On Parameter Estimation of Urban Storm-Water Runoff Model

Abstract

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.