Modeling framework for representing long-term effectiveness of best management practices in addressing hydrology and water quality problems: Framework development and demonstration using a Bayesian method

摘要: Abstract Best management practices (BMPs) are popular approaches used to improve hydrology and water quality. Uncertainties in BMP effectiveness over time may result overestimating long-term efficiency watershed planning strategies. To represent varying hydrologic/water quality models, a high level forward-looking modeling framework was developed. The components the consist of establishment period efficiency, starting for each storm event, between maintenance, life cycle. Combined, they specific type practice environmental concern (runoff/pollutant). An approach possible implementation discussed. impacts grass buffer strips (agricultural BMP) bioretention systems (urban reducing total phosphorus were simulated demonstrate framework. Data gaps captured estimating performance BMPs. A Bayesian method match distribution efficiencies with observed assumption that data represented efficiencies. matched well only small predictive uncertainties. With additional data, same can be further simulation results. results this study, which adopted models better effectiveness, help decision support creating stormwater strategies projects.