Spatiotemporal zoning of groundwater quality in Rechna Doab: analysis of Electrical Conductivity (EC), Sodium Adsorption Ratio (SAR), and Residual Sodium Carbonate (RSC) variability

Abstract

Groundwater quality is essential for sustaining human and plant life, as its degradation can harm vital organisms critical for ecosystem balance. GIS-based models have proven effective in large-scale water quality zoning, offering precise and efficient management tools. Therefore, present study was designed with objective of water quality zoning in Rechna doab. This study analyzed borehole data from 1,130 wells across the Rechna Doab region, collected from 2006 to 2019 during pre-monsoon (June) and post-monsoon (October) seasons. Key water quality parameters, including electrical conductivity (EC), sodium adsorption ratio (SAR), and residual sodium carbonate (RSC), were interpolated using the inverse distance weighted (IDW) method in GIS. The results revealed that during the pre-monsoon season, 7.94% of the area exhibited poor water quality, 58.90% marginal, and 33.16% good quality. In the post-monsoon season, these values shifted to 11.65% poor, 52.43% marginal, and 35.93% good quality zones. Geo-statistical validation using semi-variogram and kriging demonstrated high model accuracy, with mean error (ME) and mean square error (MSE) values near zero. Additionally, root mean square error (RMSE) closely matched average standard error (ASE), though root mean square standardized error (RMSSE) values greater than 1 indicated overestimation for EC, SAR, and RSC. The study concluded that groundwater quality in Rechna Doab is deteriorating over time and recommends adopting artificial groundwater recharge and conservation strategies to preserve water quality.

Keywords

• water quality
• interpolation
• inverse distance weighted
• geo-statistical
• gis
• pre-monsoon
• post-monsoon