4.6 Article

Improving Best Management Practice Decisions in Mixed Land Use and/or Municipal Watersheds: Should Approaches Be Standardized?

Journal

LAND
Volume 10, Issue 12, Pages -

Publisher

MDPI
DOI: 10.3390/land10121402

Keywords

best management practices; watershed management; experimental watershed study design; municipal watershed; adaptive management

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Best management practices (BMP) in the United States are defined as successful measures in protecting water resources from pollution, but most BMPs lack validation and standardized implementation and monitoring methods. This communication proposes a generalized and customizable BMP decision-making process to encourage standardization in BMP implementation and validation methods.
Best management practices (BMP) are defined in the United States Clean Water Act (CWA) as practices or measures that have been demonstrated to be successful in protecting a given water resource from nonpoint source pollution. Unfortunately, the greatest majority of BMPs remain unvalidated in terms of demonstrations of success. Further, there is not a broadly accepted or standardized process of BMP implementation and monitoring methods. Conceivably, if standardized BMP validations were a possibility, practices would be much more transferrable, comparable, and prescriptive. The purpose of this brief communication is to present a generalized yet integrated and customizable BMP decision-making process to encourage decision makers to more deliberately work towards the establishment of standardized approaches to BMP monitoring and validation in mixed-use and/or municipal watersheds. Decision-making processes and challenges to BMP implementation and monitoring are presented that should be considered to advance the practice(s) of BMP implementation. Acceptance of standard approaches may result in more organized and transferrable BMP implementation policies and increased confidence in the responsible use of taxpayer dollars through broad acceptance of methods that yield predictable and replicable results.

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