Aalborg Universitet Uncertainty Assessment in Long Term Urban Drainage Modelling Thorndahl, Søren Liedtke Publication date: 2008 Document Version Publisher's PDF, also known as Version of record Link to publication from Aalborg University Citation for published version (APA): Thorndahl, S. (2008). Uncertainty Assessment in Long Term Urban Drainage Modelling. Aalborg: Department of Civil Engineering, Aalborg University. (DCE Thesis; No. 12). General rights Copyright and moral rights for the publications made accessible in the public portal are retained by the authors and/or other copyright owners and it is a condition of accessing publications that users recognise and abide by the legal requirements associated with these rights. ? Users may download and print one copy of any publication from the public portal for the purpose of private study or research. ? You may not further distribute the material or use it for any profit-making activity or commercial gain ? 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Downloaded from vbn.aau.dk on: May 01, 2017 Uncertainty assessment in long term urban drainage modelling PhD Thesis Defended in public April 14, 2008 Søren Thorndahl ISSN 1901-7294 DCE Thesis No. 12 Department of Civil Engineering Aalborg University Department of Civil Engineering Water and Soil DCE Thesis No. 12 Uncertainty assessment in long term urban drainage modelling Defended in public April 14, 2008 at Aalborg University by Søren Thorndahl March 2008 © Aalborg University Scientific Publications at the Department of Civil Engineering Technical Reports are published for timely dissemination of research results and scientific work carried out at the Department of Civil Engineering (DCE) at Aalborg University. This medium allows publication of more detailed explanations and results than typically allowed in scientific journals. 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Theses are monograms or collections of papers published to report the scientific work carried out at the DCE to obtain a degree as either PhD or Doctor of Technology. The thesis is publicly available after the defence of the degree. Latest News is published to enable rapid communication of information about scientific work carried out at the DCE. This includes the status of research projects, developments in the laboratories, information about collaborative work and recent research results. Published 2008 by Aalborg University Department of Civil Engineering Sohngaardsholmsvej 57, DK-9000 Aalborg, Denmark Printed in Aalborg at Aalborg University ISSN 1901-7294 DCE Thesis No. 12 Preface This thesis is prepared as part of a PhD study during the period November 15, 2004 to March 1 2008 at Department of Civil Engineering, Aalborg University, Denmark. The study is supervised by Associate Professor Kjeld Schaarup-Jensen and co-supervised by part-time lecturer, Msc., PhD Jacob Birk Jensen. The thesis consists of a collection of seven journal and conference papers as well as an introductive review and summery. First of all, I would like to thank both of my supervisors, Kjeld Schaarup-Jensen and Jacob Birk Jensen, for numerous fruitful meetings and for their enthusiastic guidance throughout the study. I would like to express my gratitude to Associate Professor Michael R. Rasmus- sen for many discussions and his great involvement in the study. Also thanks to Professor Torben Larsen for his inputs to the project. Furthermore, I am grateful to my PhD colleague Thomas R. Bentzen with whom I have discussed and shared many professional and private matters. I would like to express my thanks to my co-authors Civil Engineer, PhD Claus Johansen, formerly NIRAS Consulting Engineers and Planners, currently EnviDan, Aalborg, Den- mark; Professor Keith J. Beven, Institute of Environmental & Natural Sciences, Lancaster University, UK. Special thanks to Professor Patrick Willems, Katholieke Universiteit Leu- ven, Belgium for our good collaboration during my stay in Leuven. I am grateful to the Municipality of Aalborg for data and for letting me use the Frejlev catchment as case. Finally, I would like to thank my girlfriend Kathrine without who’s love and support I could not have completed the project. Furthermore, lots of gratitude for her help with proof reading. Aalborg, 1 March, 2008 Søren Thorndahl i This Thesis was defended in public at Aalborg University, April 14, 2008. The Assessment committee consisted of: Associate Professor, Dr., Jean-Luc Bertrand-Krajewsky, LGCIE - Laboratoire de Génie Civil et d'Ingénierie Environnementale, INSA de Lyon, France Associate Professor, Dr., Peter Steen Mikkelsen, Department of Environmental Engineer- ing, Technical University of Denmark Associate Professor, Dr., Michael R. Rasmussen (Chairman) Department of Civil Engineer- ing, Aalborg University. On behalf of the Faculties of Engineering, Science and Medicine at Aalborg University the defence was chaired by Professor Torben Larsen. ii English summary Use of hydrodynamic models, by consultants, municipalities, etc, for analysis of urban drainage systems has evolved extensively in the last decades. The models produce a de- tailed overview of the urban drainage systems’ ability to function during rain, by predicting flooding of critical levels and overflows from combined sewer systems to receiving waters. The application of models is highly dependent on tradition and empirical assumptions con- cerning the choice of models, model parameters, and model inputs. In order to meet the design criteria a certain safety is often implemented in the choice of model parameter val- ues. In some cases, this can lead to over-dimensioned sewers, causing excessive construc- tion costs, and potentially, problems with poor self cleaning. On the other hand, however, if the necessary safeties are not implemented in the models, the sewer design will cause fre- quent flooding of certain areas or frequent overflows from combined sewer systems to re- ceiving waters. Thus, from a social and an engineering point of view there is a strong need for more research in uncertainties related to both input, parameters, and predictions in urban drainage models. Better and more reliable model results can be obtained by explaining the uncertainties and by handling them stochastically. In the end this might help reduce both construction and damage costs. This thesis consists of initial registrations and quantifications of uncertainty contributions. Next, based on a selection of the most important uncertainties, three different stochastic methods are applied, in order to propagate the uncertainties on inputs and parameters through the model to an uncertainty estimation of the model predictions. The simulations are exemplified applying a rather small catchment in the town Frejlev, located a few kilo- metres from the city of Aalborg, Denmark. The first of the applied stochastic methods is a reliability method that searches the models space for failures. In this case, failure is defined as occurrence of either surcharge or flood- ing of manholes or combined sewer overflow. The application implies a parameterisation of the rainfall input in order to generate synthetic Gauss-shaped rainfall events. This iterative search-algorithm has proven very applicable in locating failures in urban drainage systems because uncertainties with regards to different parameters and rainfall inputs can be in- cluded. The second stochastic method is a Monte Carlo based stochastic calibration which applies the GLUE method (Generalized Likelihood Uncertainty Estimation). By application of flow measurements and overflow registrations in the drainage system, this method includes an event based conditioning of the model. To find the most reliable model structure, it is possible to derive the parameter distributions which contain the largest correlation between observed and simulated time series as well as to investigate different conceptual setups of iii the model. The method has proven very applicable in modelling of drainage systems even though it has not been possible to bracket the observed time series completely by the pre- dicted confidence intervals. The last of the stochastic methods apply the results from the two previously described analyses by modelling the extreme event statistics using Monte Carlo simulations. In order to include the return period uncertainties of maximum water levels and combined sewer overflow volumes, a new methodology is proposed. This includes a derivation of correla- tions between input and