Remote sensing (RS) techniques have transformed environmental monitoring by providing efficient and comprehensive methods for assessing surface and groundwater quality. These technologies provide a efficient and cost-effective approach to monitoring surface and groundwater quality across various spectral, spatial, and temporal resolutions. The major factors influencing surface and groundwater quality include industrial pollution, agricultural runoff, and improper waste disposal. A case study is presented in this chapter to enhance understanding of the relationship and role of Remote Sensing and Geographic Information Systems (GIS) in monitoring water quality. Different remote sensing indices, such as the Normalized Difference Vegetation Index (NDVI), Normalized Difference Turbidity Index (NDTI), Normalized Difference Water Index (NDWI) and Total Suspended Matter (TSM) were calculated using band ratios to monitor water quality and validated with the actual surface data. The groundwater quality was estimated using Weighted Arithmetic Water Quality Index method (WAWQI) and spatial variation map of groundwater quality index was generated by interpolation technique in GIS with the point data acquired from CGWB. The study result showed that the value of NDVI (0.59 to −0.21), NDWI (0.21 to −0.73), NDTI (0.416 to −0.24), and TSM (0-2) were observed and for pre monsoon it was found that only, 30% of groundwater have good water quality, 44% have very poor quality, and for post monsoon season only, 21% of groundwater have good water quality, 33% have very poor quality in the study region.