Groundwater potential assessment based on GIS-based Best-Worst Method (BWM) and Step-Wise Weight Assessment Ratio Analysis (SWARA) Method

In this study, the most suitable areas in terms of groundwater potential within the borders of the adjacent area of Sivas Municipality (Sivas/Turkey) were determined with the help of Geographic Information System (GIS)-based Best-Worst Method (BWM) and Step-Wise Weight Assessment Ratio Analysis (SWARA) methods. Slope, drainage density, Topographic Position Index (TPI), lineament density, lithology, soil types, land use, geomorphology, and rainfall criteria were selected to determine groundwater potential areas. These criteria were weighted with the help of BWM, SWARA, and BWM-SWARA methods and the Groundwater Potential Index (GPI) was calculated according to the weighted linear combination method. According to the calculated GPI values, the groundwater potential of the study area was represented as excellent, very good, good, moderately good, low, and very low. According to all three methods, areas in the excellent class constituted 10.99%, 8.40%, and 11.16% of the study area, respectively, while areas in the very low class covered 8.33%, 7.98%, and 9.04% of the study area, respectively. The linear correlation coefficient (R-2) values of the BWM, SWARA, and BWM-SWARA methods were calculated as 0.80, 0.82, and 0.75, respectively, while the area under the curve (AUC) values were determined as 0.83, 0.79, and 0.81, respectively. These results showed that the accuracy of the model was very good overall. As a result, groundwater potential mapping created for the study area will contribute to better development of groundwater resources and water management planning.

Automated summary

The most suitable areas with groundwater potential in the adjacent area of Sivas Municipality, Turkey, were determined using the GIS-based Best-Worst Method (BWM) and Step-Wise Weight Assessment Ratio Analysis (SWARA) methods. Various criteria such as slope, drainage density, lithology, and rainfall were used to assess groundwater potential, and the results showed areas ranging from excellent to very low potential. The accuracy of the model was found to be very good overall, and the groundwater potential mapping created will contribute to better groundwater resource development and water management planning.