AI-Constrained Bottom-Up Ecohydrology and Improved Prediction of Seasonal, Interannual, and Decadal Flood and Drought Risks
Author(s) -
Forrest M. Hoffman,
Jitendra Kumar,
Zheng Shi,
Anthony P. Walker,
Jiafu Mao,
Yaoping Wang,
Abigail L. S. Swann,
James T. Randerson,
Umakant Mishra,
Gabriel J. Kooperman,
Hyungjun Kim,
Chonggang Xu,
Charles D. Koven,
David M. Lawrence,
Megan D. Fowler,
Martin G. De Kauwe,
Belinda E. Medlyn,
Lianhong Gu,
Liz Agee,
J. M. Warren,
Shawn Serbin,
Alistair Rogers,
Trevor F. Keenan,
Nate G. McDowell,
Nathan Collier,
Sarat Sreepathi,
Juan M. Restrepo,
Richard Archibald,
Feng Bao,
Richard T. Mills
Publication year - 2021
Publication title -
osti oai (u.s. department of energy office of scientific and technical information)
Language(s) - English
Resource type - Reports
DOI - 10.2172/1769668
Subject(s) - hierarchy , flood myth , big data , analytics , computer science , ecohydrology , data science , environmental science , climatology , artificial intelligence , data mining , machine learning , geology , geography , ecology , archaeology , ecosystem , biology , economics , market economy
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