Forecasting groundwater levels using machine learning methods: The case of California’s Central Valley-Reference-Cited by-同舟云学术

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Forecasting groundwater levels using machine learning methods: The case of California’s Central Valley

Published:2023-12 Issue: Volume:21 Page:100161
ISSN:2589-9155
Container-title:Journal of Hydrology X
language:en
Short-container-title:Journal of Hydrology X

Author:

May-Lagunes Gabriela,Chau Valerie,Ellestad Eric,Greengard Leyla^ORCID,D'Odorico Paolo,Vahabi Puya^ORCID,Todeschini Alberto^ORCID,Girotto Manuela^ORCID

Funder

National Aeronautics and Space Administration

U.S. Department of Agriculture

Publisher

Elsevier BV

Subject

Water Science and Technology

Reference36 articles.

1. Application of several data-driven techniques for predicting groundwater level, Water Resour;Bagher Shirmohammadi;Manage,2013

2. Forecasting of groundwater level fluctuations using ensemble hybrid multi-wavelet neural network-based models;Barzegar;Sci. Total Environ.,2017

3. CNRA, Continous groundwater level measurements, https://data. cnra.ca.gov/dataset/continuous-groundwater-level-measurements, 2023.

4. Evapotranspiration depletes groundwater under warming over the contiguous united states;Condon;Nat. Commun.,2020

5. Groundwater technical procedures of the U.S. geological survey;Cunningham;U.S Geological Survey Techniques and Methods,2011

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. A Surrogate Approach to Model Groundwater Level in Time and Space Based on Tree Regressors;2024

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