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Open AccessArticle

Distribution-Based Calibration of a Stormwater Quality Model

Institute for Infrastructure, Water, Resources, Environment, Muenster University of Applied Sciences, Correnstr. 25, 48149 Muenster, Germany
Institute of Urban Water Management and Landscape Water Engineering, Graz University of Technology, Stremayrgasse 10/I, 8010 Graz, Austria
Author to whom correspondence should be addressed.
Water 2018, 10(8), 1027;
Received: 26 April 2018 / Revised: 30 July 2018 / Accepted: 2 August 2018 / Published: 3 August 2018
(This article belongs to the Section Urban Water Management)
Stormwater quality models are usually calibrated using observed pollutographs. As current models still rely on simplified model concepts for pollutant accumulation and wash-off, calibration results for continuous pollutant concentrations are highly uncertain. In this paper, we introduce an innovative calibration approach based on total suspended solids (TSS) event load distribution. The approach is applied on stormwater quality models for a flat roof and a parking lot for which reliable distributions are available. Exponential functions are employed for both TSS buildup and wash-off. Model parameters are calibrated by means of an evolutionary algorithm to minimize the distance between a parameterized lognormal distribution function and the cumulated distribution of simulated TSS event loads. Since TSS event load characteristics are probabilistically considered, the approach especially respects the stochasticity of TSS buildup and wash-off and, therefore, improves conventional stormwater quality calibration concepts. The results show that both experimental models were calibrated with high goodness-of-fit (Kolmogorov–Smirnov test statistic: 0.05). However, it is shown that events with high TSS event loads (>0.8 percentile) are generally underestimated. While this leads to a relative deviation of −28% of total TSS loads for the parking lot, the error is compensated for the flat roof (+5%). Calibrated model parameters generally tend to generate wash-off proportional to runoff, which is indicated by mass-volume curves. The approach itself is, in general, applicable and creates a new opportunity to calibrate stormwater quality models especially when calibration data is limited. View Full-Text
Keywords: stormwater quality modelling; model calibration; probabilistic TSS event loads; SWMM; lognormal distribution; annual TSS loads stormwater quality modelling; model calibration; probabilistic TSS event loads; SWMM; lognormal distribution; annual TSS loads
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MDPI and ACS Style

Leutnant, D.; Muschalla, D.; Uhl, M. Distribution-Based Calibration of a Stormwater Quality Model. Water 2018, 10, 1027.

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