Articles | Volume 26, issue 15
https://doi.org/10.5194/hess-26-4013-2022
https://doi.org/10.5194/hess-26-4013-2022
Research article
 | 
05 Aug 2022
Research article |  | 05 Aug 2022

Flood forecasting with machine learning models in an operational framework

Sella Nevo, Efrat Morin, Adi Gerzi Rosenthal, Asher Metzger, Chen Barshai, Dana Weitzner, Dafi Voloshin, Frederik Kratzert, Gal Elidan, Gideon Dror, Gregory Begelman, Grey Nearing, Guy Shalev, Hila Noga, Ira Shavitt, Liora Yuklea, Moriah Royz, Niv Giladi, Nofar Peled Levi, Ofir Reich, Oren Gilon, Ronnie Maor, Shahar Timnat, Tal Shechter, Vladimir Anisimov, Yotam Gigi, Yuval Levin, Zach Moshe, Zvika Ben-Haim, Avinatan Hassidim, and Yossi Matias

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Cited articles

Addor, N., Jaun, S., Fundel, F., and Zappa, M.: An operational hydrological ensemble prediction system for the city of Zurich (Switzerland): skill, case studies and scenarios, Hydrol. Earth Syst. Sci., 15, 2327–2347, https://doi.org/10.5194/hess-15-2327-2011, 2011. 
Ben-Haim, Z., Anisimov, V., Yonas, A., Gulshan, V., Shafi, Y., Hoyer, S., and Nevo, S.: Inundation modeling in data scarce regions. Neural Information Processing Systems (NeurIPS), Artificial Intelligence for Humanitarian Assistance and Disaster Response workshop, 30 October 2019, Vancouver, Canada, https://doi.org/10.48550/arXiv.1910.05006, 2019. 
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Bhatt, C. M., Rao, G. S., Diwakar, P. G., and Dadhwal, V. K.: Development of flood inundation extent libraries over a range of potential flood levels: a practical framework for quick flood response, Geomat. Nat. Haz. Risk, 8, 384–401, 2017. 
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Early flood warnings are one of the most effective tools to save lives and goods. Machine learning (ML) models can improve flood prediction accuracy but their use in operational frameworks is limited. The paper presents a flood warning system, operational in India and Bangladesh, that uses ML models for forecasting river stage and flood inundation maps and discusses the models' performances. In 2021, more than 100 million flood alerts were sent to people near rivers over an area of 470 000 km2.