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Research article - Peer-reviewed, 2018

Water quality assessment and catchment-scale nutrient flux modeling in the Ramganga River Basin in north India: An application of INCA model

Pathak, Devanshi; Whitehead, Paul G.; Futter, Martyn N.; Sinha, Rajiv


The present study analyzes the water quality characteristics of the Ramganga (a major tributary of the Ganga river) using long-term (1991-2009) monthly data and applies the Integrated Catchment Model of Nitrogen (INCA-N) and Phosphorus (INCA-P) to the catchment.The models were calibrated and validated using discharge (1993-2011), phosphate (1993-2010) and nitrate (2007-2010) concentrations. The model results were assessed based on Pearson's correlation, Nash-Sutcliffe and Percentage bias statistics along with a visual inspection of the outputs. The seasonal variation study shows high nutrient concentrations in the pre-monsoon season compared to the other seasons. High nutrient concentrations in the low flows period pose a serious threat to aquatic life of the river although the concentrations are lowered during high flows because of the dilution effect. The hydrological model is satisfactorily calibrated with R-2 and NS values ranging between 0.6-0.8 and 0.4-0.8, respectively. INCA-N and INCA-P successfully capture the seasonal trend of nutrient concentrations with R-2 > 0.5 and PBIAS within +/- 17% for the monthly averages. Although, high concentrations are detected in the low flows period, around 50% of the nutrient load is transported by the monsoonal high flows. The downstream catchments are characterized by high nutrient transport through high flows where additional nutrient supply from industries and agricultural practices also prevail. The seasonal nitrate (R-2: 0.88-0.94) and phosphate (R-2: 0.62-0.95) loads in the catchment are calculated using model results and ratio estimator load calculation technique. On average, around 548 tonnes of phosphorus (as phosphate) and 77,051 tonnes of nitrogen (as nitrate) are estimated to be exported annually from the Ramganga River to the Ganga. Overall, the model has been able to successfully reproduce the catchment dynamics in terms of seasonal variation and broad-scale spatial variability of nutrient fluxes in the Ramganga catchment. (C) 2018 Elsevier B.V. All rights reserved.


Nutrient dynamics; Hydrology; Catchment scale modeling; River health

Published in

Science of the Total Environment
2018, Volume: 631-632, pages: 201-215

    Sustainable Development Goals

    SDG6 Clean water and sanitation

    UKÄ Subject classification

    Oceanography, Hydrology, Water Resources

    Publication Identifiers


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