五华河流域非点源污染风险区和风险路径识别
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摘要
非点源污染是亟待解决的水环境问题之一,确定非点源污染过程中的潜在风险区和风险路径是解决非点源污染问题的关键。引入景观生态学中的最小累积阻力模型,以高污染负荷的耕地、建设用地为"源",运用表示下垫面产流性质的地形湿度指数和CN值构建阻力面,对五华河流域的非点源污染高风险区和风险路径进行可视化识别和分析。结果显示:(1)在下垫面产流作用下,五华河流域低产流区主要分布在流域西南部,高产流区呈"人"形贯穿全流域。(2)最小累积阻力模型能够有效识别流域内非点源污染风险区和风险路径,五华河流域非点源污染高风险区分布于迥龙、田心、龙母、铁场、登云、通衢、鹤市、紫市、岐岭、华城、转水、潭下、水寨等地的河道两岸,以耕地为"源"的非点源污染风险路径与建设用地为"源"的非点源污染风险路径在空间分布上差异较大。(3)耕地对五华河水质的影响大于建设用地对五华河水质的影响,耕地中的富营养物质和沉积物更容易随地表径流进入受纳水体。(4)流域尺度上治理以耕地为"源"的非点源污染应在邻近耕地的河流两岸建立一定宽度的植被缓冲区,治理以建设用地为"源"的非点源污染宜围绕关键源区进行治理。本研究为非点源污染风险区和风险路径的识别提供一种新的思路,为进一步开展非点源污染治理提供理论依据。
Non-point source pollution is one of the most severe problems impacting water environments. Identifying potential risk areas and risk paths contributing to non-point source pollution is the soution to this problem. This study introduces the minimum cumulative resistance model of landscape ecology, which is based on land use and soil mapping at a scale of 1∶100000 and DEM data with a resolution of 30 m. The model takes high pollution-loaded cultivated land and construction land as the main sources and uses the Topographic Wetness Index and Runoff Curve Numbers, which can describe the underlying resistance surface runoff yield characteristics, to visually identify and analyze the risk areas and risk paths of the Wuhua River Basin. The results show that underlying surface runoff production results in low-yield flow areas that are mainly concentrated in the southwest of the basin, while high-yield flow areas herringbone throughout the study area. The minimum cumulative resistance model can effectively identify the risk areas and risk paths in this basin. The high-risk areas of non-point source pollution are mainly distributed in Jionglong, Tianxin, Longmu, Tiechang, Dengyun,Tongqu, Heshi, Zishi, Qiling, Huacheng, Zhuanshui, Tanxia and Shuizai, which are located along both sides of the river. The spatial distributions of the risk paths of cultivated land and construction land are significantly different. The effects of cultivated land on water quality of the river are greater than those of construction land on it, and the nutrients and sediments from cultivated land are more likely to run into the receiving water via surface runoff. Vegetation buffer zones should be set up on both sides of the river adjacent to cultivated land when we deal with non-point source pollution that originates from cultivated land, and the harnessment of non-point source pollution originating from construction land should be monitored around major source areas. This study provides a novel method for the identification of source areas and risk paths of non-point source pollution and a theoretical basis to formulate future management strategies.
Non-point source pollution is one of the most severe problems impacting water environments. Identifying potential risk areas and risk paths contributing to non-point source pollution is the soution to this problem. This study introduces the minimum cumulative resistance model of landscape ecology, which is based on land use and soil mapping at a scale of 1∶100000 and DEM data with a resolution of 30 m. The model takes high pollution-loaded cultivated land and construction land as the main sources and uses the Topographic Wetness Index and Runoff Curve Numbers, which can describe the underlying resistance surface runoff yield characteristics, to visually identify and analyze the risk areas and risk paths of the Wuhua River Basin. The results show that underlying surface runoff production results in low-yield flow areas that are mainly concentrated in the southwest of the basin, while high-yield flow areas herringbone throughout the study area. The minimum cumulative resistance model can effectively identify the risk areas and risk paths in this basin. The high-risk areas of non-point source pollution are mainly distributed in Jionglong, Tianxin, Longmu, Tiechang, Dengyun,Tongqu, Heshi, Zishi, Qiling, Huacheng, Zhuanshui, Tanxia and Shuizai, which are located along both sides of the river. The spatial distributions of the risk paths of cultivated land and construction land are significantly different. The effects of cultivated land on water quality of the river are greater than those of construction land on it, and the nutrients and sediments from cultivated land are more likely to run into the receiving water via surface runoff. Vegetation buffer zones should be set up on both sides of the river adjacent to cultivated land when we deal with non-point source pollution that originates from cultivated land, and the harnessment of non-point source pollution originating from construction land should be monitored around major source areas. This study provides a novel method for the identification of source areas and risk paths of non-point source pollution and a theoretical basis to formulate future management strategies.
引文
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[2]Yin Cai,Liu Miao,Sun Fengyun,et al.Influencing factors of non-point source pollution of watershed based on boosted regression tree algorithm.Chinese Journal of Applied Ecology,2016,27(3):911-919.[尹才,刘淼,孙凤云,等.基于增强回归树的流域非点源污染影响因子分析.应用生态学报,2016,27(3):911-919.]
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[5]Li Zhuheng,Liu Miao,Li Chunlin,et al.Non-point source pollution simulation under land use change scenarios in HunTaizi River Watershed.Chinese Journal of Applied Ecology,2016,27(9):2891-2898.[李铸衡,刘淼,李春林,等.土地利用变化情景下浑河—太子河流域的非点源污染模拟.应用生态学报,2016,27(9):2891-2898.]
[6]White M J,Storm D E,Busteed P R,et al.Evaluating nonpoint source critical source area contributions at the watershed scale.Journal of Environmental Quality,2009,38(4):1654-1663.
[7]Zhou H,Gao C.Assessing the risk of phosphorus loss and identifying critical source areas in the Chaohu Lake Watershed,China.Environmental Management,2011,48(5):1033-1043.
[8]Zhou Huiping,Gao Chao,Zhu Xiaodong.Identification of critical source areas:An efficient way for agricultural nonpoint source pollution control.Acta Ecologica Sinica,2005,25(12):3368-3374.[周慧平,高超,朱晓东.关键源区识别:农业非点源污染控制方法.生态学报,2005,25(12):3368-3374.]
[9]Sivertun?,Prange L.Non-point source critical area analysis in the Gissel?Watershed using GIS.Environmental Modelling&Software,2003,18(10):887-898.
[10]Endreny T A,Eric F W.Watershed weighting of export coefficients to map critical phosphorous loading areas.Journal of the American Water Resources Association,2010,39(1):165-181.
[11]Hughes K J,Magette W L,Kurz I.Identifying critical source areas for phosphorus loss in Ireland using field and catchment scale ranking schemes.Journal of Hydrology,2005,304(1-4):430-445.
[12]Niraula R,Kalin L,Srivastava P,et al.Identifying critical source areas of nonpoint source pollution with SWAT and GWLF.Ecological Modelling,2013,268(23):123-133.
[13]Wang Niu,Lu Haiming,Zhou Ying,et al.Identifying critical source areas of non-point source phosphorus export based on topographic index.Journal of China Hydrology,2016,36(2):12-16.[王妞,陆海明,邹鹰,等.基于地形指数的流域非点源磷素输出关键源区识别.水文,2016,36(2):12-16.]
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[15]Dong J,Dai W,Shao G,et al.Ecological network construction based on minimum cumulative resistance for the city of Nanjing,China.ISPRS International Journal of Geo-Information,2015,4(4):2045-2060.
[16]Blazquez-Cabrera S,Gastón A,Beier P,et al.Influence of separating home range and dispersal movements on characterizing corridors and effective distances.Landscape Ecology,2016,31(10):2355-2366.
[17]Chen Xin,Peng Jian,Liu Yanxu,et al.Constructing ecological security patterns in Yunfu City based on the framework of importance-sensitivity-connectivity.Geographical Research,2017,36(3):471-484.[陈昕,彭建,刘焱序,等.基于“重要性—敏感性—连通性”框架的云浮市生态安全格局构建.地理研究,2017,36(3):471-484.]
[18]Wang J,Shao J,Wang D,et al.Identification of the"source"and"sink"patterns influencing non-point source pollution in the Three Gorges Reservoir Area.Journal of Geographical Sciences,2016,26(10):1431-1448.
[19]Fu Yonghu.The theory and patterns for designing dematerialization and low environmental risk land-use system in intensive agricultural area[D].Beijing:China Agricultural University,2016.[付永虎.高集约化农区投入减量化与低环境风险的土地利用系统设计:理论与模式[D].北京:中国农业大学,2016.]
[20]Djodjic F,Villa A.Distributed,high-resolution modelling of critical source areas for erosion and phosphorus losses.Ambio,2015,44(2):241-251.
[21]Liu Jie,Pang Shujiang,He Yangyang,et al.Critical area identification of phosphorus loss based on runoff characteristics in small watershed.Transactions of the Chinese Society of Agricultural Engineering,2017,33(20):241-249.[刘洁,庞树江,何杨洋,等.基于小流域产流特征的磷流失关键源区识别.农业工程学报,2017,33(20):241-249.]
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[23]Zhang Jiping,Qiao Qing,Liu Chunlan,et al.Ecological land use planning for Beijing City based on the minimum cumulative resistance model.Acta Ecologica Sinica,2017,37(19):6313-6321.[张继平,乔青,刘春兰,等.基于最小累积阻力模型的北京市生态用地规划研究.生态学报,2017,37(19):6313-6321.]
[24]Li Kai,Zeng Fantang,Fang Huaiyang,et al.Analysis on nitrogen and phosphorus loading of non-point sources in Shiqiao River Watershed based on L-THIA model.Environmental Science,2013,34(11):4218-4225.[李凯,曾凡棠,房怀阳,等.基于L-THIA模型的市桥河流域非点源氮磷负荷分析.环境科学,2013,34(11):4218-4225.]
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