Abstract India’s freshwater ecosystems face unprecedented stress from industrial effluents, untreated sewage, and agricultural runoff, threatening aquatic biodiversity and public health. This study presents a spatiotemporal analysis and time-series forecasting framework for assessing and predicting river water quality across India’s major river basins. Using historical water quality trends across India’s major river basins from 2012 to 2024 obtained from the Central Water Commission. ARIMA statistical and geospatial tools will be used to forecast water quality for future trends (2025–2030) for parameters such as BOD, DO, pH, and Coliform levels. The analysis indicated highly polluted stretches in some river basins, particularly the Ganga and Yamuna, while southern river basins seem to show stable or improving trends. Geospatial views and statistical analysis were applied to locate pollution hotspots and evaluate water safety. Geospatial mapping combined with statistical forecasting is used to identify pollution hotspots and assess future water safety risks. The forecasting results indicate that although gradual improvements are projected in some regions, critical northern river basins are expected to remain above safe pollution thresholds, requiring urgent policy intervention. By integrating spatiotemporal analysis with validated ARIMA-based forecasting, this study provides a cost-effective and scalable framework to support sustainable water resource management and policy planning aligned with SDG-6 (Clean Water) and SDG-13 (Climate Action).
Deshmukh et al. (Mon,) studied this question.