Review on non-point source pollution in Miyun Reservoir

2009 ◽  
Vol 16 (5) ◽  
pp. 1311-1316
Author(s):  
Sheng-Bin HUANG
2008 ◽  
Vol 58 (11) ◽  
pp. 2235-2241 ◽  
Author(s):  
Yang Ou ◽  
Xiaoyan Wang

Miyun Reservoir is the major water source for Bijing, China. Currently, the water quality of Miyun reservoir is meso - trophict, mainly dur to the non-point source pollution (NPS) in the watershed. Phosphorus (P) is the limited factor. In this paper, Chaohe River basin, upstream of the Miyun Reservoir, is chosen as the study area, A modified P Index was developed to identify critical source areas (CSAs) of non-point source pollution by analyzing local hydrological and meteorological data, land use, soil, soil conservation, farmland management, population density, and livestock. The factors of livestock and population density are new factors added to the P Index system based on the actual local characteristics. It was found that the loss P from high-risk area accounts for only 7.95%. These areas are located mainly along streams. Livestock factor and the population density factor are most closely related to the CSAs downstream of Chaohe River basin. The management strategies are outlined according to the distribution characteristics of the critical source areas.


2002 ◽  
Vol 21 (1) ◽  
pp. 89-96 ◽  
Author(s):  
Wang Xiaoyan ◽  
Wang Yixun ◽  
Li Tingfang ◽  
He Wei ◽  
Hu Qiuju ◽  
...  

Water ◽  
2021 ◽  
Vol 13 (14) ◽  
pp. 1955
Author(s):  
Mingxi Zhang ◽  
Guangzhi Rong ◽  
Aru Han ◽  
Dao Riao ◽  
Xingpeng Liu ◽  
...  

Land use change is an important driving force factor affecting the river water environment and directly affecting water quality. To analyze the impact of land use change on water quality change, this study first analyzed the land use change index of the study area. Then, the study area was divided into three subzones based on surface runoff. The relationship between the characteristics of land use change and the water quality grade was obtained by grey correlation analysis. The results showed that the land use types changed significantly in the study area since 2000, and water body and forest land were the two land types with the most significant changes. The transfer rate is cultivated field > forest land > construction land > grassland > unused land > water body. The entropy value of land use information is represented as Area I > Area III > Area II. The shift range of gravity center is forest land > grassland > water body > unused land > construction land > cultivated field. There is a strong correlation between land use change index and water quality, which can be improved and managed by changing the land use type. It is necessary to establish ecological protection areas or functional areas in Area I, artificial lawns or plantations shall be built in the river around the water body to intercept pollutants from non-point source pollution in Area II, and scientific and rational farming in the lower reaches of rivers can reduce non-point source pollution caused by farming.


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