Validity of First-Order Approximations to Describe Parameter Uncertainty in Soil Hydrologic Models

By Jasper A. Vrugt, Willem Bouten. 2002

105 citations recorded by the source corpus.

Subfields: Civil and Structural Engineering, Environmental Engineering, Water Science and Technology

View Paper: https://www.semanticscholar.org/paper/04a3a46eaed54161d19cd70082a52047ae89d97f

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In Civil and Structural Engineering

In Environmental Engineering

In Water Science and Technology

Citations in the corpus

Analysis of parameter uncertainty in semi-distributed hydrological models using bootstrap method: a case study of SWAT model applied to Yingluoxia watershed in northwest China. (2010, methodology): “Without a realistic assessment of parameter uncertainty, it is difficult to have confidence in tasks, such as evaluating prediction limits on future hydrological responses and assessing the value of regional relationships between model parameters and watershed characteristics (Kuczera and Parent, 19”
Hydrological modelling of the Chaohe Basin in China: Statistical model formulation and Bayesian inference (2007, methodology): “The approaches based on first-order approximation of the model equations lead to an error that is hard to quantify (Vrugt and Bouten, 2002) and are being replaced by Monte Carlo techniques.”
Confronting uncertainty in model-based geostatistics using Markov Chain Monte Carlo simulation (2011, background): “However, many published contributions have shown that such linear confidence intervals typically underestimate the actual parameter uncertainty, particularly in the presence of high-dimensionality and significant model nonlinearity (e.g. Vrugt and Bouten, 2002).”
Inverse modeling of dynamic nonequilibrium in water flow with an effective approach (2012, methodology): “The advantage of using sampling techniques to approximate fpostðpjyÞ is that the uncertainty of the model parameters and the model predictions can be quantified accurately without the necessity to linearize the model at the mode of the posterior [Vrugt and Bouten, 2002; Laloy et al., 2010].”
Simultaneous heat and water (SHAW) model: model use, calibration, and validation. (2012, background): “However, these searches tend to terminate early under non-ideal conditions when the response surfaces are plagued with local minima (Duan et al., 1992; Vrugt and Bouten, 2002).”