Catchment management, SuDS and NFM for

flood mitigation. Tutta Beck, County Durham

Alex Fraser1&2 and Sim Reaney1

1, Durham University, 2, Northumberland County Council

Introduction

This presentation will:

�  Introduce research aims

�  Discuss the problems within the study site

�  Outline the risk mapping and targeting approach

�  Demonstrate methods and preliminary results from CRUM3

simulations

Why Natural Flood Management &

Catchment Based Approach? �  Winter 2015-16 events demonstrated last line approach to flood

management unsustainable

�  Environment Agency and DEFRA funding towards Natural Flood

Management and catchment management

�  Targets ‘flashy’ hydrograph

�  Multiple Benefits

�  NFM can enhance fluvial ecology (EdenDTC)

�  Amenity Value (Thacka Beck, Penrith; Holnicote, Somerset)

�  Maintenance can form part of Land Management Practices

Case Studies of this approach Demonstration test catchments and examples of LLFA projects

�  Land Management/CSF approach (ALFA, Eden DTC, Durham

University)

�  Channel management, upstream storage (Pickering, EA, FC &

Durham University)

�  Runoff attenuation (Belford, EA & Newcastle University)

�  Floodplain Storage (NT Holnicote Estate, DEFRA & JBA)

�  Attenuation, slowing flow (Hepscott, Northumberland County

Council, EA

Research Aims

�  Develop an innovative approach to managing catchment

hydrology

�  Use risk mapping to target hydrological simulations

�  Provide outputs that satisfy funding regulations

�  Long term management advice, land management to

mitigate flood risk supporting farming and rural economy.

�  Increase resilience across the catchment

Tutta Beck Catchment

Location

•  40 miles South of Newcastle

•  Adjacent to the A66 Transpennine trunk road

Hydrology

•  8km2 sub-catchment of the River Tees

•  Gravel bed watercourse with a flashy flow

regime

Characteristics

•  Predominantly agricultural

•  Heritage Designations at receptor (scheduled

Ancient Monument, Ancient Parkland, Listed

Buildings)

Twin Arch Culvert 3.2mx1.5m

Ancient Monument Confined Channel

Receptor

2x 90⁰ direction changes Observed overflow

Unsuitable Flood Barrier option

Opportunities to manage catchment for flood alleviation instead

Flood Plain Storage?

Woody Debris

Intercepting Runoff?

Ditch Blocking?

Land cover change?

Research Approach �  Output driven approach

CRUM3

Assess land management techniques using a Catchment

Based Approach, NFM and SuDS for Flood Mitigation.

Existing land cover

Land cover weighting

The GLUE approach

Model Sensitivity Analysis

SCIMAP-Flood

Flood Risk

Generation Hydrological Connectivity

Stakeholder Engagement

Parish Council Meeting

LLFA Meeting

Land Owner/Farmer

Communication

Natural Flood Management, Catchment Sensitive Farming & SuDS

Literature

Scenario Development

Catchment Modelling

Submit to Durham County Council for Detailed Design

SCIMAP-Flood Risk based mapping tool assessing catchment

characteristics and likelihood of rapid connectivity to

watercourse.

(Pearson, 2016)

SCIMAP Flood

Using SCIMAP to target

simulations

For a new catchment SCIMAP offers the opportunity to

support initial field assessments and identify areas that

have a higher risk factor than others.

Greater resolution than hydrological modelling to better

drive simulations

The results can be used to generate scenarios for detailed

simulation of

•  Woodland for flood alleviation •  Large Woody Debris dams

•  Ponds and Attenuation features

Simulation scenarios

�  Woodland for flood risk

�  Rainfall intercepted by canopy

�  Increase infiltration

�  Intercept overland flow

�  Large Woody Debris

�  Slow the flow

�  Attenuation

�  Reduce and elongate the flood hydrograph

�  SuDS attenuation

�  Volumetric storage

�  Slow Flow

Minnesota Dept. Agriculture

CRUM3 - Overview

�  Fully distributed across the

landscape (apx. every 50 m)

�  Detailed process

representation

�  1D vertical

�  2D landscape routing

�  1D channel flow

�  Detailed Outputs

Vertical Processes

�  Interception

�  Evapotranspiration

�  Runoff/overland flow

�  Infiltration

�  Soil flow

2D Representation

�  Terrestrial and fluvial

representations

�  Multiple flow routing on the

landscape

�  Muskingum-Cunge river

flow routing

Example outputs:

Validation of the CRUM3 Model

for Tutta Beck

�  Model performs well

�  Max Nash Sutcliff 0.76

�  Observed Modelled Peak

ratio 0.97

�  An ensemble of 25 models

taken forward into

scenarios

�  Captures the predictive

uncertainty of the model

CRUM3 Summary �  Fully spatially distributed catchment hydrological

simulation model

�  Detailed physical process representation

�  Predicts changes in flood peak and general catchment

hydrological behaviour

�  Suitable to testing natural flood risk management

mitigation features

�  Next slides show the results from scenarios developed

using SCIMAP-Flood and from stakeholder engagement…

Land cover change simulation

●  Intercept rainfall

●  Increase surface roughness,

improve infiltration, improve soil

structure

Vegetation can provide mitigation in a number of ways:

Botanic gardens of South Australia Minnesota Dept. Agriculture

●  Riparian buffer strips intercept

overland flow reducing

connectivity to watercourses

Blanket Land Use Change Results

�  Greatest reduction

through deciduous

landcover

�  Arable increases

discharge

�  Most simulations have

little impact on sum of

discharges meaning

little change in fluvial

environment

Buffer Strip Land Use Change Results

•  Buffer strip simulation 50m

around cells classified as

channel to disconnect

runoff

•  Greatest reduction through

Deciduous woodland

•  Most simulations have little

impact on sum of discharges

meaning little change in

fluvial environment

CSF Flood Risk Targeted Woodland

•  Reduces peak discharge under

all events (~0.5m3s-1 at Mean)

•  Second most effective

reduction of mean discharge

•  Strategy supported by

Catchment Sensitive Farming

funding initiative

•  Little impact on sum of

discharges meaning negligible

change in fluvial environment

Large Woody Debris Simulation

�  Disturbing in channel flows

(Hepscott, Belford, Stroud)

�  Promoting flooding of the

floodplain (Pickering)

�  Restricting discharge and

attenuation (Pickering)

Large woody debris can provide mitigation in multiple ways-

Hepscott Burn (Northumberland

County Council) Pickering (Odoni et al., 2010)

Large Woody Debris Results

�  Large woody debris is simulated

as a flow restriction

�  Little disturbance in sum of

discharge

�  Flood plain discharges offer

greatest reduction but would

have greatest cost

�  Arable features little reduction

o  Minimal contribution to discharge

o  Require lower flow restriction

LWD – Targeting the Upper

Catchment

�  Targeting dams to the

upper catchment

�  Aim to slow the flow and

remove water from the

flood peak

�  Maximum discharge through

dam of 0.75 m3 s-1 Black – catchment outline Blue – river channel network

Red – locations of dams

LWD – Targeting the Upper Catchment •  0.13m3s-1 reduction in

peak flow

•  Principle of

disconnecting the upper

catchment from the peak

flows

•  Little impact on sum of

discharges meaning

negligible change in

fluvial environment

Image Courtesy Nick Barber, Durham University

SuDS Attenuation (Ponds/Basins)

�  Ditch of the Future

Structures (Eden DTC)

Towcett Farm

�  Online/offline structures

(Belford)

�  SuDS Systems

SuDS/attenuation can function in multiple ways-

Eden DTC, Image Courtesy Nick Barber, Durham University

SuDS Simulation �  Capturing around 0.01%

catchment within a single

structure reduces all

discharge figures by mean

of 0.1m3s-1.

�  Simulation developed

through manipulation of

DEM

�  Little impact on sum of

discharges meaning

negligible change in fluvial

environment

Summary of Results

90th Percentile Mean 10th Percentile

Control Run results 6.5 6.3 5.8

Berm 1m High 6.4 6.2 5.7

CSF Targetting 5.9 5.7 5.3

Blanket Changes Arable 7.0 6.4 6.2

Blanket Changes Improved Grazing 6.8 6.3 5.7

Blanket Changes Coniferous 6.7 6.3 5.9

Blanket Changes Rough Grazing 6.5 5.9 4.7

Blanket Changes Deciduous 6.5 5.7 4.6

Watercourse Buffers Improved Grazing 6.6 5.9 5.5

Watercourse Buffers Coniferous 6.4 5.9 5.5

Watercourse Buffers Rough Grazing 6.4 5.8 5.1

Watercourse Buffers Deciduous 6.1 5.7 5.0

Arable 3m3s-1 6.5 6.3 5.8

Arable 4m3s-1 6.4 6.1 5.7

Arable 5m3s-1 6.4 6.1 5.7

Floodplain 4m3s-1 4.2 4.2 4.2

Floodplain 5m3s-1 5.2 5.2 5.2

0.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0

Control Run results Berm 1m High CSF Targetting Blanket Changes Arable Blanket Changes Improved Grazing Blanket Changes Coniferous Blanket Changes Rough Grazing Blanket Changes Deciduous Watercourse Buffers Improved Grazing Watercourse Buffers Coniferous Watercourse Buffers Rough Grazing Watercourse Buffers Deciduous Arable 3m3s-1 Arable 4m3s-1 Arable 5m3s-1 Floodplain 4m3s-1

Buffer Scenarios Blanket & targeted change

Scenarios

Flow Restriction Scenarios

SuD/Attenuation

Positives/Negatives of Features

•  Vegetation

+ Easily Managed - Cost to buy vegetation

+ Secondary Harvest - Cost of land take

+ Ecology Benefits - Requires spatial targeting

•  Large wood debris

+ Slow Flow deposition - Construction costs

+ Easily Maintained - Cost of land take

+ Ecology Benefits - Maintenance/Replacement

•  Attenuation

+ Water Quality Improvements - Construction costs

+ Provide secondary income - Cost of land take

+ Habitat creation - Maintenance

Summary

�  CRUM3 has evidenced that effective use of SuDS and

NFM features can lead to simulated reductions in peak

flow

�  CSF simulation shows targeted landcover change could

be more effective than generic changes

�  Targeting techniques using SCIMAP-Flood can yield

effective reductions

�  Interrelationships of catchment characteristics heavily

influence most effective mechanism for flood

management

Thank you for your time

�  Thanks to Nick Fraser, Heritage Lottery Fund, staff at Tees Rivers Trust, Northumberland

County Council and Durham County Council

�  Alex Fraser – a.r.fraser@dur.ac.uk /

alex.fraser@northumberland.gov.uk

�  Sim Reaney, sim.reaney@dur.ac.uk