Search results for " uncertainty estimation."
showing 5 items of 5 documents
Daily streamlow prediction with uncertainty in ephemeral catchments using the GLUE methodology
2009
Abstract The Generalised Likelihood Uncertainty Estimation (GLUE) approach is presented here as a tool for estimating the predictive uncertainty of a rainfall–runoff model. The GLUE methodology allows to recognise the possible equifinality of different parameter sets and assesses the likelihood of a parameters set being acceptable simulator when model predictions are compared to observed field data. The results of the GLUE methodology depend greatly on the choice of the likelihood measure and on the choice of the threshold which determines if a parameters set is behavioural or not. Moreover the sampling size has a strong influence on the uncertainty assessment of the response of a rainfall–…
Uncertainty estimation of a complex water quality model: The influence of Box–Cox transformation on Bayesian approaches and comparison with a non-Bay…
2012
Abstract In urban drainage modelling, uncertainty analysis is of undoubted necessity. However, uncertainty analysis in urban water-quality modelling is still in its infancy and only few studies have been carried out. Therefore, several methodological aspects still need to be experienced and clarified especially regarding water quality modelling. The use of the Bayesian approach for uncertainty analysis has been stimulated by its rigorous theoretical framework and by the possibility of evaluating the impact of new knowledge on the modelling predictions. Nevertheless, the Bayesian approach relies on some restrictive hypotheses that are not present in less formal methods like the Generalised L…
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…
ERROR AND UNCERTAINTY ANALYSIS OF RESIDUAL STRESS EVALUATION BY USINGTHE RING-CORE METHOD
2014
The Ring-Core Method is a technique used for the experimental analysis of the residual stresses in mechanical components. For uniform and non-uniform residual stresses estimation, the use of the method leads in general to accurate results but, unfortunately at present the user does not have appropriate procedures to correct the obtained results from systematic errors as well as to estimate the uncertainty due to random errors. In order to overcome such drawbacks, in the present work, the procedures for the correction of the effects of the main error sources and for the stress uncertainty estimation, are proposed. The practical application of such procedures allow the user to highlight the r…
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…