title: Assessing uncertainty in pollutant wash-off modelling via model validation.
abstract: Stormwater pollution is linked to stream ecosystem degradation. In predicting stormwater pollution, various types of modelling techniques are adopted. The accuracy of predictions provided by these models depends on the data quality, appropriate estimation of model parameters, and the validation undertaken. It is well understood that available water quality datasets in urban areas span only relatively short time scales unlike water quantity data, which limits the applicability of the developed models in engineering and ecological assessment of urban waterways. This paper presents the application of leave-one-out (LOO) and Monte Carlo cross validation (MCCV) procedures in a Monte Carlo framework for the validation and estimation of uncertainty associated with pollutant wash-off when models are developed using a limited dataset. It was found that the application of MCCV is likely to result in a more realistic measure of model coefficients than LOO. Most importantly, MCCV and LOO were found to be effective in model validation when dealing with a small sample size which hinders detailed model validation and can undermine the effectiveness of stormwater quality management strategies.
authors.affiliation: School of Computing, Engineering and Mathematics, University of Western Sydney, Building XB, Locked Bag 1797, Penrith, NSW 2751, Australia.
authors.forename: Khaled
authors.initials: K
authors.lastname: Haddad
authors.affiliation: Science and Engineering Faculty, Queensland University of Technology, GPO Box 2434, Brisbane 4001, Australia.
authors.forename: Prasanna
authors.initials: P
authors.lastname: Egodawatta
authors.affiliation: School of Computing, Engineering and Mathematics, University of Western Sydney, Building XB, Locked Bag 1797, Penrith, NSW 2751, Australia.
authors.forename: Ataur
authors.initials: A
authors.lastname: Rahman
authors.affiliation: Science and Engineering Faculty, Queensland University of Technology, GPO Box 2434, Brisbane 4001, Australia. Electronic address: a.goonetilleke@qut.edu.au.
authors.forename: Ashantha
authors.initials: A
authors.lastname: Goonetilleke
mesh_terms: D004784:Environmental Monitoring / Q000379:methods*; D008956:Models, Chemical; D009010:Monte Carlo Method; D011891:Rain; D035501:Uncertainty; D014872:Water Movements; D014873:Water Pollutants / Q000032:analysis*; D014876:Water Pollution / Q000706:statistics & numerical data*
chemical_list: D014873:Water Pollutants
keywords: Model uncertainty; Monte Carlo cross validation; Pollutant wash-off; Stormwater pollutant processes; Stormwater quality