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高分辨率数据驱动的流域非点源污染输出风险评估方法
引用本文:顾晶晶,冶运涛,董甲平,蒋云钟,曹引,赵红莉.高分辨率数据驱动的流域非点源污染输出风险评估方法[J].环境科学,2022,43(6):3140-3148.
作者姓名:顾晶晶  冶运涛  董甲平  蒋云钟  曹引  赵红莉
作者单位:天津大学建筑工程学院, 天津 300072;中国水利水电科学研究院水资源研究所, 北京 100038
基金项目:国家重点研发计划项目(2017YFC0405801);中国水利水电科学研究院基本科研业务费专项(资基本科研01882106)
摘    要:近年来,非点源污染已成为我国部分水库水质恶化的主要原因.以潘家口水库流域为例,引入动态降水因子和地形因子改进经典的输出风险模型,结合高分辨率的卫星反演降水产品(GPM)和高分六号卫星影像,建立高分辨率数据驱动的非点源污染输出风险评估模型,开展潘家口水库流域的非点源污染输出风险时空分布特征研究.结果表明,研究区2018年非点源污染输出风险较高,其中氮元素污染输出高风险和较高风险区约占流域总面积的70.6%,磷元素污染输出无高风险区,较高风险区约占流域总面积的21.9%.分析流域非点源污染输出风险时空分布特征,发现4~9月潘家口水库流域非点源污染输出风险呈现先增后减趋势,在7月和8月最高,与流域降水时空分布一致;结合土地利用分布特征分析,流域上游以耕地为主,城市集中在流域下游,受农业生产和人类活动的影响,这些区域的非点源污染输出风险较高.针对非点源污染输出风险时空分布特征,应制定合理的农业施肥方式,规划非点源污染“源-汇”景观布局以及建设植被缓冲带.

关 键 词:非点源污染  输出风险评估  高分辨率数据驱动  输出风险模型  潘家口水库流域
收稿时间:2021/9/27 0:00:00
修稿时间:2021/11/8 0:00:00

Risk Assessment Method of Non-point Source Pollution Output for Watershed Using High Resolution Data
GU Jing-jing,YE Yun-tao,DONG Jia-ping,JIANG Yun-zhong,CAO Yin,ZHAO Hong-li.Risk Assessment Method of Non-point Source Pollution Output for Watershed Using High Resolution Data[J].Chinese Journal of Environmental Science,2022,43(6):3140-3148.
Authors:GU Jing-jing  YE Yun-tao  DONG Jia-ping  JIANG Yun-zhong  CAO Yin  ZHAO Hong-li
Institution:School of Civil Engineering, Tianjin University, Tianjin 300072, China;Department of Water Resources, China Institute of Water Resources and Hydropower Research, Beijing 100038, China
Abstract:In recent years, non-point source pollution has become the main cause of water quality deterioration in some reservoirs in China. Taking the Panjiakou Reservoir as an example, the classical output risk model was improved by introducing a precipitation factor and terrain factor. Combined with high-resolution satellite precipitation products (GPM) and GF-6 satellite images, a high-resolution data-driven risk assessment method for non-point source pollution output was established to study the temporal and spatial distribution characteristics of non-point source pollution output risk in the Panjiakou Reservoir basin. The results showed that the non-point source pollution output risk was high in the study area in 2018. The areas with higher and highest risk of nitrogen pollution output accounted for approximately 70.6% of the total watershed area, whereas the higher risk of phosphorus pollution output accounted for approximately 21.9%. The temporal and spatial distribution characteristics of non-point source pollution output risk in the Panjiakou Reservoir basin were analyzed. It was found that the non-point source pollution output risk in the Panjiakou Reservoir basin increased first and then decreased from April to September. This was consistent with the spatial and temporal distribution of precipitation in the basin. Combined with the analysis of land use distribution characteristics, the upstream area of the basin was mainly cultivated land, whereas cities were concentrated in the downstream portion of the basin. Affected by agricultural production and human activities, the risk of non-point source pollution output was higher in these regions. In view of the temporal and spatial distribution characteristics of non-point source pollution output risk, it is necessary to formulate a reasonable agricultural fertilization method, plan the landscape layout of source-sinks, and construct vegetation buffer zones.
Keywords:non-point source pollution  output risk assessment  high-resolution data-driven  output risk model  Panjiakou Reservoir basin
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