Analytical Urban Storm Water Quality Models Based on Pollutant Buildup and Washoff Processes

Abstract

This paper presents methodology and major procedures for the development of analytical urban storm water quality models following derived probability distribution theory, which involves conceptualization of the three major components, i.e., the rainfall–runoff transformation, pollutant buildup, and washoff processes. In this study, two different types of the rainfall–runoff transformations are employed in an attempt to improve model performance by considering spatial variations of parameters associated with runoff generation mechanisms. By integrating different types of the rainfall–runoff transformations and pollutant buildup function with washoff function, two different types of pollutant washoff load models are formulated. Thereby, the probability distributions of the rainfall characteristics are mathematically transformed to create system storm water quality control measures, such as the average pollutant event mean concentration and long-term pollutant loads to receiving waters. These storm water quality control measures are closed-form analytical models and can be employed as alternatives to continuous simulation models for the evaluation of long-term system behavior. The results from case study reveal that with appropriately formulated rainfall–runoff transformation along with pollutant buildup and washoff functions, analytical storm water quality models are capable of providing comparable results to observed data and can serve as effective tools for storm water quality control analysis.