Supplementary file 1_A two-stage multicollinearity and standard deviation weighted MCDA framework for groundwater recharge potential zonation mapping.pdf
收藏NIAID Data Ecosystem2026-05-10 收录
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https://figshare.com/articles/dataset/Supplementary_file_1_A_two-stage_multicollinearity_and_standard_deviation_weighted_MCDA_framework_for_groundwater_recharge_potential_zonation_mapping_pdf/31818190
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Groundwater recharge potential zonation (GWRPZ) is essential for sustainable water resource management, especially in areas with complex hydrogeological conditions. In this study, 24 parameters were initially selected based on the literature review, and thematic maps were prepared. A multicollinearity analysis reduced the number of parameters from 24 to 20 by removing four highly correlated parameters (NDWI, TRI, NDBI, WRI). These 20 parameters were integrated into a multi-criteria decision analysis (MCDA) framework using technique for order preference by similarity to ideal solution (TOPSIS), multi-objective optimization on the basis of ratio analysis (MOORA) with relative weights, S-TOPSIS, S-MOORA, with standard deviation weights, and GWRPZ maps were prepared. The maps were divided into five recharge categories, and approximately 79% of the research region falls within zones of medium to very high recharge potential. Model accuracy was evaluated using groundwater-level data by area under the curve-receiver operating characteristic (AUC-ROC) analysis, which showed that all four models were reliable, with AUC values of 0.887 (S-MOORA), 0.844 (S-TOPSIS), 0.837 (MOORA), and 0.804 (TOPSIS). The findings indicate that standard deviation-weighted models (S-MOORA and S-TOPSIS) outperform relative weight methodologies. By providing reliable delineation of recharge zones, this research directly advances the United Nations Sustainable Development Goal (SDG) 6: Clean Water and Sanitation, through sustainable groundwater management.
创建时间:
2026-03-20



