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Scientists have built a model that accurately predicts floods without datafrom the ground.
Until recently, ground observations were needed alongside satellite data to build a full-enough picture to model climate and extreme weather events.
And as worldwide annual losses due to flooding are predicted to reach at least US$1 trillion in 2050, scientists are seeking a solution for countries that still lack data from the ground. [1] But now researchers at the University of Bristol, United Kingdom, have managed to fill the gaps that had left data-poor countries unable to predict floods.
Data on the likelihood of these extreme events in places that are difficult to assess, such as parts of South-East Asia, will help decision-makers in many ways. For example, robust predictions on flood hazard will allow insurance companies that are trying to penetrate developing markets to offer local firms lower premiums.
