Using machine learning algorithms to map the groundwater recharge potential zones

Volume: 265, Pages: 110525 - 110525
Published: Jul 1, 2020
Abstract
Groundwater recharge is indispensable for the sustainable management of freshwater resources, especially in the arid regions. Here we address some of the important aspects of groundwater recharge through machine learning algorithms (MLAs). Three MLAs including, SVM, MARS, and RF were validated for higher prediction accuracies in generating groundwater recharge potential maps (GRPMs). Accordingly, soil permeability samples were prepared and are...
Paper Details
Title
Using machine learning algorithms to map the groundwater recharge potential zones
Published Date
Jul 1, 2020
Volume
265
Pages
110525 - 110525
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