Upper Irwell – Integrated Water Management Plan

Project Overview

What’s This Project About?

Flooding is a growing concern for communities in the Upper Irwell area. This project explored how Natural Flood Management (NFM) – nature-based approach – can help reduce flood risk while also delivering environmental benefits like improved biodiversity, water quality, and carbon storage.

Rather than relying solely on traditional flood defences (like concrete walls), NFM works by restoring natural features in the landscape. These can include:

Woodland planting to slow down rainfall and increase evaporation
Improved grassland and soil management to boost infiltration and water retention
Runoff attenuation features (RAFs) like ponds or leaky barriers to temporarily store water
Floodplain reconnection to allow rivers to spill safely into adjacent land

Where Is This Happening?

The study focused on the Upper Irwell catchment, which includes the land upstream of the confluence of the River Irwell and River Roch. This area includes communities such as Bacup, Rawtenstall, Ramsbottom, and others that have experienced flooding in recent years.

What Was the Approach?

The project, led by the University of Manchester for the Environment Agency, followed a two-stage approach

Stages of the Project

1. Building a Decision-Support Workbook

A custom-built digital tool (written in Python and presented as a Jupyter Notebook) was developed to bring together multiple datasets and models into a single, user-friendly workflow. This tool allows users to:

Assess NFM potential in upstream areas for each community at risk
Estimate water storage volumes based on land use and soil type
Compare scenarios for different types and combinations of NFM
Calculate funding eligibility using the Defra Partnership Funding Calculator
Estimate flood damage reduction using Environment Agency hydrographs and property risk data

The tool uses design hydrographs (standardised flood flow estimates for different return periods) to estimate how much water would need to be stored to reduce flood risk for a given community. It then compares this to the potential storage available through NFM in the upstream catchment.

Technical Note: The tool assumes that NFM interventions can shift properties from one flood risk category to another (e.g., from “significant” to “moderate” risk), and calculates the associated reduction in economic damages.

2. Catchment-Scale Modelling and Optimisation

To go beyond individual communities, the team used a physically based hydrological model called SHETRAN. This model simulates how water moves through the landscape, accounting for rainfall, soil, vegetation, and river networks.

The model was used to:

Simulate the effects of different NFM types across the whole catchment
Divide the catchment into 60 sub-catchments for detailed analysis
Run thousands of combinations of NFM placements
Use an optimisation algorithm (NSGA-II) to identify the most cost-effective configurations

Technical Note: The optimisation process balanced two objectives – minimising the area (and cost) of NFM while maximising the reduction in flood damages. The result is a “Pareto front” of best-fit solutions, showing trade-offs between cost and benefit.

Why This Matters

Planning NFM is complex. Unlike a single flood wall, NFM needs to be implemented in many places across a landscape. This project helps by:

Combining existing data into a single, consistent framework
Providing a transparent method for comparing options
Highlighting priority areas where NFM could offer the most benefit
Supporting funding applications with evidence-based estimates

Key Insights from the Study

The workbook is ideal for screening and comparing NFM options at the community level.
The catchment model adds a broader view, showing how upstream interventions can benefit multiple communities downstream.
Both tools identified similar priority areas where relatively small interventions could have a large impact.
The approach is replicable in other catchments using national datasets and existing models.

A Note on Assumptions

To keep the analysis consistent and practical, the study made several simplifying assumptions:

NFM features were represented at a 200m grid scale, which may not capture fine-scale effects.
Storage volumes were estimated using standard assumptions about soil and land cover.
Climate change effects were not included due to data limitations.
Results are meant for strategic comparison, not detailed design.

The Flood Hub