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Water quality of river Ramganga, a major tributary of the Ganga, was monitored by monthly sampling at selected 23 stations (17 on the main stem and 6 on tributaries) during two calendar years 2014 and 2015 for 24 parameters. Cluster analysis grouped the sites in three statistically significant clusters, highly polluted, moderately polluted and less polluted, based on the similarities or differences in water quality parameter values. Discriminant Analysis helped in identifying the most representative discriminant parameters in entire dataset with more than 86% correct assignment in both temporal and spatial analysis. Despite high organic load in the middle stretch of Ramganga, the observed dissolved oxygen values were higher than 4 mg/l at almost all sampling stations on the main stem, even in lean flow period of a year. About 16–49% BOD load reduction from various point sources was estimated to maintain the desired dissolved oxygen levels (5–6 mg/l) for aquatic species during lean flow season in river Ramganga. This implies that primary treatment alone of discharge from these sources is sufficient from the point of view of sustenance of indigenous aquatic flora and fauna. Comparison of water quality of Ramganga and Ganga (before and after the confluence with Ganga) for lean flow season revealed that Ramganga does not significantly contribute to the decline in water quality of river Ganga in terms of parameters such as dissolved oxygen and heavy metals.

The basin of Ramganga River, a major tributary of Ganga, has seen rapid industrialization, urbanization, and agricultural growth in modern times, especially during and after the 1970s, with consequent changes in Land Use and Land Cover (LULC) of the basin. Object-based classification of seldom-used CORONA images (for 1970) for historical LULC scenario and LISS IV (Resourcesat-2) images (for 2013–14) for the present scenario of the basin was performed with high overall accuracies of 93% and 87% and Kappa coefficients of 0.89 and 0.82 respectively. Object-based classification using the eCognition software tool combined with manual classification of the images revealed significant decrease in total forest cover (~ 485 km2) and riverbed (~ 498 km2) LULC classes along with correspondingly increased agriculture (~ 898 km2) and built-up (~ 313 km2) classes in the basin. Further, though Ramganga reservoir (spread over ~ 70 km2), operated since in 1974, has increased the water area by ~ 1295% in Afzalgarh sub-basin of the Ramganga Basin, the overall area of water class decreased by 1.64% in the basin, probably due to loss of ponds in agricultural lands. An upward shift of about 42 km in the confluence point of Ramganga and Gangan Rivers was also observed, which may be attributed to the course shift of Ramganga in a south-west direction.