基于SWAT模型的平原河湖水网区小流域径流过程模拟
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摘要
模拟湖北省松滋市小南海流域径流过程,为未来运用SWAT模型诊断小南海流域面源污染问题提供技术支撑。小南海流域地处洞庭湖生态经济区最上游,是洞庭湖上游重要的生态涵养地。流域处于山地丘陵地区与平原河湖地区的交界地段,上游地区为山地丘陵区,下游地区为平原河湖区,水系结构和产流汇流过程较为复杂。该流域内无水文站点,水文资料缺失。选择了洞庭湖流域、鄱阳湖流域与梁子湖流域3个相似流域运用SWAT模型时所采用的水文参数,运用参数移植法确定了小南海流域的水文参数;对比基于DEM直接定义水系、使用Burn In功能对河网进行修正和Pre-defined streams预定义水系3种水系定义方法,选择最适合的Pre-defined streams方法按照现状进行水文模拟。模型划分了25个子流域,验证结果表明确定系数R~2与Nash-Sutcliffe效率系数E_(ns)均大于0.85,表明使用水系预定义法及参数移植法的SWAT模型模拟小南海流域径流过程是可行的。
The Xiaonanhai River basin is a complex water network located in the upper reach of Dongting Lake, and it is an important ecological conservation area. In 2016, we simulated the runoff from the Xiaonanhai River basin using the Soil and Water Assessment Tool(SWAT) model. The SWAT model database for the basin included the digital elevation model(DEM), soil type, land use, hydrology and meteorology. There is no hydrological station in the river basin and parameter transfer was used to estimate hydrological parameters, based on parameter selection for SWAT modeling in three similar watersheds(those for Dongting Lake, Poyang Lake and Liangzi Lake). Further, the water systems in Xiaonanhai River basin were defined in three ways:(1) direct definition, based on the DEM;(2) river network modification using the Burn-In function;(3) using the pre-defined watershed and stream dataset in ArcSWAT. Results showed that the pre-defined streams method resulted in characteristics most consistent with those observed in the Xiaonanhai River watershed. After basin definition was completed, it was divided into 25 sub-basins and hydrological simulation of the Xiaonanhai river watershed was carried out. Flow data, calculated using the runoff formula, was used to verify the model. Verification results show that the determination coefficient(R~2) and the Nash-Sutcliffe efficiency coefficient(ENS) were >0.85. Although hydrological data was lacking, the SWAT model, using pre-defined hydrology and parameter migration methods, is reliable for simulating runoff in the Xiaonanhai River basin. The study provides technical support for assessing non-point source(NPS) pollution in the Xiaonanhai watershed using the SWAT model, as efforts to reduce NPS continue.
The Xiaonanhai River basin is a complex water network located in the upper reach of Dongting Lake, and it is an important ecological conservation area. In 2016, we simulated the runoff from the Xiaonanhai River basin using the Soil and Water Assessment Tool(SWAT) model. The SWAT model database for the basin included the digital elevation model(DEM), soil type, land use, hydrology and meteorology. There is no hydrological station in the river basin and parameter transfer was used to estimate hydrological parameters, based on parameter selection for SWAT modeling in three similar watersheds(those for Dongting Lake, Poyang Lake and Liangzi Lake). Further, the water systems in Xiaonanhai River basin were defined in three ways:(1) direct definition, based on the DEM;(2) river network modification using the Burn-In function;(3) using the pre-defined watershed and stream dataset in ArcSWAT. Results showed that the pre-defined streams method resulted in characteristics most consistent with those observed in the Xiaonanhai River watershed. After basin definition was completed, it was divided into 25 sub-basins and hydrological simulation of the Xiaonanhai river watershed was carried out. Flow data, calculated using the runoff formula, was used to verify the model. Verification results show that the determination coefficient(R~2) and the Nash-Sutcliffe efficiency coefficient(ENS) were >0.85. Although hydrological data was lacking, the SWAT model, using pre-defined hydrology and parameter migration methods, is reliable for simulating runoff in the Xiaonanhai River basin. The study provides technical support for assessing non-point source(NPS) pollution in the Xiaonanhai watershed using the SWAT model, as efforts to reduce NPS continue.
引文
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孟现勇,师春香,刘时银,等,2016.CMADS数据集及其在流域水文模型中的驱动作用——以黑河流域为例[J].人民珠江,37(7):1-19.
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松滋市人民政府,2016.小南海湖综合治理规划[R].
王蕾,魏晓妹,降亚楠,等,2017.关中平原灌区SWAT模型基础数据库的构建[J].水电能源科学,35(7):13-17.
郑捷,李光永,韩振中,等,2011.改进的SWAT模型在平原灌区的应用[J].水利学报,42(1):88-97.
左俊杰,蔡永立,2011.平原河网地区汇水区的划分方法——以上海市为例[J].水科学进展,22(3):337-343.
Ning JC,Liu GH,Liu QS,et al,2012.Spatial discretization of hydrological response units and improved SWAT model[J]. Advances in Water Science, 23(1):14-20.
Schmalz B,Tavares F,Fohrer N,2008.Modelling hydrological processes in mesoscale lowland river basins with SWAT—capabilities and challenges[J]. Hydrological Sciences Journal,53(5):989-1000.
Sun W,Wang Y,Wang G,et al,2017. Physically based distributed hydrological model calibration based on a short period of streamflow data:case studies in four Chinese basins[J].Hydrology and Earth System Sciences,21(1):251-65.
程艳,敖天其,黎小东,等,2016.基于参数移植法的SWAT模型模拟嘉陵江无资料地区径流[J].农业工程学报,32(13):81-86.
陈军宁,2013.基于swat模型的鄱阳湖区非点源污染模拟研究[D]. 南昌:南昌大学.
樊琨,马孝义,李忠娟,等,2015. SWAT模型参数校准方法对比研究[J].中国农村水利水电,(4):77-81.
范丽丽,沈珍瑶,刘瑞民,等,2008.基于SWAT模型的大宁河流域非点源污染空间特性研究[J].水土保持通报,(4):133-137.
侯伟,廖晓勇,张岩,等,2015.三峡库区典型小流域SWAT模型基础数据库构建[J].西藏大学学报(自然科学版),30(2):118-124.
李硕,赖正清,王桥,等,2013.基于SWAT模型的平原河网区水文过程分布式模拟[J].农业工程学报,29(6):106-112.
梁新强,2016.非点源污染SWAT模型评估与应用[M].北京:科学出版社.
孟现勇,师春香,刘时银,等,2016.CMADS数据集及其在流域水文模型中的驱动作用——以黑河流域为例[J].人民珠江,37(7):1-19.
秦云,2017.基于SWAT模型的梁子湖流域非点源污染分析[D].武汉:湖北大学.
松滋市人民政府,2016.小南海湖综合治理规划[R].
王蕾,魏晓妹,降亚楠,等,2017.关中平原灌区SWAT模型基础数据库的构建[J].水电能源科学,35(7):13-17.
郑捷,李光永,韩振中,等,2011.改进的SWAT模型在平原灌区的应用[J].水利学报,42(1):88-97.
左俊杰,蔡永立,2011.平原河网地区汇水区的划分方法——以上海市为例[J].水科学进展,22(3):337-343.
Ning JC,Liu GH,Liu QS,et al,2012.Spatial discretization of hydrological response units and improved SWAT model[J]. Advances in Water Science, 23(1):14-20.
Schmalz B,Tavares F,Fohrer N,2008.Modelling hydrological processes in mesoscale lowland river basins with SWAT—capabilities and challenges[J]. Hydrological Sciences Journal,53(5):989-1000.
Sun W,Wang Y,Wang G,et al,2017. Physically based distributed hydrological model calibration based on a short period of streamflow data:case studies in four Chinese basins[J].Hydrology and Earth System Sciences,21(1):251-65.