Conservation management practices reduce non-point source pollution from grazed pastures

Abstract. This study aimed to develop a risk-based approach for determining control areas to manage non-point source pollution, developing a framework to prioritize catchments by considering the characteristics of polluted runoff from non-point sources. The best management, decision-making, and scientific approaches, such as the technique for order of preference by similarity to ideal solution (TOPSIS) and the Delphi technique, are required for the designation of control areas and the application of the best management practices to the control areas. Multi-criteria decision-making (MCDM) methods can handle the diversity and complexity of non-point source pollution. The Delphi technique was employed for selecting the assessment criteria/sub-criteria and determining their weights. Sub-criteria for each catchment unit were scored with either a quantitative or qualitative scale. All non-point pollution sources in mainland Republic of Korea were included, with the exception of a few islands, with catchment prioritization and pollution vulnerability evaluations shown as thematic maps. This study contributes to the field by developing a new risk-based approach for ranking and prioritizing catchments; this provides valuable information for the Ministry of Environment to use to identify control areas and manage non-point source pollution.

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Reductions in non-point source pollution through different management practices for an agricultural watershed in the Three Gorges Reservoir Area

Journal of Environmental Sciences ◽

10.1016/s1001-0742(09)60091-7 ◽

2010 ◽

Vol 22 (2) ◽

pp. 184-191 ◽

Cited By ~ 37

Author(s):

Yaowu Tian ◽

Zhilin Huang ◽

Wenfa Xiao

Keyword(s):

Point Source ◽

Three Gorges Reservoir ◽

Management Practices ◽

Agricultural Watershed ◽

Three Gorges Reservoir Area ◽

Three Gorges ◽

Point Source Pollution ◽

Reservoir Area ◽

The Three Gorges ◽

Non Point Source Pollution

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Agricultural Nonpoint Source Pollution Model Analysis and Application

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.178-181.926 ◽

2012 ◽

Vol 178-181 ◽

pp. 926-929

Author(s):

Qing Yang ◽

Sheng Nan Sun ◽

Zheng Hai Jiang ◽

Li Xian Ying ◽

Zhe Jun Liu

Keyword(s):

Point Source ◽

Best Management Practices ◽

Management Practices ◽

Swat Model ◽

Model Analysis ◽

Point Source Pollution ◽

Mechanism Model ◽

3S Technology ◽

Improved Model ◽

Non Point Source Pollution

With the point source pollution was effectively treated, non-point source pollution, especially the agricultural non-point source pollution (ANPSP), is becoming the main problem in environment. The research is focused on the model analysis and application, which could be scientifically distinguish and effectually control ANPSP. Four kinds of models were introduced here with the development of non-point source pollution, as experience statistical model, mechanism model, function model, improved model by 3S technology and the uncertain analyze. Among these models, HSPF and SWAT model were successfully applied in best management practices (BMP) for ANPSP control. In the future, our country should base on the introduction of the foreign mature techniques, which combine the 3S technology and the uncertain improved model, then enhance the autonomous model research and build the basic database.

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The Adoption of Best-Management Practices by Louisiana Dairy Producers

Journal of Agricultural and Applied Economics ◽

10.1017/s1074070800021970 ◽

2004 ◽

Vol 36 (1) ◽

pp. 229-240 ◽

Cited By ~ 39

Author(s):

Noro C. Rahelizatovo ◽

Jeffrey M. Gillespie

Keyword(s):

Data Analysis ◽

Point Source ◽

Best Management Practices ◽

Count Data ◽

Management Practices ◽

Negative Binomial ◽

Farm Size ◽

Point Source Pollution ◽

Best Management ◽

Non Point Source Pollution

This study examines the adoption of best-management practices (BMPs) in terms of the total number of practices implemented up to a certain period, using count data analysis. Poisson and negative binomial regressions were used to examine the likely determinants of producers' decisions to adopt greater numbers of technologies, and the specific case of dairy producers' adoption of BMPs was explored. Our results emphasize the significant effect of producers' awareness of the efforts to control non-point source pollution, information about BMPs, farm size, producer's educational attainment, and risk aversion on the number of BMPs adopted.

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