A Data-Driven Approach to Stormwater Quality Analysis in Two Urban Catchments

Abstract

The StormTac Web model, representing a low-complexity conceptual model (LCCM), was applied to two urban catchments featuring stormwater quality controls, a stormwater pond or a biofilter. The model calculates annual average runoff from annual precipitation and land-use specific volumetric runoff coefficients and baseflows (in storm sewers), which are multiplied by the corresponding mean stormwater quality constituent concentrations obtained from the recently upgraded StormTac Database, to yield constituent loads. The resulting runoff loads pass through the stormwater quality control facilities (a stormwater pond or a biofilter) where treatment takes place and its efficacy is described by “reduction efficiencies”. For the four selected stormwater quality constituents (TP, Cu, Zn, TSS) and two study catchments, a 201-ha residential Ladbrodammen and an 8.2-ha Sundsvall traffic corridor, the compositions of stormwater entering and leaving the control facilities were calculated by StormTac Web and compared against the measured data. In general, the calculated concentrations were smaller than the measured ones, and these differences were reduced, but not eliminated in all cases, by considering uncertainties in both calculated and measured data. Uncertainties in calculated values consisted of two components, a flow component (assumed as 20%) and a concentration component, which was assumed equal to the relative standard error (RSE) of the data in the StormTac Database. Explanations of differences in calculated and measured stormwater data were discussed with respect to temporal changes and trends in environmental practices and stormwater quality monitoring and enhancement by treatment.