Trends and probabilistic stability index for evaluating groundwater quality: The case of quaternary alluvial and quartzite aquifer system of India

Abstract

This study proposed a novel groundwater-quality stability index (GQSI), which considers probabilistic estimate of reliability and resilience based on multi-year dataset. The developed index is validated and optimized adopting optimum index factor approach. The vulnerabilities of different groundwater quality parameters are also computed to provide an insight about the deviations of their concentrations from the safe drinking water limits. The application of the developed stability index is demonstrated through a case study in quaternary alluvial and quartzite aquifer system of India. In addition, trends in the groundwater quality parameters are identified by using variance-corrected Mann-Kendall test, and trends are quantified by using Sen's slope estimation test. Box-whisker plots revealed that EC and TDS mostly exceed their maximum permissible limits prescribed for drinking water in the southern and southwest hard-rock formations. Whereas, most parameters do not cross their maximum desirable limits in the central and northern alluvial formations. Increasing trends of potassium and bicarbonate, and decreasing trends of carbonate, calcium, sulfate, and fluoride are found prominent. The GQSI values indicated high stability of groundwater quality under older alluvium geology and low stability under the gneiss and mica-schist. Results of the GQSI are found in agreement with that of groundwater-quality index (GQI) at 84% sites, which proved adequacy of the developed GQSI. Also, three classes ('low'/'poor', 'moderate', and 'high'/'good') of both the GQSI and GQI showed a good coherence at 83, 78, and 87% sites. However, GQSI is more advantageous than GQI due to former's statistical framework, consistency and comparability over different areas. Three optimum index factors, i.e., TDS, pH and nitrate, are found to have the maximum impact on overall groundwater quality with their largest variations. Results of the optimum groundwater-quality stability index (OGQSI) and GQSI closely matched with each other, and a significant linear relationship (R² = 0.70) existed between them. Therefore, OGQSI is a cost-effective approach for adequate monitoring and satisfactory evaluation of the groundwater quality in low-income nations.

Keywords: Groundwater quality stability index; Mann-Kendall test; Optimum index factor; Reliability; Resilience; Vulnerability.