Climate change is amplifying the threat of natural disasters, and floods are no exception. These destructive events endanger lives, livelihoods, and infrastructure worldwide. In response, researchers are turning to Artificial Intelligence (AI) to advance flood forecasting. How does using AI for flood forecasting look and help manage
Why Flood Forecasting?
Floods are the most common natural disaster, impacting nearly 1.5 billion people globally each year, according to the World Bank. A 2021 report by the UN Office for Disaster Risk Reduction (UNDRR) found that floods account for 70% of all deaths caused by natural disasters over the past two decades. From 2000 to 2019, floods caused an estimated $525 billion in global economic damages.
These numbers paint a grim picture, but the reality on the ground is even more devastating. In 2022 alone, floods in Australia displaced thousands of people and caused billions of dollars in damages. In Europe, severe flooding in Germany and Belgium claimed over 200 lives and caused widespread infrastructure destruction. South Asia has also been hit hard by recent floods, with millions affected in India, Pakistan, and Bangladesh.
Given the undeniable link between climate change and extreme weather events, we can only expect floods to become more frequent and intense in the years to come. The Intergovernmental Panel on Climate Change (IPCC) predicts that climate change will lead to increased precipitation extremes, including more heavy rainfall events that can trigger floods. This means that the need for accurate and timely flood forecasting has never been greater.
How Does AI Help in Flood Forecasting?
Google Research isn’t the only player in the game. AI-powered flood forecasting models are being developed by various institutions. These models leverage machine learning algorithms, like Long Short-Term Memory (LSTM) networks, to analyze vast amounts of data. This data can include:
- Real-time weather information (precipitation forecasts)
- Historical river gauge readings
- Satellite imagery (to monitor soil moisture and snowpack)
- Geographical data (topography and elevation)
AI models can predict river flooding with greater accuracy, even in areas lacking traditional monitoring infrastructure with this data.
Who is Using AI for Flood Forecasting?
One example is Google’s Flood Hub platform, which leverages a global AI model trained on publicly available geophysical and meteorological data. This allows Flood Hub to provide real-time flood forecasts in over 80 countries, reaching millions of people.
Google isn’t alone. Other research groups are also developing AI-powered flood forecasting systems. These efforts often involve collaboration with local authorities and scientific communities to ensure the models are tailored to specific regions. Here are a few examples:
- The European Centre for Medium-Range Weather Forecasts (ECMWF) has developed a global flood forecasting system that uses AI to analyze satellite data and weather predictions. This system provides forecasts for lead times of up to 10 days, and is being used by emergency response agencies around the world.
- The University of California, Irvine is collaborating with NASA to develop AI-powered flood forecasting models for specific regions in California. These models incorporate data from ground sensors, satellites, and weather stations to provide highly localized flood predictions.
- The World Bank is funding projects that utilize AI for flood forecasting in developing countries. One such project, implemented in Bangladesh, uses AI to analyze satellite imagery and river gauge data to predict floods with greater accuracy than traditional methods.
These are just a few examples of the many research groups working on AI-powered flood forecasting. By combining global datasets with local expertise, these efforts hold great promise for improving flood preparedness and reducing flood risk around the world.
Other than Floods
The fight against floods demands a global effort. Google‘s partnerships with international aid organizations and the World Meteorological Organization (WMO)’s Early Warnings for All initiative exemplify this collaborative spirit. By combining expertise and resources, researchers can further refine and expand the reach of AI-powered flood forecasting systems.
As climate change continues, the need for accurate flood forecasting will only grow. Researchers are researching AI technology to improve coverage, accuracy, and lead times for flood predictions. Beyond floods, AI holds promise for tackling other climate challenges, fostering a more resilient future.
