Developing and testing a best management practices tool for estimating effectiveness of nonpoint source pollution control

Abstract

Best management practices (BMPs) are being implemented to reduce nonpoint sources pollution in China and worldwide. The effectiveness of individual BMPs is usually assessed through controlled experiments. Field evaluation of the effectiveness of a great majority of BMPs is limited by cost of implementation, site-specific response, and length of time needed to document reliable response. Nonpoint source pollution (NPS) models are increasingly relied upon to estimate water quality response to BMP implementation. This study has developed and tested a tool for estimating the effectiveness of BMPs in controlling NPS pollution by collecting and analyzing existing data from previous studies. It includes 60 BMPs grouped into six classes. Data from combined soil and slope analyses were used to design a BMP effectiveness estimator driven by hydrologic soil groups and slope classes using Visual Basic for Applications and Structured Query Language. This tool includes five primary functions, namely: (1) effectiveness assessment for single or combined BMP, (2) statistical analyses for BMP effectiveness; (3) informational inquiry about individual BMPs; (4) updating and editing the BMPs database; and (5) external expansion as new information becomes available. The tool was tested and validated for BMPs selection in a 27.28 km2 watershed, located within the upper watershed of the Miyun Reservoir in Beijing. Results demonstrate that the tool can be served as an efficient and easy tool for identifying potentially useful BMPs in agricultural areas in China. Overall, this will also allow water environmental professionals to make more confident and accurate BMP recommendations and manage watersheds more effectively.