Abstract
Best management practices (BMPs) have been widely used to address hydrology and water quality issues in both agricultural and urban areas. Increasing numbers of BMPs have been studied in research projects and implemented in watershed management projects, but a gap remains in quantifying their effectiveness through time. In this paper, we review the current knowledge about BMP efficiencies, which indicates that most empirical studies have focused on short-term efficiencies, while few have explored long-term efficiencies. Most simulation efforts that consider BMPs assume constant performance irrespective of ages of the practices, generally based on anticipated maintenance activities or the expected performance over the life of the BMP(s). However, efficiencies of BMPs likely change over time irrespective of maintenance due to factors such as degradation of structures and accumulation of pollutants. Generally, the impacts of BMPs implemented in water quality protection programs at watershed levels have not been as rapid or large as expected, possibly due to overly high expectations for practice long-term efficiency, with BMPs even being sources of pollutants under some conditions and during some time periods. The review of available datasets reveals that current data are limited regarding both short-term and long-term BMP efficiency. Based on this review, this paper provides suggestions regarding needs and opportunities. Existing practice efficiency data need to be compiled. New data on BMP efficiencies that consider important factors, such as maintenance activities, also need to be collected. Then, the existing and new data need to be analyzed. Further research is needed to create a framework, as well as modeling approaches built on the framework, to simulate changes in BMP efficiencies with time. The research community needs to work together in addressing these needs and opportunities, which will assist decision makers in formulating better decisions regarding BMP implementation in watershed management projects.
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