Impacts of regional characteristics on improving the accuracy of groundwater level prediction using machine learning: The case of central eastern continental United States

Impacts of regional characteristics on improving the accuracy of groundwater level prediction using machine learning: The case of central eastern continental United States

Study region: Central eastern continental United States. Study focus: Groundwater level prediction is of great significance for the management of global water resources. Recently, machine learning, which can deal with highly nonlinear interactions among complex hydrological factors, has been widely...

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Bibliographic Details
Main Authors: Hejiang Cai, Haiyun Shi, Suning Liu, Vladan Babovic
Format: Article
Language:English
Published: Elsevier 2021-10-01
Series:Journal of Hydrology: Regional Studies
Subjects:
Machine learning
Groundwater level
Detrended fluctuation analysis
Principal component analysis
Regional characteristics
Central eastern continental United States
Online Access:http://www.sciencedirect.com/science/article/pii/S2214581821001592

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http://www.sciencedirect.com/science/article/pii/S2214581821001592

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