On Parameter Estimation of Urban Storm-Water Runoff Model

An existing accumulation and wash-off model was applied and calibrated on a standard asphalt parking lot located in the northeastern United States. The field measured data consisted of rainfall, flow, and runoff samples taken from over 26 storm events monitored from 2004 to 2006. The contaminants un...

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Bibliographic Details
Published in:Journal of environmental engineering (New York, N.Y.) N.Y.), 2009-08, Vol.135 (8), p.595-608
Main Authors: Avellaneda, Pedro, Ballestero, Thomas P, Roseen, Robert M, Houle, James J
Format: Article
Language:English
Subjects:
Algorithms
Ammonia
Applied sciences
Asphalt
Calibration
Computer simulation
Contaminants
Continental surface waters
Crude oil
Dissolution
Environmental engineering
Exact sciences and technology
Fittings
Hydrocarbons
Mathematical models
Methodology
Monte Carlo methods
Natural water pollution
Nitrates
Nitrites
Normal distribution
Optimization
Outlets
Parameter estimation
Parameters
Parking
Pollution
Rainfall
Rainwaters, run off water and others
Runoff
Simulated annealing
Storms
Stormwater management
TECHNICAL PAPERS
Uncertainty principles
Urban areas
Water quality
Water treatment and pollution
Zinc
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Summary:An existing accumulation and wash-off model was applied and calibrated on a standard asphalt parking lot located in the northeastern United States. The field measured data consisted of rainfall, flow, and runoff samples taken from over 26 storm events monitored from 2004 to 2006. The contaminants under consideration include: total suspended solids, total petroleum hydrocarbons-diesel range hydrocarbons (TPH-D), dissolved inorganic nitrogen (DIN) (comprised of nitrate, nitrite, and ammonia), and zinc (Zn). The objective of the study was to provide probability distributions of model parameters for contaminants that have not been documented much (TPH-D, DIN, and Zn). The best fitting parameter values were found on a storm by storm basis. Subsequently, the range and variability of these parameters are provided for modeling purposes and other urban storm-water quality applications. A normal distribution was fitted to the optimized model parameter values to describe their distributions. A simulated annealing algorithm was used as the parameter optimization technique. Several examples are given to illustrate the methodology and the performance of the model. Finally, a Monte Carlo simulation was performed to assess the capability of the model to predict contaminant concentrations at the watershed’s outlet.
ISSN:0733-9372
1943-7870
DOI:10.1061/(ASCE)EE.1943-7870.0000028