Geospatial distribution of groundwater potential zone using Remote sensing, GIS and analytic hierarchy process (AHP) approach: a case study of Raipur district, Chhattisgarh, India

Abstract

In India, groundwater is the major source of water for various activities.  Due to over-extraction, the groundwater levels are declining over the period. The Present study has an objective of investigating the groundwater potential zone (GPZ) and finding the most sensitive parameter for the study area which is Raipur district, Chhattisgarh, India. The state is located in the Mahanadi River basin with a coverage area of 2892 Km2. The following study uses the AHP (Analytical hierarchical process) technique for analysis along with geographic information system (GIS) and Remote sensing. Mapping GPZ includes various hydrogeological and topographical features. Seven different datasets namely precipitation data, drainage density, lineament density, slope data, land use land cover (LULC), soil data, and lithological conditions of the area were considered. These thematic maps were created using various raw datasets like meteorological data, digital elevation model (DEM), satellite data, soil data, and lithological data. The AHP method which is based on multi-criteria decision analysis (MCDM) assigns weights on Saaty’s scale to all layers as per their contribution to groundwater potential in the study area. After the formation of the AHP matrix, overlay analysis was performed with the normalized weights in the GIS environment. Layer-wise sensitivity analysis was performed for all the input layers. Sensitivity analysis highlights the importance of parameters by removing each parameter at a time.  The use of sensitivity analysis is to find out the relationship between the given input layers and the output layer generated. The study also cross-validated the groundwater level data of the Raipur district. This verification confirms the authenticity of the method. The study area was divided into five potentiality zones based on spatial distribution analysis. The results indicate that 22.06% and 21.34% of the study area fall under poor and good potentiality zones, respectively whereas the moderate potential zone is the most dominant one with a percentage of 37.82. The analysis also revealed that 7.87% and 10.92% of the area belong to extreme zones i.e. very poor and very good groundwater potential zones respectively. The result also shows that Raipur City and the northeastern parts of the district have a very poor groundwater potential zone. The analysis shows that the most sensitive parameter is land use land cover with a mean variation of 4.37% followed by slope, lineament density, and lithology with 4.20, 3.69, and 2.17% respectively. The least sensitive parameter for groundwater potential zone is soil type with a mean variation of 0.79% followed by drainage density and rainfall with 1.48, and 2.12% respectively. Consequently, this study can be used to locate the Groundwater Potential Zone at a lower scale for effective groundwater extraction and sustainable groundwater management.