Improved accuracy and lead times of flood warnings: rainfall radar merging

A project to develop a new rainfall product using merged rain-gauge data and data from the radar network in near real time to improve the accuracy and lead times of flood warnings.

Documents

An assessment of kriging-based rain-gauge-radar merging techniques

The development of a real time gauge QC and gauge-radar merging scheme for England and Wales

The development of a Kriging based gauge and radar merged product for real-time rainfall accumulation estimates

If you use assistive technology (such as a screen reader) and need a version of this document in a more accessible format, please email: enquiries@environment-agency.gov.uk. Please tell us what format you need. It will help us if you say what assistive technology you use.

Details

This research contributed to a larger project that aimed to improve the accuracy and lead time of flood warnings by developing a new rainfall software.

Approach

This new software uses rain-gauge data from the Environment Agency, Natural Resources Wales and the Met Office in real time, combined with data from the radar network. It produces a spatial picture of rainfall in as near to real time as possible.

This helps provide more accurate information about how much rain has fallen during a flood event. This information can be fed into river forecasting models to improve the accuracy and speed of river forecasts. This will result in better flood warnings.

Quality control of the rain-gauge data was an important step in the process to create the new software. An automated process was developed to quality control rain-gauge data in near real time. This highlights where there may be suspected problems with rain-gauges so that issues can be investigated.

Next steps

It’s expected that this merged product will feed into the Environment Agency and Flood Forecasting Centre river flood forecasting models at both national and local levels. The Met Office is likely to use the merged product to help verify its rainfall forecasting products.

This project ran from 2010 to 2016.

Updates to this page

Published 24 February 2021