Risk-based probabilistic fluvial flood forecasting for integrated catchment models
A project investigating the use of probabilistic river flood forecasting to reduce the uncertainty in flood forecasts made as part of flood risk assessments.
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Details
Objectives
This Environment Agency R&D project investigates how to use probabilistic river flood forecasting to help understand and reduce the uncertainty in flood forecasts made as part of flood risk assessments. This project aims to develop and test practical probabilistic methods in order to identify and reduce uncertainties in river flood forecasts from sources other than predicted rainfall.
Background
Reliable flood forecasts are vital to providing a flood warning service to people and businesses at risk from flooding. River flow routing and hydraulic computer models are often combined into computer model cascades. These are run automatically in the Environment Agency’s National Flood Forecasting System (NFFS) for river flood forecasting and rainfall runoff. However, the accuracy of flood forecasts can be influenced by several factors, such as the:
- accuracy of the data fed into the model
- structure of the model
- parameters and the state - the initial conditions of the scenario modelled
Having a good understanding of these modelling uncertainties is vital to maintaining and improving the flood forecasting service provided by the Environment Agency.
Outcome
This R&D project develops internal practical guidance for conducting risk-based probabilistic river flood forecasting for integrated catchment models.
This project provides advice on using probabilistic river flood forecasting techniques and selecting the most suitable method based on the situation. This will be useful for Environment Agency flood forecasting technical specialists and others involved in maintaining and improving forecasting models. This project ran from 2008 to 2011.