Department of Earth Sciences, Indian Institute of Technology Kanpur, Kanpur 208016, India.
School of Geography and the Environment, University of Oxford, OX1 3QY, UK.
Sci Total Environ. 2018 Aug 1;631-632:201-215. doi: 10.1016/j.scitotenv.2018.03.022. Epub 2018 Mar 16.
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 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>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: 0.88-0.94) and phosphate (R: 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.
本研究利用长期（1991-2009 年）逐月数据，对恒河支流拉姆甘加河的水质特征进行了分析，并将氮综合集水区模型（INCA-N）和磷综合集水区模型（INCA-P）应用于该集水区。使用流量（1993-2011 年）、磷酸盐（1993-2010 年）和硝酸盐（2007-2010 年）浓度对模型进行了校准和验证。根据皮尔逊相关系数、纳什-斯库利和百分比偏差统计以及对输出结果的直观检查，对模型结果进行了评估。季节性变化研究表明，与其他季节相比，前季风季节的养分浓度较高。尽管由于稀释作用，高流量期间的浓度降低，但低流量期间的高养分浓度对河流的水生生物构成严重威胁。水文模型的校准效果令人满意，R 和 NS 值分别在 0.6-0.8 和 0.4-0.8 之间。INCA-N 和 INCA-P 成功地捕捉到了养分浓度的季节性趋势，R 值大于 0.5，每月平均值的 PBIAS 值在±17%以内。尽管在低流量期间检测到高浓度，但约 50%的养分负荷是由季风高流量输送的。下游集水区的特点是高流量时养分输送量大，工业和农业活动的额外养分供应也普遍存在。使用模型结果和比率估计器负荷计算技术计算了集水区季节性硝酸盐（R：0.88-0.94）和磷酸盐（R：0.62-0.95）的负荷。平均而言，每年估计有 548 吨磷（以磷酸盐计）和 77051 吨氮（以硝酸盐计）从拉姆甘加河输送到恒河。总的来说，该模型成功地复制了拉姆甘加流域的季节性变化和养分通量的广泛空间变异性的集水区动态。
