BBC: We Want to Let People Know Before Floods Hit Them


The escalation of global flood risks, posing threats to life, property, and livelihoods, has spurred the deployment of artificial intelligence (AI) by flood monitoring companies to provide advanced warnings. The World Bank reports that over 1.81 billion people, or over one-fifth of the world population, are now exposed to “significant flood risk.” Multiple studies underscore the increasing likelihood and severity of floods due to climate change. To mitigate the impact of flooding, firms like 7Analytics in Bergen, Norway, employ AI to deliver real-time flood predictions, factoring in weather forecasts, land and river geography, urbanization, and drainage capacity. This AI-driven approach, more efficient and requiring less human intervention, enables precise predictions up to seven days in advance.

Founded in 2020, 7Analytics initially faced challenges in securing investments but has experienced a shift in perception as awareness of the growing flood problem has heightened. London-based Neara is another company leveraging AI to create digital flood simulations, particularly for the electricity infrastructure sector. Their models aid power networks in preparing for and minimizing flood damage, including decisions on power restoration, cable shutdowns, power diversion, and engineer deployment.

While both 7Analytics and Neara offer paid services, Google’s Flood Hub platform provides free river flood warnings in over 80 countries. Launched in India in 2018 and expanded globally in subsequent years, Flood Hub utilizes thousands of satellite images and AI simulations to predict river floods after heavy rainfall. The platform issues warnings between two and seven days in advance, facilitating timely evacuations and preventive measures. Google has learned that AI can offer predictions even in regions with limited historical data, thanks to global models that leverage experiences from other rivers.

Despite the positive impact of AI in flood prediction, experts caution about the importance of reliable underlying data. Dr. Amy McGovern, a computer scientist specializing in the trustworthiness of AI in weather prediction, emphasizes that AI models are only as good as the data they are trained on. Addressing biases in data is crucial for the responsible and ethical development of AI in flood prediction. However, the overall consensus is that AI, with its enhanced computing power, contributes significantly to more rapid and accurate flood predictions, offering hope for better-prepared communities and reduced loss of lives and damages in the future.


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