Identifying impacts of global climate teleconnection patterns on land water storage using machine learning

Identifying impacts of global climate teleconnection patterns on land water storage using machine learning

Study Region: The Zambezi River Basin in southern Africa Study focus: Modelling global freshwater systems is difficult because of the complexities of climate and anthropogenic influence on hydrological systems, especially at local scales. The rapid changes in hydrological systems caused by the influ...

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Bibliographic Details
Main Authors: Ikechukwu Kalu, Christopher E. Ndehedehe, Onuwa Okwuashi, Aniekan E. Eyoh, Vagner G. Ferreira
Format: Article
Language:English
Published: Elsevier 2023-04-01
Series:Journal of Hydrology: Regional Studies
Subjects:
Gaussian process regression
Machine learning theory
surface water hydrology
Zambezi River basin
Online Access:http://www.sciencedirect.com/science/article/pii/S2214581823000332

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http://www.sciencedirect.com/science/article/pii/S2214581823000332

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