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首页> 外文期刊>The Science of the Total Environment >Water quality assessment and catchment-scale nutrient flux modeling in the Ramganga River Basin in north India: An application of INCA model
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Water quality assessment and catchment-scale nutrient flux modeling in the Ramganga River Basin in north India: An application of INCA model

机译:印度北部拉姆甘加河流域的水质评估和集水规模养分通量模型:INCA模型的应用

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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 R2and 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.
机译:本研究使用长期(1991-2009年)每月数据分析了Rangganga(恒河的主要支流)的水质特征,并应用了氮(INCA-N)和磷(INCA-P)综合集水模型。 )到集水区。使用排放(1993–2011),磷酸盐(1993–2010)和硝酸盐(2007–2010)浓度对模型进行了校准和验证。基于皮尔逊相关性,纳什-苏克利夫和百分比偏差统计数据以及输出的外观检查,评估了模型结果。季节性变化研究显示,季风前季节的养分含量高于其他季节。在低流量时期,较高的养分浓度对河流的水生生物构成严重威胁,尽管由于稀释作用,在高流量期间其浓度会降低。 R2和NS值分别在0.6-0.8和0.4-0.8之间,可以令人满意地校准水文模型。 INCA-N和INCA-P成功捕获了养分浓度的季节性趋势,R2> 0.5,PBIAS在月平均值的±17%之内。尽管在低流量时期检测到高浓度,但季风高流量运输了约50%的养分。下游集水区的特点是高流量输送大量养分,而工业和农业实践也提供了更多的养分供应。流域的季节性硝酸盐(R2:0.88–0.94)和磷酸盐(R2:0.62–0.95)负荷是使用模型结果和比率估算器负荷计算技术计算得出的。据估计,平均每年每年从拉姆甘加河向恒河出口的磷(作为磷酸盐)约548吨(以磷酸盐计)和氮(作为硝酸盐)为77051吨。总体而言,该模型已经能够成功地根据Ramganga流域的养分通量的季节变化和大规模空间变异来再现流域动态。

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