文章摘要
齐作达, 亢戈霖, 王玉秋.GWLF模型的改进及其在新安江流域的应用研究Journal of Water Resources and Water Engineering[J].,2020,31(4):17-23
GWLF模型的改进及其在新安江流域的应用研究
Improvement of GWLF model and its application to Xin′anjiang River Watershed
  
DOI:10.11705/j.issn.1672-643X.2020.04.03
中文关键词: 非点源模型  流域污染负荷方程(GWLF)  流量  泥沙  溶解性氮  溶解性磷
英文关键词: non-point source model  generalized watershed loading function (GWLF)  flow  sediment  dissolved nitrogen  dissolved phosphorus
基金项目:国家重大科技专项 (水专项) 项目(2017ZX07301-001-06)
Author NameAffiliation
QI Zuoda1, KANG Gelin2, WANG Yuqiu2 (1.交通运输部天津水运工程科学研究所港口水工建筑技术国家工程实验室工程泥沙交通行业重点实验室天津 300456 2.南开大学 环境科学与工程学院 天津市跨介质复合污染环境治理技术重点实验室 天津 300350) 
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中文摘要:
      通用流域污染负荷方程(generalized watershed loading function,简称GWLF)作为一个简单有效的集总参数流域模型已经受到了国内外研究者的广泛认可。在笔者前期研究成果的基础上,对原始GWLF模型的算法和已有水文框架进行了深入修改,添加了河道模块内泥沙悬浮、沉积过程以及污染物衰减过程,进一步增加了模型在空间属性基础上的通用性。以安徽省新安江屯溪监测站为收口断面的上游流域为研究区域,对改进后的GWLF模型(revised GWLF)进行了应用测试,并在月尺度上针对流量、泥沙量、溶解性氮负荷量和溶解性磷负荷量的模型输出结果与原始GWLF模型进行了比较。3项统计学指标和时间序列图表明,改进版模型能够在不添加额外数据需求的前提下,更好地重现流域内水文、泥沙和水质的循环过程。
英文摘要:
      The generalized watershed loading function (GWLF) has been widely recognized as a simple and effective lumped parameter watershed model by researchers at home and abroad. On the basis of the previous work of the authors, the original GWLF model algorithm and the existing hydrological framework were further modified with the addition of the suspension and deposition process of sediment, and the attenuation process of pollutants in the river channel, which enhanced the applicability of the model spatially. Then the revised GWLF model was tested in the simulation of the upstream of Xin′anjiang River (bounded by Tunxi monitoring station) in Anhui Province and the simulation results of monthly flow, sediment, dissolved nitrogen and dissolved phosphorous were compared with those of the original model. The time series analysis of three commonly used statistical indexes show that the revised model performs better at reflecting the cycle of hydrology, sediment and water quality in the watershed without the requirement of additional data.
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