高原农业流域磷流失风险评价及关键源区识别——以凤羽河流域为例  被引量:9

Assessing Risk of Non-point Source Phosphorus Loss and Identifying Critical Source Areas in a Chinese Highland Agricultural Watershed

在线阅读下载全文

作  者:李文超[1,2] 刘申[1,2] 雷秋良[1,2] 翟丽梅[1,2] 王洪媛[1,2] 罗春燕[1,2] 刘宏斌[1,2] 任天志[3] 

机构地区:[1]农业部面源污染控制重点实验室,北京100081 [2]中国农业科学院农业资源与农业区划研究所,北京100081 [3]农业部环境保护科研监测所,天津300191

出  处:《农业环境科学学报》2014年第8期1591-1600,共10页Journal of Agro-Environment Science

基  金:公益性行业(农业)科研专项(201003014)

摘  要:以Iowa磷指数模型为基础,根据中国高原特征并参考其他磷指数模型评价体系对其进行简化和修正,建立了中国高原农业流域磷指数评价体系,并以洱海源头典型小流域凤羽河流域为例,分别对溶解态磷和颗粒态磷面源流失风险进行了评价及关键源区的识别。结果表明,两种形态的磷流失较高和最高风险区均分布于河流两侧100 m的范围内。溶解态磷流失较高和最高风险区主要为河流中下游的农田区,而颗粒态磷流失较高和最高风险区在河流上游草地和河流中下游的农田区均有分布;溶解态磷流失关键源区为中下游河流两侧100m范围的农田区,颗粒态磷流失关键源区为上中下游河流两侧100 m范围的草地和农田。研究结果为实现流域面源磷流失高效防控奠定了基础,同时表明新建立的磷指数评价体系适用于高原流域开展磷流失风险评价及关键源区识别。Based on Iowa P index model and other P index evaluation systems, a Highland Agricultural Watershed P Index Evaluation System(HAWPES)was developed and used to assess the risk of P loss and identify critical source areas by taking Fengyu River watershed,Yunnan Province as an example. Phosphorus losses in dissolved(runoff)and particulate(erosion)forms were assessed. High risk areas of P loss were located within the extent of 100 meters away from both sides of the river. Dissolved P losses mainly occurred in the farmland areas in middle and lower parts of the river, while particulate P losses happened both in farmland areas in middle and lower parts of the river and in the meadows in the upper part of the river. These results provide a basis for an effective and efficient watershed environmental management plan. The study reveals that this new P index evaluation system could be applied successfully to assessment of P loss risk and identification of critical source areas for watershed best environmental management.

关 键 词:磷指数 磷流失 溶解态磷 颗粒态磷 关键源区 

分 类 号:X820.4[环境科学与工程—环境工程]

 

参考文献:

正在载入数据...

 

二级参考文献:

正在载入数据...

 

耦合文献:

正在载入数据...

 

引证文献:

正在载入数据...

 

二级引证文献:

正在载入数据...

 

同被引文献:

正在载入数据...

 

相关期刊文献:

正在载入数据...

相关的主题
相关的作者对象
相关的机构对象