基于GIS和MUSLE的东北沟小流域非点源污染关键区识别  

Identification of Critical Non-point Source Pollution Areas in Dongbeigou Watershed Based on GIS and MUSLE

作　　者：刘楠[1] 谢永生[1,2] 索改弟[1] 景民晓[1] 陈磊[2] 

机构地区：[1]西北农林科技大学资源环境学院,陕西杨凌712100 [2]中国科学院水利部水土保持研究所,陕西杨凌712100

出　　处：《水土保持研究》2014年第2期123-126,2,共4页Research of Soil and Water Conservation

基　　金：国家科技支撑计划课题"农田水土保持工程与耕作关键技术研究"(2011BAD31B01);水利部公益性行业科研专项"工程开挖面与堆积体水土流失测算技术研究"(201201048);"风力作用下扰动地表侵蚀预报关键技术研究"(201201047)

摘　　要：以河北省平泉县东北沟小流域DEM、土地利用类型和土壤调查数据为基础,在地理信息系统(GIS)的支持下,运用修正的通用土壤流失方程(MUSLE)对研究区非点源污染进行关键区识别及分级。结果表明:关键区按所占面积从大到小依次为低风险关键区、高风险关键区和中风险关键区,且各区主要沿水域分布。关键区中农业用地占到了流域农业用地总面积的37.3%,而随着风险等级的提高,关键区中农业用地所占比例显著增加。研究区非点源污染的主要来源是沿水域分布的农业用地,与实际情况吻合,研究结果能为研究区非点源污染治理提供科学指导和理论支持。将GIS与MUSLE模型相结合能够快速识别非点源污染关键区,该方法科学有效,具有很强的适用性。Based on DEM and the survey data of land use and soil of Dongbeigou watershed, this paper combined GIS and MUSLE model to identify the critical non-point source pollution areas, and then graded the areas. The results showed that： （1） in descending order, the critical areas were ranged as low risk area, high risk area and moderate risk area. The critical areas mainly distributed along the river; （2） among the critical areas, the agricultural land took 37.3 percent of total agricultural land in the watershed, the proportion of the agricultural land increased significantly as the risk level upgraded, the agricultural lands distributing along the river were the main sources of the pollution, which was in accord with actual situation. The result can provide the basis for further pollution control. Combined with GIS technology, MUSLE model can rapidly identify the critical non-point source pollution areas. This method is scientific and reasonable, and it is of strong adaptability.

关 键 词：非点源污染 关键区 GIS MUSLE 

分 类 号：X171.5[环境科学与工程—环境科学] TP79[自动化与计算机技术—检测技术与自动化装置]