Assessing the uncertainty in distributed model predictions using observed binary pattern information within GLUE

By G. Aronica, Paul D. Bates, Matthew S. Horritt. 2002

439 citations recorded by the source corpus.

Subfields: Global and Planetary Change, Water Science and Technology

View Paper: https://www.semanticscholar.org/paper/39804c525ed4c1dded6c9a85355f8d794f19dccd

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Global and Planetary Change

In Water Science and Technology

Citations in the corpus

Indices for assessing the prediction bounds of hydrological models and application by generalised likelihood uncertainty estimation / Indices pour évaluer les bornes de prévision de modèles hydrologiques et mise en œuvre pour une estimation d'incertitude par vraisemblance généralisée (2009, methodology): “…1992), the GLUE method has become one of the most widely used and studied uncertainty assessment methods (Freer et al., 1996; Cameron et al., 1999; Aronica et al., 2002; Blazkova & Beven, 2002; Montanari, 2005; Heidari et Lihua Xiong et al. Copyright © 2009 IAHS Press 858 al., 2006; Mantovan &…”
Equifinality of formal (DREAM) and informal (GLUE) Bayesian approaches in hydrologic modeling? (2009, background): “…well capture zone delineation (Feyen et al. 2001; Jensen 2003), unsaturated zone (Mertens et al. 2004), flood inundation (Romanowicz et al. 1996; Aronica et al. 2002), land–surface–atmosphere interactions (Franks et al. 1997), soil freezing and thawing (Hansson and Lundin 2006), crop yields and…”
A simple inertial formulation of the shallow water equations for efficient two-dimensional flood inundation modelling. (2010, methodology): “This allowed new applications of hydraulic models to be considered including Monte Carlo uncertainty analysis (Aronica et al., 2002), inclusion of hydraulic models in ensemble forecasting chains (Pappenberger et al.”
Generalized likelihood uncertainty estimation (GLUE) using adaptive Markov Chain Monte Carlo sampling (2008, methodology): “Since its introduction in 1992, the GLUE framework has found widespread application for uncertainty assessment in environmental modeling, including rainfall-runoff modeling [3,15,31], soil erosion modeling [8], modeling of tracer dispersion in a river reach [20], groundwater modeling and well captur”
Joint Monte Carlo and possibilistic simulation for flood damage assessment (2013, methodology): “This model is selected for stochastic simulation of water depth in this study to form the basis of damage calculation, in view of the following facts: (1) it has been applied into various real world study cases with acceptable prediction capability (Horritt and Bates 2001; Aronica et al. 2002; Liu a”
Uncertainty in the calibration of effective roughness parameters in HEC-RAS using inundation and downstream level observations (2005, methodology): “(Aronica et al., 2002; Horritt and Bates, 2001a)”