LAUSR

Abstract Assessing the impact of land use cover on the river water quality is a pre-requisite to sustainable river basin planning and management. In recent times, non-point source pollution generated from agricultural watersheds has been significantly deteriorating water quality of major rivers such as river Ganges in India as described in this case study. The present work develops a Geographical Information System based mechanism to model non-point source pollution using multivariate regression analysis. The watershed model delineates runoff direction and identifies its lowest elevation points (outlets) near the river body where maximum pollution is caused by non-point source pollution, and thus provides a concrete evidence that agricultural runoff is the primary cause of increasing concentration of nitrogen and phosphorus compounds in the river. A case study of river Ganges basin, India is considered to demonstrate the applicability of the model. Relationships among six land cover and eleven critical water quality parameters are studied using multivariate regression near three selected sampling stations obtained using geographical information systems model. The results indicate that inorganic farming practices have a direct impact on the river water quality, leading to positive correlation (R2 ≥ 0.65) amongst ‘double-crop cover’ and ‘build-up area’ with Temperature, nitrogen as nitrite, nitrogen as nitrate, nitrite + nitrate, phosphorous as orthophosphate within the river body. Trend analysis study of temperature using Mann-Kendall test and Sen slope reveals an average of 0.23 °C/year positive trend in river temperature due to discharge of NPS pollution through agricultural watersheds. The study alarms the policymakers to educate the farmers to adopt best management practices such as increasing soil matter, usage of tile drainage, bioreactors, nutrient removal wetlands, using cover crops, etc. not only to increase crop productivity, but also to enhance the water quality in the riverine ecosystem.