Impact analysis of landuse and landcover on groundwater quality through geospatial and modelling techniques in virudhunagar district

Abstract

Groundwater supplies 30% of World s drinking water and 85% of the total India population and 95% of India urban population. In Tamilnadu, India groundwater is used for agriculture and irrigation and has the key role in the state economy. Groundwater is also an important resource for factories and industries. It also helps to recharge the several wetlands such as rivers, ponds, and lakes. So, analyzing and examining the vulnerability level of groundwater periodically is always needed. Virudhunagar, Tamilnadu, India is identified as one of the districts utilizing more groundwater and upsurges in anthropogenic activities. Thus, this study aim to assess the groundwater quality and vulnerability associated with the several parameters such as Nitrate, Magnesium, Total Dissolved Solids, Sulphate, pH, Fluoride, Calcium, Chloride, and Electrical conductivity between the year 2005 and 2015. We employed the Random Forest (RF) classification in R platform on Landsat imageries from 2005 and 2015 to obtain Landuse and Landcover (LULC) changes to understand the landscape situation of Virudhunagar district. The groundwater potential map was obtained from Inverse Distance Weighted (IDW) interpolation and watershed and water resource map of Virudhunagar district classified from Spectral Mixture Analysis (SMA) in R platform. The feasible area to collect the water sample identified from Spatial Site Suitability Analysis (SSSA) was performed in R platform. We collected water samples from fifty-three locations obtained from SSSA include open and closed well during 2015. The several groundwater quality parameters were examined in the laboratory subsequent standard titrimetric methods and Hydrochemical analysis was conducted for the year pre monsoon 2015 and post monsoon 2016. The spatial distribution of several parameters was mapped and analyzed by Classification and Regression Tree (CART) spatial distribution model in R. The groundwater vulnerability area was identified with the assist of Weighted Overlay Analysis tool (WOA) in R platform by obtained maps from CART model. 3D model of an aquifer produced in Arcscene by generating Digital Elevation Model (DEM) of Cartosat 2a satellite imagery. This 3D model provides the depth of the groundwater, dispersion of pollutants in groundwater associated with several parameters, an area with the highest potential level of groundwater pollution. Finally, SWAT model were utilized to identify the runoff area during 201 newline