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Dynamic export coefficient model for evaluating the effects of environmental changes on non-point source pollution

机译:动态出口系数模型评估环境变化对非点源污染的影响

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The classic export coefficient model has been questioned due to its fixed coefficient, especially for those large-scale watersheds where great temporal-spatial heterogeneity exists. In this paper, a dynamic export coefficient model (DECM) was proposed for simulating non-point source (NPS) pollution by incorporating the impacts of factors on export coefficients. The relationships between rainfall, slope, soil, land use, other factors and export coefficients were constructed at relatively smaller catchment based on the information of mechanistic-based model, while these dynamic export coefficients were then extended to the large ungauged basins. This new model was tested in the Three Gorges Reservoir Region (TGRR), China. The results indicated the new method improved the accuracy of large-scale NPS prediction as well as reducing the computation burden. The rainfall temporal variability was identified as the major factor influencing the variability of flow and NPS pollution with the coefficient of variation being 0.1678 and 0.2046, respectively. Using the new method, the Long watershed, the Jialing watershed, the Quxi watershed, the Xiangxi watershed and the main stream in the TGRR were identified as those sensitive regions under the changing environment. The DECM could be extended to other large scale to quantify the NPS pollution, especially data-poor watersheds.
机译:由于其固定系数,经典出口系数模型已经受到质疑,特别是对于那些存在较大的时间空间异质性的大规模流域。在本文中,提出了一种通过纳入导出系数对因素的影响来模拟非点源(NPS)污染的动态出口系数模型(DECM)。基于基于机械的模型的信息,在相对较小的集水区内建造了降雨,坡,土壤,土地利用,其他因素和出口系数之间的关系,而这些动态出口系数随后将延伸到大型未凝固的盆地。这一新模型在三峡库区(TGRR)中进行了测试。结果表明,新方法提高了大规模NPS预测的准确性,并降低了计算负担。降雨时间变异性被鉴定为影响流动变化和NPS污染的主要因素分别为0.1678和0.2046分别为0.1678和0.2046。使用新方法,长流域,嘉陵流域,祛痘流域,湘西流域和TGRR中的主流被确定为改变环境下的那些敏感区域。 DECM可以扩展到其他大规模,以量化NPS污染,尤其是数据差的流域。

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