AI-based seasonal weather and river flow scenarios can improve flood risk assessment
A research paper published in the journal Natural Hazards and Earth System Sciences, ‘Evaluation of AI-based seasonal weather ensembles as input for fluvial flood risk estimation: a case study over the Elbe basin‘, has found that artificial intelligence can be used to help improve fluvial flood risk assessment
Floods cause major social and economic losses, but estimating risk is difficult because extreme events are rare. Artificial intelligence was used to generate over a thousand realistic winter weather seasons and river flows for the Elbe basin. The approach reproduced observed patterns and produced a wider range of extreme storms, showing that artificial intelligence can expand plausible flood scenarios for improved risk assessment.
Citation
Ashcroft, J., Poulston, A., Koch, M., Ertl, G., Brown, K., Butler, J., Hammond, A., Jordan, O., Warren, S., Lamb, R., Young, P. J., and Wood, D.: Evaluation of AI-based seasonal weather ensembles as input for fluvial flood risk estimation: a case study over the Elbe basin, Nat. Hazards Earth Syst. Sci., 26, 3129–3161, https://doi.org/10.5194/nhess-26-3129-2026, 2026.
