An integrated assessment and visualization framework combining PCA-weighted WQI and human health hazard index to map...

Agricultural runoff, waste disposal, and other anthropogenic activities introduce pollutants into aquifers, underscoring the need for robust groundwater quality assessment. Conventional groundwater assessment frameworks rely on subjective weight assignment in Water Quality Index (WQI) development and interpret WQI and health risk separately, resulting in a fragmented evaluation of risks. This study proposes an integrated assessment and visualization framework that jointly evaluates (i) a Principal Component Analysis weighted Groundwater Quality Index (PCAWQI) and (ii) human health risk (non-carcinogenic Hazard Index, HI), providing an integrated appraisal of drinking water suitability across Maharashtra, India, a drought-prone state with high groundwater dependence. Using monitoring data from 2012 to 2022, we derive objective indicator weights via PCA (mitigating the subjectivity of conventional index methods), validate performance against an entropy-weighted WQI (EWQI) benchmark, and deploy bivariate choropleth mapping to visualise the joint distribution of quality and health-risk classes for precise hotspot identification. Our findings show that over the decade, the share of sampling locations with a Hazard Index for children exceeding unity (HI_children > 1), indicating a higher likelihood of adverse health effects, increased from 59.1% to 63.3%, primarily driven by rising nitrate concentrations attributable to human activities. PCAWQI indicates an improvement in "excellent" quality locations from 11.1% to 17.78%; however, in 2022, 82.22% of locations still fell within marginal-to-extremely-poor categories, highlighting persistent concerns despite expanded sampling coverage. Spatially, coastal districts (such as Ratnagiri, Sindhudurg, Raigad) predominantly exhibit excellent to marginal quality with low health risk, whereas interior districts (Ahmednagar, Solapur, Osmanabad, Beed, Jalgaon, Latur, Nanded, Chandrapur, and Gadchiroli) contain high number of wells classified as moderate to extremely poor in both PCAWQI and HI. By integrating objective index weighting with health risk estimation in a geospatial platform, the proposed framework delineates true hotspots and their spatio-temporal dynamics, supporting targeted surveillance, remediation, and more efficient groundwater-quality management.