Correcting the mathematical structure of a hydrological model via Bayesian data assimilation

By N. Bulygina, Hoshin V. Gupta. 2011

73 citations recorded by the source corpus.

Subfields: Environmental Engineering, Global and Planetary Change, Water Science and Technology

View Paper: https://www.semanticscholar.org/paper/b26a290adcfc4b2c2cd978cc3f7a93dc5064ac27

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In Environmental Engineering

In Global and Planetary Change

In Water Science and Technology

Citations in the corpus

Rating curve estimation under epistemic uncertainty (2015, background): “…uncertainty affects water resource and flood estimates (Kuczera, 1996; Petersen-Overleir et al., 2009; Peel and Bloschl, 2011), model calibration (McMillan et al., 2010; Thyer et al., 2011) and model structure choice (Bulygina and Gupta, 2011); so accurate estimates of the uncertainty are needed.”
Bridging the gap between GLUE and formal statistical approaches: approximate Bayesian computation (2013, background): “…into structural adequacy has resulted in data-based mechanistic (Young, 2002, 2012), data assimilation (Vrugt et al., 2005; Smith et al., 2008; Bulygina and Gupta, 2011), and other stochastic techniques (Reichert and Mieleitner, 2009) for inference and iterative reﬁnement of the mathematical…”
Towards a comprehensive assessment of model structural adequacy (2012, methodology): “Alternatively, the Bayesian Estimation of Structure approach [Bulygina and Gupta, 2009, 2010, 2011] seeks to use data to refine all of the equations in a model, not just those associated with streamflow recessions.”
Toward diagnostic model calibration and evaluation: Approximate Bayesian computation (2013, background): “, 2007; Vrugt and Robinson, 2007], the hypothetico-inductive data-based mechanistic modeling framework of Young [2012], and Bayesian data assimilation [Bulygina and Gupta, 2011].”
Estimating epistemic and aleatory uncertainties during hydrologic modeling: An information theoretic approach (2013, methodology): “Recently, a new method called the Bayesian estimation of structure (BESt) approach [Bulygina and Gupta, 2009, 2010, 2011] has been proposed to resolve the underlying structure of the model via data assimilation conducted on the raw data.”
Flow Prediction in Ungauged Catchments Using Probabilistic Random Forests Regionalization and New Statistical Adequacy Tests (2019, methodology): “Approximate p(z| •) by a mixture of KGaussian distributions (components) with mean μk and covariance matrix Σk for k = 1, K (Bulygina & Gupta, 2011; Muller et al., 1996).”