Uncertainty in rainfall-runoff modelling: an application of GLUE approach to the Rome's urban area.
Year: 2012
Type: conference-paper
Abstract: Most problems in hydrological forecasting require the identification of appropriate model structures or parameter \nvalues. This is usually accomplished by model calibration techniques, which aim at comparing observed and \npredicted responses and attempting to improve some measure of model performance. There is a very extensive \nliterature on methods of model calibration. In this work we focus on a widely applied approach which rejects the \nconcept of an optimal model in favour of the equifinality concept of allowing for multiple acceptable models, i.e. \nmultiple models may provide acceptable simulations of the response of the system of interest. This is the basis of \nthe Generalized Likelihood Uncertainty Estimation (GLUE) approach, which is used here as a tool for estimating \nthe predictive uncertainty of a rainfall–runoff model. The GLUE methodology investigates the possible equifinality \nof different parameter sets and assesses the likelihood of a parameter set to being an acceptable simulator when \nmodel predictions are compared to observational data. Our work is intended to analyse the influence of different \nlikelihood measures and acceptability thresholds on the uncertainty analysis in the rainfall–runoff modelling of a \ncase study catchment in the suburb of Rome, Italy.
Language: English
Subfield: Water Science and Technology
Field: Environmental Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W3041626063