A Data-Driven Approach to Stormwater Quality Analysis in Two Urban Catchments
2022 (English)In: Sustainability, E-ISSN 2071-1050, Vol. 14, no 5, article id 2888
Article in journal (Refereed) Published
Abstract [en]
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.
Place, publisher, year, edition, pages
MDPI, 2022. Vol. 14, no 5, article id 2888
Keywords [en]
urban runoff, stormwater quality and treatment, data-driven approach, uncertainties in pollutant concentrations and loads, StormTac Web model and database
National Category
Water Engineering
Research subject
Urban Water Engineering
Identifiers
URN: urn:nbn:se:ltu:diva-89905DOI: 10.3390/su14052888ISI: 000769156900001Scopus ID: 2-s2.0-85126371889OAI: oai:DiVA.org:ltu-89905DiVA, id: diva2:1648405
Funder
Vinnova, 2016-05176
Note
Validerad;2022;Nivå 2;2022-03-30 (hanlid)
2022-03-302022-03-302023-09-05Bibliographically approved