Showing papers by "Francois Clemens published in 2002"

Bayesian Estimation of Return Periods of CSO Volumes for Decision-Making in Sewer System Management

Abstract: Decisions on the rehabilitation of a sewer system are usually based on a single computation of CSO volumes using a time series of rainfall as system loads. A shortcoming of this method is that uncertainties in knowledge of sewer system dimensions are not taken into account. Besides, statistical uncertainties are left aside. This paper presents the effect of variations in sewer system dimensions on return periods of calculated CSO volumes. As an example the sewer system of ‘De Hoven’ (the Netherlands) is used. CSO volumes per storm event are computed using Monte Carlo simulations with a reservoir model of the sewer system. In each Monte Carlo run random values for the sewer system dimensions are drawn and substituted in the model. With regard to the computed CSO volumes probability distributions are estimated taking into account the statistical uncertainties involved. For this purpose so-called Bayes factors are used to determine weights that describe how well a probability distribution fits the computed data, i.e. the better the tit, the higher the weighing. With the fitted probability distributions the 95% uncertainty intervals of calculated CSO volumes and their corresponding return periods are computed. The results show that uncertainties in knowledge of sewer system dimensions cause a considerable variability in return periods of calculated CSO volumes.

Influence of model parameter uncertainties on decision- making for sewer system management

Abstract: Decisions on the rehabilitation of a sewer system are usually based on a single computation of CSO volumes using a time series of rainfall as system loads. Therefore, uncertainty in knowledge of model parameters is not taken into account. Moreover, statistical uncertainties are left aside. This paper presents the effect of uncertainties in model parameters on overall model results taking into account statistical uncertainties. It could even be argued that it does not matter whether the predictions from the model are uncertain. What matters is whether the decisions informed by these predictions are insensitive to such uncertainties. As an example the sewer system of 'De Hoven' (the Netherlands) is used. CSO volumes per storm event are computed using Monte Carlo simulations. In each Monte Carlo simulation of 1000 runs a different combination of fixed and variable model parameters is used. Probability distributions of computed CSO volumes are estimated taking into account the model uncertainties involved. The extent to which uncertainty in individual model parameters influences model results is quantified using relative confidence intervals of the statistical parameters of estimated distribution functions. The results show that the uncertainty in overall model results decreases the most if contributing areas are exactly known. Also the gain of model calibration is shown.

Evaluation of a Method for the Design of Monitoring Networks in Urban Drainage

Abstract: When designing a measuring network several questions must be answered. Basic properties like defining sampling interval and the exact locations for measuring sites are mostly based upon expert's judgement. In this paper a design method for measuring networks aiming at obtaining information for model calibration is proposed. This method is based upon the application of a hydrodynamic model for initial design. Based on a min-max approach for the sampling frequency, a first estimate is obtained. Based on a mathematical analysis of the model parameterization and information content of potential measuring locations it is possible to judge measuring networks objectively. Moreover, by applying some optimization technique (e.g. a genetic algorithm) an automated optimization of the measuring network is possible. The method was applied to design a monitoring network in the drainage system of Loenen. During the second half of 2001 measuring data were obtained allowing for an evaluation of the design method.

Interactions Within the Wastewater System: Modeling of Sewer Processes

Abstract: Since the beginning of the last decade, an integrated approach towards the urban water system has often been advocated. From a scientific point of view, this approach is preferable, but in day-to-day engineering practice the problem arises to what extent the interactions, and sewer processes, within the wastewater system should be included in wastewater system optimisation studies. This paper briefly describes the methodology applied to evaluate the relative importance of each sewer process with respect to the interactions within the wastewater system and, subsequently, the possibility to model the, in this respect, most important sewer processes.