Flood Guard project helps communities understand flood risk

Teesside University master’s student Abdul Rehman has completed Flood Guard, a project exploring how past floods and weather information could help people better understand the risk of flooding.

As part of his MSc Data Science dissertation, Abdul built Flood Guard as a complete machine-learning system using two open data sources. It looks at information from previous floods alongside environmental and weather data to identify patterns and conditions that could be linked to a higher risk of flooding.

The system was also developed as a public web application, designed to provide seven-day flood-risk forecasts for some cities in the north of England. It gives explanations about the weather conditions behind each forecast, helping users understand why a particular risk level has been produced for Sheffield, Doncaster, Bradford, Leeds and Newcastle.

Flood Guard is a proof of concept and is not designed to predict floods with absolute accuracy. Instead, it shows how learning from past flooding can help people understand what conditions may lead to greater flood risk in the future.

The project demonstrates how data can be used to address a real-world problem and could help local communities and those responsible for planning and managing areas at risk of flooding make more informed decisions. Users can access Flood Guard here: https://northeastflood.netlify.app/