Global Flood Partnership

Lorenzo Alfieri, Sagy Cohen, John Galantowicz, Guy J.P. Schumann, Mark A. Trigg, Ervin Zsoter, Christel Prudhomme, Andrew Kruczkiewicz, Erin Coughlan Perez, Zachary Flamig, Roberto Rudari, Huan Wu, Robert F. Adler, Robert G. Brakenridge, Albert Kettner, Albrecht Weerts, Patrick Matgen, Saiful A.K.M. Islam, Tom Groeve, Francesco DottoriPeter Salamon

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

Abstract

Every year riverine flooding affects millions of people in developing countries, due to the large population exposure in the floodplains and the lack of adequate flood protection. Preparedness and monitoring are effective ways to reduce flood risk. State-of-the-art technologies relying on satellite remote sensing as well as numerical hydrological and meteorological predictions can detect and monitor severe flood events at the global scale. This chapter describes the emerging role of the Global Flood Partnership (GFP), a global network of scientists, users, and private and public organizations active in global flood risk management. Currently, a number of GFP partner institutes regularly share results from their experimental products, developed to predict and monitor where and when flooding is taking place in near real time. Products of the GFP have already been used on several occasions by national environmental agencies and humanitarian organizations to support emergency operations and to reduce the overall socioeconomic impacts of disasters. The chapter includes a discussion on existing challenges and ways forward to improve rapid access to flood information and increase resilience to flooding.
Original languageEnglish
Title of host publicationGlobal Drought and Flood: Observation, Modeling, and Prediction
EditorsH. Wu, D.P. Lettenmaier, Q. Tang, P.J. Ward
PublisherAGU
Chapter17
Pages307-322
ISBN (Electronic)9781119427339
ISBN (Print)9781119427308
DOIs
Publication statusPublished - 12 Sep 2021

Publication series

NameGlobal Drought and Flood
Publisher10.1002/SERIES5064
ISSN (Electronic)2328-8779

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