Soft Computing Ensemble Models Based on Logistic Regression for Groundwater Potential Mapping
Source abstract
Abstract
Groundwater potential maps are one of the most important tools for the management of groundwater storage resources. In this study, we proposed four ensemble soft computing models based on logistic regression (LR) combined with the dagging (DLR), bagging (BLR), random subspace (RSSLR), and cascade generalization (CGLR) ensemble techniques for groundwater potential mapping in Dak Lak Province, Vietnam. A suite of well yield data and twelve geo-environmental factors (aspect, elevation, slope, curvature, Sediment Transport Index, Topographic Wetness Index, flow direction, rainfall, river density, soil, land use, and geology) were used for generating the training and validation datasets required for the building and validation of the models. Based on the area under the receiver operating characteristic curve (AUC) and several other validation methods (negative predictive value, positive predictive value, root mean square error, accuracy, sensitivity, specificity, and Kappa), it was revealed that all four ensemble learning techniques were successful in enhancing the validation performance of the base LR model. The ensemble DLR model (AUC = 0.77) was the most successful model in identifying the groundwater potential zones in the study area, followed by the RSSLR (AUC = 0.744), BLR (AUC = 0.735), CGLR (AUC = 0.715), and single LR model (AUC = 0.71), respectively. The models developed in this study and the resulting potential maps can assist decision-makers in the development of effective adaptive groundwater management plans.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Groundwater and Watershed Analysis · Hydrology and Watershed Management Studies · Hydrological Forecasting Using AI
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Vietnam Academy for Water Resources, Hanoi 100000, Vietnam
Institute for Water and Environment, Hanoi 100000, Vietnam
Department of Watershed Management Engineering, College of Natural Resources, TarbiatModares University, Tehran, P.O. Box 14115-111, Iran
Research Institute of Forests and Rangelands, Agricultural Research, Education, and Extension Organization (AREEO), P.O. Box 64414-356, Tehran, Iran
Faculty of Geography, VNU University of Science, Vietnam National University, 334 Nguyen Trai, Hanoi 100000, Vietnam
Department of Civil, Environmental and Natural Resources Engineering, Lulea University of Technology, 971 87 Lulea, Sweden
Institute of Geological Sciences, Vietnam Academy of Sciences and Technology, 84 Chua Lang Street, Dong da, Hanoi 100000, Vietnam
Department of Electronics & Communication Engineering, SRM Institute of Science and Technology, Ghaziabad 201204, India
Department of Computer Science and Engineering, GIET University, Gunupur 765022, India
University of Transport Technology, Hanoi 100000, Vietnam
Institute of Research and Development, Duy Tan University, Da Nang 550000, Vietnam
Department of Science & Technology, Bhaskarcharya Institute for Space Applications and Geo-Informatics (BISAG), Government of Gujarat, Gandhinagar 382002, India
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