Uncertainty propagation in urban hydrology water quality modelling

Arturo Torres Matallana*, U. Leopold, G.B.M. Heuvelink

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference paperAcademicpeer-review

Abstract

Uncertainty is often ignored in urban hydrology modelling. Engineering practice typically ignores uncertainties and uncertainty propagation. This can have large impacts, such as the wrong dimensioning of urban drainage systems and the inaccurate estimation of pollution in the environment caused by combined sewer overflows. This paper presents an uncertainty propagation analysis in urban hydrology modelling. The case study was the Haute-Sûre catchment in Luxembourg for one yearly time series measured in 2010, and 10 individual rainfall events measured in 2011. The selection of model input variables for uncertainty quantification was based on their level of uncertainty and model sensitivity. Probability distribution functions were defined to represent the uncertainty of the input variables. We applied a Monte Carlo technique using a simplified model, EmiStatR, which simulates the volume and substance flows in urban drainage systems. We focus in loads and concentrations of chemical oxygen demand and ammonium, which are important variables for wastewater and surface water quality management.

Original languageEnglish
Title of host publicationProceedings of Spatial Accuracy 2016
EditorsJean-Stéphanie Bailly, Daniel Griffith, Didier Josselin
PublisherInternational Spatial Accuracy Research Association (ISARA)
Pages313-321
ISBN (Print)9782910545105
Publication statusPublished - 2016
Event12th International Symposium on Spatial Accuracy Assessment in Natural Resources and Environmental Sciences, Accuracy 2016 - Montpellier, France
Duration: 5 Jul 20168 Jul 2016

Conference

Conference12th International Symposium on Spatial Accuracy Assessment in Natural Resources and Environmental Sciences, Accuracy 2016
CountryFrance
CityMontpellier
Period5/07/168/07/16

Keywords

  • EmiStatR
  • Monte Carlo
  • Uncertainty propagation
  • Urban hydrology modelling

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