Early warning systems for floods based on AI: Protecting communities with cutting-edge technology

Early warning systems for floods based on AI: Protecting communities with cutting-edge technology | Photo: Iqro Rinaldi

Floods are among the most devastating natural disasters, affecting millions of people worldwide and causing billions of dollars in economic damage. In recent years, advances in artificial intelligence (AI) have enabled the development of more accurate flood prediction models. These AI-driven early warning systems offer the potential to save lives, protect livelihoods, and reduce the overall economic toll of floods. The ability to forecast riverine floods up to seven days in advance could significantly improve the resilience of vulnerable communities, particularly in areas with limited data and resources.

Floods are the most common natural disaster, directly affecting nearly 1.5 billion people globally, or roughly 19 percent of the world's population. In addition to the human toll, floods cause approximately $50 billion in economic losses every year. However, the effectiveness of flood prediction has historically been hindered by limited access to data, especially in developing regions where resources are scarce. This is where AI-driven technologies are making a difference.

AI-based flood forecasting represents a leap forward in predicting riverine floods, particularly in regions where data is sparse. Google Research’s innovations in AI have demonstrated the power of machine learning in generating accurate flood forecasts, enabling early warnings up to seven days in advance in over 80 countries. These predictions are particularly vital for vulnerable populations who are disproportionately affected by climate change and natural disasters. The technology used by Google Research has proven capable of overcoming the limitations caused by insufficient local streamflow data, ensuring more reliable and widespread forecasts across diverse regions.

How AI is revolutionising flood forecasting

Traditionally, flood forecasting has been limited by the availability of data, particularly in less developed or rural areas. Many rivers across the world lack streamflow gauges, which are essential for accurate predictions. In response, Google Research has applied AI to scale flood forecasting, using machine learning models to fill in data gaps and improve accuracy. The result is an AI-driven system capable of predicting floods up to seven days in advance, providing a valuable lead time for affected communities.

In India, the Ganges-Brahmaputra basin, one of the most flood-prone areas in the world, served as the testing ground for Google's first flood prediction pilot in 2018. The system used real-time data, including river level readings, historical flood data, and geographic terrain, to create highly accurate flood forecasts. This pilot was a success and demonstrated the potential of AI to scale flood forecasting globally.

Expanding global coverage through ai

Building on the success of the India pilot, Google expanded its flood forecasting capabilities, covering Bangladesh and later 80 countries globally. With the launch of the Flood Hub platform, AI-based flood predictions became available for regions in Africa, Asia, and Latin America. By 2023, Google had increased the system’s reach to over 460 million people across the globe, including areas previously underserved due to a lack of local data.

One of the key breakthroughs was integrating machine learning models with hydrological physics-based flood simulations. This collaboration with academics and hydrological experts has enabled the creation of a more reliable global flood forecasting system that can function even in areas with minimal or no local data. The result is a scalable, AI-powered system that is helping governments, communities, and aid organizations prepare for floods in real time.

Partnerships driving change in vulnerable communities

In addition to technical advancements, Google has partnered with various humanitarian organizations and local governments to implement AI-based flood forecasts in vulnerable regions. These partnerships have been especially crucial in areas like Sub-Saharan Africa and Southeast Asia, where access to technology can be limited.

For example, the World Meteorological Organization (WMO) is collaborating with Google to support the Early Warnings for All initiative, which aims to provide global flood forecasts to everyone by 2027. By working together with international organisations, researchers, and local governments, AI flood prediction systems are becoming integral tools in disaster preparedness and climate adaptation.

Challenges and opportunities for further expansion

While AI-driven flood forecasting holds great promise, there are challenges to overcome. In many vulnerable communities, access to the internet and smartphones—key tools for receiving real-time alerts—remains limited. Additionally, the quality of AI predictions depends heavily on the data available. In some areas, insufficient monitoring infrastructure can hinder the accuracy of forecasts.

However, these challenges also present opportunities for further innovation. As AI systems continue to improve, so too will their ability to predict a wider variety of flood-related events, such as flash floods or urban flooding. In the future, AI’s role in disaster management could extend to other climate-related hazards, such as droughts or heatwaves, providing a comprehensive tool for global climate adaptation efforts.

The integration of AI into flood forecasting highlights the importance of global collaboration in addressing climate change. While technological advancements are vital, effective solutions require coordination between governments, scientists, NGOs, and local communities. The ongoing development of AI-based flood prediction systems underscores the need for a collective, international effort to address the challenges of climate change.

AI-powered flood forecasting is a significant step forward in global disaster preparedness. By extending the reach of early warning systems and improving the accuracy of flood predictions, AI is playing a critical role in protecting vulnerable communities from the devastating effects of floods. As the technology continues to evolve, the global society must work together to ensure that AI can be used to mitigate climate change impacts across the world.

Continued investment in AI research and global collaboration will be essential to achieve the United Nations’ Sustainable Development Goals (SDGs), particularly SDG 13: Climate Action and SDG 11: Sustainable Cities and Communities.

For more information on AI in flood forecasting and other climate-related initiatives, visit the Google Research blog.