Sep 4, 2017 - The Effects of Natural Flood Management in Rural ... of addressing floods within a holistic approach, involving every ...... Avery, Lisa M. 2012.
Master Programme in
Flood Risk Management
MSc Thesis (WSE-FRM 17-19)
The Effects of Natural Flood Management in Rural Catchments: A research and hydraulic modelling study applied within the River Thames catchment in the United Kingdom Alberto Pinto Samra 1034905 September 2017
The Effects of Natural Flood Management in Rural Catchments: A research and modelling study applied within the River Thames catchment in the United Kingdom
Master of Science Thesis by
Alberto Pinto Samra
Supervisor Prof. Dimitri Solomatine (UNESCO-IHE), Chairman
Mentors David Ramsbottom (HR Wallingford) Dr. Gerald Corzo Pérez (UNESCO-IHE)
Examination committee Prof. Dimitri Solomatine (UNESCO-IHE)
David Ramsbottom (HR Wallingford)
Dr. Gerald Corzo Pérez (UNESCO-IHE)
Dr. Berry Gersonius (UNESCO-IHE)
This research is done for the partial fulfilment of requirements for the Master of Science degree at the UNESCO-IHE Institute for Water Education, Delft, the Netherlands
Delft, The Netherlands 4 September 2017
The findings, interpretations and conclusions expressed in this study do neither necessarily reflect the views of the UNESCO-IHE Institute for Water Education, nor of the individual members of the MSc committee, nor of their respective employers.
“La educación es el alma de los pueblos y abono de los ejércitos de la libertad” -
Francisco Morazán
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Summary Over the last decades, special attention has been drawn towards sustainable ways of addressing floods within a holistic approach, involving every aspect of Flood Risk. Natural Flood Management is believed to deliver a wide range of potential benefits to the environment and society when certain measures and techniques which involve working with natural processes. This research compiles some of the existing evidence which can be useful in the process of assessing this new approach with a special focus on flood reduction. Using 2D hydrodynamic modelling software, some of these benefits have been successfully quantified by including a number of nature based measures throughout a particular study area within the River Thames catchment in the UK. Flow and Water Level hydrographs from design storms of 5, 10, 50, and 100-year return period have been collected by the model in four different locations within this catchment and plotted to observe the benefits of implementing the measures. Peak flow reductions of up to 56% were observed downstream for the 1:10 year design storm event by implementing a specific combination of Woody Dams, Hedgerows, Riparian Vegetation, Sediment Traps, Earth Bunds and Offline Storage throughout the upstream region of this particular study area. Measures which directly increase storage capacity account for up to 45% of the total peak flow reductions, and are believed to be the most effective of the measures analysed by this research. Other measures such as Riparian Vegetation and Woody Dams, which were represented as increased hydraulic roughness and porous elements across the channel and floodplain respectively, are less efficient in storing direct runoff, yet they enhance the performance of storage measures and are believed to deliver useful environmental benefits. This highlights the importance of the interaction between nature based measures of different types. The methodology described in this document may be found useful by hydraulic modellers, environmental scientists and other professionals undertaking further research on Natural Flood Management.
Keywords Catchment, floodplain, runoff, hydrograph
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Acknowledgements This research would not have been possible without the great opportunity granted by Erasmus Mundus, UNESCO-IHE and HR Wallingford, or without the help and support of David Ramsbottom, who I thank for guiding and helping me all along the way. Special thanks to Dr. Ir. Gerald Corzo for the mentoring, and to my HR Wallingford colleagues Marta Roca, Caroline Hazlewood, Juan Gutierrez, Sajni Malde, Dirk Diederen, Gordon Glasgow, Olalla Gimeno, Mark Davidson and all the others who helped me develop this research in any way without having the obligation to do so. I also want to thank dearly Joanne Old, David McKnight, Tim Taylor and Lewis Purbrick from the Environment Agency, as well as Richard Bennett from Wild Oxfordshire for sharing their time with us, along with valuable information that helped enrich this document. To my family, especially my parents, thanks for all the sacrifice in supporting me with my education. Last, but not least, I want to thank my new FRM-5 family for all the good memories that we have acquired together. In these 2 years I have learned more about the world and harvested more friendships than I could ever imagine. All the incredible people from all around the world that I have met along the way have contributed to my personal growth and knowledge. I hope we meet again sometime in the future…
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Table of Contents
Summary ................................................................................................................................... ii Keywords .................................................................................................................................. ii Acknowledgements .................................................................................................................. iv List of acronyms ...................................................................................................................... xi
Chapter 1 Introduction .......................................................................... 12 1.1
Background and Framework ...................................................................................... 13
1.1.1
Current Flood Management Practice in England .................................................. 14
1.1.2
Catchment Flood Management Measures ............................................................. 15
1.1.3
Natural Flood Management ................................................................................... 16
1.2
Problem statement and motivation............................................................................. 18
1.3
Objectives .................................................................................................................. 19
1.4
Research Questions .................................................................................................... 20
1.5
Innovation and Future Applications........................................................................... 21
Chapter 2 Literature Review ................................................................. 22 2.1
Large Woody Debris ‘Leaky’ Dams .......................................................................... 23
2.2
Offline Storage Ponds ................................................................................................ 29
2.3
Hedgerows, tree belts and buffer strips...................................................................... 33
2.4
Rural Sustainable Drainage Systems (RSuDS).......................................................... 36
2.5
Riparian vegetation .................................................................................................... 41
2.6
Analysis from the Literature Review ......................................................................... 45
2.6.1
NFM in hydraulic modelling ................................................................................. 48
Chapter 3 Methodology .......................................................................... 50 3.1
Case Study: Littlestock-Brook, Oxfordshire UK ....................................................... 50
3.1.1
Flooding history .................................................................................................... 51
3.1.2
Existing flood reduction measures ........................................................................ 53
3.1.3
The Littlestock-Brook NFM Project...................................................................... 55
3.2
Modelling rationale .................................................................................................... 56
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3.2.1
Littlestock-Brook 2D Hydrodynamic Model ........................................................ 56
3.2.2
Monitoring Locations ............................................................................................ 62
3.2.3
Model calibration process...................................................................................... 63
3.2.4
Modelling NFM measures in InfoWorks ICM ...................................................... 66
3.2.5
Locating the measures ........................................................................................... 67
3.2.6
Sensitivity Analysis for the number of Woody Dams ........................................... 70
3.2.7
Modelling scenarios............................................................................................... 72
3.2.8
Model runs and result data collection .................................................................... 73
Chapter 4 Results and Discussion ......................................................... 75 4.1
Modelling Scenarios Results ..................................................................................... 76
Scenario No.1 – Woody Dams and Riparian Vegetation ................................................... 77 Scenario 2 – LWD, Riparian Vegetation, Hedgerows and Earth Bunds ............................ 79 Scenario 3 – Offline Storage Area ...................................................................................... 82 Scenario 4 – Offline Storage Area, Earth Bunds and Sediment Retention Ponds .............. 85 Scenario 5 – All measures on Reach 2 (none elsewhere) ................................................... 88 Scenario 6 – All measures on Reach 1 (none elsewhere) ................................................... 90 Scenario 7 – All NFM measures in place ........................................................................... 92 4.2
Assessing individual NFM measures ......................................................................... 94
Scenario 8 – Woody Dams ................................................................................................. 94 Scenario 9 – Riparian Vegetation ....................................................................................... 95 Scenario 10 – Hedgerows ................................................................................................... 95 Scenario 11 – Field Corner (Earth) Bunds ......................................................................... 96 Scenario 12 – Sediment (retention) Ponds ......................................................................... 96
Chapter 5 Conclusions and Recommendations ................................... 97 5.1
The effectiveness of NBMs in terms of peak flow reduction .................................... 97
5.2
Factors affecting the performance of NBMs in the model......................................... 99
5.3
Modelling NFM measures ....................................................................................... 103
5.4
Quantitative assessment of NFM ............................................................................. 104
5.5
Further research and modelling ............................................................................... 105
5.6
Displaying Results ................................................................................................... 106
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Appendices ............................................................................................... 107 Appendix 1............................................................................................................................ 107 Appendix 2.......................................................................................................................... 108 Appendix 3............................................................................................................................ 109
References ................................................................................................ 110
List of Figures Figure 1. Photograph of Natural log jams in Fisher Creek, Washington USA (Bureau of Reclamation and US Army Corps of Engineers 2015) ................................................................ 23 Figure 2. Photograph of a LWD under ‘normal’ and ‘flood’ conditions (Source: JBA ©Mark Wilkinson) ................................................................................................................................... 24 Figure 3. Impact of beaver dams on peak discharges (Puttock et al. 2017) ................................ 25 Figure 4. Peak water level reduction for two similar rainfall events before and after NFM (Stroud District Council 2017).................................................................................................... 26 Figure 5. Large Woody Dam schematic...................................................................................... 28 Figure 6. Offline storage pond in the Belford Beck catchment (P. Quinn et al. 2013) .............. 29 Figure 7. Synthetic pond network model
(P. Quinn et al. 2013) ............................................. 30
Figure 8. Modified hydrograph. Upper blue line: using a single feature (550 m3); lower green line: 35 different features (19,250 m3) (P. Quinn et al. 2013)................................................. 30 Figure 9. The effect of floodplain bunds between Piles Mill and Paddock Wood on the flood hydrograph and volume stored (National Trust Holnicote 2015) ............................................... 31 Figure 10. Hedgerows in the English countryside (Source: Whatcom Conservation District) ... 33 Figure 11. Flood-breaking hedges obstructing the flow in Southern France (Strosser et al. 2014) ..................................................................................................................................................... 34 Figure 12. Hedgerows schematic ................................................................................................ 35 Figure 13. Runoff-intercepting sediment traps in the River Coquet catchment (Northumberland © Nick Barber, Newcastle University) ....................................................................................... 36 Figure 14. Plot representing the behaviour of the 3-cell sediment trap under a rainfall event (Barber 2013) .............................................................................................................................. 36 Figure 15. Corner field pond in Nafferton [Source: Quinn et al., 2007] ..................................... 37 Figure 16. Left: Partially blocked drains; Right: Meandering ditch with increased roughness (Forbes, Ball, and McLay 2015) ................................................................................................. 38
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Figure 17. A Rural SuDS 'Treatment train' (Duffy et al. 2016) ................................................... 38 Figure 18. Sediment trap schematic ............................................................................................ 40 Figure 19. 'Field corner' earth bunds schematic .......................................................................... 40 Figure 20. Eddleston Water Project (Source: ©Tweed Forum) .................................................. 41 Figure 21. Riparian vegetation schematic ................................................................................... 43 Figure 22. Preliminary Evaluation of the NFM Measures .......................................................... 45 Figure 23. Hypothetical catchment under Integrated Natural Flood Management ..................... 46 Figure 24. Hypothetical rural catchment “Catchment 2” with NFM on one tributary river ....... 47 Figure 25. Flow hydrographs for monitoring points A and B (Left); Flow hydrographs for monitoring point C (Right).......................................................................................................... 48 Figure 26. Woody Dam front view ............................................................................................. 49 Figure 27. Hedgerow front view (Source: www.greennews.ie) .................................................. 49 Figure 28. Littlestock-brook catchment overview ...................................................................... 50 Figure 29. Simulation results for the July 2007 flood event ....................................................... 51 Figure 30. Environment Agency monitoring station at The Heath ............................................. 52 Figure 31. Church Road culvert (Left: 2010, Right: 2017) ......................................................... 53 Figure 32. Channels at The Heath (Left: Dec 2008, Right: May 2017) ...................................... 54 Figure 33. Modelled Flood Storage Area using the 20 July 2007 rain event .............................. 54 Figure 34. Woody dam upstream of The Heath .......................................................................... 55 Figure 35. NFM measures proposed by the Environment Agency and Wild Oxfordshire, The Evenlode Catchment Partnership (Old and Vaughan 2016)....................................................... 55 Figure 36. Littlestock Brook DTM resolution............................................................................. 56 Figure 37. Littlestock-brook 2D mesh zone ................................................................................ 57 Figure 38. Littlestock-brook 2D Surface extent .......................................................................... 58 Figure 39. Design storm events (1 : 50, 7-hour duration ). Left: Winter season, Right: Summer season .......................................................................................................................................... 60 Figure 40. Cross-section X-23 .................................................................................................... 62 Figure 41. Result-gathering locations within the catchment ....................................................... 62 Figure 42. Channels and Culvert near The Heath (Left: raw DTM, Right: Corrected DTM) .... 63 Figure 43. Water levels obtained from the model at Cu1 for the 2007 event ............................. 64 Figure 44. Water level hydrograph with property flood threshold.............................................. 65 Figure 45. Enhanced Offline Storage Area ................................................................................. 67
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Figure 46. A 3-D view into the model with measures in place ................................................... 67 Figure 47. Runoff paths and NFM measures locations within the catchment............................. 68 Figure 48. Runoff paths intercepted by a Field Corner (earth) Bund near The Heath ................ 69 Figure 49. Flow paths and some measures during a 1:100 year event ........................................ 69 Figure 50. Woody Dam Sensitivity Analysis monitored in location Cu1 for events 1:10 and 1:100............................................................................................................................................ 71 Figure 51. Result data collection in InfoWorks ICM .................................................................. 74 Figure 52. All flow hydrographs from the 100-year event at location Cu-1 from Scenarios 1 to 7 ..................................................................................................................................................... 75 Figure 53. Result-gathering locations ......................................................................................... 76 Figure 54. Scenario 1 - Hydrographs collected at Cu1 and R1_DS for a 1:10 year event .......... 77 Figure 55. Scenario 1 - Hydrographs collected at Cu1 and R1_DS for a 1:100 year event ........ 78 Figure 56. Scenario 2 - Hydrographs collected at Cu1 and R1_DS for a 1:10 year event .......... 79 Figure 57. Catchment outlet draining through the floodplain ..................................................... 80 Figure 58. Scenario 2 - Hydrographs collected at R1_US and R1_DS for the 1:100 year event 80 Figure 59. Scenario 2 - Hydrographs collected at R1_US and R2_DS for a 1:100 year event ... 81 Figure 60. Scenario 3 - Hydrographs collected at Cu1 and R2_DS for a 1:10 year event .......... 82 Figure 61. Scenario 3 - Hydrographs collected at Cu1, R2_DS and R1_US for the 1:100 event83 Figure 62. Storage Area at its maximum capacity (2007 event) ................................................. 84 Figure 63. Scenario 4 - Hydrographs collected at Cu1 and R1_DS for the 1:10 year event ....... 85 Figure 64. Earth bunds retaining water during a 1:10 year event ............................................... 86 Figure 65. Scenario 4 - Hydrographs collected at Cu1 and R1_DS for the 1:100 year event ..... 86 Figure 66. Scenario 4 - Hydrographs collected at R1_US and R2_DS for the 1:100 year event 87 Figure 67. Scenario 5 - Hydrographs collected at Cu1, R1_US and R2_DS for a 1:10 year event ..................................................................................................................................................... 88 Figure 68. Scenario 5 - Hydrographs collected at Cu1 for a 1:100 year event ........................... 89 Figure 69. Scenario 6 - Hydrographs collected at Cu1, R1_US and R2_DS for the 1:10 year event ............................................................................................................................................ 90 Figure 70. Scenario 6 - Hydrographs collected at Cu1, and R2_DS for the 1:10 year event ...... 91 Figure 71. Scenario 7 - Hydrograph collected at Cu1 and R1_DS for a 1:100 year event ......... 92 Figure 72. Scenario 7 - Hydrographs collected at Cu1 and R2_DS for the 2007 event .............. 93 Figure 73. Measures from Scenario 7 acting in combination to reduce floods downstream during
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a 1:50 year event ......................................................................................................................... 93 Figure 74. Scenario 8 - Hydrographs collected at Cu 1 for the 1:10 year event ......................... 94 Figure 75. Scenario 9 - Hydrographs collected at Cu1 for the 1:10 year event .......................... 95 Figure 76. Scenario 10 - Hydrographs collected at location Cu1 for the 1:10 year event .......... 95 Figure 77. Scenario 11 - Hydrographs collected at Cu1 for a 1:10 year event ........................... 96 Figure 78. Scenario 12 - Hydrographs collected at Cu1 for a 1:10 year event ........................... 96 Figure 79. Modelled peak flow reductions caused by each NBM .............................................. 97 Figure 80. Modelled peak flow reductions caused by each modelling scenario ......................... 98 Figure 81. Evaluation of the NFM measures from the obtained results .................................... 103
List of Tables Table 1. Table of Organizations involved in Flood Risk Management in the UK (Source: Environment Agency) ................................................................................................................. 14 Table 2. Channel and land use modelling scenarios and associated values for Manning's n ...... 42 Table 3. Table of Hydraulic and Hydrological processes affected by NFM measures ............... 45 Table 4. Typical Manning roughness coefficients for various open channel surfaces ................ 59 Table 5. Design rainfall profiles obtained from ReFH ................................................................ 61 Table 6. NFM Measures as represented in the model ................................................................. 66 Table 7. Table of measures implemented .................................................................................... 70 Table 8. Table of Scenarios with combination of measures........................................................ 72 Table 9. Modelling simulation table ........................................................................................... 73 Table 10. Table of individual measure scenario.......................................................................... 94
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List of acronyms CEH – Centre for Ecology & Hydrology CFMP – Catchment Flood Management Plan Defra – Department of Environment, Food and Rural Affairs EA – Environment Agency FEH – Flood Estimation Handbook ICM – Integrated Catchment Management IWRM – Integrated Water Resources Management LWD – Large Woody Dam NBM – Nature Based Measures NFM – Natural Flood Management NWRM – Natural Water Retention Measures RBMP – River Basin Management Plan ReFH – Revitalised Flood Hydrograph model SEPA – Scottish Environment Protection Agency SuDS – Sustainable Urban Drainage Systems
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Chapter 1
Introduction
The common approach of coping with the water volumes from fluvial floods has been traditionally oriented towards highly engineered structures which retain, slow down or divert river discharges to minimise potentially damaging effects over populations or properties within exposed areas. Often, decision-makers tend to lean more towards these types of measures which are proven to be more effective at reducing damages to infrastructure, property and the population in general due to flooding. Raising flood walls or dykes may be a practical solution for coping with excessive discharges on rivers, but is not always the most sustainable one when future Sea Level Rise and Climate Change projections are taken into account. In response to this, new research has been going on throughout the European Union on so-called Natural Flood Management techniques. This concept involves practices which mimic natural hydrological and morphological processes within a river system and its catchment in order to cope with large volumes of water. It aims to reduce floods by focusing on the source of large volume river discharges. This research suggests a new approach, by gathering scientific evidence and using software tools and expert knowledge, for assessing the impacts of Natural Flood Management measures within a catchment. It also intends to justify the potential effectiveness of nature-based catchment measures on flood risk reduction. The following document is the result of 6 months of work done at HR Wallingford in the United Kingdom, where the tools and methods utilised by this research were developed and applied to a small scale catchment located within the River Thames Catchment in England.
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1.1 Background and Framework The terms ‘river catchment’, ‘watershed’ or ‘river basin’ are used to describe an area of land which naturally drains the surface waters from rainfall, snow or ice melt from higher grounds into a river network and eventually into bigger water bodies such as lakes or the sea. The European Commission Floods Directive states that “Flood risk management plans should focus on prevention, protection and preparedness. With a view to giving rivers more space, they should consider (where possible) the maintenance and/or restoration of floodplains, as well as measures to prevent and reduce damage to human health, the environment, cultural heritage and economic activity.” (European Parliament and European Union Council 2007) The United Kingdom’s Department for Environmental, Food and Rural Affairs (Defra) started producing Catchment Flood Management Plans (CFMPs) since the late 1990s, with the intention of addressing flood risk not only at a local scale, but throughout the entire river catchment as well on a long-term basis (50 to 100 years). These include measures which involve physical changes within the catchment such as storage reservoirs, flood walls, dykes (levees), embankments; as well as measures which do not require any physical changes in the river system (i.e. flood forecasting, early warning systems, emergency plans). The European Commission Water Framework Directive is currently interested in developing River Basin Management Plans (RBMPs) which include a number of measures that are meant to improve the quality of the water in rivers, lakes, watercourses etc. The European Commission Floods Directive, together with the Water Framework Directive, produced a document in 2014 in which a series of Natural Flood Management (NFM) measures were analysed. There is evidence which suggests that NFM may produce environmental benefits, but there is still a high degree uncertainty on the effectiveness that this approach has on reducing flood risk at specific locations within a catchment. There seems to be a common interest among most of the EU member states towards implementing natural catchment flood measures which produce significant environmental improvements along with flood risk reduction. Despite the fact that the necessary framework exists, there is still much work to be done on providing methods for assessing the effectiveness of these measures. Some research has been carried out previously, but there are many knowledge gaps which need to be filled before fully relying on them and including them in the decision-making process.
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1.1.1 Current Flood Management Practice in England In 2010, the Flood and Water Management Act was signed by Her Majesty, Queen Elizabeth II, to establish mechanisms which would enable government authorities to address different water related issues in England and Wales. The British government has made the maintenance of England’s flood defence capacity a national priority (Defra 2011). The Environment Agency was then granted responsibilities which cover strategies for flood risk management at a national level. The following table (Table 1) gives an overview of the different public agencies which play key roles in the society and the process of flood risk management.
Table 1. Table of Organizations involved in Flood Risk Management in the UK (Source: Environment Agency)
Local
Regional
National
Scale
Organization
Roles and Obligations
Department for Environment, Food & Rural Affairs (Defra)
● ●
Creating the National policy for flood and coastal protection Provide funding for flood risk management authorities
Environment Agency
● ●
Has a strategic overview of all sources of flooding Operational responsibility to manage flooding from main rivers and the sea
Department for Communities and Local Governments
● ● ●
Sets out national planning framework for development and flood risk Ensures flood risk is appropriately factored into planning processes Coordinates local authorities' recovery
Cabinet Office
● Develops cross-sector resilience programmes for civil contingencies, which includes floods
Regional flood and coastal committees
● Ensure that plans are created to identify, communicate and manage flood risks across catchment and shoreline areas ● Promote efficient and targeted investment ● Provide linkages between flood risk management authorities and other bodies
Lead Local flood authorities
● ● ●
Local resilience forums
● Multi-agency partnerships that plan and prepare for localised incidents, including those related to flooding
District and borough councils
Internal drainage boards
Preparing local flood risk management strategies Creating and maintaining registers of flood risk assets Manage flood risk from surface, ground and other water systems
●
Ensure new developments are safe, flood resilient, do not increase flood risk overall and reduce flood risk where possible ● ●
Independent public bodies covering around 10% of the country Responsible for water-level management in low-lying areas and regulation of activities on ordinary watercourses within drainage districts
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In 2011, the Environment Agency along with Defra, published the National Flood and Coastal Erosion Risk Management Strategy for England in 2011 (Defra & Environment Agency 2017), which lists a number of guidelines for dealing with risk of flooding and coastal erosion including. Some of the items considered in this strategy are: •
Possible future scenarios of flood risk and coastal erosion;
•
Roles and functions of organizations involved;
•
Measures for coping with the issues at hand;
•
Costs and funding of these measures;
•
Mechanisms for the prevention of future development within areas at risk;
•
Increasing resilience through raising awareness, improving flood prediction, warning and post-flood recovery;
•
Achieving environmental, social and economic benefits, within the boundaries of sustainable development.
Evidence shows that long-term strategic planning on a catchment scale has a weak influence on local flood risk planning. Catchment plans consider all sources of flooding, but there’s less data available on surface and ground water due to the lack of detailed modelling done for these sources of flooding. Considering that more work has to be done to increase local awareness and engagement with the catchment approach, the Environment Agency annually publishes summary reports and progress updates of all CFMPs. (National Audit Office 2011) Recently, several NFM initiatives are being implemented throughout the UK, focusing primarily on floodplain and river restoration, land management and Natural Water Retention Measures (NWRM), among other which are addressed in detail on Chapter 2.
1.1.2 Catchment Flood Management Measures The approach established by the CFMPs in the UK involves measures which contribute to flood risk management of the downstream region in a catchment by implementing different ways of controlling the water flows within a river system. Three main categories of flood protection measures that involve physical changes have previously been identified by HR Wallingford (2016): •
Direct protection – cope directly with flood waters in order to protect areas at risk (i.e. flood walls, flood banks and demountable flood barriers). Property resistance (preventing the entry of flood water) and property resilience (preventing damage) are also ways of reducing damage from floods at a local scale.
•
Measures that increase flow conveyance of the river and floodplain – moving flood defences away from the river channel (i.e. Room for the River Programme, NL), removal of obstructions to lower river levels, enlargement of river channels (two-stage channels).
•
Measures that reduce flood flows – upstream flood storage (i.e. dams, reservoirs, and polders), changes in land use and/or agricultural practices, Natural Water Retention Measures (small wooden dams, tree belts, etc.)
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Measures which do not involve physical changes – flood forecasting, flood warning, emergency planning and response – do not have any effect in the hydraulics of the river. These types of measures go beyond the scope of the research and therefor, are not included in this document. (HR Wallingford 2016)
1.1.3 Natural Flood Management This research focuses on “Nature Based” measures (referred to as NBM in this document). Using natural processes, they can reduce and/or delay flood peaks (maximum water levels reached in a particular flood event) and flood volumes in order to reduce the scale of fluvial floods and to increase the lead time within which emergency measures can be implemented. A significant amount of research has been done on Natural Flood Management (NFM) in the UK, especially by the Scottish Environment Protection Agency (SEPA). In 2015 this government agency published practical Natural Flood Management Handbook on which they define methods and strategies for delivering benefits in flood risk management based on measures which are inspired by natural processes. Natural flood management is here defined as an approach which “involves techniques that aim to work with natural hydrological and morphological processes, features and characteristics to manage the sources and pathways of waters. These techniques include the restoration, enhancement and alteration of natural features and characteristics, but exclude traditional flood defence engineering that works against or disrupts these natural processes.” (Forbes, Ball, and McLay 2015) The European Commission is increasingly investing on research and implementation of Natural Water Retention Measures (NWRM), because they recognise the multiple potential benefits these have on the environment and water resources. NWRM are defined as “multi-functional measures that aim to protect water resources and address water-related challenges by restoring or maintaining ecosystems as well as natural features and characteristics of water bodies using natural means and processes.” These measures aim to use and enhance the natural storage capacity of soils, aquifers, wetlands and other types of water dependent ecosystems in order to improve biodiversity, water quality, and reduce the vulnerability to floods and droughts. (Strosser et al. 2014) Some ways of retaining water through natural means which have been already implemented throughout the globe include: •
Wetland restoration
•
Green Infrastructure
•
Sustainable Urban Drainage Systems (SuDS)
•
Rainwater harvesting
•
Soil conservation practices
Pilot projects involving simple NWRM have been implemented across the EU. Experience from projects in France and Germany showed that buffer strips (strips of natural vegetation) and hedges are an effective way to improve natural water infiltration and slowing down the runoff caused by heavy rainfall. Buffer strips were proven to reduce runoff by 50 to 80% and sediment yield by 55 to 97%, depending on the size and other characteristics of the area. (Strosser et al. 2014) Other 16
measures which involve changes in agricultural practices also have significant impacts on the groundwater recharge, runoff and sediment yield in areas destined predominantly for agriculture and cattle ranching. Another study conducted in Finland showed that a specific wetland could manage to reduce up to 38% of the peak flows and 47% of the stream discharges. Wetlands contribute to the surface water quality and may account for 40% of the Earth’s terrestrial carbon reserves, which shows some of their multipurpose attributes. (Strosser et al. 2014) Though experience has revealed the multiple benefits NWRM have on water ecosystems, and their potential benefits on reducing runoff by improving natural infiltration and storage processes, there’s still much uncertainty on whether these measures provide the same quality and quantity of benefits when applied to different types of catchments and measuring the effects at different locations. Recently the British Government has destined £15 million to the implementation of several ‘slowthe-flow’ schemes included in Defra’s National Flood Resilience Review. This with the intention of incentivising a ‘whole catchment’ approach which is believed to deliver multiple benefits in terms of the environment, the economy and society in general. (“Natural Flood Protection Scheme to ‘Slow the Flow’ in the North West | Infrastructure Intelligence” 2017)
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1.2 Problem statement and motivation The south of England faced the wettest period in 250 years, during the autumn and winter of 2013 and 2014. Moreover, the total value of flood defence assets estimated by the Environment Agency is £24 billion, coupled with £606 million for funding for flood risk management in 2013-2014. (National Audit Office 2014) According to the UK’s MET Office, the period between December and January, which left more than 370 mm of rain in the central-south part of the country, has been the wettest one since 1910. This extreme event was found to be triggered by pattern perturbations to the jet stream over the Pacific Ocean and North America, which ended up affecting Canada and the USA, as well. These perturbations were caused by an irregular pattern of rainfall over Indonesia and the tropical West Pacific, which at the same time was associated with higher temperatures in the region. (Slingo et al. 2014) The increasing frequency and intensity of this type of events, due to the effects of Climate Change, is likely to produce more flood events which may cause damage and losses even where flood defences are already in place. Such is the case of the floods in the north western county of Cumbria (2015) in England, where high rainfall of over 340 mm (Storm Desmond), coupled with saturated soils ended up in floods which caused two fatalities and major damages to the road and railroad network, including the Pooley Bridge at Ullswater, built in 1764. (Slingo et al. 2014) At Keswick, relatively new flood defences with a cost of £6 million which were designed using a 100 year return period, were overtopped when the River Greta rose to more than 5.20 m, just over 60 cm above the levels reached during the 2009 highs. (The Telegraph 2017) The flood defence overtopping in Cumbria can only add to the current premise which states that continuing to raise flood defences may not be the most efficient solution when dealing with raging weather events like Storm Desmond in 2015. This suggests that structural measures must be coupled with a series of upstream catchment measures which help to improve the storage capacity, reducing or delaying the flood peaks. Modelling done for the Thames Catchment Flood Management Programme showed that significant changes in flood retention in the upper part of the Thames catchment reduce the flood volume, yet this has little impact on peak flows in the lower part of the catchment because of the effect of inflows from the downstream tributaries. (HR Wallingford 2004) Despite the existing evidence, there’s still a huge amount of uncertainty on whether combining different NBM in different locations can help attenuate the flood peaks and flood volumes when storms events occur in a particular catchment. As HR Wallingford has suggested before, the positive benefits have been proven to be mostly environmental and focused on a local scale, yet these benefits are reduced considerably in the downstream areas. This is one of the main drivers for conducting research on how to determine the effectiveness of NFM on dealing with floods within a catchment, and to identify the ideal locations where these measures should be placed in order to minimize the flood hazard downstream.
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1.3 Objectives The main goal of this research is to provide evidence about the impacts which certain Natural Flood Management measures implemented throughout a catchment may have on peak flows and water levels at specific locations, as well as providing guidelines for the proper assessment of these effects. This objective was fulfilled by completing the following tasks: 1. Identifying the most effective NBM in terms of flood reduction at local scale (which in the UK is typically below 10 km2), and other potential impacts they may have within the IWRM approach. Specifically, this was done by compiling evidence from research conducted and documented previously by different authors and performing a multi-criteria evaluation of a number of measures which were observed to be the most feasible ones to analyse. 2. Analysing the physical, hydraulic and hydrological processes within the catchment that may be affected by these measures, as well as defining the strategy for including them in a hydrodynamic model in order to observe patterns of change they might trigger. 3. Selecting a study catchment which would suit the research in terms of its extension, morphology, data availability, flood hazard, location, and other factors that may facilitate the process of acquiring tangible results. 4. Using a full 2D hydrodynamic model to quantify the effects of the selected NBM on the monitored flows and water levels at specific locations within the catchment. By observing changes on the hydrographs (before and after NFM) flood reduction benefits can be quantified for the local scale and potential benefits can be derived for the catchment further downstream. 5. Applying an effective visualization technique for presenting the results obtained from the model runs (e.g. inundation maps, plotted hydrographs).
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1.4 Research Questions After going over a significant amount of literature written on NFM and its impact on the environment and floods, many knowledge gaps and a significant amount of uncertainty were identified. Some of the questions which came up when reviewing the literature include the following:
1. Which are the most effective NBM, in terms of flood hazard reduction at local catchment scale (1 to 10 km2)? 2. Which elements and processes contribute to the effectiveness and performance of these measures applied under different circumstances? 3. How should different NBM be included in hydrodynamic models in order to get accurate results on the effects they may have? 4. Once they have been implemented, what impacts do they have on flooding at different catchment locations? 5. Which rules or parameters can be applied to the obtained results in order to assess NFM in a quantitative way? 6. What would be the most effective way of presenting the results in order for decision-makers and society in general to understand the impacts of these measures on reducing floods?
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1.5 Innovation and Future Applications This piece of research may present a step forward in providing a framework for the implementation of flood reduction measures and techniques moving towards the common goal of sustainable development. It collects valuable information which proves the effects of NBM when dealing with floods in the midst of climate uncertainty. A defined methodology for assessing the impacts of these measures in a catchment are provided in this document, which is expected to help flood managers consider these alternative and more sustainable ways of dealing with flood issues. Moreover, this research poses a new approach towards the way in which specific measures within the realm of NFM are included in hydraulic models in order to observe their effects on floods. Supporting professionals and decision-makers involved in Flood Risk Management at many different levels is the overall aspiration of this research. Flood modellers might show particular interest on the results obtained from different ways of including NBM in hydrological and hydraulic models. Professionals working with flood risk assessments may be provided with sufficient evidence of the effectiveness of these measures on reducing flood risk at specific locations. It also provides framework for future research within the scientific community. The results obtained from this research may have several practical applications in the future. It may be used in the process of raising awareness among decision-makers and the population in general on the positive effects of NBM on society, infrastructure the environment. Developing training workshops targeted to decision-makers, and populations living and/or working within a catchment on the benefits of ‘working with nature’, could also be done with the evidence presented here. This report is expected to provide the necessary evidence for triggering or boosting the funding of research and development projects on NFM and the use of these types of measures as means of reducing floods in the UK and other parts of the world.
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Chapter 2
Literature Review
Natural Flood Management is a relatively new approach which is being adopted by many countries like the UK, USA, Italy and France (among others). It combines different nature-based interventions to try and replicate natural processes that contribute to water retention and runoff attenuation which has been proven to reduce and/or delay peak flows at river reach scale downstream. These measures are typically placed throughout the upstream rivers, intermittent streams and runoff paths that form when heavy rainfall hits a particular catchment. Most of the benefits delivered by nature based catchment interventions are related to water quality improvement, erosion control, the environment and the overall quality of life in the community. However, some scientific evidence has been found suggesting that these measures also contribute in a way to flood alleviation downstream, yet their effectiveness depends on many different variables. Because these measures involve natural processes rather than technically defined or ‘engineered’ ones, there is still a significant amount of uncertainty regarding their implementation. The effects of these measures are sometimes very hard to quantify and in many cases they are assessed in a qualitative way due to the lack of data and monitoring. Most of the research projects and case studies analysed in this section are very recent and some of them involve long-term effects which have not yet been observed. During an initial scoping study, several NFM measures and approaches were identified. However, this flood management approach includes methods such as ‘floodplain restoration’ or ‘better agricultural practices’, which typically involve other complex social and natural processes that go beyond the scope of this research. For instance, crop rotation, which according to the European Commission (2014) is the practice of growing different types of crops in the same area in sequential seasons, is believed to improve soil structure, reduce erosion and increase the infiltration capacity. The benefits achieved by implementing this practice throughout an entire agricultural area can be multiple, yet this is not believed to cause significant changes on fluvial floods by itself. Therefore, 5 types of measures were selected by evaluating (in a qualitative way) each of the initially identified measures with respect to their potential impacts and applying values and relative weights to the multiple evaluation criteria (see Appendix 1). Some evidence regarding these multiple benefits has been found from research undertaken previously by several authors. The following section is a compilation of the findings collected through a literature review and analysis of scientific papers, project reports and other documents from many different sources. The aim of this section is to provide a clear overview of each type of intervention in order to be able to assess their effects.
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2.1 Large Woody Debris ‘Leaky’ Dams Large Woody Debris Dams (LWD) is the term which is used to describe pieces of dead wood thicker than 1cm in diameter and longer than 1m that accumulate and interlace to form a natural barrier (Linstead and Gurnell 1999). These barriers can form naturally as a result of falling trees and branches on the river or put in place by beaver communities. Their local and immediate impact is obstructing the channel flow leading to slower flow velocities and increased water levels in the upstream vicinity. Recent studies have shown that debris dams can contribute to changes in flood hydrographs by storing water (in-stream) temporarily. These changes are believed to reduce and/or delay flood peaks which may in time reduce flood frequency and magnitudes downstream. When coupled with other measures, such as riparian vegetation or off-line storage ponds, LWD (under the right circumstances) can deliver significant positive benefits.
Figure 1. Photograph of Natural log jams in Fisher Creek, Washington USA (Bureau of Reclamation and US Army Corps of Engineers 2015)
LWD dams have several effects on a river system, some of these are listed below: •
Improve river-floodplain hydrological interaction
•
Provide temporary (in-channel) storage
•
Retain sediment, organic matter and other pollutants flowing from the upstream region
•
Provide habitat for aquatic ecosystems within the river
Large woody debris creates a physical obstruction that can reduce the area in a channel’s crosssection, forcing the water to flow onto the riverbanks and floodplain. Riparian woodland plays an important role in the natural formation of woody dams, as they provide the raw materials for them. As the natural process of trees falling inside the channel occurs, they retain fallen tree branches and other pieces of debris flowing in the river. The effect of woody debris in river can increase the hydraulic roughness and influence in certain way the flow behaviour (Hygelund and Manga 2003).
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In a ‘engineered’ LWD dam, the pieces of wood are fixed to the ground and interlaced in such a way that they restrict the water flow and slow it down, causing the water level to increase in the area immediately upstream of the dam. This obstruction causes temporary ponds which provide storage capacity, slow the water flow and let the sediment floating in the water accumulate at the bottom.
Figure 2. Photograph of a LWD under ‘normal’ and ‘flood’ conditions (Source: JBA ©Mark Wilkinson)
The energy loss accounted to the presence of in-channel pieces of wood which the increase in hydraulic roughness can be analysed using Manning’s equation. This additional roughness can lead to reduced river discharges downstream, following the same principles of Manning’s equation for open channel flow. (Bureau of Reclamation and US Army Corps of Engineers 2015)
Evidence •
Research undertaken by Puttock et al. (2017) at the Devon Beaver Project in South West England, specifically on a small first order stream located at the headwaters of the River Tamar, focused on the effects of beaver dams. The outcome of this study showed significant changes to the storage, flow regimes and water quality downstream as a result of introducing Eurasian beavers in the site which build 13 dams extending up to 30m long, over an approximate area of 1,500 m2. Conclusions from this study state that the hydrological effects of beaver activity are likely to be site specific, and depend on several factors like channel characteristics and biodiversity. The results on peak discharge attenuation can be observed on the graph below (Puttock et al. 2017)
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Figure 3. Impact of beaver dams on peak discharges (Puttock et al. 2017)
•
Gregory et al. (1985) observed a difference in travel time of over 100 minutes along a 4 km reach with and without dams for a discharge of 0.1 m3/s, decreasing to 10 minutes at a higher discharge of 1.0 m3/s. (Gregory, Gurnell, and Hill 1985).
•
A more recent study reported that for a 1-in-100 year discharge (~5.5 m3/s) on river Fenni in Wales, a system of 5 LWD located in a 0.5 km reach, could delay the average time to peak within the main river (~10 hours) by up to 15 minutes due to increased roughness. These woody debris dams were also accounted for elevating the water levels immediately upstream, which caused the water to spill onto the floodplain. The catchment covers a total of 9.2 km2 upstream of the study site. The same study modelled leaky barriers as partial (70%) blockages within the channel, rather than increased roughness, showed a 2-3 minute increase in flood peak arrival over a single reach. (Thomas and Nisbet 2012).
•
Odoni & Lane 2010 predicted that by combining woody debris dams with riparian woodlands planted along the watercourse could reduce the flows by 8-10% at Pickering. Desynchronization in the Laver catchment was also said to be delayed by 55 minutes, leading to a 1-2% reduction in the design peak flows predicted in River Ripon downstream of the confluence of two rivers. (Blanc, Wright, and Arthur 2012)
•
In the Ourthe Orientale sub-basin in Belgium, there was a 2.2 year increase in the flood frequency of a 60 m3/s event, after beaver dams were put in place (Nyssen, Pontzeele, and Billi 2011). These structures also accounted for more than 17,000 m3 of sediment deposited behind them in a 7 year period along the River Chevral (de Visscher et al. 2014).
•
An empirical study done in a 280 m long first order channel by the Ore Mountains in Germany, where a LWD dam was installed, showed a significant flood wave delay and a 2.2% decrease in the peak discharge for a 3.5 year return period event due to increased roughness (Wenzel et al. 2014)
•
The Stroud Rural Sustainable Drainage project has implemented a number of NFM interventions, including 170 LWD along 18km of river reach. In 2016 a 35-40mm over 12 hours rainfall event was monitored and plotted against a similar event in 2012, before the RSuDS interventions, to observe the impact of these measures. The graph below shows the 25
same time to peak with a substantial reduction in maximum water depths, yet the groundwater levels were higher during the 2012 event. This suggests that more work needs to be done in monitoring before making any final conclusions on the effects of these measures. The measurements were done approximately 1 km downstream of the last instream structure placed at this particular river reach. An estimated 80% of this sub-catchment drains through NFM structures.
Figure 4. Peak water level reduction for two similar rainfall events before and after NFM (Stroud District Council 2017)
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Key Case Studies •
13 beaver dams increased water storage on the site by ~1,000 m3
•
Peak discharges (0.04 ± 0.03 m3/s ) reduced by 30% ± 19% to 0.03 ± 0.02 m3/s
•
Times between peak rainfall and peak discharge (127 ± 51 min) increased by 29% ± 21% (198 ± 100 min)
•
Overall mass balance showed 22% more water entered the dams (~235,000 m3) than it left the site below beaver dams (~183,000 m3) over a monitored period of 2 years.
Devon
Scale: 5 ha of wetland, 20 ha grassland upstream
(Brazier et al. 2014; Puttock et al. 2017)
New Forest
•
Experiments done on 25 reaches of a 4.5 km highland river section during periods of low flows, where natural LWD had formed.
•
Manning’s channel roughness coefficients calculated for ‘complete’ (dams stretching along the entire cross section of the channel); ‘partial’, (dams only extend across a part of the channel); and ‘control’ (no dams present) reaches were 0.963, 0.634 and 0.286 respectively. This coefficient was seen to decrease gradually as discharges increased.
•
21% reduction of flood peak magnitude (0.05 ~ 0.35 m3s-1)
•
33% increase in flood peak travel time for flows that were less than 1 m3s-1
•
55% decrease in average flow velocities (0.038 ~ 0.084 m/s) (Linstead and Gurnell 1999)
•
Reduced flood risk in Pickering from a 25% in any year chance to less than 4%.
•
Reduced flood peak by 15-20% during the Boxing Day event in 2015, by a combination of upstream measures including 167 LWD (~7,000-8,000 m3 additional storage) among others (riparian woodland, check dams, and a large flood storage bund)
Pickering
Catchment area: 69 km2
(Nisbet et al. 2015)
Stroud
•
170 LWD installed in an 18 km reach of River Frome, which cope with 20% of the river’s discharges.
•
No registered floods after the major flood event in 2007 (before NFM) Catchment area: 235 km2
(Stroud District Council 2017)
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Remarks Most studies on LWD dams have been done at local and relatively small scale rather than at entire catchment level. Evidence suggests that placing a number of woody dams along a river reach might lead to a delay and/or attenuation of the flood peak in the same river reach downstream. The research done by Linstead and Gurnell (1999) poses significant evidence of the hydraulic changes caused by LWD on river discharges. Particularly, they successfully determined the values of roughness (Manning’s n) for three control dams placed across three different river reaches. However, Manning’s roughness coefficient may not be the most precise way of representing the physical changes such as channel section geometry or the ‘weir effect’ caused by LWD on hydraulic channels. Therefore, a new approach for assessing these effects is needed. Some other considerations have to be made before placing these structures in place. For example, the free movement of fish and other aquatic species could be disrupted if they are placed incorrectly. To prevent the dams from being washed away, they must be properly fixed to the ground and regular maintenance and monitoring should be done, especially after high flow periods. Figure 5 below shows a schematic analysis of how LWD perform under low-to-medium flows.
Figure 5. Large Woody Dam schematic
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2.2 Offline Storage Ponds Offline Storage Ponds are portions of land within the floodplain which are designated to collect and retain flood water. Usually the water is diverted into them when the river goes beyond certain stage and it is retained by containment bunds of earth dykes (typically no taller than 1m) which prevent the water from spilling out, creating a reservoir effect. The water is kept for as long as necessary and then naturally drained or gradually released through an outlet mechanism such as spillways, weirs or pipes. Offline storage ponds may also be referred to in some literature as ‘polders’, ‘flood storage areas’, and ‘wash lands’, depending on their location and functionality. These features are successful in delivering the following benefits: •
Flood magnitude reduction by reducing the peak discharges
•
Flood wave attenuation by delaying hydrographs
•
Sediment transport reduction by collection and deposition of the sediment in the storage area
Their main objective is to collect water from a watercourse during high flow season and release it gradually after the flood peak. They can be classified as ‘online’ if they are connected to the river or stream directly, and ‘offline’ if the water is diverted into them either naturally (when water levels exceed certain threshold) or through an engineered mechanism (Morris et al. 2004).
Figure 6. Offline storage pond in the Belford Beck catchment (P. Quinn et al. 2013)
Typically, after a hydrological and hydraulic study of a river system followed by a flood risk assessment of a specific area, a desired volume of reduced river discharge is acquired. These features may deliver the storage capable of reducing the desired volume of water when implemented in a series of locations along the watercourse.
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Evidence •
Quinn et al., (2013) modelled a hypothetical storage pond network (Figure 7) for the Belford Burn catchment in England (5.7 km2), with a total storage capacity of 19,250 m3, which delivered approximately 30% flood peak reduction for the observed events (3.0~3.5 m3/s) and 15% for Flood Estimation Handbook design storm events (1:100 years; ~2.8 m3/s).
Figure 7. Synthetic pond network model
(P. Quinn et al. 2013)
The model results show significant attenuation of the flood peak and suggest that as the amount of storage ponds increases, more benefits in discharge reduction downstream are to be expected. As figure 8 shows below, this modelling study by Quinn et al. (2013) in Belford was successful in delivering additional storage during storm events with potential flood risk consequences. The cost of this project was estimated in £ 3.2 million (£ 27 / m3 of stored water).
Figure 8. Modified hydrograph. Upper blue line: using a single feature (550 m3); lower green line: 35 different features (19,250 m3) (P. Quinn et al. 2013)
•
A project done on Holnicote in West Somerset intended to generate tangible data which supports that working with natural processes can contribute to reducing local flood risk while producing a range of different benefits for the environment and the community 30
(National Trust Holnicote 2015). This project involved the construction of 5 low level bunds within the floodplain A 1D-2D model was used to assess the effect of 5 offline storage ponds located in the river’s floodplain. Results show a 10% decrease in peak discharge during the modelled storm event (1:100) and suggests up to a 25% reduction for floods with smaller return periods (1:5 year). The results of the modelling study done by the National Trust on the Defra Multi-Objective Project can be seen in Figure 9 below.
Figure 9. The effect of floodplain bunds between Piles Mill and Paddock Wood on the flood hydrograph and volume stored (National Trust Holnicote 2015)
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Key Case Studies •
An estimated 15-30% reduction of flood peaks was shown as a result of modelling a hypothetical pond network with storage capacity of almost 20,000 m3 and with a 1:100 year event.
•
Belford was flooded 7 times between 1997 and 2007 causing serious damage. Since the construction of 35 different RAFs (providing additional 8,000 m3 storage) only one property has been affected by flooding.
Belford
Catchment area: 5.7 km2 (P. Quinn et al. 2013)
Holnicote
•
10% decrease in flood peaks caused by the 24/12/2013 event with return period of 75-100 years. See figure 5 above.
•
Reduced flood risk for almost 100 properties Catchment area: 40 km2 (National Trust Holnicote 2015)
Remarks The concept of storage ponds is quite simple: they aim to provide the necessary storage volume upstream for the reduction of floods downstream. These features may be a useful way for flood managers to control flood wave magnitudes and their time to peak flow, in other words, to modify the shape of the flood hydrographs. In practice, however, there are many other aspects that affect the performance of these measures (e.g. event intensity, frequency, duration, soil conditions). For example, some storage ponds may fill up completely before the flood wave arrives, and therefor will not have storage capacity for attenuating the flood. This can be avoided by ensuring the correct volume as well as proper inlet and outlet mechanisms (which may go beyond the scope of NFM). Another aspect to consider when implementing these measures is that their storage capacity depends on the initial volume they have when the flood wave arrives. Quinn et al. (2013) suggest that these features should be able to drain between 4 to 24 hours after they fill up in case multiple storm events hit the catchment upstream. This time will depend on the hydrological and morphological characteristics of the site. Storage ponds are also effective ways to trap the sediment and debris floating in the water, but may in time accumulate at the bottom, reducing therefor the storage capacity. This suggests that maintenance and monitoring should be carried out regularly.
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2.3 Hedgerows, tree belts and buffer strips Hedgerows, tree belts and buffer strips are long stretches of natural vegetation, such as native trees and bushes that are typically planted at the edges of fields and grasslands or along watercourses. They form a natural barrier that is effective in slowing down and partially storing runoff due to their water infiltration and evapotranspiration capacities. Suspended sediments and other particles suspended in the water may also be retained by these natural features, improving the water quality downstream. Figure 10. Hedgerows in the English countryside
These features are typically present at the boundaries (Source: Whatcom Conservation District) of farm and grasslands or near watercourses with main purpose of: •
Reducing overland flow speeds and delaying runoff peak flows
•
Provide a natural infiltration area where a certain amount of water is stored and eventually released as evapotranspiration
•
Trapping sediments and other pollutants suspended in the water before it reaches main watercourses.
A hedgerow has been defined in The Countryside Survey (1990) as “a more or less continuous line of woody vegetation that has been subject to a regime of cutting in order to maintain a linear shape” (Barr et al. 1990). Carter (1985), Dabney et al. (1995) and Gilley et al. (2000) suggest that a well maintained hedgerow can constitute a ‘porous barrier’ which obstructs overland flow paths causing the flow velocity to decrease and upslope ponding which can delay the time to peak in runoff. (Defra 2006) The European Commission (2014) claims in their “Natural Water Retention Measures” guide, that buffer strips may reduce runoff by 50-78% and sediment transport by 55-97%. This document also suggests that flood risk may be reduced in the presence of these features due to the increased attenuation of surface water energy. However, results may vary depending on the size and location of the buffer strips. Generally, increasing the width of the buffer strip may increase the roughness area and at the same time lead to a greater ‘trapping’ effect (Borin et al. 2005). These features have been historically present in the British landscape, yet only recently have researchers started to assess their benefits in a quantitative way. Between 2009 and 2014, about 6 km of hedgerows were planted across the River Leze floodplain (perpendicular to the flow direction) in the mid-Pyrenees region in southern France with the intention of reducing flood intensities at exposed areas within the catchment (Figure 11). The project intended to reach a total of 35 km of hedgerows in the river by 2016 in order to reduce a predicted 25% of the peak flows downstream.
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Figure 11. Flood-breaking hedges obstructing the flow in Southern France (Strosser et al. 2014)
Evidence •
The performance of planted buffer strips in Veneto, North Italy was assessed by Borin et al. (2005), and the results showed a significant 78% reduction of the total runoff compared to ‘no buffer strip’ soil conditions, where the cumulative runoff depth was 231 mm over a 4 year period. This experiment was done on a rectangular 35 m long farm field with 1.8% slope, and a 6 m wide double-row buffer strip consisting of trees and shrubs mixed with grass in between them.
•
Results from experiments done at Mogliano, Italy show that the total measured runoff decreased from 97 mm (without buffer strip) to 61 mm (with buffer strip) between the years of 2003 and 2005. Besides this, significant sediment and pollutant transport reductions were obtained (NO3-N and dissolved phosphorus reduced by almost 100%, 60-90% reduction of herbicides). (Borin et al. 2005)
•
The dimensions for buffer zones vary across EU member states, with width ranging from 0.6m to 20m. Their effectiveness will depend on their design and context. For example, on slopes of less than 7º consisting of medium grain size chalk and limestone soils or 11º for sandy and light silty soils, a 6m buffer strip may be sufficient to slow overland flow. On higher slopes, a 12m buffer strip may be required. (Strosser et al. 2014)
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Key Case Studies
River Leze, France
•
Hedgerows placed perpendicular to the flow direction (spaced every 300-500 m) in a runoff path were predicted to reduce peak flows by up to 25% (Strosser et al. 2014)
Veneto, Italy
•
78% reduction of total cumulative runoff over a 4 year period, compared to no buffer strip conditions were cumulative runoff depth was 231mm.
•
Reported a reduction of total suspended solid losses from 6.9 to 0.4 t ha-1. (Borin et al. 2005)
Remarks Hedgerows seem to be an effective way of reducing the overland flow on rural areas. They constitute a natural barrier which slows down the runoff, trap the suspended sediment and increase infiltration rates. Most of the existing literature focuses on water quality, reduction of total suspended solids and other pollutants such as herbicides and organic matter. Their effectiveness will depend on the width of the buffer strip, type and density of the vegetation, field slope, direction and magnitude of the runoff, among other site-specific characteristics. Though some case studies have shown that these features can be useful in reducing flow velocities and water levels downstream, the impact they may have seems to be greater at a local scale, rather than throughout large distances. The schematic shown below (Figure 12) explains in principle, how hedgerows are believed to modify the runoff during a storm event. By creating a physical obstruction, part of the runoff may be retained or delayed in its path to the watercourse. The effectiveness will depend on many variables such as: the stage and density of the plant species, the geometry of their base structure, terrain slope and land cover upstream, etc.
Figure 12. Hedgerows schematic
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2.4 Rural Sustainable Drainage Systems (RSuDS) Rural SuDS are individual or ensembles of interacting features which replicate natural processes in their environment with the main purpose of attenuating overland flow of water from farm fields and grasslands located within rural catchments. In simple terms, these features intercept, divert, store and improve the quality of surface runoff before it reaches a main watercourse. (Avery 2012) In this section, the following RSuDS will be covered: •
Sediment traps
•
Dry / wet retention ponds
•
Ditches
Some of these landscape features are also referred to as ‘Runoff Attenuation Features’, because their main goal is to capture and ‘treat’ in a natural way as much runoff as possible in order to reduce the amount of sediment, chemical substances and other pollutants suspended in the water. This is done by a series of interventions spread across a rural area. Overland flow might be directed by bunds or ditches into retention ponds were the water accumulates and is slowly drained into the soil or discharged by an outlet pipe located in the lower end of the storage area.
Figure 13. Runoff-intercepting sediment traps in the River Coquet catchment (Northumberland © Nick Barber, Newcastle University)
Figure 14. Plot representing the behaviour of the 3-cell sediment trap under a rainfall event (Barber 2013)
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Sediment traps, as their name suggests, are Figure 15. Corner field pond in Nafferton [Source: excavated areas were runoff enters and is Quinn et al., 2007] retained for some time, allowing the sediment to settle at the bottom before the water is discharged (Forbes, Ball, and McLay 2015). The previous graph taken from Barber (2013), explains how a multi-cell sediment trap captures runoff during a storm event and then release it gradually through a spillway. This process has a “smoothening” effect on the hydrograph. The total suspended sediment load was reduced by up to 88% for this specific event. The accumulation of the sediment at the bottom of these features may be useful for the retention of soil and nutrients that can be then reused with the same agricultural purposes. The accumulated sediment should be removed regularly in order to ensure a higher storage capacity. Dry ponds may also be placed at the corner of farm fields, where the ground is lowered with the intention of accumulating the overland flow coming in from the rest of the fields after irrigation or a heavy rainfall event. The water is then slowly percolated into the soil, leaving the sediments and pollutants accumulated at the bottom of the pond. Containment earth bunds may also be raised around these ponds to increase the storage capacity. These features, have a higher impact on downstream water quality, but may also contribute to the attenuation of flood peaks at a subcatchment scale by trapping part of the runoff before it reaches the main watercourse. Their main benefit is that these ponds only form whenever rainfall exceeds certain threshold and the soil is saturated, which gives landowners the liberty of using these portions of land during dry periods. Wet ponds, on the other hand, are areas designated specifically for water retention and treatment, and are totally or partially flooded most of the time. Identifying the way in which runoff behaves during a specific rainfall event can be done collecting information from the terrain using LiDAR or aerial photography and generating a Digital Elevation Model (DEM) using GIS tools. The program should be able to roughly identify the low-level areas were the flow accumulates, although a hydrological rainfall-runoff model would provide more accurate information about the overland flow for specific rainfall conditions along with other parameters like soil moisture and infiltration rates. Ditches may be also implemented in rural areas with the purpose of collecting runoff and directing it into larger water bodies with delayed times of arrival. This is done by increasing the surface roughness with riparian vegetation on their banks or by increasing their length and reducing their slope by creating a meandering effect. The roughness may be increased either by riparian vegetation or placing gravel of different sizes or rocks along the channel banks to slow down the flow and at the same time trap the sediment. This will delay the time it takes the water to reach the river and improve water quality as well.
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Figure 16. Left: Partially blocked drains; Right: Meandering ditch with increased roughness (Forbes, Ball, and McLay 2015)
Evidence Quantifiable evidence of runoff reduction measurements from field experiments or project monitoring is lacking, or is not available yet. Most of the literature, including the well-documented PhD thesis by Barber (2013), is focused primarily on sediment retention and water quality. What is commonly known is that RSuDS, when implemented correctly, can modify certain parameters (e.g. roughness, slope, infiltration rates, and storage capacity) in the landscape, which may delay the timeto-peak of downstream watercourses or even reduce peak discharges onto the river. As Duffy et al. (2016) suggested, Rural SuDS, can be implemented in a way that they resemble a natural water ‘treatment train’ by slowing and capturing the runoff, and letting it drain slowly into water bodies through swales, wetlands or other types of features. Figure 18 shows a conceptual representation of this idea.
Figure 17. A Rural SuDS 'Treatment train' (Duffy et al. 2016)
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Key Case Studies •
Belgium
A system of earth dams and grassed waterways had a mean peak discharge reduction of 69% at the catchment outlet. Runoff coefficient were reduced by 40% in the vicinity of the grassed waterways. The outcome of the project was reduced downstream water and sediment discharge. (Evrard et al. 2008)
•
Nafferton Farm
Interventions done on a ditch in Nafferton Farm gave a positive outcome of permanent flow reductions, although the peak flow reductions were hard to quantify as their natural effects are non-linear and change in time. Measurements done 400 m upstream and downstream of the interventions showed an estimated 20-40% decrease in peak flow for a 1:1 year rain event. (P. F. Quinn et al. 2007)
Netherton Burn, River Eden
•
Catchment area: 10 km2
•
The overland flow from a farm was re-directed into a large flood storage pond via a 3 cell sediment trap designed to hold up to 156 m3 of water.
•
For a recorded peak discharge of 115 L/s, an estimated 23 min time of residence in the sediment trap was determined, compared to a 1~5 min flow travel time without the intervention. (Barber 2013)
Remarks Rural SuDS could portray effective ways of dealing with flood water in the mid-to-upper catchment of a river. However, more data and monitoring of on-going projects is needed in order to assess their flood risk reduction potential properly. An important fact is that they can be easily placed in the landscape without any major environmental or visual impacts, and they can have lower construction and maintenance costs involved. Some farmers in the UK have expressed that field corner bunds (dry ponds) are a useful way of retaining and recycling fertilizer and rich soils which can otherwise wash away with runoff. The range of benefits delivered by these features can include water quality and sediment yield reduction due to the increase in infiltration rates. Nevertheless, it is important to monitor the groundwater table level as well, since higher infiltration could lead to an increase in the groundwater height and eventually cause flooding. The sketches in the following page schematize some of these measures in order to understand how they work.
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Figure 18. Sediment trap schematic
Figure 19. 'Field corner' earth bunds schematic
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2.5 Riparian vegetation Riparian vegetation refers to the plant and woodland present in the adjacent land areas parallel to the watercourse. The riparian zone is typically narrow (less than 5 m on each side) and consists of native trees and shrub species (Environment Agency 2017). From a flood management point of view, this may contribute to slowing down the flow by creating additional roughness and obstructions to the river flow. Other benefits delivered by the presence of riparian woodlands include: aquatic species proliferations, water quality improvement, and sediment yield reduction. Riparian woodland delivers the following benefits at reach scale: •
Reduction of instream flow velocities
•
Improvement of water quality downstream
•
Soil erosion control and sediment transport reduction
•
Ecological benefits such as habitat creation and river-floodplain interaction
In general terms, woodland creation/restoration increases the local evapotranspiration and infiltration rates, which contributes to changes in the water cycle. More significantly, when they reach a mature stage, they are expected to increase roughness along the river banks. By slowing down the flow, the woodland is also effective at increasing sediment deposition on the floodplain, reducing downstream siltation within the river channel. A number of studies have been done in the UK in Figure 20. Eddleston Water Project (Source: ©Tweed Forum) recent years to try and quantify the effects of planting riparian woodland along river banks. However, longterm data is still lacking because the planted trees are still too young to generate and significant changes. Therefore, modelling studies are a better source of data for assessing these impacts. Modelling studies suggest that the placement of riparian woodland within a catchment has a significant influence on the magnitude of peak flows by the de-synchronization effect they may create downstream. This means that by increasing the time of concentration in one of the river’s tributaries, the probability of peak flows from two or more tributaries to coincide can be reduced (or increased, if not assessed correctly). Riparian woodland also provides additional materials for LWD dams located within the river reach, due to falling trees and branches which may make their way on to the leaky barrier. So, it is suggested that riparian woodland performs better at delivering the benefits when coupled with LWD dams.
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Evidence •
Modelled riparian woodland strips along a 20 km reach within the river Mimente’s catchment in southern France (125 km2) were estimated to reduce peak discharges from a 2year return period event (200 m3/s) by 3.8%. This same study concluded that increasing the roughness on the riparian zones was useful for minor floods, but not very significant for a 100-year return period event (~720 m3/s) (Ghavasieh, Poulard, and Paquier 2006).
•
A 1D flow routing model studied the influence of riparian vegetation on the propagation of flood waves by increasing the roughness along 50 km of channel banks to simulate the presence of riparian vegetation. The model predicted a 12% reduction on a peak discharge corresponding to a 1:100 year event (816 m3/s), by increasing the roughness from 0.043 (no vegetation condition) to 0.15 which is the maximum roughness coefficient for natural channels with dense and mature riparian woodland, suggested by Chow (1959). (Anderson, Rutherfurd, and Western 2006)
•
A modelling study of the 98 km2 Lymington River catchment in southern England, where restoration of riparian woodland across 20-50% of the catchment was predicted to reduce peak flows (~12 m3/s) by up to 19% for a 3% AEP flood (Dixon et al. 2016). Table 2 below shows the scenarios used in this study with their respective hydraulic resistance values.
Table 2. Channel and land use modelling scenarios and associated values for Manning's n
(Dixon et al. 2016)
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Key Case Studies
Pickering Beck
•
A modelling study predicted that planting 50 ha of riparian woodland, coupled with nearly 100 LWD dams could reduce the 1:25 year event (~20 m3/s) by 4%.
•
Catchment area: 69 km2 (Nisbet et al. 2015)
•
River Lymington
A modelling study of this 98 km2 catchment predicted that the restoration of riparian vegetation on 20-50% of the catchment would reduce peak flows by up to 19% for a flood event with exceedance probability of 3% (Dixon et al. 2016)
•
Eddleston
Various NFM interventions (including 66 ha of riparian woodland planting) have been implemented on a 70 km2 upland sub-catchment in the River Tweed near Scottish borders. The modelling of these interventions indicates that additional roughness combined with enhanced storage and infiltration associated with dense forest cover may create a peak flow (~8.5 m3/s) reduction of up to 23%. (Forbes, Ball, and McLay 2015)
Figure 21. Riparian vegetation schematic
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Remarks In hydraulic terms, increased channel roughness is proven to have both attenuating and delaying effects on flow discharges. However, research using physical modelling would be required in order to assess accurate roughness coefficients to represent different types of riparian vegetation on a 1D channel flow model. Some studies have provided evidence of the effectiveness of increasing roughness along riparian zones, yet the accuracy of these results is debatable due to the assumption of Manning’s n values. Riparian woodland restoration and management is thought to deliver more benefits when coupled with other NFM measures such as LWD dams. These two types of interventions may complement each other in the sense that LWD would create a partial obstruction of the flow and this would cause the water to spill into the riparian zone of the channel. Riparian woodland also can provide raw materials for LWD dams. Figure 21 shows the schematic representation of this particular feature. The age and type of vegetation planted along the riparian zone seems to influence the overall impact in the flow. This means that as the plants and trees age and the riparian zone becomes more densely vegetated, the roughness they create will increase. Further research and monitoring is suggested in order to assess these effects.
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2.6 Analysis from the Literature Review Contributions from the scientific papers, reports and publications analysed beforehand suggest that upstream catchment NFM interventions (under the right circumstances) have the potential to reduce floods downstream. Whether these measures are effective in doing so will depend on each project and site-specific characteristics. The overall conclusion here is that the selected measures affect or ‘enhance’ certain hydraulic and hydrologic variables which can have an impact on river discharges and water levels downstream. The list of identified variables affected by the analysed measures have been summarised and listed on the table below, followed by a preliminary evaluation of their performance based on the existing literature represented with a 1 to 10 scale shown on Figure 22.
Table 3. Table of Hydraulic and Hydrological processes affected by NFM measures
Hydraulic & Hydrologic Parameters affected by NFM
NFM Intervention Large woody debris dams Offline storage ponds Hedgerows & Buffer strips Riparian vegetation Sediment traps / swales Dry / wet retention ponds
Storage capacity
Roughness (n)
Infiltration
Runoff
Figure 22. Preliminary Evaluation of the NFM Measures
10 9 Degree of enhancement
8 7 6 5 4 3 2 1 0 Large woody Offline storage Hedgerows & debris dams ponds Buffer strips
Riparian vegetation
Sediment traps
Dry / wet retention ponds
Affected Hydraulic & Hydrological Parameters Storage capacity
Roughness
Infiltration
Runoff
(Scale: 0 = No effect; 10 = High effect)
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It is very likely that an individual measure does not have a significant effect on flood peaks, but when combinations of measures are applied throughout a particular catchment the effects could increase. An ‘Integrated Natural Flood Management’ approach is therefore suggested in order to observe the flood reduction benefits. Figure 23 depicts a hypothetical rural catchment (“Catchment 1”) under a NFM regime, where a number of properties located within a floodplain downstream are at risk of flooding, and several measures spread throughout the catchment have been placed in such a way that significant impacts on river discharges, water quality and the environment may be achieved. This approach should also involve working with the community throughout the entire process, in order to achieve better results and a positive social impact. The on-going NFM Projects at Stroud and River Eden in the UK are good examples of community involvement on mitigating flood risk using NFM.
Figure 23. Hypothetical catchment under Integrated Natural Flood Management
*Not to scale
Natural Flood Management should not aim to replace traditional methods of addressing flood risk, yet it can be useful approach for decision makers to consider when planning for sustainable development and IWRM. Evidence suggests that these interventions can have a positive effect on low intensity flood events, but are less effective when coping with larger events. More quantitative data is needed on their effectiveness at different scales, and site-specific analyses should be performed before taking these measures into account. Hydrograph synchronization between different tributaries should also be considered when making placing NFM interventions in different tributaries throughout a catchment, as the flood peaks could 46
become greater if the times to peak discharges from two rivers or more coincide. This could lead to an increase in flood risk downstream. Some case studies show that some NFM measures like LWD dams and riparian vegetation are effective in slowing down the flow, therefore delaying flood peaks. This suggests that this peak ‘de-synchronization’ could prevent water levels to exceed a certain threshold downstream, as it can be seen in the following example. Figure 24 shows another hypothetical catchment (“Catchment 2”), where discharges from River 1 and River 2, caused by a rainfall event with return period T have been collected at points A and B, and are plotted on Figure 25. In normal conditions (meaning no NFM interventions have been done yet) both river peak at nearly the same time for points A and B. After NFM interventions have taken place on River 2, a 30 min delay in the peak has successfully been achieved (QB’) for a similar event with return period T, but the peak discharge value remains roughly the same. When monitoring is done further downstream at point C the effects of peak de-synchronization can be observed, as less water volumes flow at the same time through point C.
Figure 24. Hypothetical rural catchment “Catchment 2” with NFM on one tributary river
*Not to scale
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QA
QB (No NFM)
QB' (with NFM)
QC (QA+QB)
1.8
3
1.6
2.5
QC' (QA+QB')
Flow (m3s-1)
Flow (m3s-1)
1.4 1.2 1 0.8 0.6 0.4
2 1.5 1 0.5
0.2 0
0 0
20 40 Time (min)
0
60
20 40 Time (min)
60
Figure 25. Flow hydrographs for monitoring points A and B (Left); Flow hydrographs for monitoring point C (Right)
This simple example done by plotting generic data for a conceptual catchment explains the importance of peak flow timing. However, this hypothesis needs to be proven by modelling studies and on-site data monitoring for different catchment locations, NFM interventions and different rainfall events.
2.6.1 NFM in hydraulic modelling As it has been stated previously, the multiple benefits from NFM are often difficult to quantify in a tangible way. There is a limited amount of research on how to represent NBMs on hydraulic models. Therefore, achieving positive results from a model is up to the expert’s knowledge and the way he or she believes is the most accurate way to model these features. After a careful analysis of the existing literature, the following methodology for including the selected measures was derived:
•
Large Woody Dams (LWD) – A 2D porous surface placed across the section of a channel would be a good way of including the pieces of wood and debris found in these features, as seen in Figure 26. The porosity can be defined as the total area covered by the voids in this woody debris mesh divided by the total surface area of the dam. 𝐿𝐿𝐿𝐿𝐿𝐿 𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝𝑝 =
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∑ 𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝑣𝑣𝑣𝑣𝑣𝑣𝑣𝑣𝑣𝑣 𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇 𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐿𝐿𝐿𝐿𝐿𝐿
Figure 26. Woody Dam front view
•
Hedgerows – In the same way, hedges are natural 2D vertical surfaces which present physical obstructions to the flow paths as it can be seen in the photograph below. Therefore, the same approach has been proposed for modelling hedges as porous vertical elements stretching across the terrain as detailed below.
𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴ℎ𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒 𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝐴𝑣𝑣𝑣𝑣𝑣𝑣𝑣𝑣𝑣𝑣 Figure 27. Hedgerow front view (Source: www.greennews.ie)
•
Riparian vegetation – All the evidence collected and analysed previously points towards modifying Manning’s roughness coefficient in a hydraulic model for representing the riparian zones of a channel with highly vegetated surfaces. This has been previously addressed with more detail in the Remarks on Section 2.5.
•
Field corner bunds (dry ponds), Offline storage and Sediment (retention) Ponds – are all ways of storing water within the upstream region in a catchment. These features involve physical changes to the landscape such as excavation of the soil, or raising earth bunds along a specific area in order to capture and store the runoff produced by storm events. This can be achieved in a hydraulic model by modifying (raising or lowering) the 2D mesh zone in order to display these changes.
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Chapter 3
Methodology
The literature review presented in the previous section intended to obtain valuable pieces of information which could provide guidelines for the next steps in the process. In this chapter, the methods and tools used for completing the main objective and the tasks outlined in section 1.3 are described. A careful selection of the study area in which the NFM interventions were then tested took place, followed by the elaboration and calibration of a 2D hydrodynamic model for the selected catchment, as well as the process of choosing the right locations for these measures along with several simulations and data collection from the obtained results.
3.1 Case Study: Littlestock-Brook, Oxfordshire UK The study catchment chosen for this research was the Littlestock-Brook in West Oxfordshire, UK. This watershed is part of the River Evenlode sub-catchment, which is at the same time a River Thames tributary. The Littlestock-Brook is a rural catchment with an estimated area of about 16 km2 consisting mostly of farmland and pasture fields with small urban areas, Milton and Shipton-underWychwood, located in the downstream region. Inside the catchment there are more than 800 buildings plus 5 other ones which have a higher value for the community (churches, healthcare, schools, etc.). The map below shows an overview of the catchment.
Figure 28. Littlestock-brook catchment overview
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The stream network, formed by small channels and farmland draining ditches, has an approximate total length of approximately 36 km. The catchment’s slope is relatively steep for England, with elevations ranging from 243 to 91 mAD. This height difference in such short distances, along with other factors such as land use and land cover, accounts for the rapid response to storm events, meaning relatively high discharges with short lead times. Even though there have not been any deaths accounted yet to floods in this catchment, economical losses caused by the rising water levels have been produced over the years. This research has been focused on the small scale watershed upstream of the bridge on Church Road, near The Heath, which has an area of approximately 6.7 km2 (approximately 40% of the total Littlestock-Brook sub catchment). However, results were also gathered at the outfall of the 16 km2 catchment in order to observe any changes from these implemented measures at a larger scale and formulate new hypotheses about the extent of the impacts that these measures have throughout a catchment.
3.1.1 Flooding history There are a number of properties (±20) under flood hazard at Milton-under-Wychwood, which have been affected several times over the last decades. Some of the most recent recorded flood events were: 28th December 1979, 25th November 2006 and on 20th July 2007. On the 2007 event the water levels upstream of the culvert at The Heath reached the some of the highest elevations ever recorded, when the downstream culvert at Church Road couldn’t drain the large water volumes properly, creating a backwater effect which lead to the flooding of at least 9 properties, plus 83 other properties downstream flooded by the Evenlode in Shipton and Ascott-under-Wychwood. This flood event was the outcome of an unusual rainfall event which left over 115 mm of rain in a 20 hour timeframe, estimated by Halcrow to match a 1 in 380 year storm event (0.26% AEP).
Flood Storage Area
Bridge
The Heath
Figure 29. Simulation results for the July 2007 flood event
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Level reached during the 2007 event
Figure 30. Environment Agency monitoring station at The Heath
In recent years, the Environment Agency along with Wild Oxfordshire have been developing a pilot project as part of a Natural Flood Management research in the area. As a result, a number of nature based interventions have been designed for this specific catchment (including 12 woody debris dams which are already in place). A monitoring station which records water levels, flow and turbidity was put in place after the 2007 event by the EA to cope with the lack of data. There are also 3 rain gauges in the surroundings of the catchment, plus one privately owned inside the catchment, which record precipitation data that can be used to determine rainfall depths and intensities for particular events, calculating design return periods, forecasting and so on.
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3.1.2 Existing flood reduction measures Church Road Bridge (culvert) opening In 2010, local authorities and residents got together and decided to hire a private consultancy group to prepare an assessment report on the sources and pathways of flooding in the area. This consultancy group analysed the catchment using a hydraulic model on behalf of the EA and produced a report in which the bridge opening at Church Road was identified to be increasing the flood vulnerability of the neighbouring houses and properties. Observed water levels downstream of the bridge were 103.66 mAOD as opposed to 104.59 mAOD, which was the observed water level upstream of the bridge. This backwater effect (bridge afflux) caused the water from the channel to spill onto the road and the surrounding properties. After the weakness had been identified, the community and the corresponding authorities decided to increase the drainage capacity of this structure by creating a parallel semi-circular opening beside it. This would allow the river to drain more efficiently when coping with large volumes of water. The photographs below shows a ‘before and after’ of the Church Road Bridge works. Figure 31. Church Road culvert (Left: 2010, Right: 2017)
(FortRidge Consulting Limited 2010)
The catchment upstream of the Church Road culvert is about 6.9 km2 which drain the runoff from the farmlands upstream into a small urban area called The Heath in Milton-under-Wychwood, which is characterised by rectangular ‘u-shape’ channels with bed width of about 2.00 m and vertical walls on both sides of about 0.80 m in average. The two photographs in the following page show the channels at The Heath during a high flow period in 2008 (left) and during the low flow, dry season in May 2017.
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Figure 32. Channels at The Heath (Left: Dec 2008, Right: May 2017)
Dec 2008 photograph from FortRidge Consulting Limited, 2010
Flood storage area At some point in history, it is believed that the channel was diverted in order to create a fish pond which is now being used as an offline flood storage area (See Figure 33). It is an adjacent low-lying grassland surrounded by earth bunds which keep the water in place until the water levels drop downstream. There is a ‘fish bone’ inlet structure consisting of underground pipes which direct the water from the stream into the storage area. This feature has been tested and modelled on ICM and was found to be working at approximately 1/3 of its capacity (approximately 5,000 m3), filling up and overtopping the outlet spillway before the peak of the rainfall arrives, as shown in Image 4 below. A NFM intervention has been proposed and modelled for this measure and is described in detail in Section 3.2.4.
Current watercourse
Inlet Original watercourse (Approximate) Outlet
Figure 33. Modelled Flood Storage Area using the 20 July 2007 rain event
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Woody Dams Due to the high gradients in the catchment, and the Figure 34. Woody dam upstream of The Heath fact that most of the land cover is highly erodible, there have been issues concerning accumulation of sediment, rocks and other debris downstream near The Heath in Milton. This is one of the reasons why the Wild Oxfordshire Project along with The EA decided to implement some NFM measures. Up to date, a total of 12 woody dams have been installed along a 600 m river reach upstream of The Heath, in an attempt to stabilize the channel bed and retain therefore some of the sediment that is now being transported by the river into the downstream areas.
3.1.3 The Littlestock-Brook NFM Project In an effort to observe the potential benefits of nature based measures, the EA along with Wild Oxfordshire have plans to install more woody dams along the stream network, create tree belts and retention ponds upstream, as well as some field corner (earth) bunds on some of the farms where high runoff has been observed by previous surface water modelling studies (See Figure 37). Most of the land owners are keen to cooperate with the project, and the community involvement seems to be on the right track for developing an interesting project. Figure 35. NFM measures proposed by the Environment Agency and Wild Oxfordshire, The Evenlode Catchment Partnership (Old and Vaughan 2016)
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3.2 Modelling rationale Hydraulic modelling applied to the Littlestock Brook has been limited. In 2004 carried out a broad scale JFLOW modelling study for the whole Evenlode catchment, plus a small scale study in Wychwood due to previous floods here. However, no 1D or 2D models had been focused on this particular catchment until the recent one done by Halcrow for The Environment Agency in 2012. This study involved building a 1D-2D model in ISIS TUFLOW for an area covering just over 30% of the Littlestock and part of the Evenlode downstream. (Halcrow Group Limited 2012) A new approach was suggested for this research. This approach includes a full 2D hydrodynamic model which would allow the user to identify flow paths and ponding areas throughout the catchment with a higher degree of accuracy, and at the same time save computational time due to the limited timeframe for the research. Giving the fact that most of the selected measures are to be placed in the upper catchment or on the flood plain, and that HR Wallingford has the proper software tools to follow this approach, it seemed to be the most efficient way.
3.2.1 Littlestock-Brook 2D Hydrodynamic Model Ground Model & 2D Mesh Zone The ground model was generated from open source Light Detection and Ranging, or LiDAR, data available, with a 1m resolution for the lower catchment merged with a different resolution for the upper catchment. This change in resolution can be observed in Figure 36, and is typically the result of merging different point-source datasets into a single raster surface. Given that this was the best open-source terrain data available, it was then processed using a GIS software package in order to identify the stream network and catchment boundary for the specified outfall (where the Littlestock meets the Evenlode).
1m resolution
10m resolution
Figure 36. Littlestock Brook DTM resolution
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The main purpose of this model is to evaluate a specific rainfall hyetograph as it is applied directly into the mesh, and from this data generate flow hydrographs at specified locations, from which the user can observe patterns of change due to the implemented NFM measures. In a way, it is purely a rainfall-runoff (hydrologic) model, but it also includes the analysis of the runoff intensities and patterns throughout the 2D surface and the channels, which makes it a hydrodynamic model. The selected software to complete this task was InfoWorks ICM, which allows the user to analyse an entire catchment from many perspectives in order to identify all sources of flooding. On the one hand, ICM uses St. Venant Equations to analyse hydraulic models built entirely on 1D using prismatic (pipes and channels) or non-prismatic (rivers) elements, and on the other hand, it solves shallow water equations (Navier-Stokes) to analyse the overland flow in the 2D mesh zone. Apart from its user friendly interface, the main advantage of this software is that it couples both 1D and 2D modelling in a single space and time domain. Some other useful features from this software which can be used for the purpose of this research are the following: •
An irregular triangular mesh with the option to work with different element sizes for areas where the user finds convenient, and terrain-sensitive meshing where the mesh detects fluctuations in the ground model.
•
Voids which can be used to represent buildings or structures which deflect the flow and affects its path and velocity.
•
Roughness zones polygons to represent different types of land cover throughout the 2D mesh zone.
•
Porous walls, which are useful to represent measures such as woody dams, hedgerows and other natural features.
•
Mesh level zones, are areas in the mesh zone which can be lowered or elevated and are useful for including earth bunds or dry/wet retention ponds.
Figure 37. Littlestock-brook 2D mesh zone
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The previous figure is a screenshot taken from the early stages of the modelling process, where the 2D mesh zone can be observed, along with some voids which represent the properties at The Heath. In the zoomed image, the different mesh element sizes can also be observed. The general floodplain 2D mesh has elements between 1.00 and 250.0 m2, while in the stream network, the mesh size ranges between 0.50 and 1.00 m2 for a more detailed analysis. In Figure 40 below, the full extent of the 2D surface can be observed. The bright green line is the model boundary, and the dark blue dot to the east represents the catchment’s outlet, where it connects to River Evenlode and the Thames downstream. The stream network can be also identified as it is included in the model with a finer resolution, hence the darker colours in the channels.
Figure 38. Littlestock-brook 2D Surface extent
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2D Surface roughness coefficients There are several factors that affect Manning’s roughness coefficient, which can be variable throughout a channel. Some of these factors include: size and shape of the grains forming the floodplain and channel bed, the type of vegetation present in the surface, the alignment of the channel (meandering or straight), and the irregularity of the surface, among many others. As a general rule, it can be said that as a channel or floodplain surface becomes more ‘artificial’ or less natural, the roughness coefficient n approaches to 0. (Chow 1959) Manning’s roughness coefficients, which are to be specified for the 2D zone, were assessed using Chow’s 1959 Open-Channel Hydraulics, which is still a valid approach for this parameter. After the site visit to the study area and observing historical maps, along with satellite imagery, it was decided that the catchment is composed mainly by arable fields and grasslands. The values for Manning’s roughness were obtained from the following table:
Table 4. Typical Manning roughness coefficients for various open channel surfaces (Chow 1959)
Typical Manning’s Roughness Coefficient n
Land cover
Natural stream channels Clean, straight stream
0.030
Clean, winding stream
0.040
Winding with weeds and pools
0.050
With heavy brush and timber
0.100
Flood Plains Pasture
0.035
Field crops
0.040
Light brush and weeds
0.050
Dense brush
0.070
Dense trees
0.100
The final Manning’s values were then calibrated and were applied to the model as follows: 0.040 for the open channels, 0.100 for woodland areas, and 0.050 for the rest of the 2D surface. However, these values remain mere approximations to what exists in reality, therefore, a proper calibration of these parameters is necessary and should be performed by on-site measurements in order to obtain more accurate results.
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Soil Water Content & Infiltration As the scope of this research does not include groundwater hydraulics and due to the lack of data about historical soil moisture contents in the study catchment, infiltration schemes (such as Horton’s infiltration model) were not taken into account. Instead, knowledge and experience in hydraulic modelling from HR Wallingford experts suggested to use a fixed effective infiltration rate. A fixed infiltration rate means that the rate at which water from precipitation (after initial losses) infiltrates remains the same, regardless of the soil moisture content. This effective infiltration rate is calculated with the following formula: 𝐼𝐼𝐸𝐸 = (1 − 𝑓𝑓𝑓𝑓𝑓𝑓𝑓𝑓𝑓𝑓 𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟 𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐𝑐) ∗ 𝑖𝑖
where 𝐼𝐼𝐸𝐸 is the effective infiltration (mm/hr), 𝑖𝑖 is the rainfall intensity (mm/hr), and the fixed runoff coefficient is a dimensionless value between 0 and 1 which represents the percentage of effective rainfall which turns into runoff after the initial losses. (Vojinovic and Abbot 2012) This runoff c was empirically determined to be within 0.40 and 0.60 for this specific catchment, and after the calibration process it was set to 0.40 for the entire catchment. This means that for a certain volume of rainfall in a given period of time, 60% of the total volume infiltrates into the soil at a fixed rate. Input rainfall hyetographs The desired rainfall profiles, or hyetographs, for the selected return periods (5-yr, 10-yr, 50-yr and 100-yr) were generated using the Revitalised Flood Hydrograph model or ReFH. This method is widely used in the UK for estimating design storm and flood events, and is especially useful in areas where no hydrometric data is available. The Flood Estimation Handbook, developed by the Institute of Hydrology in 1999, included a spatially generalised depth-duration-frequency model (DDF), which enables the estimation of design rainfall hyetographs for durations ranging between 30 minutes and 8 days and for any location in the UK, based on annual maximum rainfall values. The revitalised rainfall-runoff method introduces the use of a seasonal correction factor, one for winter and another one for summer events. This enhancement in the methods allows the user to obtain different hyetographs for the same event with return period T depending on the season on which the event occurs. (Rodding Kjeldsen 2007)
Figure 39. Design storm events (1 : 50, 7-hour duration ). Left: Winter season, Right: Summer season
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The design storm profiles were obtained using the ReFH software. These profiles are symmetric and contain a single peak. The rainfall intensity increases every time step until it reaches the peak and then decreases symmetrically, as it can be observed in Graph 7. The difference between the winter and the summer design events can also be observed. While the winter peak approaches 12.7 mm/hr, the summer event reaches a maximum of 22.1 mm/hr for the same duration and frequency. This difference may be explained by the fact that typically summer events have shorter durations and higher peaks, while winter events have longer durations and more constant rainfall intensity rates. The following design storm hyetographs were obtained:
Table 5. Design rainfall profiles obtained from ReFH
Season
Return Period
Duration
Winter Winter Winter Winter Summer Summer Summer Summer Winter Winter Winter Winter Summer Summer Summer Summer
5-year 10-year 50-year 100-year 5-year 10-year 50-year 100-year 5-year 10-year 50-year 100-year 5-year 10-year 50-year 100-year
7-hr 7-hr 7-hr 7-hr 7-hr 7-hr 7-hr 7-hr 26-hr 26-hr 26-hr 26-hr 26-hr 26-hr 26-hr 26-hr
Due to the long computational time required for each model run and the short timeframe for this research, only the Winter profiles for 7-hr duration were modelled (shaded in Table 5 above). Further model runs using the rest of the design events is recommended in for comparison. See Chapter 5 – Conclusions and Recommendations.
Upstream channel inflows (base flow) Before a rainfall event strikes, it is very likely that the stream network has a relatively constant initial flow, or base flow. In the summer period, this flow is usually low and is originated from the subsurface runoff and other groundwater sources entering the channel. However, in the winter season, this base flow might be increased by the overland flow due to various types of precipitation and higher groundwater levels. A total of 3 point sources (inflows) were included in the model, one in each river branch. A typical channel cross section was then analysed for each river branch, correspondingly, and the steady initial flows were then calculated using the flow rate formula Q=A*V. The water levels used for calculating 61
the wetted perimeter, as well as the flow velocities were assumed with the help of expert knowledge. Figure 40 shows cross section X-23 obtained from the model. The initial flows for each model run were done by running the model only with the inflows for 24 hours in order to obtain a constant initial flow and saving this final state, which would then be used as a ‘initial condition’ for the actual model runs. A proper assessment of the initial conditions for each modelled event should be done taking historical water levels, field measurements and surveying. Figure 40. Cross-section X-23
Elevation (mAD)
113 112.5 112
Winter base flow
111.5 111 110.5 0
1
2
3 4 Distance (m)
5
6
7
3.2.2 Monitoring Locations In order to observe patterns of change or the effects of the implemented nature based solutions, flow and water level hydrographs should be compared. This comparison should be done by running the model without any measures, extracting the results (hydrographs), then running the model again with the measures in place, and finally collecting results in the same locations. These locations were selected carefully in order to observe the changes and potential benefits of these measures for reducing the floods in an area under flood hazard. The known as The Heath, inside the LittlestockBrook, has been previously identified to be sensitive to flooding, which is the main reason why local residents and authorities have decided to take action. The figure below show these locations as they were placed within the model: R1_DS - Catchment outlet
R1_US - Upstream of the Heath on Reach 1
R2_DS - Upstream of The Heath on Reach 2
Cu1 - Upstream of the culvert on Church Rd.
Figure 41. Result-gathering locations within the catchment
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The result lines (dark red) pick up all the flow across the entire channel section and floodplain, whereas the result points (bright red) are used for monitoring the water levels in the channel in metre above datum (mAD). Monitoring location at the bridge on Church Road ‘Cu1’ was chosen with two main purposes: to observe the flow and water levels in a vulnerable location, where the two tributaries join, and also to compare the collected data with the observed during the 2007 flood event, which would help in the calibration process of the model described in the following section.
3.2.3 Model calibration process Ground model corrections Typically, when utilising any DTM generated from aerial photography or LiDAR data, there are some corrections that need to be performed in order for the ground model to approximate reality. Objects such as trees and vehicles should be removed from the generated surface, channels and bridges should be corrected manually in most cases, which is exactly what had to be done for the Littlestock-Brook 2D ground model. The image below shows some of the corrections performed on the ground model such as: channel section adjustment and the inclusion of the bridge opening on the Church Road culvert.
Figure 42. Channels and Culvert near The Heath (Left: raw DTM, Right: Corrected DTM)
(*Height exaggeration factor = 2)
The measurements required to do the corresponding adjustments were taken during a site visit to the Littlestock-Brook catchment. The new semi-circular opening which was built after the 2007 event to increase the drainage capacity was not included, yet the main bridge opening was enlarged in order to compensate for this, providing roughly the same drainage capacity.
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Manual calibration for the 20 July 2007 rainfall event After going through all the data available, it was decided that the model would be calibrated using the observed peak water level on the 20 July 2007 flood event against the peak water level obtained from the model at the same location (Cu1). Then, the calibration process was done manually by adjusting the following variables: •
Manning’s roughness coefficient (channel and floodplain)
•
Fixed runoff coefficient
•
Rainfall event
The rainfall event selected for the 2007 flood event was a generic hyetograph created to match the available description of the actual rain event. Gauged data is not available for this specific event within the Littlestock-Brook, yet the total amount of rainfall and duration were recorded. The 20 July 2007 event was a 20-hour duration rainfall event which left a total of 115 mm of water during this timeframe. The hyetograph for this event was constructed using a FEH Summer Design profile as a template (given that this was a summer event), but also made to match the recorded depth and duration.
Observed maximum water level = 104.59
Figure 43. Water levels obtained from the model at Cu1 for the 2007 event
After adjusting the parameters and running the model several times, the model was calibrated to match the observed water level upstream of the Church Road Bridge, missing by only 0.04 m. The water level observed at the upstream side of the bridge was 104.59 mAD, and the obtained water level was 104.55 mAD.
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Property Flood Threshold The thresholds for which properties around The Heath flood were surveyed by Halcrow in November 2009. Following a conservative approach, the lowest of these values was selected and implemented for the post processing of the results. This assures that whenever the water levels reach or go above this line, there will be at least one property flooded. Finally, the flood threshold was set to 104.20 mAD with a confidence interval of ±0.05m as it can be observed in the result water level hydrograph on the graph below. This particular case shows the observed water levels at location Cu1 (upstream of the culvert) after having modelled a 5-year return period event with and without measures in place. For a more detailed analysis of the results see Chapter 4 – Results and Discussion.
FLOOD THRESHOLD
Figure 44. Water level hydrograph with property flood threshold
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3.2.4 Modelling NFM measures in InfoWorks ICM Natural measures can sometimes present difficulties whenever there is an attempt to model them with conventional approaches. Structures such as concrete dams, spillways, pipes or channels are typically the elements present in hydraulic models, yet these elements are in a way more stable and predictable than natural ones. The need to model Sustainable Urban Drainage Systems (SUDS) like rain gardens, green roofs, infiltration trenches, permeable pavements, etc. has been increasing in recent years due to the boom in ‘Green Infrastructure’ and ‘Water Resilient Cities’ development. InfoWorks ICM allows the user to include these kinds of structures, which is another reason why this tool was chosen for the research. The selected NFM measures were included in the model as described in Table 6 below, following the methodology described in section 2.6.
Table 6. NFM Measures as represented in the model
Measure
Modelling element
Variable
Value
Woody Dam
Porous wall
Porosity
0.10 - 0.25
Hedgerow
Porous wall
Porosity
0.30
Riparian Vegetation
Roughness zone
Manning's n
0.07 - 0.10
Field corner (earth) bund
Mesh level zone
Height
1.00 m
Offline Storage
Mesh level zone (raised perimeter)
Height
1.00 m
Retention (sediment) Pond
Mesh level zone (lowered surface area)
Volume
variable
*The values for the variables involved in each measure were assessed using existing literature or HR Wallingford experts’ judgement where no parameters exist. Woody dams were included as porous walls with porosity ranging between 0.10 and 0.25 (depending on their location) and laid across the channels from the bottom all the way up to the top of the banks. Hedgerows were placed mostly in the locations where they already exist, yet their porosity was assumed to be constant throughout the catchment (0.30), and were represented by 2 m high porous walls. Riparian vegetation is represented by roughness areas along the channels. Earth bunds, as stated previously, have been included by raising the mesh level zones by 1 m. Sediment ponds were also modelled as mesh level zones which were lowered to resemble an excavated area where the water would be retained. Lastly, the storage area was designed by simply raising ~1m earth bunds all around it and lower ones for the inlet and outlet so they act as spillways. The flood water is diverted from the channel ‘naturally’ by the existence of a low-porosity (0.10) Woody Dam close to the inlet. The accumulation of water upstream of this woody dam would cause the water levels to raise and therefore spill into the storage area during the case of a storm event. Before draining through the lowered spillway and drainage channel, the storage area fills up storing up to 30,000 m3. In practice, this feature should also include a pipe drainage below in order to drain and have enough storage capacity for subsequent events. This pipe has not been included in the model. See Figure 45 in the next page for more details about the modelled Offline Storage Area.
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Woody Dam Raised Inlet
Drainage Channel Spillway
Raised Earth Bunds
Figure 45. Enhanced Offline Storage Area
The image below was taken from the actual Littlestock-Brook model. The bright orange element in the channel is the representation of a woody dam modelled as a porous wall, the brown coloured irregular elements on the floodplain are the field corner (earth) bunds, and the light green area surrounding the channel itself symbolises the riparian vegetation.
Figure 46. A 3-D view into the model with measures in place
3.2.5 Locating the measures The next step in the modelling process was to find the correct approach in order to place the measures in the right locations, where they would intercept more runoff from the catchment’s surface. Moreover, the measures needed to be ‘optimised’ in a way, due to the fact that most of the catchment consists of arable land destined to agriculture. This means that the land owners would not be content with the idea of losing large portions of land for the sole purpose of placing flood prevention measures in them.
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Key locations for placing the measures were then found by observing the runoff paths from the first model runs after the calibration process took place. By doing this, the patterns and ponding areas where the overland flow accumulates can be identified and the corresponding measures can be implemented. The following image shows an exemplification of the way in which the measures have been placed within the catchment. The elements overlaid on the background image do not suggest the exact position of the measures, as they are merely a schematic representation of reality.
Sediment Woody Dams
Runoff Earth bunds
Hedgerows
Hedgerows
Runoff
Figure 47. Runoff paths and NFM measures locations within the catchment
It is to be noted here that in some cases, new hedges were included were runoff paths exist and the terrain allows it. However, most of the modelled hedgerows are already present on the catchment’s landscape and therefore, they have just been introduced in the model and ‘enhanced’ in a way by defining a certain porosity or the proportion of vegetated vertical surface per unit area. This approach suggests that the porosity at the very base of the hedges should be measured precisely for each case. Further research is suggested on the way hedgerows affect hydraulic models when included as vertical elements with different porosities. See Chapter 5 – Conclusion and Recommendations for more details about further research.
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Runoff paths
Field corner (earth) bund
Figure 48. Runoff paths intercepted by a Field Corner (earth) Bund near The Heath
The image above shows the way in which a typical 1 m high earth bund placed strategically at the corner of a field can retain a significant volume of water during a high intensity storm event, after the soil is fully saturated and the runoff increases. In this particular case, the flood could not be prevented downstream, because the in-stream volumes of water are too large and they eventually spill into the properties. Therefore, more measures are to be implemented upstream in order to retain the flood volumes.
Riparian vegetation Runoff paths LWD
Runoff paths
New hedgerows LWD Runoff paths Existing woodland Existing hedgerows Figure 49. Flow paths and some measures during a 1:100 year event
After analysing the results from the Littlestock-Brook model results, observing the runoff paths and ponding areas throughout the catchment, some ideal locations for the measures were obtained and finally a number of NBMs were placed throughout the sub-catchment upstream of The Heath. Table 7 describes the amount of measures implemented in this model.
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Table 7. Table of measures implemented
Quantity 70
NFM Measure Woody Dams ~ 5,000 m3
9.20 km
Hedgerows
14.72 ha
Riparian Vegetation
1
Offline Flood Storage Area ~ 30,000 m3
13
Sediment (retention) Ponds ~ 3,100 m3
1,960 m
Field Corner (earth) Bunds ~ 28,000 m3
The optimal number of measures has not been assessed in detail due to time limitations. This means that the amount of MBMs should be analysed carefully, by performing a sensitivity analysis of each of these throughout various locations within the catchment in order to obtain the highest flood reduction with the minimum number of measures in the correct locations. The selected measures were placed throughout the sub-catchment upstream of the bridge (culvert) at Church Road, as show in the map included in Appendix 2.
3.2.6
Sensitivity Analysis for the number of Woody Dams
Placing the woody dams in the best possible locations involves bearing in mind several aspects. Depending on the slope of the channel bed, there must be a minimum spacing between them, in order to allow them to fill up entirely before conflicting with the next one upstream. Other important factors have to do with the morphology and navigability or the river. Aquatic ecosystems should also be taken into account, meaning that the passage of fish or other species should be accounted for. Yet more importantly, is to assess in a proper way, the real effect of these woody dams and how increasing or decreasing their quantities may affect the results obtained. Ideally, a sensitivity analysis should be performed for all the parameters involved in each measure, such as location, roughness and porosity. However, this research only cover the sensitivity of increasing the number of woody dams from 10 to 70, and the results were obtained for 10, 20, 30, 40, 50, 60 and 70. The maximum amount of woody dams was 70, due to the stream network layout, topography and slope of the channels. A minimum spacing of ~30 metres applies for most of the cases, yet there are some exceptions. This analysis was done by running the model with no measures in place, and then increasing the number of woody dams by 10 (moving upstream, away from The Heath) for each model run until reaching 70. The hydrographs were collected at location Cu1 and plotted against each other. These results show that there is a small and negligible reduction in the flow hydrographs as the number of dams increases, and that as the intensity of the storm event increases this difference between no woody dams and 70 woody dams decreases. For the 1:50 and 1:100 events, the flow increases slightly at Cu1. This might be the case of the woody dams being filled up with water before the peak of the rainfall and releasing it with more kinetic energy when the flood wave arrives. See Figure 50 on the following page and the conclusions on Chapter 5 for more details.
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FEHWin_1:10 - Flow at The Heath (Cu1) 5 4.5 4
Flow (m3s-1 )
3.5 3 2.5 2 1.5 1 0.5 0 00:00:00
01:00:00
02:00:00
03:00:00
04:00:00
05:00:00
06:00:00
07:00:00
Time (hr : min)
FEHWin_1:100 - Flow at The Heath (Cu1) 8
7
6
Flow (m3s-1 )
5
4
3
2
1
0 00:00:00
01:00:00
02:00:00
03:00:00
04:00:00
05:00:00
06:00:00
07:00:00
Time (hr : min) 10 LWD
20 LWD
30 LWD
40 LWD
50 LWD
60 LWD
70 LWD
Figure 50. Woody Dam Sensitivity Analysis monitored in location Cu1 for events 1:10 and 1:100
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3.2.7 Modelling scenarios The impact of each individual measure can be assessed by adjusting the model manually and running simulations for each of the individual measures to observe what effect they have on flow and water level hydrographs. However, this approach suggests a huge amount of computational time and the results obtained are believed to show little or no effect on floods downstream. With this in mind, a new approach was suggested for the purpose of obtaining tangible results which could then be analysed and which could demonstrate the potential benefits of NFM. The new approach to modelling the selected measures included the creation of modelling scenarios, which would include a number of NBMs in combination with other measures. These scenarios were created bearing in mind the guidelines found during the literature review, which suggest how the benefits of implementing NFM measures can be maximised by placing them in ensemble with other measures of the same nature. For instance, it is a common belief that Woody Dams (LWD) might be useful in wetland restoration by forcing the in-channel water flows to spill into the floodplain. Therefore, other measures such as riparian woodland or earth bunds can also be implemented alongside in order to amplify their benefits. As Duffy et al. (2016) have suggested previously, Rural SuDS or NFM measures (in this case), can have potentially larger benefits when implemented as an ensemble of several features.
Table 8. Table of Scenarios with combination of measures
Scenario Base Case
Implemented Measures Catchment with no measures implemented
1
Woody Dams + Riparian Vegetation
2
Woody Dams + Riparian Vegetation + Hedgerows + Field Corner (earth) Bunds
3
Offline Flood Storage Area
4
Offline Flood Storage Area + Field Corner Bunds + Sediment (retention) Ponds
5
All measures implemented on Reach 2, no measures elsewhere
6
All measures implemented on Reach 1, no measures elsewhere
7
All measures implemented on both Reach 1 & Reach 2
The table above contains the 7 scenarios which were then modelled in ICM. The Base Case Scenario includes no measures what so ever. It is merely the calibrated model in its ‘initial state’ before implementing the measures. This scenario was useful for comparing hydrographs and observing the changes caused by all the measures contained in the other scenarios. Scenarios 1 and 2 were created for assessing the effects of combining Woody Dams, Riparian Vegetation, Hedgerows, and Field Corner Bunds differently. Scenario 3 was done for assessing the effectiveness of the proposed Offline Storage upstream of The Heath. Scenario 4 was created to assess the measures which 72
increase the catchment’s retention capacity. Scenarios 5 and 6 were created to compare the effects of measures implemented on two different tributaries and to verify the importance of peak synchronisation. And lastly, Scenario 7 was created to observe the effect of all the proposed measures implemented throughout the catchment. The following section explains how the results were collected from the model.
3.2.8 Model runs and result data collection The Base Case Scenario and Scenarios 1 to 7 included a total of 5 runs per each FEH Design rain event plus the 2007 event. A total of 40 model runs were performed as described in the following table: Table 9. Modelling simulation table
Scenario - Base Case Run 1 2 3 4 5
Scenario - No. 4
Rain Event
Run
FEHWin-7hr_1:5 FEHWin-7hr_1:10 FEHWin-7hr_1:50 FEHWin-7hr_1:100 20-Jul-07
21 22 23 24 25
Scenario - No. 1 Run 6 7 8 9 10
11 12 13 14 15
Rain Event
Run
FEHWin-7hr_1:5 FEHWin-7hr_1:10 FEHWin-7hr_1:50 FEHWin-7hr_1:100 20-Jul-07
26 27 28 29 30
16 17 18 19 20
Rain Event FEHWin-7hr_1:5 FEHWin-7hr_1:10 FEHWin-7hr_1:50 FEHWin-7hr_1:100 20-Jul-07 Scenario - No. 6
Rain Event
Run
FEHWin-7hr_1:5 FEHWin-7hr_1:10 FEHWin-7hr_1:50 FEHWin-7hr_1:100 20-Jul-07
31 32 33 34 35
Scenario - No. 3 Run
FEHWin-7hr_1:5 FEHWin-7hr_1:10 FEHWin-7hr_1:50 FEHWin-7hr_1:100 20-Jul-07 Scenario - No. 5
Scenario - No. 2 Run
Rain Event
Rain Event FEHWin-7hr_1:5 FEHWin-7hr_1:10 FEHWin-7hr_1:50 FEHWin-7hr_1:100 20-Jul-07 Scenario - No. 7
Rain Event
Run
FEHWin-7hr_1:5 FEHWin-7hr_1:10 FEHWin-7hr_1:50 FEHWin-7hr_1:100 20-Jul-07
36 37 38 39 40
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Rain Event FEHWin-7hr_1:5 FEHWin-7hr_1:10 FEHWin-7hr_1:50 FEHWin-7hr_1:100 20-Jul-07
Each simulation took in average 30 minutes for the 7-hour duration events and around 60 minutes for the 20-hour duration events. The simulations were done only for the duration of the rain event, in order to frame the peak flow due to the peak of rainfall in each case. This was done with the purpose of saving computational time. However, as described in Chapter 5, longer simulations are recommended in order to observe the downfall trajectory of the hydrographs and formulate conclusions on this. A total of five model runs were done for every scenario and the results were gathered in the specified locations:
R1_DS - Catchment outlet
R1_US - Upstream of the Heath on Reach 1
R2_DS - Upstream of The Heath on Reach 2 Cu1 - Upstream of the culvert on Church Rd.
Figure 51. Result data collection in InfoWorks ICM
The results gathered in these locations were Flow and Water Level hydrographs in the form of time series data which was then plotted into several graphs using the statistical computing software R Studio. In the following chapter, these results are presented and discussed.
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Chapter 4
Results and Discussion
As it has been stated previously, a useful way in which the effects of NBMs can be observed is by collecting the hydrographs from the monitoring locations within the catchment, for each rainfall event, without the measures in place and plotting them against the resulting hydrographs for the same events in the same locations with the measures from each scenario included. This allows the experts to analyse how these measures affect the hydraulics and/or the hydrology of the catchment in any way. When observing the hydrographs for each scenario plotted against the Base Case, a basic rule may apply: if the correlation between the two hydrographs is high, then the measures from this particular scenario do not have any significant hydraulic/hydrological effects on the catchment; on the other hand, if the correlation between these two hydrographs is low, then the catchment’s response to this particular event under this specific scenario measure scheme is affected significantly. In the second case, the results may have to be analysed in order to quantify potential benefits in terms of flood reduction. This approach is useful when the benefits from the applied measures are analysed in terms of flood peak delay/reduction. However, other important benefits such as ecosystem restoration, sediment retention, water quality or life quality improvement amongst the community cannot be measured following this approach. If these additional impacts are to be quantified, then different methodologies should be applied for each case. The results obtained from the modelling phase of this research have been positive in the sense that the benefits of NFM on reducing floods (under certain circumstances) have been proven. As the graph below suggests, one of the main findings of this study is that by increasing the amount of measures and combining them amongst each other, the flow rates seem to decrease downstream near the flood sensitive area. On this plot, the Base Case, or no measure scenario, is plotted along with all the other scenarios and the results were taken at the bridge on Church Road for a 100-year return period event. As previous hypotheses suggested, by combining and increasing the number of measures, more reductions in the water flow are obtained. This pattern prevails for all the modelled events.
Figure 52. All flow hydrographs from the 100-year event at location Cu-1 from Scenarios 1 to 7
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4.1 Modelling Scenarios Results In this section, the resulting hydrographs have been analysed and attempts to formulate basic rules and equations which may be applied when analysing NFM measure schemes throughout a catchment. For practical reasons, only a portion of the total amount of plots obtained from the model have been included here. For the rest of the plots, see the Appendix section at the end of this document. In order to understand these results better it is important to keep in mind to which location the hydrographs correspond to. The table and image below may be of some assistance for the reader when analysing the results:
R1_DS - Catchment outlet
R1_US - Upstream of the Heath on Reach 1
R2_DS - Upstream of The Heath on Reach 2 Cu1 - Upstream of the culvert on Church Rd.
Figure 53. Result-gathering locations
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Scenario No.1 – Woody Dams and Riparian Vegetation In the first scenario, the roughness from the riparian zones along both of the tributary rivers has been increased from 0.04 to 0.07 (Manning’s n), resembling the existence of mature and dense vegetation. These ‘enhanced’ riparian zones have been coupled with the proposed 70 woody dams with a porosity of 0.25 spread out along both river reaches as well. As it was foreseen, these measures had mainly a delaying effect on the flow peaks, yet the woody dams have been estimated to partially store approximately 5,000 m3. In other words, the LWD are only capable of retaining this volume of water for a certain period of time before it is released naturally.
Figure 54. Scenario 1 - Hydrographs collected at Cu1 and R1_DS for a 1:10 year event
As Figure 54 reflects, there is a slight delay of about 10 minutes, plus a very low decrease in the flow peak at location Cu1. The small delay in the peak may be caused by the increase in the roughness due to the riparian vegetation. On the other hand, the change in the rising limb and slight decrease, are believed to be caused by the presence of the 70 LWD, which cause the water to spill from the channel into the floodplain, and into the flood storage area. This experiment shows that the woody dams can be useful for the purpose of floodplain connectivity inside the catchment. This same effect is more notorious downstream near the catchment outlet at location R1_DS, where the effect of the woody dams cause a ~1 m3/s decrease in the flow. However, the water levels stay roughly the same in both cases. 77
Figure 55. Scenario 1 - Hydrographs collected at Cu1 and R1_DS for a 1:100 year event
On the other hand, the 100-year return period event for this scenario shows different results. There was a small reduction in the peak (0.20 m3/s) but no delay what so ever. As stated before, the small reductions in the peak flows can be the result of the woody dams, by diverting water from the channel into the floodplain, and eventually into natural ponding areas throughout the catchment (in the case of Reach 2, into the Offline Storage Area). Overall, the water levels in all cases remained roughly the same for the location of interest (Cu1), which means flood would not be reduced in any way by installing woody dams and planting riparian vegetation along the river channels only. From this, it can be said the impact of these measures on reducing floods is very low, except for the cases where the water is forced by the woody dams into the floodplain and into storage or ponding areas. Some benefits of applying these measures individually are mainly environmental, meaning that they can be useful in floodplain restoration, they may increase the channel-floodplain interaction, ecosystem and water quality improvement, etc. Depending on the porosity of the woody dams and the stage of growth and density of the riparian vegetation, different results might be observed, therefore, more research is recommended regarding these parameters. See Chapter 5 of Conclusions and Recommendations for more details.
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Scenario 2 – LWD, Riparian Vegetation, Hedgerows and Earth Bunds This scenario contains the same measures described in Scenario 1, with the addition of existing (and enhanced) 2m-high hedges with a porosity of 0.30 and 1m-high earth bunds placed strategically in some field edges throughout the catchment. The results for this scenario were found to be rather positive compared to the previous ones.
Figure 56. Scenario 2 - Hydrographs collected at Cu1 and R1_DS for a 1:10 year event
As the graphs suggest, by implementing this particular combination of measures the floods in The Heath may be reduced for events with return periods of up to 10 years. The great reduction in the flow peaks is believed to be caused by the large amounts of runoff from the fields being trapped by the raised earth bunds in these strategic locations. Moreover, the results obtained at the catchment’s outfall show a significant reduction as well. It is to be noted on the Water-level hydrograph on the bottom right corner, that the water levels remain the same even when the flows suffer significant reductions. This was found to occur in every model run, and is the result of measuring the water level in the channel, when most of the water flows through the floodplain as it can be seen in Figure 57 on the next page. Furthermore, extent of future research done in this catchment should include the flood hazard assessment of the properties shown to be flooded downstream near River Evenlode. 79
Main channel
Monitoring location: R1_DS
Figure 57. Catchment outlet draining through the floodplain
There was another particularity found in the results of this modelling scenario which has to do with the synchronization of the flow peaks from both tributaries (R1 and R2). This effect is most notorious when the catchment experiences the 1:100 year design storm, where the peak flows from both reaches were delayed by approximately 40 minutes, and suffered significant reductions as well. As an outcome, the total peak flow at the catchment’s outlet was reduced by nearly 5 m3/s. This phenomenon may serve as proof for the hypothesis regarding peak synchronization presented on Section 2.6 after the existing literature on NFM was analysed.
Figure 58. Scenario 2 - Hydrographs collected at R1_US and R1_DS for the 1:100 year event
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As stated previously, during this particular case, there were significant changes registered by the monitoring locations on both reaches. Up to 40 minute delays and nearly 1 m3/s peak flow reductions were achieved by these specific combination of measures. It is believed that the measures which affect the hydrograph in a greater way are the earth bund placed across the catchment on both reaches. The breaks in the hydrograph trajectory at approximately time step 05:00 are believed to be caused by the storage capacity of the most crucial earth bunds being reached and therefore overtopped. Increasing the number of field corner bunds in strategic locations across the catchment would lead to a greater reduction of the peak flows, and therefore a potential reduction of the floods could occur. These changes can be observed on the result graph below.
Figure 59. Scenario 2 - Hydrographs collected at R1_US and R2_DS for a 1:100 year event
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Scenario 3 – Offline Storage Area The storage area designed for this scenario is believed to store up to 30,000 m3 which can potentially reduce floods downstream near The Heath. The results of the model runs show that, indeed, this is possible for events with return periods of up to 10 years, as shown in the result graph below. The effect of the Offline Storage Area can be observed on Figure 60. There is a significant reduction of the flow and a slight reduction of the water levels at the monitoring location (upstream of The Heath on Reach 2) due to the diversion of water into the storage area.
Figure 60. Scenario 3 - Hydrographs collected at Cu1 and R2_DS for a 1:10 year event
However, floods cannot be prevented for larger events such as the 1:50 or 1:100 with this only measure in place. While approximately 28,000 m3 from Reach 2 are being stored for the particular case of the 1:100 event, there are still other 30,000 m3 of water coming in from Reach 1.
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Figure 61. Scenario 3 - Hydrographs collected at Cu1, R2_DS and R1_US for the 1:100 event
The total volume of water stored by the Offline Storage Area is approximately 30,000 m3, which at the same time is believed to be directly proportional to the reduced volumes shown in the hydrograph (~27,000 m3). The water volume retained upstream of the storage feature might account for the missing ~3,000 m3 as shown in the image below.
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~3,000 m3
~27,000 m3
Figure 62. Storage Area at its maximum capacity (2007 event)
As these results suggest, other measures should be considered as part of a NFM measure scheme in order to reduce floods downstream. The overland flow created by the water spilling out of the storage area can be retained by placing earth bunds or retention ponds, changing the land use of the field downstream of the storage area from agricultural land to wet lands or marsh, etc. However, these measures should be discussed with the landowners, and some compensation mechanisms should exist, which would be able to quantify the benefits and feasibility of retaining these flood volumes in this area against the cost of transforming this plot of land into a natural water retention area.
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Scenario 4 – Offline Storage Area, Earth Bunds and Sediment Retention Ponds This modelling scenario includes all the measures which increase the storage capacity within the catchment directly. The total stored volume by the measures in this scenario is estimated in 53,000 m3, which is subdivided in ~30,000 m3 of offline storage, ~3,000 m3 stored in retention ponds, and ~20,000 m3 stored in field corner bunds. Floods have been successfully prevented for design storms with return periods of up to 50 years, as it can be seen in the graph below. However, during the 1:100 event, the water levels at Cu1 reach the flood threshold.
Figure 63. Scenario 4 - Hydrographs collected at Cu1 and R1_DS for the 1:10 year event
One of the main impacts of raising 1-metre earth bunds along the lower ends of certain fields across the catchment seems to be a particularly effective way of storing water upstream. These earth bunds create a kind of ‘dry pond’, meaning that they retain water only whenever large rain events hit and the soil is nearly saturated. This effect is visible in all cases where earth bunds were placed throughout the catchment, as the following image depicts.
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Figure 64. Earth bunds retaining water during a 1:10 year event
As mentioned before, during the 1:100 event the flood threshold is reached by the water levels close to The Heath. This suggests that more natural storage is needed upstream in order to retain the excess runoff caused by this design storm event.
Figure 65. Scenario 4 - Hydrographs collected at Cu1 and R1_DS for the 1:100 year event
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The flow peaks are lowered significantly on both Reaches 1 & 2 for all the events except the 2007 one. This is due to the excessive volume of rainfall caused by this particular event. Storage features should be able to cope with this massive volume of rainfall. However, for lower duration and intensity rainfall, these measure seem to be effective in reducing floods. In theory, by increasing the number of natural storage features upstream should reduce the flow hydrographs downstream even more. The water levels also drop by significant amounts during this scenario, except at the catchment outlet (due to the phenomenon explained on page 79)
Figure 66. Scenario 4 - Hydrographs collected at R1_US and R2_DS for the 1:100 year event
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Scenario 5 – All measures on Reach 2 (none elsewhere) This scenario was aimed at observing the effects of peak synchronization and how it can be avoided using NFM a scheme in order to maintain the water levels below the flood threshold. The measures implemented here include Woody Dams, Riparian Vegetation, Earth Bunds, Offline Storage, and Sediment Traps, upstream of The Heath on Reach 2. The results obtained at all locations inside the catchment, except R1_DS (Reach 1), show significant reductions on peak flows for all storm events. The flood threshold by The Heath was not reached for events 1:5 and 1:10, yet during stronger events such as 1:50, 1:100 and the 20-July-2007 event, some properties were subject to flooding.
Figure 67. Scenario 5 - Hydrographs collected at Cu1, R1_US and R2_DS for a 1:10 year event
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As expected, the result hydrographs show a large reduction of the flow due to all the measures implemented on this river reach. It is also the interaction between measures which may be causing the large reduction of the peak flow in this case. For instance, woody dams slow and partially retain the flow, forcing it into the riparian zone which causes the flow to slow down even more due to the increased roughness; this at the same time causes the water to spill into the flood plain and into natural storage or ‘ponding’ areas like the ones created by the earth bunds or in this case the Offline Storage Area. Conversely, the results from the other river reach (R1_US) which does not contain any NFM measures in this scenario, show that the flow is roughly the same as the Base Case Scenario. There is a slight change in the water levels, and this might be caused by the fact that since water from the other reach is being held upstream, there is less backing up of water near the culvert and therefore, more space for the water to flow. Even though the measures implemented on Reach 2 have a big effect on the flow hydrographs downstream, they are still not enough to prevent flooding at The Heath for events larger than the 1:10 year one, as shown in the graphs below taken from a 100 year return period event at the bridge in Church Road. Therefore, this particular combination of measures implemented in this river reach is believed not to be effective when flood reduction at Cu1 is desired for events stronger or equally strong to the 1:50 year one. However, significant peak reductions are achieved on both locations downstream (Cu1 and R1_DS).
Figure 68. Scenario 5 - Hydrographs collected at Cu1 for a 1:100 year event
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Scenario 6 – All measures on Reach 1 (none elsewhere) In order to compare results of applying measures on only one of the tributaries with the previous scenario, Scenario 6 shows the opposite effect. Here, measures have been implemented on Reach 1 and no other measures elsewhere, as opposed to the previous scenario. The result hydrographs show larger reductions in the flow and water levels at location R1_US, and little or no changes on hydrographs obtained from location R2_DS, as expected.
Figure 69. Scenario 6 - Hydrographs collected at Cu1, R1_US and R2_DS for the 1:10 year event
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In this particular reach, there are a number of earth bunds creating additional offline storage, which may account for the ‘flattening’ effect on the peak in the flow hydrograph at R1_US. As seen in the flow hydrograph at R1_US, this specific set of measures accounts for the ~27,000 m3 reduction in the discharge from Reach 1, which is enough to prevent floods from rainfall events of up to 10-year return period. Despite the valuable contribution of these upstream measures towards reducing flood volumes downstream, they are still not able to avoid flooding for events such as 1:50, 1:100 or 20-Jul-2007. The result graph below depict this effect for the 100-year return period rainfall event. This suggests that the potential of these measures to store water upstream, reduce and delay flood peaks exists, yet in order to prevent the floods, more measures would have to be implemented in other parts of the catchment as well. Furthermore, a significant reduction in the peak flow at the catchment outlet (R1_DS) has been achieved by implementing these measures on Reach 1.
Figure 70. Scenario 6 - Hydrographs collected at Cu1, and R2_DS for the 1:10 year event
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Scenario 7 – All NFM measures in place Finally, Scenario 7 proved that by implementing all the proposed NFM interventions together, the chances of flooding downstream are significantly reduced. This is mainly caused due to the interaction between them and the overall increase in the storage capacity of the catchment upstream of the culvert. By implementing all the proposed measures throughout the catchment, floods caused by rainfall events of up to a 100-year return period can be potentially prevented at location Cu1. This is mainly the cause of almost 70,000 m3 of additional storage provided by the Offline Storage Area (~30,000 m3), the Earth Bunds (~28,000 m3), Sediment Ponds (~3,000 m3) and the Woody Dams (~5,000 m3 of partial storage); of which approximately 60,000 m3 have been effectively used. There is also a large reduction of the peak flow at the catchment outfall, which suggests that by implementing these upstream catchment measures throughout this and other sub-catchments, tributary river discharges can be reduced during storm events, bringing some benefits further downstream on the Evenlode.
Figure 71. Scenario 7 - Hydrograph collected at Cu1 and R1_DS for a 1:100 year event
On the other hand, larger events such as the 2007 one, wouldn’t have been prevented by implementing these measures. This is believed to be true because the volume of water exceeded the storage capacity provided by the NFM landscape features. Furthermore, there is a danger of increasing flood hazard when the storage features are full before the peak of the rainfall hits and the water starts spilling out, as depicted in Figure 71. In this particular case, the Offline Storage Area 92
and the earth bunds are filled with runoff from the heavy rainfall and the duration of the event is way too long for them to cope with the large volumes of water.
Maximum t
Figure 72. Scenario 7 - Hydrographs collected at Cu1 and R2_DS for the 2007 event
Figure 73. Measures from Scenario 7 acting in combination to reduce floods downstream during a 1:50 year event
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4.2 Assessing individual NFM measures After gathering and observing the results from the 7 modelling scenarios, other questions emerged regarding the effects of the measures individually. In order to assess the effects of each measure individually, it was necessary to create additional scenarios for each of them and plot the resulting hydrographs taken from the same locations against the Base Case (no measures) scenario. Such scenarios can be observed in the following table:
Table 10. Table of individual measure scenario
Scenario Base Case
Implemented Measures Catchment with no measures implemented
8
Woody Dams
9
Riparian Vegetation
10
Hedgerows
11
Field Corner (earth) Bunds
12
Sediment (retention) Ponds
Scenario 8 – Woody Dams Woody dams were found to cause little or no effects on flow hydrographs, except for when the water is pushed by the LWD into the floodplain and into natural storage or ponding areas. More research should be performed on the correct values for porosity of the woody dams in order to observe their effects properly. In some cases the flood hazard was increased, as the one shown below, and this is believed to be caused by the storage and release of water with slightly higher kinetic energy.
Figure 74. Scenario 8 - Hydrographs collected at Cu 1 for the 1:10 year event
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Scenario 9 – Riparian Vegetation The results for this scenario were as expected. Slight delays and small reductions due to the increased roughness along the channels. Depending on the type, age and density of the vegetation, these effects is believed to increase. More work is advised on assessing this roughness values in a precise way by performing on-site measurements or physical modelling. Other benefits from riparian vegetation which do not affect floods directly and have not been quantified include: floodplain connectivity, ecosystem and water quality improvement, bed sediment retention, etc.
Figure 75. Scenario 9 - Hydrographs collected at Cu1 for the 1:10 year event
Scenario 10 – Hedgerows Hedgerows were found not to have any effects on the hydrographs. This might be due to the approach chosen for their inclusion in the hydraulic model. Further modelling test should include the totality of the existing hedges upstream of The Heath, and sensitivity analyses should be performed to observe changes on the hydrographs when adjusting their porosity. Details like the location, base soil composition, type and vertical density of the hedges should be taken into account.
Figure 76. Scenario 10 - Hydrographs collected at location Cu1 for the 1:10 year event
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Scenario 11 – Field Corner (Earth) Bunds The 1-metre high earth bunds were found to be the most effective of the analysed measures in terms of peak flow reductions. In some cases, such as the 1:10 year event, there were reductions of up to 25% for location Cu1. In an ideal world, every farm field should have a raised bund on their lowest spot in order to intersect the runoff flow path and retain it partially. However this needs to be discussed with the landowners first, because it might bring damage to their crops in the times of heavy rainfall.
Figure 77. Scenario 11 - Hydrographs collected at Cu1 for a 1:10 year event
Scenario 12 – Sediment (retention) Ponds Sediment retention ponds were found to reduce slightly the chances of flooding downstream at location Cu1. The slight reduction is believed to be caused by the small volumes of water they retain and their locations within the catchment. This effect could be maximised if several landowners decided to sacrifice a small portion of their land and dedicate it to sediment retention by excavating these ponds in the ground and installing an outlet mechanism.
Figure 78. Scenario 12 - Hydrographs collected at Cu1 for a 1:10 year event
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Conclusions and Recommendations
Chapter 5
It can be said that Natural Flood Management is still in its infancy. Ongoing projects and research aim to pioneer within a branch of flood risk management which has an enormous potential to tackle the current effects of Climate Change and unplanned urban development in a more sustainable way. After more than 6 months of discussions, literature compilation and analysis, modelling experiments, and result analyses, conclusions from this research have been drawn. These conclusions are in line with the original research questions which arose during its early stages. The reader is invited to formulate its own conclusions from the results obtained throughout the course of this MSc Thesis.
5.1 The effectiveness of NBMs in terms of peak flow reduction While quantifying the benefits of Nature Based Measures is a difficult task to perform, this research has been able to produce some favourable outcome which can be used to assess these measures in a proper way. If the reduction of peak flow is desired in order to reduce floods downstream, then the most effective way of doing so is implementing all the selected measures in combination. However, in order to compare which measures are more effective for this purpose, the results obtained from Scenarios 8 to 12 have been used. The following graph shows how the different types of measures respond to storm events with different annual exceedance probabilities. It is to be noted here that negative peak flow reduction means an increase in the peak flow itself. Peak flow reductions at Cu1
30%
Peak flow reductions at R1_DS
20%
25% Peak Flow Reduction (%)
Peak Flow Reduction (%)
15% 20% 15% 10% 5%
10%
5%
0%
0% 0% -5%
Woody Dams
5%
10%
15%
0%
20%
10%
15%
20%
AEP (%)
AEP (%) Riparian Vegetation
5%
-5% Hedgerows
Earth Bunds
Figure 79. Modelled peak flow reductions caused by each NBM
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Sediment Ponds
As opposed to the original hypotheses, Woody Dams, Riparian Vegetation and Hedgerows seem to have a negative effect for events with higher probabilities of occurring such as the 1:5 and the 1:10. One reason for these negative results could be their effect on peak synchronization, yet the reason for this is not perfectly clear and more test should be performed for these cases. Conversely, these same measures seem to perform better under less frequent (and more intense) rain events like the 1:50 or the 1:100. This interesting phenomenon may have to be analysed in a more thorough way in order to obtain the best conclusion out of it. On the other hand, measures which affect the storage capacity of the catchment in a more direct way seem to perform better under more frequent (and less intense) events such as the 1:5 and the 1:10. In other words, they cause higher peak reductions when the catchment experiences storm events with low or mild intensities. The reason for this comes down to storage volumes. When the maximum storage volume of these features is reached and they start spilling out the surplus water, the runoff increases, hence the increase in the hydrographs. Peak de-synchronization is yet another factor which could explain the positive results of implementing these particular measures. A similar result is observed when comparing the original 7 modelling scenarios, which include combinations of several measures, amongst each other. As it was expected and stated in the form of hypothesis on Section 2.6 - Analysis from Literature Review, by applying a combination of different NFM interventions throughout the catchment, the peak flows can be reduced and the probabilities of flooding downstream can be reduced. As seen in Figure 79 below, the most efficient scenarios were those which created additional storage upstream: Scenario 4 – Offline Storage, Earth Bunds and Sediment Ponds; and Scenario 7 – All the measures implemented throughout the entire sub catchment. Note here, that the difference between these two scenarios is quite significant, which may prove that the other measures (Woody Dams, Riparian Vegetation and Hedges) account for a ~10% peak flow reduction as well. This adds to the reasons why NBMs should be implemented as a combined set of measures complementing each other.
Peak flow reductions at R1_DS 30%
50%
25% Peak Flow Reduction (%)
Peak Flow Reduction (%)
Peak flow reductions at Cu1 60%
40% 30% 20% 10%
20%
Scenario 2 Scenario 3
15% Scenario 4 Scenario 5
10%
Scenario 6
5%
0% 0% -10%
Scenario 1
5%
10%
15%
20%
Scenario 7
0% 0%
5%
10%
15%
20%
AEP (%)
AEP (%)
Figure 80. Modelled peak flow reductions caused by each modelling scenario
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Depending on the location where the results are collected, there seem to be different effects. As it has been expected, the effects of the NFM interventions seem to be less downstream near the catchment outlet. The peak flow reductions further downstream will depend on the increase in catchment area for each ‘pour point’ taken and the number of other tributaries joining the main channel. Since there were no NFM interventions done on other tributaries, the flood reducing potentials seem to be lower. However, even more peak flow reductions are expected when the same type of measures are placed on other parts of the catchment as well. Peak synchronization would also cause peak flows to decrease (or increase, in case they coincide with higher peaks). These reductions on the peak flows were computed using the following equation: 𝑄𝑄𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵 − 𝑄𝑄𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑆𝑛𝑛 � ∗ 100 𝑃𝑃𝑃𝑃𝑃𝑃𝑃𝑃 𝑓𝑓𝑓𝑓𝑓𝑓𝑓𝑓 𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟 = � 𝑄𝑄𝐵𝐵𝐵𝐵𝐵𝐵𝐵𝐵
The first conclusion from these analyses states that the most effective measures of the selected NBMs for this particular case study, are the ones which increase the storage capacity of the catchment directly. This effectiveness has been only measured in terms of the reduction of floods caused by overland flow and not taking into account other environmental benefits or the effect of infiltration and groundwater. Therefore, if these other benefits are also desired, combining these measures with others such as hedges, woody dams or riparian vegetation may be more efficient. The effectiveness of these measures is also relative to the location where the results are analysed. The further downstream from the interventions these measurements are taken, the less benefits will be encountered.
5.2 Factors affecting the performance of NBMs in the model There are, of course, a number of elements and processes which may affect the results obtained and have not been accounted for in this research. Some of these factors are described below for each measure.
Woody Dams The effects of woody dams may have on flow and water level hydrographs downstream may vary depending on: •
Location within the stream network. A more thorough study should be able to identify the specific benefits of woody dams depending on where they are located. For instance, woody dams located close to other potential storage locations in the floodplain were found to be more effective in reducing discharges downstream. The slope of the river reach in which they are implemented will also affect the flow velocities and the way in which they retain the water.
•
Location within the channel. Depending on how they are placed within the channel, they might be able to retain more (or less) volumes of water. In some case studies these dams have been placed across the channel and surrounding floodplain as well in order to retain the
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water spilling out from the channel itself. Other cases such as the woody dams placed by the EA in the Littlestock-Brook, they only rise up to 0,50 m above the channel bed. •
Layout and type of material. The type of materials used for the construction of these dams will affect the lifespan of the dam itself. The way in which they are fixed to the ground will define the reliability on these features to be performing without being washed away during high flow seasons.
•
Porosity. The porosity of the dams should be assessed by performing field measurements or physical modelling. This variable will be affected by the way in which the materials used to build the dam are laid out. If there are many spaces in between logs of woody debris the porosity will be high, in any other case, the porosity will decrease.
Riparian Vegetation The way in which trees and other plant species planted along the channels affect flow velocities will depend on the following: •
Age and type of vegetation. The stage of growth in which these plant species are at the time when the specific storm event hits will affect the response they have on the peak flows. In other words, more dense and mature riparian vegetation will increase the roughness along the channel, which is proven to delay the peak flows slightly.
•
Extension. If the riparian zone for a particular channel is extended into the floodplain, the increased roughness may affect also the water spilling out from the channel or the overland flow running parallel to it.
Hedgerows Significant reductions of total cumulative runoff were reported by Strosser et al., 2014 when these were placed across runoff paths in their case study in France. This effect was not observed when including hedgerows in the Littlestock-Brook model. As explained in section 2.6.1 the modelled hedgerows were represented as porous walls with a fixed porosity, yet the chosen porosity values may not be the correct ones. The amount and locations of the chosen hedges should also be revised. Another key aspect to consider here, is that the results from this modelling study were collected in the same location for all the measures. It may be the case that the way in which results were collected is not the ideal one for analysing the effects of this particular measure. Hedgerows should be analysed more thoroughly with field measurements and/or physical modelling. These features, which are commonly found within the British and Continental Europe landscape, are believed to have the potential of affecting runoff in rural catchments. Some of the factors which should be taken into account are the following: •
Base structure. The way in which these features affect runoff will depend on how they are planted on the landscape. If they are planted over small lumps (bunds) of soil, or the
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vegetated surface goes all the way down to the ground they might have a higher potential to retain overland flow. •
Porosity. Again, the density of the vegetated surface will define the way these features affect the flow, which at the same time depends on the age and type of plant species. Another crucial aspect here, is the fact that this porosity value will change depending on the season. During the winter, most of the hedges lose their leaves, therefore, a higher porosity should be considered.
•
Location and orientation. The hedges which are found to be most effective are the ones which are placed on field edges in a perpendicular way to the flow direction.
Offline Storage It is still debated whether or not these measures are to be included within the realm of NFM. This is mainly due to the fact that large volume storage areas should include more highly engineered designs and mechanisms due to dam safety. However, in the UK, the Dams and Reservoirs Act states that storage areas of up to 10,000 m3 can be built using ‘soft engineering’ techniques, such as placing 1m high earth bunds around a low lying area. Some of the factors affecting these measures are the following: •
Storage volume. This will be affected mainly by the height of the earth bunds surrounding them.
•
Spillway height. In case the storage areas are designed with inlet and outlet spillways, this will affect the storage volume and the stage of the storm event at which they fill up. Whenever a storage area is found to reach its maximum storage capacity before the peak of the rainfall event, then the person in charge of designing it might want to consider raising the inlets. This of course would have to be assessed using the proper tools such as hydraulic modelling software.
•
Location within the catchment. Their location within the catchment will affect their performance in a significant way. In other words, these storage features should be placed close enough to the source of flooding, yet far away from the area under flood hazard (in case of a breach).
Field Corner (earth) Bunds These measures, which were proven to be highly effective on reducing river flows, may have their performance affected by some of the elements described below: •
Length and Height. This will affect directly the volume of water the can retain. Ideally, they should be able to stretch along the whole low end of the field in which they are located. If this is not possible, their location should be optimised by observing the runoff paths. 101
•
Location. As stated before, they should be located at the lower end of the fields and in areas where the overland flow is greater. In some cases, placing them along a main watercourse in order to intercept the water that spills out of it during high flows, may be a good way of using them.
•
Interaction with other measures. These features were found to perform better when they are combined with other measures. For instance, woody dams in the channel may cause the water to spill into these ponding areas. Or they can also be placed to intercept surplus water spilling out from a larger storage area upstream.
Sediment (retention) Ponds These measures provide additional storage upstream and also bring a number of other benefits related to water and environmental quality due to the retention of sediment and surface water pollutants. Some factors which may affect the way in which they store the runoff were identified and described below: •
Volume. The area and depth of the excavated soil will define the storage volume directly.
•
Location. Their location within the catchment seems to be another important element. They should be placed in locations where they prevent as much runoff as possible from going into main watercourses ‘untreated’ (carrying sediment, organic matter and other pollutants).
•
Terrain slope. The slope of the piece of land in which they are placed will define how much water gets into them without spilling out or without having to dig huge amounts of land. In places where high slopes prevail, the designer might want to consider building earth bunds around the selected area instead.
Based on the modelling study performed, the preliminary hypothesis about the hydraulic and hydrological parameters affected by the NFM scheme (Described on section 2.6) was revised and the conclusions about these processes can be observed in the graph below. It is to be noted here that infiltration was not considered during the modelling process because the initial soil conditions were assumed as fully saturated, yet it is believed to be related to the ‘ponding’ or accumulation of runoff in the low areas of the catchment or as an outcome from Field Corner Bunds or Storage Areas. Infiltration can also be improved by the diversion of the flow from the channel into the floodplain caused by some of the analysed measures.
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Degree of enhancement
Figure 81. Evaluation of the NFM measures from the obtained results
10 9 8 7 6 5 4 3 2 1 0 Large woody Offline storage Hedgerows & debris dams ponds Buffer strips
Riparian vegetation
Sediment traps
Dry / wet retention ponds
Enhanced Hydraulic & Hydrological Parameters Storage Capacity
Roughness
Infiltration
Runoff
(Scale: 0 = No effect; 10 = High effect)
5.3 Modelling NFM measures One of the main findings of this research is that by the use of 2D hydrodynamic modelling, runoff patterns can be identified and the NBMs can be placed in key locations in order to achieve better results. However, the way in which these measures respond to different storm events will also depend on how these measures are included in the models. In further modelling studies, the modeller might find it convenient to include other variables which were not considered in this study such as evapotranspiration, infiltration and their effect on the groundwater table and overall river discharges. For the sole purpose of observing changes in the river discharges due to direct runoff from specific storm events, the NBMs should be analysed as physical obstructions using 2D overland flow hydraulic models. In other words, representing them by either porous elements which slow the flow retaining it partially, or by physical changes done directly on the mesh. When porous elements are to be included in a model, the porosity values for each measures should be assessed empirically or by field measurements. However, achieving the desired degree of porosity would be constrained by the fact that these measures work with natural elements which in time may decay, grow, or suffer seasonal changes. On the other hand, measures such as woodland and riparian vegetation are more related to the resistance that the runoff experiences when flowing through these surfaces. In other words, the surface roughness, which in hydraulic terms can be expressed as Manning’s n. The values for this roughness coefficient have been assessed by Vent Te Chow (1959) and are still commonly used in hydraulic modelling. However, these parameters are mere approximations which may change from location to location and, therefore, a detailed analysis of these values should be done before defining them in any model.
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5.4 Quantitative assessment of NFM In order to assess the effects of NFM on rural catchments on a quantitative way, some basic principles may be applied. Firstly, hydrological principles such as the rainfall-runoff relationship may be found useful for this purpose. Using concepts such as effective rainfall, which is the amount of rainfall that is neither retained on the land nor infiltrated into the soil and eventually reaches the channel, turning into direct runoff, can be a simple way of quantifying such benefits. The Natural Resources Conservation Service (NRCS) of the United States of America has developed a simple and useful method for estimating direct runoff from rainfall in ungauged agricultural watersheds. (Mockus and Hjelmfelt 2004) This method, originally developed by Mockus et al. (1956), which considers input and output volumes based on the Conservation of Mass Principle, states that: for > 𝐼𝐼𝐼𝐼
(𝑃𝑃−𝐼𝐼 )2
→ 𝑄𝑄 = (𝑃𝑃−𝐼𝐼 𝑎𝑎)+𝑆𝑆 𝑎𝑎
;
and for 𝑃𝑃 ≤ 𝐼𝐼𝑎𝑎 → 𝑄𝑄 = 0
where:
Q = depth of direct runoff (mm) P = depth of rainfall (mm) Ia = initial abstraction (mm), or losses such as infiltration, interception and evapotranspiration during the early stages of the storm S = maximum potential retention (mm), which depends upon land cover and other soil properties. This last variable S, or the maximum potential retention can be directly affected by NFM, when storage volumes are improved due to earth bunds, sediment ponds, or other measures. By increasing the value of maximum potential retention, less direct runoff is expected and, therefore, less river discharges. This effect should be reflected when applying the rainfall and runoff depths to the area of the catchment under NFM scheme and the duration of the storm event. As an example of this, the modelled 100-year event with duration 7 hours left a total of 43 mm in rainfall depth over the 16 km2 catchment. The portion of the catchment under analysis an estimated area of 6.7 km2, and had an original retention potential S of 15,000 m3. After all the NFM measures were put in place (Scenario 7), this potential was increased to 70,000 m3. Initial abstractions were not taken into account for this particular case, but the runoff coefficient used was 0.40. Then, applying the direct runoff formula described previously, the reduction in direct runoff can be computed as follows: (𝑃𝑃−𝐼𝐼 )2
(0.4∗𝑃𝑃)2
𝑄𝑄1 = (𝑃𝑃−𝐼𝐼 𝑎𝑎)+𝑆𝑆 = (0.4∗𝑃𝑃)+𝑆𝑆 = 𝑎𝑎
1
(0.4∗43𝑚𝑚𝑚𝑚)2
15,000𝑚𝑚3 (0.4∗43𝑚𝑚𝑚𝑚)+� ∗1000� 6.7𝑘𝑘𝑘𝑘2
=
295.84 𝑚𝑚𝑚𝑚2
17.2𝑚𝑚𝑚𝑚 + 2.24𝑚𝑚𝑚𝑚
= 15.22 𝑚𝑚𝑚𝑚
This direct runoff depth expressed in terms of total volume of runoff produced by the analysed portion of the catchment during this 7-hour duration event is: 𝑉𝑉1 = 15.22𝑚𝑚𝑚𝑚 ∗ 6.7𝑘𝑘𝑘𝑘2 = 𝟏𝟏𝟏𝟏𝟏𝟏, 𝟗𝟗𝟕𝟕𝟒𝟒 𝒎𝒎𝟑𝟑
104
Now, considering the increase in the potential retention from 15,000 m3 to 70,000 m3, the results are as follows: (𝑃𝑃−𝐼𝐼 )2
(0.4∗𝑃𝑃)2
𝑄𝑄2 = (𝑃𝑃−𝐼𝐼 𝑎𝑎)+𝑆𝑆 = (0.4∗𝑃𝑃)+𝑆𝑆 = 𝑎𝑎
2
(0.4∗43𝑚𝑚𝑚𝑚)2
70,000𝑚𝑚3 (0.4∗43𝑚𝑚𝑚𝑚)+� ∗1000� 6.7𝑘𝑘𝑘𝑘2
=
295.84 𝑚𝑚𝑚𝑚2
17.2𝑚𝑚𝑚𝑚 + 10.45𝑚𝑚𝑚𝑚
= 10.70 𝑚𝑚𝑚𝑚
Then, the total volume of runoff produced by this catchment after NFM in terms of volume: 𝑉𝑉2 = 10.70𝑚𝑚𝑚𝑚 ∗ 6.7𝑘𝑘𝑘𝑘2 = 𝟕𝟕𝟕𝟕, 𝟔𝟔𝟔𝟔𝟔𝟔 𝒎𝒎𝟑𝟑 And finally the effects of the implemented NBMs can be observed in terms of direct runoff volume: 𝑁𝑁𝑁𝑁𝑁𝑁 𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑 𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟 𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟 = 𝑉𝑉1 − 𝑉𝑉2 = 𝟑𝟑𝟑𝟑, 𝟎𝟎𝟎𝟎𝟎𝟎 𝒎𝒎𝟑𝟑 This total direct runoff volume reduction is a 30%, which can be then analysed for the total catchment area. If the total area of the catchment is 16 km2, and by applying a NFM measure scheme on 6.7 km2 (40%) of the catchment, this 30% reduction of direct runoff can be achieved, then the same rules may be applied on other parts of the Littlestock-Brook or the Evenlode as well. These simple calculations provide tangible results which decision makers can find useful when analysing the Natural Flood Management from a hydraulic point of view. However, many other aspects should be considered such as the environmental benefits which they are believed to deliver.
5.5 Further research and modelling This research can and should be extended in order to continue the development of new parameters which will in time allow water professionals involved with NFM to assess the potential benefits from these type of measures on flood reduction. Further research and modelling studies undertaken in the future should consider the following: •
Including existing hedgerows, tree belts and wooded areas on 2D overland flow models in order to observe how these features affect the accuracy of hydrodynamic models and flow paths behaviour when these features are considered. Other approaches such as increased roughness and infiltration zones could be tested in order to compare results with the ones obtained by modelling them as vertical porous elements.
•
Run the model using longer storm durations, and return periods (e.g. 26-hr, 1:200, 1:500) in order to observe how these measures perform under stronger events. The Climate Change scenario should also be considered where further research is to be undertaken, due to its effect on storm frequency and intensities.
•
Increase the simulation time (e.g. 7hr to 12hr, 20hr to 24hr) in order to observe the decrease in of the flow peaks in time. This research only covered the effect of NBMs on hydrographs during the duration of the storm events (mainly for computational time saving), yet 105
observing the decrease on these hydrograph in time or the effect of subsequent events would present interesting results. •
Apply rainfall to sub catchments, rather than applying it directly on the entire mesh zone. This would be useful when analysing larger catchments, where rain events do not cover the whole extension of the watershed.
•
Analyse the losses due to infiltration (e.g. Horton infiltration scheme). Most of the measures influence the rate at which water infiltrates into the soil. However, this would have an effect on the ground water table, which would then have to be included as well.
•
It is important to bear in mind that NBM affect hydrological characteristics within the catchment. Therefore, future research should consider losses due to infiltration, interception and evapotranspiration, as well as including the groundwater table rise.
5.6 Displaying Results The results from this type of research should be presented in a way that they can be easily comprehended by the user. Decision makers are often more involved in the politics and management of water rather than on technical concerns, which is why user-friendly results are useful. This MSc Thesis includes an example of a useful way of presenting these results (See Appendix 3). The map contains the flood extent with corresponding water depths for the 1:100 FEH Design Storm, along with all the measures that were implemented in this particular case. On the bottom left corner the corresponding hydrographs extracted from the model for each monitoring location can also be observed. These hydrographs contain the results of the Base Case (no measure) Scenario and the Scenario 7 (All measures in place), which may be useful for drawing conclusions and showing that in fact, Natural Flood Management has the potential of delivering multiple benefits, including flood hazard reduction.
106
Appendices Appendix 1
NFM Approach
Upstream Floodplain Urban areas
3
Relative weight of importance
High Positive 2
Environment 85%
75%
Social
100%
Cost & Maintenance
Evaluation Criteria Flood Attenuation 100%
1
Medium Positive
2
1
2
Low Positive
2
0
1
Neutral
2
-1
3
2
Low Negative
0
2
1
-2
0
1
0
-1
-1
0
0
-2
1
-2
-3
-1
-2
-2
-1
-1
-3
-3
-3
-1
0
-1
1
Medium Negative
0
1
1
2
2
2
2
2
0
2
2
2
0
-3
2
2
1
0
2
1
2
2
2
2
2
2
1
Overall Rating
-1
2
1
0
0
0
2
0
1
-2
2
2
2
1
2
1
2
0
2
2
1
2
-1
1
2
2
1
3
1 2 0 0 0 0 2 0 0 1 0
2
3
2 3 0 2 1 3 3 1 0 3 0
1
3
2 2 2 0 3 2 2 0 0 0 0
2
3
3 3 2 3 3 3 3 1 1 2 2
2
3
2 3 2 2 3 1 2 1 3 3 0
1
3
3 2 0 2 3 2 2 1 2 2 1
3
0
3 3 0 3 0 3 3 2 0 0 0
1
0
1 1 0 3 0 0 2 3 0 0 0
2
2
2 3 3 1 3 3 1 0 3 3 3
3
2
1 2 2 3 3 2 1 0 1 3 3
2
Lifespan 3
Maintenance needs 3
Initial cost 1
Level of acceptance 0
Visual impat
2
Stakeholder involvement
3
Impact on the community
2
CO2 absorption / retention
3
Creation of habitat
3
Improvement of soils
3
Reduce erosion / sediment yield
3
Increase infiltration / recharge
2
Increase evapotranspiration
3
Slow river water
2
Store river water
1
Slow runoff
2
High Negative
Woodland creation / restoration Instream Large Woody Debris 'leaky' dams (LWD) Riparian vegetation management Hedges, tree belts and buffer zones Agricultural drainage improvement Offline storage ponds Rural SuDS (swales, ponds, bunds, sediment traps, etc.) River meandering Floodplain restoration & management Moving flood defences away from the river Infiltration trenches / swales Retention ponds Rainwater harvesting / Green Roofs
107
Store runoff
1
IMPACT
Appendix 2 Appendix 2
108
Appendix 3 Appendix 3
109
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