6.7 TIMS relative efficiency
TIMS have been used throughout this study to collect suspended fine sediment and interpret in spatial channel processes or the impact of established flood defences on transport. Results throughout chapter six have touched on and
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Chapter Six: Geomorphological and Hydrological appraisal of installed flood management assets displayed data collected from adjacent samplers. To explore the relative efficiency of the TIMS summary tables have been created for each location where 2 samplers were installed (Table 6.3Table 6.4Table 6.5). The results will initially discuss the total sediment load and physical property analysis of the suspended sediment and then the relative efficiency of the adjacent TIMS.
The mass of sediment trapped within the TIMS used to calculate load shows the smallest difference in sampler collection occurred downstream at Brentingby Dam where the difference in total mass collected was 2.3g. The largest difference between samplers was recorded upstream of Ham Bridge silt traps resulting in 37.2g more sediment being collected in the left TIMS, indicating the TIMS are capable of capturing relatively similar loads. A similar study investigating the relative efficiency of TIMS found monthly average in mass collection varied by 2.17g at Danby Brook and 29.8g Glaisdale Brook on the River Esk, North Yorkshire suggesting TIMS efficiency at collecting mass in both catchments is similar (Perks, 2013). Furthermore, the results were found to underpredict the actual sediment load by 66-99% but in a predictable nature, highlighting the relative efficiency of the TIMS sampler (Perks, 2013).
Table 6.2 shows the percentage difference of daily sediment loads collected for adjacent samplers for each sampling period. The results show adjacent TIMS differences range from 3.5%-171%, indicating a high degree of variation. The lowest degree in variation was observed in August 16 (36.7%) and July 16 (50.5%) which consequently refers to the two shortest sampling periods (35days) suggesting that increase in sampling frequency may increase the relative efficiency of TIMS for sediment load calculations. The silt trap with the lowest average difference is located upstream of Burton Brook (62.9%) which has the smallest channel cross section, suggesting TIMS may work well on smaller streams where variance of suspended sediment load is not varied across the cross section. Potential reasons for the high degree of variance are described in section 6.8.
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Table 6.2 percentage difference between adjacent samplers.
Jun- Jul- Aug- Oct- Mar- May- Aug- Oct- Average % 16 16 16 16 17 17 17 17 difference Ham Bridge 67.6 3.5 64.7 105.5 72.7 123.8 155.2 40.1 79.1 upstream Ham Bridge 55.0 9.9 0.7 - - 168.4 142.5 64.3 73.5 downstream Burton Brook 55.2 28.9 72.3 140.2 50.7 24.3 106.1 25.6 62.9 upstream Burton Brook 61.3 171.8 16.7 141.3 6.3 123.2 171.0 117.0 101.1 downstream Brentingby Dam 87.2 53.1 33.9 5.7 131.3 11.4 67.9 19.3 51.2 upstream Brentingby Dam 31.8 35.7 31.8 75.1 118.6 14.3 118.7 171.8 74.7 downstream Average temporal 59.7 50.5 36.7 93.6 75.9 77.6 126.9 73.0 variation
Table 6.3 Ham Bridge silt trap adjacent TIMS comparison with Mann Whitney non parametric test
Ham Bridge Silt Trap
Upstream Left CV % Right CV% Total F P Df Total Mass (g) 196.48 190.4 121.51 159.7 14 0.9 .36
Median D16 (µm) 1.62 45.7 1.35 29.3 14 0.75 0.42
Median D50 (µm) 6.19 57.0 5.89 45.6 14 0.03 .86
Median D84 (µm) 33.50 93.5 28.72 60.7 14 0.12 0.74
Median Organic Matter (%) 4.05 106.2 3.31 70.9 12 0.39 0.55
Downstream Total Mass (g) 71.09 158.9 125.64 146.0 10 1.31 0.32
Median D16 (µm) 1.23 13.9 1.37 26.6 10 9.8 0.025
Median D50 (µm) 4.54 16.9 5.82 64.8 10 2.2 0.19
Median D84 (µm) 22.85 57.7 30.07 122.9 10 0.7 0.13
Median Organic Matter (%) 2.50 67.7 3.06 96.2 10 0.00 0.95
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Table 6.4 Burton Brook silt trap adjacent TIMS comparison
Burton Brook Silt Trap
Upstream Left CV % Right CV % Total Df F P
Total Mass (g) 160.23 102.5 144.24 104.9 14 0.15 0.71
Median D16 (µm) 1.01 10.3 1.00 10.4 14 0.22 0.65
Median D50 (µm) 3.96 13.5 4.03 13.9 14 0.07 0.79
Median D84 (µm) 16.05 36.4 18.40 46.5 14 1.37 0.56
Median Organic Matter (%) 2.10 13.5 2.34 13.9 14 1.22 0.31
Downstream Total Mass (g) 78.85 157.1 90.56 96.7 14 0.16 0.69 Median D16 (µm) 1.16 42.4 0.90 19.2 14 1.92 0.2 Median D50 (µm) 4.05 24.9 3.69 16.7 14 0.78 0.41
Median D84 (µm) 13.87 52.4 14.71 26.5 14 0.08 0.77
Median Organic Matter (%) 4.38 24.9 11.21 16.7 14 1.87 0.21
Table 6.5 Brentingby Dam adjacent TIMS comparison
Brentingby Dam
Upstream Left CV% Right TIMS CV% Total Df F P TIMS Total Mass (g) 104.45 154 146.2 182.11 14 0.01 0.9 Median D16 (µm) 1.52 38.5 1.90 53.3 14 3.05 0.12
Median D50 (µm) 5.85 41.9 7.12 55.2 14 1.55 2.5
Median D84 (µm) 40.59 82.4 41.76 59.5 14 0.03 0.86
Median Organic Matter (%) 2.47 89.8 2.64 74.2 14 0.62 0.46
Downstream
Total Mass (g) 61.9 163.18 59.60 186.67 14 1.00 0.15 Median D16 (µm) 1.80 57.63 1.53 40.8 14 1.5 0.25
Median D50 (µm) 7.59 77.1 8.66 110.8 14 0.15 0.72 Median D84 (µm) 44.35 77.2 42.89 81.7 14 0.02 0.90 Median Organic Matter (%) 3.35 112.77 2.70 71.356 14 0.79 0.41
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Chapter Six: Geomorphological and Hydrological appraisal of installed flood management assets Physical property analysis found variations in organic matter between adjacent TIMS to range from 0.24% upstream of Burton Brook to 6.38% downstream of Burton Brook (Table 6.4). Similar variations were also found in particle size analysis for D16, D50 range where minimum variation (D16 0.01µm D50 0.07µm) was identified upstream of Burton Brook silt trap and the largest (D16 0.4µm D50 1.27µm) upstream of Brentingby Dam. The consistency in particle size variation may be indicative of channel cross sectional area. The site located upstream of Burton Brook has the smallest cross-sectional area of flood defence sites of 2.85m2 whereas downstream of Brentingby Dam has the largest of 8.46m2. Smaller channel cross sections are likely to have less variation in suspended sediment load compared to larger sites such as Brentingby Dam where samplers were spaced further apart within the channel. The median D50 sediment sizes are smaller than those calculated by Phillips et al (2000) on the River Clyst and River Exe but the variation between adjacent TIMS is found to be greater (9.8 - 5.9µm River Clyst and 24.4-14.6µm River Exe).
The D84 median particle sizes are found to have the largest variation between samplers (0.84 µm downstream of Burton Brook to 4.8 µm downstream of Ham Bridge), which is consistent with suspended sediment analysis from storm samples (5.3.4). Furthermore, sediment size analysis from the River Esk found the magnitude of variation in particle size was greatest in locations of coarsest sediment (Perks, 2013) which is in keeping with observed results on the River Eye. The calculated D16, D50 and D84 values are similar to the ranges calculated from the suspended sediment captured downstream in Melton Mowbray (Table 6.6), suggesting the TIMS do collect a representative suspended sediment sample.
Table 6.6 Comparison of particle sizes between suspended sediment collected during high flow events in Melton Mowbray and TIMS sites with adjacent samplers.
Particle Size Storm sample (µm) TIMS (µm) D16 0.56-1.31 0.9-1.59 D50 2.64-6.48 3.69-7.12 D84 10.48-75.42 13.87-44.35
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Chapter Six: Geomorphological and Hydrological appraisal of installed flood management assets The results of the Mann-Whitney U Test between adjacent samplers returned no statistically significant differences (P>0.05). Similar results were obtained by Perks (2013) when determining relative efficiency in adjacent samplers who concluded the absence of statistically significant results provided confidence that the TIMS is consistent and precise in these environments. Previously TIMS have been found to collect a geochemically representative sample in terms of organic matter and particle size (Hatfield & Maher, 2008; Russell et al., 2000). The low variation observed in adjacent TIMS suggests the TIMS installed on the River Eye have successfully captured a representative sample.
6.8 TIMS limitations As discussed in chapter 4.4.4 the method of deploying TIMS to analyse suspended sediment within a channel has several limitations which will be reflected on in terms of this study.
1. Water depth
Due to fluctuation in river stage, samplers did not remain at 0.6 mean depth within the channel continuously, causing a fluctuation in the suspended sediment sampled by the TIMS devices. One of the largest changes to placement of 0.6 mean depth was observed upstream of Brentingby Dam affecting the sample collected in March 17. The dam was closed during the winter period for several days causing the TIMS to be submerged under 2.6m of water, which took several weeks to recede (Personal communication with Environment Agency, 2017). In contrast, during the summer months some TIMS inlets were found to be above water level, reducing the time the samplers were actively collecting a suspended sediment sample (Table 6.7). Due to TIMS static nature, it is impossible to determine when the water level receded below the inlet and therefore the results cannot be adjusted to account for the missing days. Installing the samplers during the summer months would mitigate some risk in addition to shorter times between collection periods in the spring/ summer and autumn/ winter periods, as many TIMS incurred this problem between January- June 2016. However, the problem also occurred between a 30-day collection period July – August 16 (Table 6.7). Additionally,
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Chapter Six: Geomorphological and Hydrological appraisal of installed flood management assets a time lapse installed on the river bank could be used to monitor the water level and calculate the number of days where TIMS are affected by water level.
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Chapter Six: Geomorphological and Hydrological appraisal of installed flood management assets
Table 6.7 List of TIMS affected by changes in water level
Location Date Effect Site 2 (main Eye) Collection 1 June 2016 Site 7 (main Eye) Site 13 (main Eye) Site upstream of TIMS inlet found to Brentingby Dam be above water level Site 2 Collection 3 August Site 13 2016 Site 16/17 Site 13 Collection 7 August 2017 Site 16/17 Collection 5 March TIMS experienced 2017 artificially higher water levels
2. Blockages of the inlet
Between collection periods, detritus was found surrounding the TIMS, most commonly attached to reinforced rods and therefore causing turbulence under the sampler, downstream of the inlet. Similarly to McDonald et al’s (2010) findings organic detritus was found in the inlet tube and removed during collection periods at all TIMS locations. However, the organic matter did not block the inlet tube entirely though it may have impeded the quantity of sediment captured.
3. Absence of secondary data
Perhaps the largest limitation to comparing the study to previous studies conducted or other UK lowland river catchments is the absence of secondary data to calculate the absolute TIMS efficiency, as previously successfully completed by Perks et al (2014). Though absolute efficiency was not within the scope of this study due to the project focusing on the relative contributions from spatial areas within the catchment, future work could incorporate the use
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Chapter Six: Geomorphological and Hydrological appraisal of installed flood management assets of turbidity monitors for comparison to other catchments, developing a greater understanding of the efficiency of TIMS in different environments.
4. Sampling method
The laboratory methods used to analyse the suspended sediment samples are well practised, standardised tests and have been successfully conducted on similar sediment samples (see sections 4.5.1-4.5.3), therefore reducing the introduction of error. However, calculation of the total mass of sediment collected by the samplers may incur a systematic error from the transfer of the sample from the TIMS to the bucket, from the use of the siphon pump (which has previously been mentioned in section 4.5.1) and transfer of samples in the laboratory. Whilst every care was taken to ensure the loss of sediment was minimised by covering both ends of the TIMS when removing them from the channel and thoroughly washing the sample containers to ensure all the sample was collected, small masses of sediment may have been lost, systematically from all samples during the process. A quantification of associated loss from the siphoning method was conducted by Perks et al (2014) who found 0.12% loss in suspended sediment from using the technique.
5. Sampler not representative of cross section.
A final limitation of the TIMS samplers regarding its upscaling from a point in the cross section to calculate suspended sediment concentration for the entire cross-sectional area, when it is not considered to be consistent (Wass and Leeks, 1999). Relative TIMS efficiency has shown that even within two points in the same cross section the results do have differences, though not statistically significant. Previous research from Phillips et al (2000) showed mass retention ranging from 31-71% and between 66.4-96.1% from Perks et al (2014). However a study by (Schindler Wildhaber et al., 2012) found total weekly load of suspended sediment collected by TIMS correlated with mean weekly suspended sediment concentration recordings with Spearmans rank values of 0.8 (n212). An underprediction of sediment load from TIMS is not unexpected due to sensitivity of sampling flux in relation to their placement within the channel. Conditions such as in channel hydraulics, sediment
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Chapter Six: Geomorphological and Hydrological appraisal of installed flood management assets properties, local forcing, sampler positioning and source material are all factors which will indicate how representative a collected sample is. This may reflect results observed between adjacent samplers at Burton Brook being more similar (Table 6.4) due to a reduction in cross sectional area compared to larger sites such as Brentingby Dam. Sampling bias between samplers installed throughout the catchment cannot be easily quantified or predicted (Mcdonald et al, 2010) and therefore sampler position and placement within the channel should be kept consistent between sites (Perks et al., 2014).
Though the sediment loads predicted by TIMS samplers in the River Eye are likely to underestimate sediment flux it provides a good relative indication of fine sediment transport throughout the catchment. TIMS offer a low-cost method of exploring the spatial patterns of fine sediment transfer and to determine whether installed management measures such as the silt traps are efficient at reducing downstream suspended sediment loads. The installation of samplers over prolonged periods enable the identification of temporal patterns which may not be captured by random sampling.
6.9 The geomorphic and hydrologic impact of online silt traps
The results from the hydrological and geomorphological study complement findings from Pepper and Rickard (2009), who found the effects of dredging can occur upstream of the dredged reach in an attempt to return the river to a natural gradient. Furthermore, a report conducted by HR Wallingford found that in areas where a large width-depth ration were present, deposition is likely to occur upstream of the improved reach (Fisher, 1992). Alterations to sediment budgets in modified reaches can cause a reduction in channel capacity, thus increase local flood risk. The construction of artificial levees, causing a deeper channel reduced the sediment storage by 90% on the lower Mississippi River (Kesel, 2003). Dredging on the River Stour shows that channel widening is favourable to deepening to prevent deposition (Fisher, 1992), thus suggesting that the design of silt traps should be a depended section of the channel to encourage deposition in these areas. The effects of installing silt traps on the upstream and downstream reaches need to be
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Chapter Six: Geomorphological and Hydrological appraisal of installed flood management assets considered to ensure the overall flood risk is not worsened (Pepper & Rickard, 2009).
Due to NFM installations being in relative infancy compared to traditional flood defences, there is an absence of literature on hydrological and geomorphological impacts on features such as silt traps. This analysis provides a vital insight into the potential impacts of installing NFM features within the catchment as causing a subsequent localised increase in flood risk upstream. Installing multiple NFM measures within a catchment must consider the potential hydrological impacts at a catchment scale as opposed to focusing on alleviate flood risk in downstream reaches only.
Extracting sediment to artificially widen and deepen the channel for a silt trap is a similar process to dredging; a means of flood prevention (Bravard et al, 1999). The result from the hydrological and geomorphological appraisal reflect the results found by Pepper & Rickard (2009), where construction of a structure in the watercourse can cause sediment upstream and a rise in flood level. Further problems which must be considered for future silt trap installation is the potentially impact upon fish passage and bank stability as a result of channel widening (Pepper & Rickard, 2009).
The long term influence of the silt trap must also be considered. Gob et al’s (2005) study of the Semois river dredging found through topographical surveys that the impact of dredging as a means of flood prevention is a temporary solution as 10 years after the construction, the bed will assume its initial shape. Pepper & Rickard (2009) report determined silt traps as an unsustainable solution due to the traps requiring emptying at regular intervals to maintain efficiency. These findings complement the work undertaken at Ham Bridge in 2011 to remove the silt collected within the trap. Though a costly exercise, the advantage of a silt trap is the sediment will mostly collect in one place and the expense of dredging can be determined at the design stage (Fisher, 1992; Pepper & Rickard, 2009). It has been 7 years since Ham Bridge silt trap was excavated after initial excavation occurred 8 years after installation. The variation in mass of suspended sediment collected upstream and downstream of Ham Bridge and Burton Brook silt traps may be indicative of the silt traps
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Chapter Six: Geomorphological and Hydrological appraisal of installed flood management assets being full and therefore currently less efficient at removing fine sediment from the channel. Due to the diversity in river hydrology, morphology and sediment type it is difficult to predict the impact of silt traps on all river systems. Regular hydrological and morphological monitoring is vital to maintaining the efficiency of natural flood management measures such as silt traps.
6.10 Chapter Summary This chapter explored the geomorphic and hydrological impacts of installed flood defences in the River Eye catchment. The relative sediment loads, organic matter content and particle sizes of suspended sediment were analysed to determine the up/downstream differences of the silt trap and the relative efficiency of TIMS samplers installed adjacently in the channel.
The daily sediment load results for the total time period showed both silt traps decreased sediment load. At Ham Bridge the TIMS determined a decrease of 5-54% from upstream to downstream of the silt traps. Burton Brook observed a decrease of 42-55%. In contrast, Brentingby Dam was show to have little impact on sediment load with left samplers indicating a 11% increase downstream and right samplers 23% decrease. The results are likely to reflect the observed bank erosion on the left bank which may have caused the disparity.
The organic matter results implied the silt traps have very little influence on organic matter content. This may be a result of organic matter representing one of the finest components of fine sediment and therefore are able to remain in suspended load at low velocities such as those created by the silt trap. This result was supported by particle size analysis which indicated the silt traps and Brentingby Dam do not affect the D16 or D50 ranges. However, there was an observed decrease in D84 downstream of Ham Bridge (18.9µm and 13.0µm) and Burton Brook (11.9µm and 5.9µm) which is indicative of the silt trap encouraging the deposition of larger particles due to a decrease of velocities within the silt trap.
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Chapter Six: Geomorphological and Hydrological appraisal of installed flood management assets The relative TIMS efficiency identified differences of sediment load adjacent samplers of 4%-171% suggesting TIMS are not similar despite the absence of significant Mann Whitney U results, highlighting the importance of positioning within the channel. The results do suggest that the physical properties of the samplers are similar between adjacent samplers which is in keeping with the literature.
The chapter discussed the effectiveness of both silt traps in reducing fine sediment downstream and its hydrological implications. Burton Brook was shown to be more effective at reducing sediment load on 7/8 occasions (59.7- 98.0%). Ham Bridge silt trap was shown to reduce sediment load by 32.5-71.9% on 5/8 occasions. The data reports the silt traps are most efficient during moderate flows experienced in spring/ autumn. Additional hydrologic appraisal of Ham Bridge identified the silt traps increase the surface water elevation upstream of the silt trap, which during high flow events can propagate over 200m upstream and remain for over 27 hours, highlighting the potential of increased local flood risk.
This chapter has provided a unique insight into established NFM’s geomorphic and hydrologic impacts which is vital for future flood management and maintenance of structures. Though understanding the social perceptions and attitudes to sediment management and flood risk is integral to the future of natural flood defences.
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Chapter Seven: Social attitudes and perception of flood risk management in the River Eye Catchment 7 Chapter Seven Social attitudes and perception of flood risk management in the River Eye Catchment
7.1 Chapter Scope
This chapter seeks to explore the social dimension of flood risk management using the results from a survey undertaken by three catchment stakeholder groups; managers, farmers and residents. Specialist questions were initially analysed to provide background context to the questionnaire responses, described in 7.2. The results of the questions which were sent to all stakeholder groups were then discussed and compared to identify disparities and similarities in social attitudes. 7.3-7.5 describes the results relating to questions asked on awareness, resilience and responsibility respectively.
7.2 Context
The three catchment stakeholders; mangers, farmers and residents were asked a series of questions to provide a contextual basis to their responses on awareness, resilience and responsibility.
7.2.1 Managers
The catchment managers questionnaire had a successful return rate of 75% (15/20 respondents), resulting in a comprehensive range of responses to be collected. The high return rate suggests the use of online questionnaire was appropriate for this stakeholder group. The survey respondents covered a wide range of environmental management sectors in the River Eye catchment (Figure 7.1) with the largest number of responses 16.4% jobs focused on wildlife. Sediment and water quality accounted for 11.5% indicating that
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Chapter Seven: Social attitudes and perception of flood risk management in the River Eye Catchment although some catchment managers are working within this area for many it is not their primary focus. The survey results identified catchment managers have a range of 6 months- 30 years’ experience within their current roles, with 60% of the respondents having worked in this catchment for >10 years. This contextual information suggests that the survey results are based on wide range of experience from within the catchment.
Navigation 4.9% Other 3.3% Flood defences 6.6% Flood risk 9.8% Farming practises 9.8% Water quality 11.5% Catchment management 8.2% Sediment 11.5% Channel morphology 9.8% Fisheries 8.2% Wildlife 16.4%
Figure 7.1 The environmental areas catchment managers are focused on within the River Eye catchment.
7.2.2 Farmers
The online survey sent to farmers yielded at 17.5% (7/40 responses) response rate, this is not uncommon as a large percentage of farmers do not respond to surveys (Pennings et al, 2002). A study investigating survey responses from farmers in USA received a 35% response rate after sending two copies of the survey and conducting follow-up telephone calls (Pennings et al, 2002). Disseminating the questionnaire via email to cause minimal interference to farming practises has been successful form of communication by Natural England (Personal communication with Natural England advisors) and therefore suggests lack of engagement with the topic or questionnaires. Despite the smaller response rate to the catchment managers questionnaires,
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Chapter Seven: Social attitudes and perception of flood risk management in the River Eye Catchment the responses incorporated a diverse range of arable, mixed and combinable crop farms, which affected a large spatial area from 18-360 fields per respondent. The farmers in the survey have all been working within the catchment for over 10 years indicating the responses are informed and based on experience.
7.2.3 Residents
The residents postal questionnaire had a response rate of 16% (32/200 responses). Questionnaires were completed and returned by residents from a large spatial area (Figure 7.2) providing a broad overview of attitudes to flood risk from respondents both within and outside of the EA flood risk area.
Figure 7.2 Map of responses at a street level to the postal survey. Purple indicates the streets that responded and red, the streets that did not reply. 82% of the responses received were from homeowners, and 100% of responses were from residents which had been living in their homes for over 2 years (Figure 7.3). 58% of the residents have been in the same property for over 20 years, and therefore were present during the 1998 and 2000 flood
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Chapter Seven: Social attitudes and perception of flood risk management in the River Eye Catchment events within the town. Residents with a living flood memory have been found to be more resilient to flooding (McEwen et al , 2017) and are more likely to be engaged with catchment flood risk and defences as they were living within the catchment during the implementation of the Melton Mowbray Flood Alleviation Scheme (see section 3.3.1).
0-1 years Homeowner
2-5 years
Tennant 5-10 years
10-20 years Living with Parents
20-30 years
Prefer not to say Over 30 years
0 20 40 60 80 100 0 10 20 30 40
Figure 7.3 demographics of residential respondents. Left: homeowner status. Right: number of years in property.
The varying response rates of 75% (catchment managers) 17.5% (farmers) and 16% (residents) suggests a disparity in engagement between the three stakeholder groups. Farmers and residents have comparatively lower response rate to catchment managers suggesting they are less engaged with flood risk in Melton Mowbray and the upstream catchment. One resident (resident 18) responded to the questionnaire with an attached letter.
“This [questionnaire] is a total waste of time and money. Since flood defences were made up river some years ago no serious flooding has occurred in Melton…in 100 years according to the environment agency.” Resident Respondent 18
The response suggests the resident, who has lived within the catchment for over 30 years, is not aware of flood events occurring in 1998 or 2002 and furthermore appears disengaged with flood risk management. This response
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Chapter Seven: Social attitudes and perception of flood risk management in the River Eye Catchment may provide an indication for a lower return rate from residents and highlights the importance of catchment managers engaging with local stakeholders to improve communication and engagement with flood risk management strategies within the River Eye catchment.
7.3 Awareness to flood risk and sediment management within the River Eye Catchment
This section analyses the (54) responses of all three stakeholder groups regarding questions asked on awareness of flood risk and sediment management practises.
7.3.1 Main contributors to flood risk in Melton Mowbray
Stakeholders were asked to rank the contribution that catchment features had on flood risk within the River Eye catchment (Figure 7.4). Catchment managers and farmers were more aligned in views identifying the hydrological driving factor rainfall as the largest contributor to flood risk within the catchment (60% and 83% respectively). In contrast, residents identified land use and geomorphic changes such as; building on floodplains 48% and channel depth (48%) as the highest contributors to flood risk. Recent UK media attention of flooding has focused on Somerset Levels flood debate where both channel capacity and building on floodplains were discussed repeatedly, suggesting the media may influence public perception. This is supported by Bohensky & Leitch's (2014) study of the media’s influence on public perception of flooding after 2011 Brisbane floods where the media coverage was found to influence perception. Residents ranked rainfall as the third highest contributor, indicating stakeholder groups are relatively aligned.
Sediment and soil runoff was ranked moderate or high by most respondents: 73% Catchment mangers, 80% farmers and 66% indicating a general awareness for the influence of sediment on flood risk. This awareness is encouraging for acceptance of future catchment management plans that may continue to use soft engineering approaches to reduce the volume of sediment entering the river to maintain channel capacity and therefore reduce flood risk.
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Chapter Seven: Social attitudes and perception of flood risk management in the River Eye Catchment
Figure 7.4 Likert scale displaying the results to the question “What do you think are main contributors to flood risk in this area?” Farmers were asked three questions to identify their perception of their farms flood risk (Figure 7.5). 66.6% of respondents consider themselves at risk of
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Chapter Seven: Social attitudes and perception of flood risk management in the River Eye Catchment flooding, whilst only 50% have experienced flooding on their land. In addition, 67% of respondents indicate that the River Eye or a tributary of the river is within or in close proximity to their land. The results suggest the farming community have a high perception of personal flood risk. An open question enabled those farms which experienced inundation to describe the damage caused. This result contrasts a questionnaire surveying risk perception of muddy floods where farmers were shown to have weak awareness of risk despite personal expert knowledge from farming practise (Heitz et al, 2009)
“Livestock fencing washed down, river bank erosion, deposits of flood rubbish, waterlogging of and botantical changes to grazing, culvert damage” Farmer 6.
Residents were also asked the same three questions to determine their attitudes towards flood risk. 24% of responses do consider themselves at risk of flooding and it appears perception does not rely on distance to river channel as 82% of residents do not have the River Eye on or bordering their land (Figure 7.6).
Of the 19% of residents who answered yes to their properties flooding, several provided details of the damaged caused. Residents discussed damage to ground floor of property including “gardens, flooring and kitchen units from 8- 9inches of flood water”. One resident described the extent of the damage caused by flooding to their property (respondent 30).
“Water flooded the whole of the garden, kitchen, outbuildings. Damage to white goods, carpets, cupboards, plants and outhouse contents.” Respondent 30.
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Chapter Seven: Social attitudes and perception of flood risk management in the River Eye Catchment
70
60
50
40
30
20 % of % respondents
10
0 Yes No Yes No Yes No Do you consider yourself at Does a river cross or Has your land risk of flooding? border your land? ever flooded?
Figure 7.5: Questions asked to farmers to indicate their perception of flood risk
90
80
70 60 50
40
30
% of % respondents 20 10 0 Yes No Yes No Unsure Yes No
Do you consider yourself Does a river cross or border Has your property at risk of flooding? your land? ever flooded?
Figure 7.6: Residents responses to questions regarding their personal perception of flood risk
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Chapter Seven: Social attitudes and perception of flood risk management in the River Eye Catchment The results from this section of the survey, indicate the residents have a good awareness of flooding threat, which is in keeping with Brilly and Polic’s (2005) findings in Celje where awareness was increased as a consequence of living in a flood prone area.
7.3.2 Exploring stakeholder awareness to flood risk management
To assess the awareness of catchment managers of current national policy, the survey asked two questions regarding popular topics. The survey found 100% of catchment managers believed in a catchment-based approach, a result which is positive for future integrated catchment management. The result indicates an understanding from catchment managers of installing flood mitigation measures throughout the catchment to work with hydrological and geomorphic processes which affect sediment delivery and flood risk (see section 2.7.2). The survey identified managers work on a variety of scales within the catchment. 50% of respondents job roles covered the entire catchment, whilst the remaining respondents were concerned with individual reaches of the River Eye such as the SSSI and navigation channels. Whilst it is inevitable that managers will have to focus on specific areas for management, communication between managers must be prioritised to achieve an integrated catchment management plan.
Acceptance of NFM features already in the river is hard to quantify as is determining future attitudes towards flood risk strategies. Stakeholders were asked an open question to state which flood defences they were aware of on the River Eye. This question provides an indication of the level of engagement with current management strategies between the stakeholders without prompting the respondents with pre-defined answers.
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Chapter Seven: Social attitudes and perception of flood risk management in the River Eye Catchment Managers Farmers Residents
0% 3% 0% 6% 9% 19% 28% 9% 19% 35% 23%
18% 6% 9% 28% 6% 31% 9% 24% 18%
0%
Figure 7.7 Awareness of current flood defences in River Eye Catchment
The responses were categorised into seven discreet groups (Figure 7.7). The decision was made to divide those responses which mentioned Brentingby Dam by name and those which inferred its presence by another name or location to determine the potential awareness of stakeholders. The results show 35% of catchment managers, 28% of farmers and 19% of residents answered “other”, a category which refers to fictitious flood defences such as; “locked flood gates”, “second river from overflow” and “rock weirs” or those installed outside the River Eye catchment. The “other” category was the highest flood defence category for both catchment managers and farmers. This response rate may be a reflection that 16% of the catchment managers who responded directly work in flood risk or flood defence sectors (Figure 7.1). The lack of awareness from managers working on different environmental sectors of the River Eye indicates the need to improve communication between managers working in the same spatial area on different environmental issues. This is further supported by only 16% of catchment mangers identifying NFM silt traps within the catchment. Increasing the awareness at the top-down level is fundamental to successful future investments in NFM and for disseminating a consistent message to key
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Chapter Seven: Social attitudes and perception of flood risk management in the River Eye Catchment stakeholders such as farmers who are often affected by its implementation. This is vital for successful catchment-based approach management strategies.
The results depict farmers as the most informed of the stakeholder groups with 54% naming explicitly or alluding to a feature (Brentingby Dam, silt traps or the Melton Mowbray Flood Alleviation Scheme). This may be a result of the scheme being installed in the rural upstream reaches of the catchment which is predominately agricultural. Similarly, 50% of residents are also aware of the upstream dam at Brentingby, although only 19% were able to name it. These results support earlier contextual findings of a lack of engagement in the River Eye catchment between stakeholders. Improving communication, may increase awareness of current or future flood management strategies and potentially an increase in community resilience.
Figure 7.7 highlights the lack of awareness of current soft engineering approaches within the catchment. Only 6% of catchment managers and 9% of farmers were aware of the silt traps installed at Ham Bridge and Burton Brook. The results may underrepresent the percentage of stakeholders that are aware of the silt traps existence due to the silt traps not being recognised explicitly as a flood defence. The results highlight the importance of improving awareness of installed soft engineering measures in order to increase acceptance of NFM and highlight the potential multiple benefits this technique can result in.
7.3.3 Stakeholder awareness of fine sediment processes Fine sediment
The title page of the questionnaire informed stakeholder groups of the fine sediment problem identified by catchment managers through the 2003 Melton Mowbray flood alleviation scheme. Initially, all stakeholder groups were asked to identify the potential sources of fine sediment within the River Eye catchment (Figure 7.8).
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Chapter Seven: Social attitudes and perception of flood risk management in the River Eye Catchment Managers Farmers Residents
4% 0% 6% 22% 28% 25% 28% 33% 22%
14% 9% 9% 8% 5% 25% 6% 28% 28%
Figure 7.8 Responses from all stakeholders on the perception of fine sediment sources in the River Eye Catchment. The responses from all three groups had a similar distribution with stakeholders identifying; river banks, natural features (geology, soil type, slope) and agricultural fields as the top three contributors to fine sediment (catchment managers:28%,25%, 25% farmers: 28%,33%,28% residents: 22%, 22% 28%). The result indicates a general awareness of the physical catchment features influence on the landscape and a consensus of potential origins. The results also indicate an awareness from stakeholders that fine sediment sources vary spatially throughout the catchment are not limited to local sites such as river banks and floodplains. This is supported by the majority of each stakeholder group (Managers 93%, Farmers 80% and Residents 64%) identifying that fine sediment is capable of travelling the length of a river channel (Figure 7.9). The results suggest all three stakeholders have an understanding of natural sediment transport, particularly that sources of fine sediment may not be spatially close to areas of deposition.
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Chapter Seven: Social attitudes and perception of flood risk management in the River Eye Catchment
Residents
Managers
Farmers
0 10 20 30 40 50 60 70 80 90 100 % of respondents
Length of river Length of trib A few metres
Figure 7.9 Responses from all stakeholders on the potential distance fine sediment can be transported downstream.
The similarities in stakeholder responses is encouraging for future management plans as awareness of sediment sources and transport occurring on a catchment scale indicates an acceptance of applying a catchment-based approach. Furthermore, installation of NFM measures across the catchment may also be accepted as flood defence methods due to their process-based understanding.
Although all three stakeholder groups have displayed a general awareness for sediment sources and processes, when asked to identify areas within the catchment where they have witnessed deposition (Figure 7.10), the answers are less conclusive. Catchment managers and farmers are more confident in their awareness of fine sediment deposition (50% and 46% respectively answered “yes”). Over 80% of residents answered “no” or “not sure” to seeing evidence suggesting they are less aware of areas of fine sediment deposition.
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Chapter Seven: Social attitudes and perception of flood risk management in the River Eye Catchment
60
50
40
30
20 % of % respondents
10
0 Yes No Not Sure
Managers Farmers Residents
Figure 7.10 Identifying areas of fine sediment within the River Eye Catchment. Several respondents provided examples of sites within the catchment where they had observed sediment deposition. Residents provided the most spatially detailed examples of fine sediment deposition with two respondents identifying the stretch of river behind the football pitches next to Masterfood’s factory. Responses from farmers were more generic and specified to the rural uplands.
Observations from farmers located in rural areas of the catchment suggest high surface connectivity from the fields. This response reflects differences observed in the DTM and DSM comparisons in chapter five where, the inclusion of surface features such as roads increased catchment connectivity. Field runoff was shown to be high in sub-catchment such as Burton Brook where topography increased connectivity and arable land cover resulted in elevated erosion risk, suggesting these features are potential sources within the River Eye catchment. Furthermore, cattle trampling has been observed at locations such as downstream of Brentingby Dam (see section 6.5.3).
“Runoff from fields and livestock poaching, erosion from road verges” Farmer 1.
However, one catchment manager who is concerned with navigation identified fine sediment deposition specifically in the downstream reaches of the catchment:
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Chapter Seven: Social attitudes and perception of flood risk management in the River Eye Catchment “During river clearance operations around Melton Ring” Catchment Manager 10.
The examples provided by all stakeholder groups identify specific sediment hot spots downstream of the flood defences within the town of Melton Mowbray. Observations of fine sediment deposition may not be common to stakeholders not working within these fields, explaining the uncertainty in response across all stakeholder groups. To gain further understanding stakeholders were asked to rank environmental observations within the River Eye catchment that are indicative of fine sediment supply and quantity (Figure 7.11).
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Chapter Seven: Social attitudes and perception of flood risk management in the River Eye Catchment
Figure 7.11 Likert scale showing catchment stakeholders observations of changes to the river features within their memories. Dark colours symbolise reduction and light colours an increased.
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Chapter Seven: Social attitudes and perception of flood risk management in the River Eye Catchment The Likert scale (Figure 7.13) shows that the most popular response from all three catchment stakeholder groups was “no change”, suggesting that observations on river features are low or there has been little change to sand/ silt deposition and water quality in recent years. Alternatively, it could be argued that “no change” is representative of stakeholders uncertainty in observations, thus highlighting the need for engagement and educating catchment stakeholders. Both catchment managers and farmers appear more positive in their general views on specific river features (i.e. out of channel flows and clean river water Figure 7.11) as the Likert scale is shifted to the right, compared with residents which is slightly bias to the left.
Catchment managers noticed “large increases” in wildlife diversity, population and clean river water, which are indicative of reduced sand and silt within the catchment. There was greater diversity in catchment managers opinion on the volume of sand and silt on the river bed which may be a result of the locations catchment managers are working in.
The 40% of managers which identified an increase in sand/ silt depositing on the bed have roles in navigation, flood risk management and water quality which are predominately focused downstream of the River Eye, in Melton Mowbray. These catchment roles are directly influenced by channel capacity and therefore suggest that sediment deposition has increased within the town. This idea is further supported by the results from the resident’s questionnaire, who are situated within this area. Residents indicated a 56% large increase in silt deposition. The spatial patterns identified are concurrent with the descriptions given by local residents and catchment mangers that previously identified the downstream reaches as areas of fine sedimentation. An observed increase in sediment deposition in the town of Melton Mowbray may be a consequence of the installation of Brentingby Dam. During periods of high water levels the dam is used to reduce the volume of water passing through the River Eye downstream to prevent out of channel flows. A reduction in high flows through the town may increase sediment deposition due to a loss in energy to keep sediment in suspended flow downstream.
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Chapter Seven: Social attitudes and perception of flood risk management in the River Eye Catchment Managers working upstream within agricultural land and the SSSI site are responsible for the 20% observation of a decrease in sands and silts. Installation of silt traps and changes to agricultural practises in recent years may contribute the reduction of fine sediment deposition from these areas. A geomorphological appraisal of the silt traps at Ham Bridge and Burton Brook found they are effective in reducing fine sediment downstream. This was further supported by sediment load map (Figure 5.10) in chapter five showing decrease in suspended sediment load downstream of the silt traps, particularly in the SSSI (site 9) which was observed to have the smallest sediment load in the catchment. However, 57% of farmers noticed no change in fine sediment levels, whilst 43% observed increases. Due to the anonymity of these respondents the areas of observed increase cannot be validated.
Small increases in out of channel flows have been observed by all three stakeholder groups; catchment managers 38%, Farmers, 40% and residents 8% suggesting a reduction in channel capacity due to sediment deposition. The residents observed a smaller increase in out of channel flows which may be indicative of the successful use of Brentingby Dam during high flow events. If sedimentation is occurring within the downstream reaches of the River Eye through the town of Melton Mowbray the dam may see an increase in use during high flows to compensate for the reduced channel capacity.
7.3.4 Natural Flood Management awareness
Similarly, to the paradigm of catchment based management, 100% of catchment managers answered “yes” to hearing the term “Natural Flood Management” and provided definitions. Several definitions given by catchment managers were simplistic reiterations of the term.Although the sentiment is correct, the response shows lack of a comprehensive understanding of NFM.
“Using natural measures to reduce flood risk.” Respondent 9.
Several responses provided examples of NFM measures in lieu of a definition (e.g. respondent 2, respondent, 7). Although the responses indicate some catchment managers are able to identify NFM examples, it suggests a lack of
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Chapter Seven: Social attitudes and perception of flood risk management in the River Eye Catchment understanding of the underlying processes and understanding behind the selection. For NFM to be implemented successfully every catchment needs to be treated differently, that means that processes need to be understood to identify the optimal locations for NFM and which features to install (Pattison & Lane, 2012). For stakeholders to successfully implement NFM, a greater understanding of the processes involved is requited by catchment managements in order to educate and engage the public.
“SUDS, rewilding, tree planting on flood plains” Respondent 2
“Flood management controlled by natural methods e.g. silt traps, field storage, leaky dams, reprofiling…” Respondent 7
Only 13% of respondents attempted to describe the processes involved in NFM (e.g. respondent 9 and respondent 12), indicating a deeper understanding than the majority of catchment managers.
“The use of natural landscape features (wetlands, ponds meadows...) and ecosystems to manage the effects of flooding. In some instances landscape feature may be created(engineered) or existing features managed more effectively. In some instances these activities may be some distance upstream from the areas at risk of flooding” Respondent 9
“mitigation of peak flows and retention of sediment using natural sustainable features” Respondent 12
For effective installation of natural flood management measures, advise to land owners must be given in specific context to the land in question by trusted and informed advisors (Holstead et al., 2017).
7.4 Resilience to flooding
This section investigates the theme of resilience within catchment stakeholders to flood risk and its impacts. Resilience has previously been defined by Walker et al., (2002) as having three key attributes: 1) Maintenance of structure and function in the face of disturbance, 2) to continue to be self
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Chapter Seven: Social attitudes and perception of flood risk management in the River Eye Catchment organised in the event or anticipation of a disturbance and 3) the capacity for learning and adaptation.
7.4.1 Personal resilience to flooding
Farmers and resident stakeholders were asked questions to determine their personal resilience to flood risk. Farmers were asked in terms of NFM and setting aside land for flooding in rural upstream areas. Residents were asked questions relating to individual changes they would be prepared to make to their properties.
Farmers were asked if they were willing to set aside land for flood risk management (Figure 7.12). This question was used as an indicator for willingness to participate in NFM schemes and resilience for personal flood protection. The results show only 17% of farmers were willing to consider setting aside land for flooding. The results reflect findings by Holsted et al (2017) who found farmers are concerned with installing NFM measures in isolation, when it should be a joint responsibility. Holstead et al, (2017) found 53% of farmers who had not installed NFM was due to their views on land being too valuable and a further 38% have not been incentivised due to insufficient funding.
17%
33% Yes No Unsure
50%
Figure 7.12 Percentage of farmers willing to set aside land for flood risk management
For the farming community to embrace NFM, implementation must be integrated in policy to ensure consistent messages are communicated to
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Chapter Seven: Social attitudes and perception of flood risk management in the River Eye Catchment reduce isolation in installation and be adaptable to current agricultural practises. For NFM to be truly effective the financial, social and cultural barriers involved in soft engineering techniques need to be addressed.
Residents were asked to identify which of the popular flood property mitigation measures they would most likely install in their homes to reduce personal flood risk (Figure 7.13). Less invasive, resillience measures such as installation of water butts to collect rainwater were the most popular flood mitigation option. 35% of respondents have already installed this feature. Metal barriers on external doorways (36%) is the most likely mitigation measure to be installed in response to flood risk. In contrast, alterations to external housing features, resistance measures, such as permeable driveways and gardens are the least popular options. The results indicate residents are more likely to make internal changes to their properties as opposed to external alternations to driveways and gardens. The results support findings from Brilly and Polic’s (2005) study where residents were also prepared to take small personal counter measures to mitigate flood risk. The accounts of previously flooded residents show the flood threat in Melton Mowbray is still within recent memory, suggesting community may be resilient to flood risk as residents have remained in properties and recovered from flood incidents as opposed to relocating Figure 7.6. This indication of resilience to flooding in the residents stakeholder responses is positive as Stark and Taylor (2014) argue that successful community resilience will enable local communities to assist governments in crisis response and recovery, not replace.
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Chapter Seven: Social attitudes and perception of flood risk management in the River Eye Catchment
Rise plug sockets
Tiled or conrete ground floor
Metal barriers on doors
Set aside garden to flood
Driveway to gravels
Patio to grass
Water Butt
% of respondents -60 -40 -20 0 20 40 60 80 100
Figure 7.13 Likert scale showing personal property protection residents may use to reduce flood risk.
Managers were asked to rank which elements of their jobs they consider are barriers to their work targets (Figure 7.14). This question was asked to determine how resilient catchment managers are to difficulties in installing measures to improve the catchment. The results show funding is considered the largest barrier to catchment managers work, whilst social groups such as farmers, land owners and residents were seen by most managers as a moderate barrier to work. This result is in keeping with Holstead et al (2017) who found long-term financial incentives are required to increase the uptake of NFM in farming communities, not the communities themselves. Furthermore, a survey conducted by Heitz et al (2009) on risk perception found local councils struggle to implement best practise due to conflict with other stakeholders such as farmers, populations and other governing agencies.
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Chapter Seven: Social attitudes and perception of flood risk management in the River Eye Catchment
9 8 7 6 5 4 3 2 Numberresponses of 1 0 Funding Other Landowners Farmers Residents Other organisations
None low moderate high
Figure 7.14 Catchment Managers barriers to work
7.4.2 Methods of reducing fine sediment deposition
To ascertain current attitudes to hard and soft engineering approaches, stakeholders were asked to rank between “very ineffective” and “very effective” which of the following measures would be in reducing fine sediment and flood risk. The measures represent two methods of future flood risk; hard engineering and soft engineering (see section 2.8).
The Likert Scale (Figure 7.15) displays a more diverse range of opinions by the catchment managers and famers on hard engineering responses, shown by the shift to the left on these measures. In contrast, residents generally appear neutral or positive in attitude towards the suggested measures.
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Chapter Seven: Social attitudes and perception of flood risk management in the River Eye Catchment
Figure 7.15 Likert Scale depicting the opinion of stakeholders perceived effectiveness of future flood defences
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Chapter Seven: Social attitudes and perception of flood risk management in the River Eye Catchment Soft engineering methods such as winter crops on arable fields, fencing on river banks to limit damage, planting of trees to increase soil stability and silt traps to encourage deposition in known locations have been positively viewed by catchment managers. For instance 87% of catchment managers believe that planting trees is an “effective” or “very effective” method of reducing fine sediment in rivers. Similarly, 80% of respondents rank winter crops in the same regard.
The positivity towards future NFM measures in the catchment were further emphasised through the open question asking stakeholders “what future flood defences would you like to see in your area”. 77% of catchment managers responded with Natural Flood Management or examples of working with natural processes, indicating a shift from reliance on hard engineering structures. Managers also recognised the need for future planning for sustainability:
“More holistic approach rather than focussing on short term fixes when problems arise.” Catchment Manager Respondent 6
The results reflect Landstrom et al's (2011) research on community engagement with NFM measures in the town of Pickering, North Yorkshire which focused at reducing runoff from upland areas which had been exacerbated in recent years by poor land management such as over grazing, overstocking and poor drainage (Forestry Commission, 2015). The successful collaborative scheme raised awareness and resilience to flooding within the community and raise awareness of natural flood measures.
Many respondents emphasised the importance of working with natural processes as means of resilience to flooding rather than adopting traditional engineering methods which artificially alter the watercourse.
“more water storage at peak flow times” Catchment Manager Respondent 14.
42% of farmers attitudes had a positive attitudes towards future flood management plans which caused more out of bank flows and were generally
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Chapter Seven: Social attitudes and perception of flood risk management in the River Eye Catchment more concerned with sediment delivery downstream as opposed to seeking more flood defences:
“Melton has always flooded this is nothing new. Why are more defences needed, there have been no significant floods since the dam was built? Flooding of flood plain is natural and supposed to happen! It would be quite nice if arable farmers upstream stopped sending us their sediment though.” Farmer Respondent 1
Similarly, farmers who participated in the survey have indicated an acceptance of soft engineering measures with 100% of respondents ranking silt traps as an “effective” measure to reduce sediment run off. This is extremely positive for future catchment management as many NFM measures rely on compliant farmers to install and maintain features. 100% of respondents ranked planting winter crops to increase soil stability and reduce runoff as “effective”, indicating farmers understand sediment transport within the catchment and the adverse environmental and economical effects loss of top soil during the winter.
Interestingly, farmers responses were most diverse when ranking the effectiveness of planting trees (Figure 7.15). Farmers who ranked planting trees “ineffective” were arable and combinable crop farmers. This type of farming practise wouldn't benefit from tree planting in comparison livestock farming where trees can provide a corridor to prevent access to animals reducing bank stability. The loss of field edges and soil moisture content to trees would have a negative influence on arable crops.
Farmers often view natural flood management efforts as a “planting tree exercise” (personal communication with farmer during fieldwork) without much thought to location or long-term stability. In contrast, residents ranked planting trees as the most effective soft engineering measure with 60% of respondents ranking it “effective” or “very effective”. This may be a direct result of media portraying NFM as planting more trees and providing a greater aesthetic appeal in comparison to re-wilding methods, such as the publicity received from the NFM work undertaken in Pickering, North Yorkshire.
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Chapter Seven: Social attitudes and perception of flood risk management in the River Eye Catchment Residents showed a stronger preference to hard engineering approaches. Flood embankments, bank protection and dredging were highly ranked as “effective” and “very effective” (73%, 81% & 93% respectively). These results indicate public confidence in traditional flood defence structures which are visual in their defensive method. Farming respondents similarly approve of hard engineering methods positively, particularly bank protection (80% effective and very effective responses), This is in keeping with moderate to high ranking of bank erosion as flood risk factor and an observed increase in out of channel flows. indicating an overall positive trend towards sediment reduction methods. This may be a result of the farming community witnessing sediment runoff in the rural catchment reaches.
Catchment managers appear the least positive stakeholder to hard engineering methods, represented by the decreased percentage in “very effective” rankings compared to soft engineering measures. In addition 50% of managers “neutral” on flood embankments, compared to dredging where 54% ranked it “ineffective” or “very ineffective” in reducing sand and silt.
Dredging was the most divisive measure of sediment reduction between stakeholder groups with 19% of catchment managers, 60% of farmers and 93% of residents ranking it as “effective” or “very effective”.
Dredging received increased press coverage in the wake of the Somerset Levels 2014 flooding in which local action group FLAG increased publicity on the flood defence measure to insight a response from the Environment Agency. This may have contributed to the positive association with dredging practises as a method of flood defence. Farmers saw the removal of silt from the channel as a positive move for flood risk and suggested dredging as the method to achieve this:
“I think the rivers should be dredged to clear out the silt.” Farmer respondent 4
The residential survey provided a consensus of responses of wanting the river “cleared out” maintenance:
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Chapter Seven: Social attitudes and perception of flood risk management in the River Eye Catchment “River's cleaned out more often” Residential respondent 29
Stakeholders were also asked an open question to determine the broader opinions of dredging (Figure 7.16).
7.4.3 Attitudes towards channel dredging Catchment Farmers Residents Managers
20% 3% 19% 40% 6% 13% 60% 67% 72%
Figure 7.16 Catchment stakeholders attitudes towards channel dredging The results reflect the Likert Scale in (Figure 7.15) indicating a trend in negative opinion of dredging by catchment managers. Many responses from this stakeholder group justified their opinion, suggesting a comprehensive understanding of the dredging process and subsequent aversion:
“Not supportive. It is a reactive process with a large impact and disturbance to water courses and wildlife & morphology.” Catchment Manager 12
“increases channel capacity short term lowers level of river and possibly velocity increasing bank erosion and transport times” Catchment Manager 1
However, 20% of respondents, mainly those working within maintaining river navigation believe dredging is an effective method and are yet to value alternative methods in the same regard:
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Chapter Seven: Social attitudes and perception of flood risk management in the River Eye Catchment “For me this is the most effective way to reduce the risk. Other things come close but are secondary.” Catchment Manager 14
The catchment managers response reflects the fundamental difficulties in transitioning from sole reliance on hard engineering flood defences. Dredging provides tangible, visual results which clearly demonstrate an increase in channel capacity. Increasing stakeholders cultural beliefs in proactive flood measures which aim to maintain channel capacity is a key challenge for future sustainable flood defences.
Farmers appear the most positive towards dredging, through the survey returning no negative responses. This may be a result of dredging being a historic deep rooted agricultural practise (Gray, 1996). However, there is encouragement from respondents such as this who are aware that it isn’t a long term solution or appropriate for the River Eye catchment.
“Channel dredging increases the storage area so reducing flood risk but needs to be combined with measures to reduce the volume of silt entering the channel.” Farmer 3
Residents had highest number of positive comments which included responses such as “excellent” “important” “very good”. Responses such as these provide little indication of the reason behind the positive response. It may be a result of the observed sedimentation downstream through the town of Melton Mowbray where the residents survey was based. Furthermore, many of the residents responses referred to river aesthetics, such as how clean the river was and removal of debris, as opposed to flood remediation. This may reflect that 75% of residents do not consider themselves at risk of flooding (Figure 7.6) and therefore are not as concerned with flood risk measures:
“I think it is a good idea. Also we live in such a filthy environment now, our river is full of rubbish i.e. large waste bins, mattresses, bicycles, tyres, toys, bottles its endless.” Resident 17
However, 6% residents expressed caution when using dredging techniques, highlighting potential negative impacts:
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Chapter Seven: Social attitudes and perception of flood risk management in the River Eye Catchment “Would be Ok with channel dredging as long as done in a way to minimalize effect on wildlife.” Resident 29
A CIWEM (2014) report found though dredging can increase channel capacity in the excavated area the straightening of channels can increase flood velocity and exacerbate flooding downstream. Modifications to channel banks and morphology can increase sediment erosion resulting in more fine sediments entering the river channel which may negatively affect water quality as well as the channel capacity. Maintaining an unnatural channel capacity requires expensive maintenance, estimated at approximately £20 000 per km (CIWEM 2014). In contrast, NFM installing in Pickering was estimated at £4.2 million with minimal future maintenance costs, indicating a more cost-effective approach. With 100% of catchment managers ranked “funding” as a moderate or high barrier to work (Figure 7.14), cost effective solutions to flooding are becoming increasingly important.
The results of the dredging question highlight a disparity in stakeholder opinions which may result in resistance to NFM and soft engineering approaches. Greater communication is required between catchment managers and farmers and residents to disseminate public awareness of alternative flood defences and increase community resilience.
The results of the survey has identified stakeholder awareness for mitigation measures at both the individual and catchment scale indicating both awareness and resilience to flood risk. Heitz et al (2009) found complementary attitudes in residents, farmers and local council when exploring the risk perception of muddy floods in Alsace, France. The local council were found to have a sstrong awareness of risk and believe they are informed to make decisions (Heitz et al, 2009), which is similar to the River Eye with many catchment manager responses indicating a strong awareness of fine sediment within the catchment.
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Chapter Seven: Social attitudes and perception of flood risk management in the River Eye Catchment 7.5 Stakeholders perception of responsibility
This section explores the theme of responsibility in three areas of flood management: 1) informing residents of an impending flood, 2) protecting personal property and 3) implementing flood risk management strategies.
7.5.1 Responsible for informing residents
Residents were asked which of the following groups were responsible for informing them of imminent flood events (Figure 7.17). 86% of respondents held the Environment Agency either Highly or Solely responsible. Larger consortiums such as National Government and Local Councils were identified as highly responsible 37% and 22% to inform residents, suggesting these authorities are most trusted to disseminate information. This is a contrast to literature where a survey revealed that respondents rely on local authorities as a main source of information for risk highlighting that policies conducted at the national or regional bodies are weaker at raising awareness (Heitz et al., 2009). Trust in local authorities to provide hazard news and warnings is a continuing theme in hazard awareness studies (Brilly & Polic, 2005; Heitz et al., 2009). Local solutions such as local radio commentary were found to be more trusted in disseminating concise information (Brilly & Polic, 2005).
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70
60
50
40
30
% of % respondents 20
10
0 No Small Moderate High Sole
Residents Local action groups Local council Community groups
Environment Agency National Government Military
Figure 7.17 Residents were asked to rank who was responsible for informing residents of an imminent flood event. 7.5.2 Responsible for implementing flood risk management
Finally, all stakeholders were asked to rank the responsibility of the following groups in managing flood risk (Figure 7.18) (Q17). The results show the stakeholders agree that larger government derived organisations (represented by the darker colours) are held accountable for managing flood risk. The Environment Agency was identified as the most responsible by all three stakeholder groups, with local council and National Government ranked second and third respectively. The results reflect the reality that the Environment Agency are the principle operating authority for flood defences (Butler & Pidgeon, 2011) with local councils responsible for the maintenance of local flood defences (Brown & Damery, 2002).
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Chapter Seven: Social attitudes and perception of flood risk management in the River Eye Catchment
Managers 100 80 60 40 20
% of % respondents 0 0 1 2 3 4 5
You Homeowners Landowners Farmers Local council Environment Agency Natural England National Government
Farmers 60
40
20
% of % respondents 0 0 1 2 3 4 5
You Homeowners Landowners Farmers Local council Environment Agency Natural England National Government
Residents 40 30 20 10
% of % respondents 0 0 1 2 3 4 5
You Homeowners Landowners Farmers Local council Environment Agency Natural England National Government
Figure 7.18 Question asked to all stakeholders: Who is responsible for flood risk management? Where 0 is not responsible and 5 is highly responsible. Individuals such as “you” “homeowners” and “landowners” (represented by the lighter colours) were ranked comparatively lower in responsibility indicating a detachment of responsibility at the individual level. For residents, 74% ranked “you” responsibility between 0-2 (low responsibility) suggesting that communities in Melton Mowbray may be less resilient to future flooding as they
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Chapter Seven: Social attitudes and perception of flood risk management in the River Eye Catchment feel less responsibility. Reduced resilience to flooding maybe a result of a loss of flood memory within the community, which can increase community resilience (McEwen et al, 2017) as only 19% of residents have personally experienced flooding (Figure 7.3). For communities to increase resilience to future flood risk, engagement is required from larger organisations to include local residents in decision making.
However, some residents inferred resilience and responsibility for property protection when asked which future flood defences they would like to see in the River Eye catchment:
“Better availability of sand bags. Higher level walls at the back of our house, adjacent to brook and river too. Regular dredging of river channel” Resident 33
The mention of sand bags as a flood defence infer an attitude of reactive flood defence measures as opposed to proactive planned defences. Residents who have experienced flooding are more aware of flood risk (Burningham et al, 2008). The property-level request for flood protection measures indicates personal resilience to flood risk. The subsequent mention of dredging as a mitigation solution highlights residents awareness for larger scale flood defences to maintain channel capacity and reduce the quantity of out of channel flows.
7.5.3 Responsible to protect residential property during a flood event
Residents were also asked which groups were responsible to protect their properties in the event of a flood (Q16). Here, 25% of residents hold themselves highly or solely responsible for personal property protection, compared to only 10% who deem themselves responsible identifying an impending flood (Q15) (Figure 7.17). Local Council and Environment Agency are considered the most responsible with 67% and 50% of respondents ranking their positions as highly or solely responsible. This indicates a good awareness from stakeholders of flood risk responsibility as the Environment
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Chapter Seven: Social attitudes and perception of flood risk management in the River Eye Catchment Agency are responsible for the management of flood risk from main rivers (Environment Agency, 2018a).
40
35
30
25
20
15 % of % respondents 10
5
0 No Small Moderate High Sole
Residents Local action groups Local council Community groups Environment Agency National Government Military
Figure 7.19 Residents were asked to rank which of the following catchment stakeholders were responsible for providing protection to their properties during a flood. 7.6 Chapter Summary
This chapter sought to identify the potential social barriers to flood risk management for three catchment stakeholders: catchment managers, farmers and residents. Questionnaires were successfully answered to create an understanding of stakeholders perceptions of awareness, resilience and responsibility of flood risk.
Stakeholders were observed to have a strong awareness to the intrinsic links between sediment delivery’s influence on channel capacity and subsequent flood risk as 73% of catchment mangers, 80% of farmers and 66% of residents ranked sediment and soil runoff a moderate or high contributor to flood risk. The results suggest all three stakeholder groups are aware of natural sediment transport and its potential sources of river banks, natural features and agricultural fields, particularly that sources of fine sediment may not be spatially close to areas of deposition, which have been supported by results in chapters five and six. The survey also identified an increase in sediment
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Chapter Seven: Social attitudes and perception of flood risk management in the River Eye Catchment deposition downstream in Melton Mowbray by, the 40% of catchment mangers who work within this area in navigation, flood risk and water quality sectors. In contrast, mangers who are focused upstream within agricultural land and within the SSSI saw a decrease in sand and silts, in keeping with earlier findings that silt traps are efficient in reducing fine sediment downstream.
The survey highlighted potential disparities between stakeholder groups and their awareness of current flood defences. Farmers were found to be the most informed with 54% naming explicitly or alluding to a feature (Brentingby Dam, silt traps) of the Melton Mowbray Flood Alleviation Scheme. Only 19% of residents were able to name Brentingby dam, highlighting a lack of engagement with flood defences protecting the town of Melton Mowbray.
Residents and farmers were found to be resilient to flood risk with both stakeholders prepared to make person changes to increase flood protection and perceptive to new soft engineering approaches to future flood risk. Though residents did show a strong preference to traditional engineering approaches with the following ranked as effective or very effective: 73% Flood embankments, 81% bank protection and 93% dredging. However, larger organisations of the Environment Agency and national government were identified as the most responsible for managing flood risk.
Catchment managers appear the least positive stakeholder to hard engineering methods, and 100% of managers ranked “funding” as a moderate or high barrier to work, highlighting the importance of finding cost effective solutions to flooding. In addition, 50% of managers “neutral” on flood embankments, compared to dredging where 54% ranked it “ineffective” or “very ineffective” in reducing sand and silt. Dredging was the most divisive measure of sediment reduction between stakeholder groups with 19% of catchment managers, 60% of farmers and 93% of residents ranking it as “effective” or “very effective”.
The successful collection of catchment stakeholders views on sediment management and flood risk are extremely important to identifying the potential non- technical barriers of future flood management. The results of the survey
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Chapter Seven: Social attitudes and perception of flood risk management in the River Eye Catchment can be compared to previously collected geomorphic, and hydrological data to determine whether stakeholder perceptions align with reality.
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Chapter Eight: Conclusions
8 Chapter Eight Conclusions
8.1 Chapter Scope
This chapter summarises the findings of this study and revisits the main thesis aim and objectives. The overall aim of this research was: To investigate the current influence of fine sediment on fluvial flood risk in the River Eye, Leicestershire. To achieve the aim the thesis employed a novel hydrological geomorphological, engineering and social science based approach to produce an integrated answer, inclusive of human interactions (both engineering and social) with water and sediment. A series of five objectives were created to identify the interactions of fine sediment and flood risk within the River Eye catchment. initially focusing on the sources and transport of fine sediment (geomorphology and hydrology)(chapter five) and then assessing their interactions with existing flood mitigation measures (engineering)(chapter six) and finally the non-technical (social) issues which may impact fine sediment influence on flooding (chapter seven). An evaluation of this unique approach will be conducted in the fifth objective as well as a series of recommendations to catchment managers.
In order to assess if the aims of the thesis have been met, the results of objectives 1-4 will be discussed followed by a critical evaluation of the methods and results. A series of catchment recommendations will be made followed by areas of potential future work.
8.2 Objective one: Identify the sources of fine sediment within the River Eye catchment
Objective one sought to identify the sources of fine sediment within the River Eye catchment using a risk-based model. Connectivity and erosion risk in the River Eye were relatively low due to small topographical changes within the catchment, suggesting in-channel sediment is likely to originate from local
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Chapter Eight: Conclusions sources such as channel banks. SCIMAP identified Burton Brook and Langham Brook tributaries as the sub-catchments with the highest sediment connectivity and erosion risk, indicating these are likely sources of fine sediment within the catchment. This result was supported by TIMS data which identified Burton Brook as the location with greatest sediment yield per km2 (17.4g km2 day), suggesting it is a significant source of fine sediment which may influence channel capacity and downstream flood risk. Changes to land cover risk weightings identified arable fields as having the largest impact on erosion risk, due to its dominance in catchment land cover (68.5%), indicating it is a likely source of fine sediment. The use of a DSM layer which includes the representation of surface features such as buildings, roads, hedgerows and footpaths showed an increase in catchment connectivity. Similarly, future climate predictions saw an increase in connectivity and erosion risk during the winter scenarios, suggesting more of the catchment will potentially become connected to the channel, highlighting the importance of sediment management. SCIMAP has successfully fulfilled objective one of the thesis by identifying sources of fine sediment within the catchment.
8.3 Objective two: Determine the spatial-temporal patterns and controls of fine sediment transport
Low cost samplers (TIMS) were successfully deployed into the catchment across 11 locations to monitor the spatial and temporal patterns of fine sediments transported in the suspended load. The samplers were installed for a 21 month period and identified the Eye main tributary having the highest sediment load of 499.9g day-1, reflecting the hot spots of connectivity observed in SCIMAP models. The monitoring identified suspended sediment load is higher in the upper reaches of the catchment, particularly at Stapleford woods located on the main channel upstream of Ham Bridge silt trap. The observed decrease in sediment load downstream is indicative of the silt trap at Ham Bridge successfully reducing suspended sediment downstream.
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The addition of in-channel TIMS data provided an indication of suspended sediment spatial patterns identifying sites on the main channel, particularly Stapleford woods (site 5) upstream of Ham Bridge silt trap, as containing the highest sediment load. The sudden decrease in sediment loas observed in locations on the main channel downstream of the Ham Bridge indicate the silt traps effectiveness in reducing downstream sediment load and yield. With the inclusion of sediment data downstream of the silt traps, the specific sediment yield in relation to catchment contributing area showed an absence of a negative trend, suggesting spatial patterns of fine sediment transfer are not continuous throughout the catchment and local sources of fine sediment are being introduced downstream. This is supported by particle size analysis from TIMS which indicates no evidence of downstream fining and an elevation in organic matter content downstream, suggesting bank erosion is a likely source of fine sediment.
The relative efficiency of the TIMS samplers was also determined at 6 locations where adjacent samplers were installed in the channel. The samplers were found to have a percentage sediment load difference of 4%-171%, indicating a high degree of variation due to sampler positioning within the cross section. As samplers were installed in similar positions within each channel it is likely the relative efficiency between sites is within this range although sites located in smaller channels were found to be less variable. The analysis of physical suspended sediment properties in adjacent samplers were found to be similar, suggesting they provide an indication of spatial fine suspended sediment transfer, though not as robust as high cost methods of sampling. However, they do provide a temporal record which is unable to be achieved through spot sampling.
8.4 Objective three: Assess the impact of existing flood defences on natural sediment transport
The geomorphic and hydrologic monitoring of three flood defence sites in the River Eye have provided an insight into their impact on fine sediment dynamics.
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Both silt traps located at Ham Bridge and Burton Brook are shown to be effective in reducing the suspended sediment load downstream of their installation. Burton Brook silt trap is arguably more effective as the reduction in suspended sediment load downstream was recorded between 59.7-98.0% on 7/8 occasions by the samplers compared to Ham Bridge which estimated 32.5-71.9% on 5/8 occasions. The silt traps were found to be most effective during moderate flows, commonly experienced in spring and autumn. In contrast, Brentingby Dam was shown not to have an effect on suspended sediment load, suggesting the presence of the dam does not impede flow or fine sediment when the sluice gates are open.
The silt traps also observed a reduction in D50 and D84 particle sizes from upstream to downstream, suggesting the traps are retaining the coarser component of fine sediment. This result suggests that the silt traps may also trap coarse sediment entering the silt trap due its morphology. A reduction in coarse sediment downstream may reduce available habitats for fish spawning with the SSSI, though sampling of the silt trap is required to determine the particle sizes retained within. In addition the sediment traps do not appear to have an influence on organic matter content, which is usually transported with the finest particles and therefore reflects the results observed in the particle sizes.
A hydrologic appraisal of the silt trap at Ham Bridge observed a backing up of water during high-flow events which may increase flood risk upstream of the silt trap. The effect of back up was observed for 27 hours during one event suggesting the position of silt traps within the catchment should be carefully considered with respect to impact on local flood risk.
8.5 Objective four: Determine the non-technical barriers to sustainable natural flood risk and sediment management
Chapter seven focused on answering objective four by disseminating questionnaires to catchment stakeholders on the themes of awareness, resilience and responsibility to determine the non-technical barriers to flood risk management.
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Stakeholders were found to have a strong awareness to links between sediment delivery, channel capacity and subsequent flood risk as 73% of catchment mangers, 80% of farmers and 66% of residents ranked sediment and soil runoff a moderate or high contributor to flood risk. The results suggest sediment mitigation measures to maintain flood risk would not incur social barrier to future flood risk. In addition, the survey identified an observed increase in fine sediment within Melton Mowbray by catchment managers who work in navigation, flood risk and water quality, identifying a future research area and a potential increase in flood risk from fine sediment deposition. This is contrasting to catchment mangers situated in SSSI who noticed a decrease in fine sediments, reflecting the results of the TIMS data in chapter five. A key finding of the questionnaire was the lack of awareness from stakeholders of the flood defences currently protecting the town of Melton Mowbray. Only 19% of residents were able to name Brentingby dam, highlighting a lack of engagement of the public with upstream flood measures. However, residents situated downstream in Melton Mowbray did appear resilient to future flooding, willing to make personal changes to properties to increase personal protection. National bodies such as the Government and Environment Agency were identified as those responsible for managing flood risk, indicating stakeholders perceptions of flood risk management are aligned to the reality.
100% of Catchment mangers identified funding as a barrier to work, emphasising the importance of finding sustainable, cost effective solutions to flooding. Perceptions on current flood defences also identified a barrier to natural flood management. Residents showed a strong preference to traditional engineering techniques ranking flood embankments (73%) and bank protection (81%) as the most effective measures of flood defence. Dredging appeared the most divisive measure of sediment reduction to mitigate flood risk with 19% of catchment managers, 60% of farmers and 93% of residents ranking it as effective or very effective. This result highlights the disparity in stakeholder thinking within the catchment and identifies the importance of educating stakeholders of the alternative methods of sediment removal (such as silt traps) to improve sustainable flood management. For the farming community to embrace NFM, implementation must be integrated in
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8.6 Critical evaluation of methods
This section reviews the problems with the methods used to achieved objectives 1-4 and the limitations associated with the results. The methods have been broken down into three key areas: modelling, physical data collection and social data collection.
Using modelling to identify potential sediment sources within the catchment provided some limitations to the study. Firstly, data availability. Terrain data was unavailable for the whole catchment at 1m or 2m LiDAR resolution resulting in a 5m DTM and DSM being used. At this resolution morphologically significant features such as the silt traps and dam were not included into the model, providing an under representative assessment of connectivity and erosion risk within the catchment. Furthermore, though the inclusion of surface features was shown to be successful a higher resolution DSM would have provided increased detail of specific areas; particularly those highly connected. Similarly, the absence of long term rain gauges in the catchment and additional soil and land cover information from land owners resulted in using national mapping layers from BADC and CEH provides less detail. The inclusion of additional land cover data which could have incorporated risk weightings associated with farmers that employ practises such as tilling and bare earth fields in the summer which would increase erosion risk in these areas, improving the quality of the output.
Arguably, the largest sources of error within the thesis are associated with physical data collection and its subsequent limitations. The limitations directly associated with TIMS samplers has been outlined in Chapter Six (section 6.8) this section will focus on the wider limitations of using this methodology on the study. Firstly, the results of the TIMS samplers indicate a higher degree of relative efficiency when samples are made at regular collections. During high
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The installation of mini divers upstream of ham bridge provided an insight into water level in the upper reaches of the River Eye. The installation of stilling wells upstream of Ham Bridge silt trap were limited to areas where the wells could be secured to the river bank and in areas where water was going to be present throughout the year, resulting in all three stilling wells being placed in deeper sections of the channel, which may have dampened changes in water level. Water levels were checked to ensure the inside and outside of the wells were measuring the same depths. During times of diver data collection, the readings before and after collection on occasion would misalign due to the sudden change in pressure, resulting in further compensation of the data to ensure water levels were continuous. The absence of an upstream gauge in the catchment meant there was no secondary data source appropriate for determining how accurate the divers are in recording precise water level readings. To comprehensively assess the hydrologic implications of silt traps on river channels, additional divers should have been installed downstream of
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Social data collection though robust, is limited due to the number of respondents. Catchment mangers are well represented (75% return rate but the response rates indicated farmers and residents were less engaged (17.5% and 16% respectively) which may result in under representative viewpoints. A potential reason for reduced responses from both farmer and resident stakeholder is the methods used to contact them. Farmers were emailed via Natural England due to their comprehensive contact list. However, association with Natural England may have negative connotations for farmers. Similarly, using a postal survey to contact residents may have limited responses as it requires residents to return the questionnaires using the stamped addressed envelope, requiring time. Employing door-to-door methods and telephone calls may have increased response rate and captured viewpoints of stakeholders who were unengaged with the questionnaire.
8.7 Objective five: Create a catchment management plan containing recommendations to improve sediment management within the River Eye catchment incorporating a combined hydrology, geomorphology, engineering and social science approach
Based on the successful answering of objectives 1-4 a series of recommendations to catchment managers has been made:
- Silt traps
The results of thesis have shown the silt traps installed at Burton Brook and Ham Bridge are effective in reducing fine sediment load downstream, particularly in moderate flows. A key recommendation from this would be to sample the sediment collected in the silt traps to confirm if coarser particles are being trapped which may have consequences for both aquatic life and flood risk. Regular monitoring of the silt traps is required in two key areas: hydrology and geomorphology. Long term water level monitoring up/downstream of the silts traps would provide further insight into the influence
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Chapter Eight: Conclusions of silt traps during high flows, insuring future NFM measures do not increase local flood risk. Secondly, a survey of the silt trap to determine its current capacity and subsequent depth checks to calculate rate of deposition would help create a maintenance plan for optimal efficiency.
- Source areas
This study has found potential source areas of high connectivity in Burton Brook, Langham Brook and River Eye tributary, highlighting target areas of the catchment focus sediment interventions measures to inhibit connectivity pathways linking sources to the channel. Two additional source areas to target sediment management are agricultural fields and river banks. Installation of buffer strips on field boundaries and fencing would help to reduce fine sediment delivery and cattle trampling increasing erosion.
- Monitoring an forecasting
The study has shown the importance of monitoring both the catchment with low-cost effective samplers and individual features such as Ham Bridge silt trap and Brentingby Dam. Creating a long term spatial and temporal dataset would be invaluable for monitoring fine sediment delivery and transport and calculating the effectiveness of future NFM measures. A key recommendation would be the installation of a gauging station in the upper rural reaches of the catchment to monitor upstream water levels. Additional monitoring through the installation of turbidity monitors would provide valuable insight into fine sediment transport within the channel.
- Awareness
Results from the social survey have identified a lack of awareness of current flood and sediment mitigation measures within the catchment from farmers and the public. Efforts need to be made to increase awareness of existing flood defences, highlighting the success of installed NFM measures such as Burton Brook silt trap to increase understanding of the potential multiple benefits associated with NFM. Improving the publicity surrounding soft engineering
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Chapter Eight: Conclusions techniques that are working with natural processes may help to change publics perception on dredging as a desirable flood management method.
- Engagement
The final recommendation for catchment managers is to improve stakeholder engagement with farmers and residents to increase resilience. To improve uptake of NFM, farmers and landowners need to be informed of potential NFM benefits both personally and at a catchment scale. Personal benefits can include economic when measures preventing sediment runoff are installed as soils can be replaced on to the land with no additional costs of adding topsoil or fertilsisers. The introduction of a demonstration site which has already installed NFM features in the catchment or a series of meetings targeted at engaging the rural community would improve the transition to sustainable sediment management.
The second section of objective five was to reflect on the novel approach used to determine the influence of fine sediment on flood risk. This study identified potential sources of fine sediment through hydrological connectivity and erosion risk modelling, which may cause a reduction in channel capacity if connected to the channel. Three sub-catchments and arable fields were identified as areas of increased erosion risk. A geomorphological study of spatial and temporal patterns of suspended fine sediment was achieved by installing low cost samplers throughout the catchment, providing a comprehensive insight into sediment transport, identifying tributaries and sites on the main channel with significant contributions to fine sediment delivery. An assessment of the installed flood defences provided a unique opportunity to evaluate established silt traps in the catchment finding them effective in reducing fine sediment load downstream. Finally, the inclusion of the social questionnaire enabled the identification of barriers to flood risk including lack of awareness of current flood measures, but a strong understanding of potential sediment sources which aligned with physical evidence collected in the catchment.
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The results from the social questionnaire have explored stakeholders awareness, resilience and responsibility for physical processes within the catchment. The results from objectives one and two provide an insight into whether these perceptions held by stakeholders are in keeping with the physical evidence found during the study.
When asked to identify the potential sources of fine sediment within the catchment, all three stakeholder groups named; natural features, agricultural fields and river banks as the three main contributors (Figure 7.8). Results from SCIMAP modelling have identified sub-catchments such as Burton Brook and Langham Brook which have the highest topography in the catchment as highest erosion risk. Similarly, the SCIMAP results which investigated risk weighting for arable and improved grassland land covers saw a reduction in erosion risk when the weighting was reduced, predominately arable, suggesting these are likely to be sediment sources. Thirdly, suspended sediment yield calculations which included downstream TIMS data from the silt traps showed an absence of a negative correlation between catchment contributing area and sediment yield, suggesting sediment is being introduced throughout the catchment. This is supported by the TIMS analysis showing no evidence of downstream fining in the catchment, indicating that river banks are a likely source.
Catchment stakeholders were asked to rank the effectiveness of silt traps as a method of flood defence. 100% of farmers, 74% of catchment managers and 48% of residents believed silt traps are an effective flood defence. The results from the hydrologic and geomorphic appraisal suggest the silt traps are effective in reducing the suspended sediment load downstream, indicating a natural maintenance of channel capacity downstream, sustaining flood risk. However, only 17% of farmers said they would be willing to set asides land for flood risk, suggesting engaging farmers with installation of NFM features may be difficult.
Finally, stakeholders were asked whether they had witnessed fine sediment deposition on the bed. 40% of catchment managers, 40% of farmers and 83% of residents had seen an increase in fine sediment deposition (Figure 7.11).
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This result is surprising as the geomorphic appraisal of silt traps has shown them to be effective at reducing sand and silt downstream. However the observation from residents may be an indications of high volumes of fine sediment from Thorpe and Scalford Brooks which join the River Eye downstream of Brentingby Dam. Furthermore, the result suggests an increase in potential sediment sources downstream of Brentingby Dam. The results suggest that attitudes of stakeholders to fine sediment catchment processes are well aligned to the physical findings of the study. In conclusion, this framework is successful in providing a comprehensive insight into fine sediment dynamics and their interactions with current flood defences and key catchment stakeholders.
8.8 Future work
A potential future aim of research would be to test how transferrable this novel framework and methods are for another catchment with existing problems relating to excess fine sediment delivery into the channel. Other potential future research objectives resulting from this thesis include:
- Collection of higher resolution catchment specific land cover, crop and soil data to incorporate into risk weighting for SCIMAP models to refine areas of erosion risk.
The current standard land cover data used for SCIMAP is a 25m resolution land cover grid, which is updated approximately every 7 years by CEH. Using a combination of aerial imagery and qualitative methods to obtain farmers crop rotation information a GIS shapefile layer could be created, bespoke to each catchment. This data could be categorised using more in-depth risk weightings to generate a land cover layer which is both current and at a higher resolution to obtain a greater understanding of potential erosion risk at a sub-catchment scale. In addition, seasonal differences in connectivity and erosion risk could be more accurately measured using seasonal land cover layers.
- An improved variant of SCIMAP incorporating Bayesian parameter selection or an intelligent Monte Carlo method.
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Given the limitations of SCIMAP discussed in this thesis, a potential future research could involve creating an alternative to SCIMAP which incorporates Bayesian parameter selection, which uses probability to quantify the uncertainties. The creation of a new model also provides the potential for a higher resolution to be used, where available.
- Installation of mini divers up/in and downstream of silt traps to determine the impact of these features on water level, gaining a complete picture of hydrologic impacts.
This study focused on the upstream impact of silt traps on hydrology, where it found their presence can cause elevated water levels upstream. To determine the impact both within the silt trap and downstream a further series of mini divers would need to be installed at similar distances to those installed upstream. Further research into the downstream impact on hydrology would provide future researchers in NFM and catchment managers a greater understanding of where to install these measures without increasing local flood risk.
- Survey of the silt traps at Ham Bridge and Burton Brook to determine organic matter, particle size distribution and rate of deposition and provide an indication of maintenance.
A potential extension to the current research would be to take sediment core of the silt trap to determine the deposition rate and changes in chemical composition to the silt trap since its installation in 2003. This data combined with the spatial and temporal information presented in the thesis would provide a greater detail of maintenance required for the silt trap and if the silt trap does encourage the deposition of coarser sediment which may impact the SSSI.
- Explore the sediment dynamics and relative efficiency of TIMS
Following research by Phillips et al (2000) the efficiency of the TIMS at collecting a representative sediment sampler could be further explored to quantify the consistent error within this study. By conducting flume experiments using the TIMS from this study to determine the inlet and chamber
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Chapter Eight: Conclusions velocities. In order to calculate the absolutre efficiency, a turbidity sampler could be installed within the catchment at the same site as two TIMS to compare the calculated sediment load and yield. An extension to this work would benefit future research in this field would be a computational fluid dynamics study of the velocity field and associated sedimentation dynamics within the TIMS sampler.
- Explore fine sediment transport downstream of Brentingby Dam, Thorpe and Scalford Brook tributaries to determine whether observations made by residents who identified increases in in-channel fine sediment within Melton Mowbray during the survey are accurate in identifying increased sedimentation downstream.
The methods used in this study could be extended further downstream to consider the influence of the Scalford Brook and Thorpe Brook tributaries which join the River Eye at Melton Mowbray. Installing TIMS up and downstream of the confluences would determine if sediment within the River Eye channel through the town is originating from the rural catchment or the two tributaries which are situated within the urban extent. Complementary channel cross section survey would provide an insight into deposition rates within the channel through the town which could potentially increase flood risk to properties. This data could be compared to the qualitative data collected which found sedimentation is occurring within the town of Melton Mowbray.
- Apply geomorphic and hydrologic monitoring up and downstream before NFM measures such as silt traps are installed within catchments, to determine their absolute effectiveness in relation to baseline data collected before installation.
Due to the installation of the silt traps occurring 11 years before this research project began, no baseline data was obtainable. Future studies on catchments which have planned NFM should ensure a detailed baseline of data is collected before measures to reduce sediment are installed. Installing water level monitors and TIMS for a minimum of 1 year up and downstream of planned locations would provide valuable information which can be compared to results
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10 Appendix
1.1 Cross sectional areas of sites 1-11
Site 1
Width (m) 0 2 4 6 8 10 0 0.2 0.4 0.6 0.8
Depth(m) 1 1.2 1.4
Site 2
Width (m) 0 2 4 6 8 10 0 0.2 0.4 0.6 0.8
Depth(m) 1 1.2 1.4
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Site 3
Width (m) 0 2 4 6 8 10 0 0.2 0.4 0.6 0.8
Depth(m) 1 1.2 1.4
Site 4
Width (m) 0 2 4 6 8 10 0 0.2 0.4 0.6 0.8
Depth(m) 1 1.2 1.4
Site 5
Width (m) 0 2 4 6 8 10 0 0.2 0.4 0.6 0.8
Depth(m) 1 1.2 1.4
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Site 6
Width (m) 0 2 4 6 8 10 0 0.2 0.4 0.6 0.8
Depth(m) 1 1.2 1.4
Site 7
Width (m) 0 2 4 6 8 10 0 0.2 0.4 0.6 0.8
Dpth(m) 1 1.2 1.4
Site 8
Width (m) 0 2 4 6 8 10 0 0.2 0.4 0.6 0.8
Depth(m) 1 1.2 1.4
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Site 9
Width (m) 0 2 4 6 8 10 0 0.2 0.4 0.6 0.8
Depth(m) 1 1.2 1.4
Site 10
Width (m) 0 2 4 6 8 10 0 0.2 0.4 0.6 0.8
Depth(m) 1 1.2 1.4
Site 11
Width (m) 0 2 4 6 8 10 0 0.2 0.4 0.6 0.8
Depth(m) 1 1.2 1.4
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1.2 Catchment Mangers questionnaire 1.3 Farmers questionnaire 1.4 Residents questionnaire
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