Literature DB >> 29524896

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

Devanshi Pathak1, Paul G Whitehead2, Martyn N Futter3, Rajiv Sinha4.   

Abstract

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 R2 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 R2>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 (R2: 0.88-0.94) and phosphate (R2: 0.62-0.95) loads in the catchment are calculated using model results and ratio estimator load calculation technique. On average, around 548tonnes of phosphorus (as phosphate) and 77,051tonnes 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.
Copyright © 2018 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Catchment scale modeling; Hydrology; Nutrient dynamics; River health

Year:  2018        PMID: 29524896     DOI: 10.1016/j.scitotenv.2018.03.022

Source DB:  PubMed          Journal:  Sci Total Environ        ISSN: 0048-9697            Impact factor:   7.963


  2 in total

1.  Hydrodynamic and water quality modeling of a large floodplain lake (Poyang Lake) in China.

Authors:  Bing Li; Guishan Yang; Rongrong Wan; Hengpeng Li
Journal:  Environ Sci Pollut Res Int       Date:  2018-10-16       Impact factor: 4.223

2.  Chemical and microbiological risk assessment of urban river water quality in Vietnam.

Authors:  Kien Thanh Nguyen; Hung Manh Nguyen; Cuong Kim Truong; Mohammad Boshir Ahmed; Yuhan Huang; John L Zhou
Journal:  Environ Geochem Health       Date:  2019-05-07       Impact factor: 4.609

  2 in total

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