Search results for " hydrological models"

showing 2 items of 2 documents

Approximate Bayesian Computation for Forecasting in Hydrological models

2018

Approximate Bayesian Computation (ABC) is a statistical tool for handling parameter inference in a range of challenging statistical problems, mostly characterized by an intractable likelihood function. In this paper, we focus on the application of ABC to hydrological models, not as a tool for parametric inference, but as a mechanism for generating probabilistic forecasts. This mechanism is referred as Approximate Bayesian Forecasting (ABF). The abcd water balance model is applied to a case study on Aipe river basin in Columbia to demonstrate the applicability of ABF. The predictivity of the ABF is compared with the predictivity of the MCMC algorithm. The results show that the ABF method as …

Predictive uncertainty Probabilistic post-processing approach Bayesian forecasting Sufficient statistics Hydrological models Intractable likelihood
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Effects of climate and land use changes on runoff extremes

2017

The analysis of the hydrological changes and their interacting triggering factors are objectives defined within the Panta Rhei decade 2013-2022. Climate change and urbanization are among the most recurrent causes for hydrological changes at the global level. This work proposes a modeling framework for the analysis of the alterations in the watershed hydrological response and, more specifically, in runoff extremes, induced by such perturbations. A weather generator and a cellular automata land-use change model are used to generate hypothetical scenarios accounting for relevant trends at the global level. Such scenarios are successively considered to force a physically-based and spatial-distr…

Settore ICAR/02 - Costruzioni Idrauliche E Marittime E Idrologiahydrological change climate change urbanizationclimate change hydrological models extremes
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