Uncertainty inherent to a conceptual model StormTac Web simulating urban runoff quantity, quality and control

Abstract

Assessing uncertainties of urban drainage models is important for their applications. While most attention in the literature was paid to large comprehensive models, little has been published about Low-Complexity Conceptual Models (LCCMs). This paper explores the uncertainties inherent to a conceptual, data-based proprietary model StormTac Web, simulating annual urban runoff quantity and quality, and serving here as an example of a LCCM. The analyses were demonstrated for a small urban catchment, Sätra in Stockholm, Sweden, using the Law of Propagation of Uncertainties and Morris screening methods. The results indicate that the uncertainty of the modelled annual runoff quality (about 30%) is greater than that of annual runoff volumes (about 24%), and the latter uncertainties can significantly contribute to the uncertainty in runoff quality. In computations of pollutant loads, the most sensitive inputs were land-use specific parameters, including the annual volumetric runoff coefficients and default pollutant concentrations for various land uses.