Evaluation of GIS-based multicriteria decision analysis and probabilistic modeling for exploring groundwater prospects

摘要

Quantification of groundwater resources is indispensable for developing an efficient strategy for sustainable groundwater management. Integration of remote sensing (RS) and geographical information system (GIS) techniques with multicriteria decision analysis (MCDA) has emerged as a powerful tool for the economical and rapid assessment of groundwater resources at a macroscale. The main intent of this study is to evaluate the performance of two GIS-based approaches, namely MCDA as Approach I and probabilistic modeling as Approach II for groundwater prospecting. In Approach I, the thematic layers and their features relevant to groundwater prospect were extracted using RS and GIS, and appropriate weightages were assigned to individual layers and their features based on the analytic hierarchy process (AHP) scale. After the normalization of these weights, the selected thematic layers were integrated in the GIS environment to generate a groundwater prospect map. In Approach II, two probabilistic models, viz. frequency ratio (FR) and weight of evidence (WOE), were used. The FR and WOE probability values were calculated for each of the selected themes and then groundwater prospect maps were generated by overlaying the themes in GIS. The groundwater prospect maps thus obtained by the two approaches were classified into four distinct groundwater potential zones. These maps were verified using the available well-yield data. The verification results indicated that out of the AHP, FR and WOE techniques, the AHP technique is superior (prediction accuracy of 77 %) to the probabilistic models (FR and WOE), though the WOE model also performed reasonably well with a prediction accuracy of 73 %. It is concluded that for more reliable results, the AHP technique can be used for assessing groundwater potential in a given area/region. The findings of this study are useful for the cost-effective identification of suitable well locations as well as for the efficient planning and development of groundwater resources.