Fate and transport modelling of urban highway contaminants by a multi-objective evolutionary method

A hybrid mechanistic data-driven approach was used to identify optimal structures for the processes of a mechanistic build-up wash-off model for predicting the continuous pollutographs of various constituents from urban highway surfaces. The mechanistic model is based on mass balance and the advective-dispersive transport of pollutants in runoff. Using the pollutograph data of seven constituents (TSS, DOC, Cr, Cu, Ni, Pb and Zn) collected from highly urbanized highway sites in California, we applied the two-layer model identification approach to find unique optimum functional forms that represent the processes and their optimum parameter values. The comparison of the model results and observed data indicate acceptable agreement for the examined constituents and rain events. The build-up and wash-off model developed using this approach honours the physical processes involved and is a reliable tool for predicting constituent pollutographs as well as understanding the physical and underlying processes.