AI for Flood Resilience

The most frequent and deadly natural hazards worldwide are floods. Severe, devastating floods have recently posed significant challenges for communities worldwide: Greece, US, Spain, Turkey, India, and more, causing extensive loss of life and property. Enter REOR20, a startup that brings together AI and physics to help individuals, governments, and insurers understand flood risk and, for the first time, protect against floods based on accurate and complete data. Danny Chatziprodromou, CEO & co-founder,  (photo) joins us to discuss the limitations of traditional flood simulation models, physics-based neural networks, and more.

 
Danny, great to have you on the newsletter to discuss how technology can help more people stay safe from floods.

DC: Thanks for having me, Alex. Looking forward to our discussion.

How do we know the risk of flood in a particular area today? And how is this information used for civil protection?

DC: Floods occur in three different ways: fluvial (rivers and streams break out of their banks and water flows out onto the adjacent low-lying areas), pluvial (extreme rainfall event creates a flood independent of an overflowing water body — flash floods are usually falling under this category), and coastal (inundation of land areas along the coast by seawater due to intense windstorm events happening at the same time as high tide and tsunamis). In many countries, we have static flood maps showing a community’s flood zone, floodplain boundaries, and base flood elevation using data from aerial images (drones, airplanes), satellites or topography. Civil protection agencies use these maps to understand and mitigate flood risks and, as new information arises e.g. weather forecasts, to determine the potential risk of an event (e.g. rainstorm) and, if necessary, take actions to alleviate any effects.

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