中文关键词北运河上游非点源污染风险分区PNPI模型指数函数法权重 英文关键词upper Beiyun River basinnon-point source pollutionrisk zoningPNPI modelexponential function methodweights

作者	单位	E-mail
李华林	北京林业大学水土保持学院, 北京 100083	lihualin@bjfu.edu.cn
张建军	北京林业大学水土保持学院, 北京 100083
张耀方	北京市水科学技术研究院, 北京 100048
常国梁	北京市水科学技术研究院, 北京 100048
时迪迪	北京林业大学水土保持学院, 北京 100083
徐文静	北京林业大学水土保持学院, 北京 100083
宋卓远	北京林业大学水土保持学院, 北京 100083
于佩丹	北京林业大学水土保持学院, 北京 100083
张守红	北京林业大学水土保持学院, 北京 100083 北京市水土保持工程技术研究中心, 北京 100083	zhangs@bjfu.edu.cn

中文摘要 非点源污染已成为影响水生态环境和人类健康的重要因素之一，而解析非点源污染风险时空变化特征是非点源污染治理的重要前提.基于1980~2020年土地利用数据，采用潜在非点源污染指数（potential non-point pollution index，PNPI）模型探究基于不同赋权方法的北运河上游潜在非点源污染风险时空变化特征.结果表明：①流域潜在非点源污染风险呈东南部高西北部低的空间特征.研究时序内流域潜在非点源污染极高和高风险区面积呈减少趋势，极高和高风险区主要土地利用类型由旱地、水田和果园逐渐变为城镇用地和农村居民地.②均方差决策法、熵值法、变异系数法和专家打分法均得出土地利用指标权重最大，平均权重分别为0.46、0.53、0.45和0.48，而不同赋权方法确定的径流指标和距离指标权重差异较大，得出的各非点源污染风险等级区的面积占比差异也较大.③指数函数法通过构建土地利用指标、径流指标和距离指标的指数函数描述源因子与运输因子之间的关系，输出结果更符合流域非点源污染风险空间分布特征，极低和极高风险区面积占比分别为54.22%和6.23%.以上结果可为流域非点源污染风险分析及治理提供科学参考. 英文摘要 Non-point source pollution has become an important factor affecting the aquatic ecological environment and human health, and the analysis of spatial-temporal variations in non-point source pollution risks is an important prerequisite for pollution control. Based on land-use and land-cover data from 1980 to 2020, the potential non-point source pollution index (PNPI) model was applied in the upper Beiyun River Basin using different weighting methods. The results showed that:① The potential risk of non-point source pollution is high in the southeast and low in the northwest of the basin. Between 1980 and 2020, the total area of extremely high-risk and high-risk non-point source pollution regions showed a decreasing trend, and the main types of land use for extremely high-risk and high-risk regions gradually evolved from paddy fields, drylands, and orchards to urban and rural residential land; ② The weighting of the land use index determined by the mean-square deviation decision, entropy, coefficient of variation, and expert scoring methods was largest among the three PNPI indices, with average weightings of 0.46, 0.53, 0.45, and 0.48, respectively. However, the weightings for runoff and distance indices determined by different weighting methods were notably different, and the proportions of regions with different levels of non-point source pollution risk also varied; ③ The exponential function method, which describes the relationship between source factors and transport factors by constructing the exponential functions of land use, runoff, and distance indices, provided results that are more consistent with the spatial distribution characteristics of non-point source pollution risk in the basin. The proportions of extremely low-risk and extremely high-risk regions are 54.22% and 6.23%, respectively. These results provide scientific reference for risk analysis and the control of non-point source pollution in this basin.

PDF全文下载地址:

https://www.hjkx.ac.cn/hjkx/ch/reader/create_pdf.aspx?file_no=20210624&flag=1&journal_id=hjkx&year_id=2021