Groundwater quality monitoring by correlation, regression and hierarchical clustering analyses using WQI and PAST tools

Abstract Groundwater quality monitoring is very important in terms of environmental and economic factors. The value of water quality parameters increases regularly due to the seawater influx that takes place in the Contai region of India. The present study aims to analyze the state of groundwater more accurately in terms of WQI ensemble with various statistical indicators in the Contai region. Parameters such as pH, temperature, turbidity , total hardness, TDS, EC, Fe, Mn, and Cl for twenty sampling stations have been considered for this analysis. Water quality data is compared with the Indian standard and World Health Organization standard for drinking. Maximum numbers of parameters are found within the allowable range for all sampling stations. Only mean concentrations of the TDS (504.35 mg/l) and Fe (0.333 mg/l) are slightly higher than the allowable drinking water limit. Groundwater is alkaline, fresh, and moderately hard to very hard type. Some stations are affected by seawater influx due to high concentrations of TDS, TH, Cl, and EC. The WQI score here ranges from 18.61 to 85.68 and indicates that water quality lies between excellent to very poor for drinking. Only 5% of samples show an excellent level of drinking water. All statistical analyses were performed using the PAST tool. The integration matrix shows that TDS has a strong relationship with EC and Cl. Also, EC has a strong connection with Cl. The integration result identifies the role key parameters such as TDS, EC, and Cl. Cluster analysis using Ward's technique with Euclidean distance divides the twenty sampling stations into three main clusters with respect to the resemblance of the water characteristics. The salinity under the first cluster is found relatively high than the other two clusters.