Floods are one of the most frequent natural disasters. According to a World Bank study, 1.47 billion people—about 19% of the global population—face significant flood risks. Flooding causes massive economic losses, with damages reaching $50 billion every year. Historically, large-scale flood forecasting was nearly impossible due to the complexity of the problem and limited resources. The lack of streamflow gauges on most rivers made it even harder to ensure safety, especially in developing countries and vulnerable communities.
Traditional methods for creating flood maps can take up to 24 hours, but with machine learning, it only takes 1-2 minutes as per the National Institute of Water and Atmospheric Research. Scientists combine weather forecasts, river flow data, inundation maps, and risk assessments five days before a potential flood. This process helps create detailed models that show—down to specific streets—the people, property, and infrastructure at risk during storms.
A study published in Nature explains how AI can revolutionize flood forecasting, especially in areas most affected by climate change. Using AI, researchers improved predictions for river floods up to seven days in advance. This technology has been used to provide flood forecasts for 80 countries, covering regions with 460 million people. In some cases, these forecasts are also made available through Google Search, Google Maps, and Android notifications.
The study, detailed further on Google’s Research blog, highlights how AI-powered global hydrology tools have made significant advancements in flood forecasting, even in countries with limited data. This enables global expansion of flood prediction systems. Early warning systems are critical in reducing fatalities, and longer lead times can greatly help communities prepare. With AI, the average lead time for global forecasts increased from zero to five days, and accuracy in parts of Africa and Asia now matches levels previously seen only in Europe.
Researchers in Spain developed an early system that uses sound to detect water leaks. This system includes software that remotely monitors water levels, fluid types, sensor batteries, and overall network status.
In Malaysia, researchers explored how the Internet of Things (IoT) can help in disaster management. Their proposed system uses wireless sensor networks (WSNs), cameras, mobile phones, and weather stations to gather water levels, flow data, and environmental information. The weather stations track temperature, wind speed, and direction, while cameras capture images of the surroundings.
Data is transmitted via Wifi and Zigbee to a middleware layer, where it is processed and analyzed. The system generates detailed flood maps, showing the extent, timing, and location of floods. People can access this information on their smartphones and receive emergency alerts.
In 2019, researchers from Australia, South Korea, and France reviewed studies on IoT-based sensors and computer vision for flood monitoring. They highlighted how these technologies are used for real-time flood tracking, mapping, and early warnings, such as estimating water levels. They also explored their role in managing coastal lagoons.
AI systems study key factors like rainfall, river flow, and soil moisture to predict floods. Machine learning uses past flood data to improve predictions, becoming more accurate over time. These systems can deliver results in minutes, making them crucial in emergencies.
Experts highlight that the quick predictions from AI help authorities send out timely warnings, organize emergency responses, and evacuate people in danger.
Using AI for flood forecasting comes with challenges. Many developing countries lack real-time data and advanced technology needed for these systems. AI models also need large, high-quality datasets for training, which are not always available in some regions.
AI’s role in disaster management is expected to expand. Future updates might include using AI with drones for ground-level monitoring and factoring in long-term climate change impacts for more accurate predictions.
Collaboration among governments, tech companies, and environmental organizations will be critical to ensure that AI-based flood forecasting helps vulnerable communities worldwide.
With its speed and reliability, AI is already transforming flood management, offering a promising path toward safer and more resilient communities.