A stochastic stormwater quality volume-sizing method with first flush emphasis

Area of Science:

• Environmental Engineering
• Hydrology
• Water Quality Management

Background:

• Urban stormwater runoff carries pollutants impacting waterways.
• Best Management Practices (BMPs) are used to mitigate stormwater pollution.
• Assessing the effectiveness of BMPs in reducing pollutant discharge is crucial.

Purpose of the Study:

• To assess the impact of stormwater volume captured by BMPs on pollutant discharge frequency.
• To develop a systematic approach for evaluating regulatory guidelines for stormwater pollution control.
• To inform the selection of BMPs based on water quality and economic considerations.

Main Methods:

• A Monte Carlo simulation technique was employed.
• A power law relationship between cumulative load and flow was assumed to model the first flush effect.
• Pollutograph data from three urban highway sites in West Los Angeles were analyzed.

Main Results:

• The study provides a method to evaluate the frequency of exceeding pollutant concentration thresholds based on captured stormwater volume.
• The effectiveness of BMPs is influenced by site-specific factors like rainfall depth.
• The developed approach allows for a systematic evaluation of regulatory guideline impacts.

Conclusions:

• The proposed method enables informed decision-making for stormwater management strategies.
• It facilitates a trade-off analysis between the probability of violating concentration criteria and economic factors in BMP selection.
• This systematic approach aids in optimizing BMP performance for urban stormwater pollution control.