Open AccessMachine learning assisted hybrid models can improve streamflow simulation in diverse catchments across the conterminous US
Author(s) -
Goutam Konapala,
ShihChieh Kao,
Scott Painter,
Dan Lu
Publication year - 2020
Publication title -
environmental research letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.37
H-Index - 124
ISSN - 1748-9326
DOI - 10.1088/1748-9326/aba927
Subject(s) - streamflow , computer science , consistency (knowledge bases) , range (aeronautics) , process (computing) , hydrological modelling , environmental science , machine learning , hydrology (agriculture) , climatology , artificial intelligence , drainage basin , geology , cartography , geotechnical engineering , geography , materials science , composite material , operating system
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