Comparison of Linear and Non-Linear Optimization Models for Storm Water and Non-Point Source Pollution Best Management Practice Decision Support

2007 ◽  
Author(s):  
J. F. Limbrunner ◽  
R. M. Vogel ◽  
S. C. Chapra ◽  
P. H. Kirshen
Keyword(s):  
Decision Support ◽  
Point Source ◽  
Management Practice ◽  
Linear Optimization ◽  
Best Management Practice ◽  
Storm Water ◽  
Optimization Models ◽  
Point Source Pollution ◽  
Best Management ◽  
Non Point Source Pollution

Ecology Ditch: A Best Management Practice for Storm Water Runoff Mitigation

2003 ◽  
Vol 8 (3) ◽  
pp. 111-122 ◽  
Author(s):  
Michael E. Barber ◽  
Steven G. King ◽  
David R. Yonge ◽  
Wade E. Hathhorn
Keyword(s):  
Management Practice ◽  
Best Management Practice ◽  
Storm Water ◽  
Water Runoff ◽  
Best Management ◽  
Storm Water Runoff

scholarly journals Framework to prioritize watersheds for diffuse pollution management in the Republic of Korea: application of multi-criteria analysis using the Delphi method

2019 ◽  
Vol 19 (12) ◽  
pp. 2767-2779 ◽  
Author(s):  
Gyumin Lee ◽  
Kyung Soo Jun ◽  
Minji Kang
Keyword(s):  
Decision Making ◽  
Point Source ◽  
Best Management Practices ◽  
Delphi Technique ◽  
Management Practices ◽  
Point Sources ◽  
Republic Of Korea ◽  
Point Source Pollution ◽  
Best Management ◽  
Non Point Source Pollution

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.

scholarly journals The Adoption of Best-Management Practices by Louisiana Dairy Producers

2004 ◽  
Vol 36 (1) ◽  
pp. 229-240 ◽  
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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