Search results for "Uncertainty assessment"
showing 9 items of 9 documents
Uncertainty assessment of a membrane bioreactor model using the GLUE methodology
2010
A mathematical model for the simulation of physical-biological organic removal by means of a membrane bioreactor (MBR) has been previously developed and tested. This paper presents an analysis of the uncertainty of the MBR model. Particularly, the research explores the applicability of the Generalised Likelihood Uncertainty Estimation (GLUE) methodology that is one of the most widely used methods for investigating the uncertainties in the hydrology and that now on is spreading in other research field. For the application of the GLUE methodology, several Monte Carlo simulations have been run varying the all model influential parameters simultaneously. The model was applied to an MBR pilot pl…
The influence of rainfall time resolution for urban water quality modelling
2010
The objective of this paper is the definition of a methodology to evaluate the impact of the temporal resolution of rainfall measurements in urban drainage modelling applications. More specifically the effect of the temporal resolution on urban water quality modelling is detected analysing the uncertainty of the response of rainfall–runoff modelling. Analyses have been carried out using historical rainfall–discharge data collected for the Fossolo catchment (Bologna, Italy). According to the methodology, the historical rainfall data are taken as a reference, and resampled data have been obtained through a rescaling procedure with variable temporal windows. The shape comparison between ‘true’…
Bayesian approach for uncertainty quantification in water quality modelling: The influence of prior distribution
2010
Summary Mathematical models are of common use in urban drainage, and they are increasingly being applied to support decisions about design and alternative management strategies. In this context, uncertainty analysis is of undoubted necessity in urban drainage modelling. However, despite the crucial role played by uncertainty quantification, several methodological aspects need to be clarified and deserve further investigation, especially in water quality modelling. One of them is related to the “a priori” hypotheses involved in the uncertainty analysis. Such hypotheses are usually condensed in “a priori” distributions assessing the most likely values for model parameters. This paper explores…
Uncertainty assessment of sewer sediment erosion modelling
2008
Urban stormwater quality modelling has become a fundamental issue in the evaluation of the receiving water bodies' quality state. Laboratory study as well as field campaigns have widely demonstrated that combined sewer sediments present cohesive-like properties which increase their resistance to erosion. However, only few models take sewer sediments into account considering their rheological properties. In the present paper different sewer sediment erosion models have been tested and their uncertainties have been assessed. The main goal was to discriminate the algorithms with respect to their robustness and the reduction of uncertainty. In order to accomplish such objective the GLUE methodo…
Assessment of the integrated urban water quality model complexity through identifiability analysis
2010
Urban sources of water pollution have often been cited as the primary cause of poor water quality in receiving water bodies (RWB), and recently many studies have been conducted to investigate both continuous sources, such as wastewater-treatment plant (WWTP) effluents, and intermittent sources, such as combined sewer overflows (CSOs). An urban drainage system must be considered jointly, i.e., by means of an integrated approach. However, although the benefits of an integrated approach have been widely demonstrated, several aspects have prevented its wide application, such as the scarcity of field data for not only the input and output variables but also parameters that govern intermediate st…
Uncertainty Assessment of a Water-Quality Model for Ephemeral Rivers Using GLUE Analysis
2011
Every model is, by definition, a simplification of the system under investigation. Although it would be desirable to reduce the gap between the simulated and the observed behaviors of the system to zero, this reduction is generally impossible owing to the unavoidable uncertainties inherent in any modeling procedure. Uncertainty analyses can provide useful insights into the best model approach to be used for obtaining results with a high level of significance and reliability. The evaluation of parameter uncertainties is necessary for calibration and for estimating the impact of these uncertainties on model performance. In this context, the uncertainty of a river water-quality model developed…
Uncertainty in urban stormwater quality modelling: The influence of likelihood measure formulation in the GLUE methodology
2009
In the last years, the attention on integrated analysis of sewer networks, wastewater treatment plants and receiving waters has been growing. However, the common lack of data in the urban water-quality field and the incomplete knowledge regarding the interpretation of the main phenomena taking part in integrated urban water systems draw attention to the necessity of evaluating the reliability of model results. Uncertainty analysis can provide useful hints and information regarding the best model approach to be used by assessing its degrees of significance and reliability. Few studies deal with uncertainty assessment in the integrated urban-drainage field. In order to fill this gap, there ha…
Parameter uncertainty analysis of water quality model for small river
2009
Urban runoff modelling uncertainty: Comparison among Bayesian and pseudo-Bayesian methods
2009
Urban stormwater quality modelling plays a central role in evaluation of the quality of the receiving water body. However, the complexity of the physical processes that must be simulated and the limited amount of data available for calibration may lead to high uncertainty in the model results. This study was conducted to assess modelling uncertainty associated with catchment surface pollution evaluation. Eight models were compared based on the results of a case study in which there was limited data available for calibration. Uncertainty analysis was then conducted using three different methods: the Bayesian Monte Carlo method, the GLUE pseudo-Bayesian method and the GLUE method revised by m…