Prediction and evaluation of groundwater characteristics using the radial basic model in Semi-arid region, India

Accuracy in groundwater quality monitoring plays a vital and decisive role in environment eco-system, human health and agriculture practices. The present study aims to identify the relationship between the water quality parameters and sources of contamination using radial basic function (RBF) networks. The primary focus of the study is to understand the prioritisation of ionic concentration in terms of groundwater quality. Additionally, the multivariate statistical analysis of groundwater for 30 sample locations was carried out in the present study. Piper and Gibbs plot divulged that, rock-water interaction, ion exchange process, weathering of host rocks are the primary process that influences the groundwater quality in the study area. The principal component analysis (PCA) of groundwater confirmed that two phenomena such as geogenic and anthropogenic activities govern the chemical composition of groundwater. These major phenomena are validated by Hierarchical Cluster Analysis (HCA) and K-mean cluster analysis. The RBF network reveals that anion (R-2 = 0.95) plays a vital role in the quality of groundwater than cations (R-2 = 0.901). The major sources of contamination observed in the study area are weathering of host rocks, ion exchange process, excess utilisation of synthetic fertilisers. The leachate of dumping yards and agriculture field are might be the source of higher concentration of anions in the groundwater chemistry, and it leads to an increase the value of pH in groundwater. The integrated approach of the present study suggests that remedial measure to be followed to avoid the contamination of groundwater in the study area. The research findings may provide useful information to the decision-maker regarding the groundwater pollution risk management mainly in arid and semi-arid regions.