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Mathematical modeling of first flush in highway storm runoff using genetic algorithm.
Arash Massoudieh1, Ali Abrishamchi, Masoud Kayhanian
1Department of Civil and Environmental Engineering, Engineering III, University of California, Davis, CA 95616, USA.
A new model predicts highway runoff pollution during storms by accounting for pollutant buildup and wash-off. Different mechanisms affect particle-bound versus dissolved pollutants, with linear buildup observed between rain events.
Area of Science:
- Environmental Engineering
- Hydrology
- Water Quality Modeling
Background:
- Highway runoff is a significant source of urban water pollution.
- Understanding pollutant transport during precipitation events is crucial for water management.
- Existing models often simplify the complex interactions of pollutants on pavement surfaces.
Purpose of the Study:
- To develop and validate a mechanistic model for predicting highway runoff pollutographs.
- To investigate the detachment and build-up mechanisms of various highway pollutants.
- To differentiate pollutant behavior based on their physical state (particle-associated vs. dissolved).
Main Methods:
- Developed a mechanistic model incorporating pollutant detachment, reattachment, and dry-period build-up.
- Utilized a hybrid genetic algorithm for parameter estimation using measured highway pollutographs.
- Validated the model's predictive capability using data from different monitoring seasons.
Main Results:
- Model parameters differed significantly between particle-associated and dissolved constituents, indicating distinct detachment mechanisms.
- A linear build-up of pollutants on highway surfaces during dry periods was observed.
- Pollutant removal during dry periods was found to be negligible or not concentration-dependent.
Conclusions:
- The model provides insights into the differing dynamics of particle-bound and dissolved pollutant runoff.
- Linear pollutant accumulation during dry spells is a key factor in highway runoff quality.
- Further research is needed to account for unknown factors influencing pollutant build-up rates.
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