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Groundwater level response identification by hybrid wavelet–machine learning conjunction models using meteorological data |
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| Authors: | Samani Saeideh Vadiati Meysam Nejatijahromi Zohre Etebari Behrooz Kisi Ozgur |
| Institution: | 1.Department of Water Resources Study and Research, Water Research Institute (WRI), Tehran Province, District 4, Bahar Blvd, Tehran, Iran ;2.Global Affairs, Hubert H. Humphrey Fellowship Program, University of California, 10 College Park, Davis, CA, 95616, USA ;3.Department of Minerals and Hydrogeology, Faculty of Earth Sciences, Shahid Beheshti University, Evin Ave, Tehran, Iran ;4.CalNRA/Dept. of Water Resources/ Sustainable Groundwater Management Office, 715 P Street, Sacramento, CA, USA ;5.Department of Civil Engineering, Technical University of Lübeck, 23562, Lübeck, Germany ;6.Department of Civil Engineering, Ilia State University, 0162, Tbilisi, Georgia ; |
| Abstract: | Environmental Science and Pollution Research - Due to its heterogeneous and complex nature, groundwater modeling needs great effort to quantify the aquifer, a crucial tool for policymakers and... |
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