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

How Bayesian data assimilation can be used to estimate the mathematical structure of a model

(2010) Nataliya Bulygina et al.   STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT

Understanding predictive uncertainty in hydrologic modeling: The challenge of identifying input and structural errors

(2010) Benjamin Renard et al.   WATER RESOURCES RESEARCH

A short exploration of structural noise

(2010) John Doherty et al.   WATER RESOURCES RESEARCH

Forecasting skill of model averages

(2009) C. L. Winter et al.   STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT

Estimating the uncertain mathematical structure of a water balance model via Bayesian data assimilation

(2009) Nataliya Bulygina et al.   WATER RESOURCES RESEARCH

Analyzing input and structural uncertainty of nonlinear dynamic models with stochastic, time-dependent parameters

(2009) Peter Reichert et al.   WATER RESOURCES RESEARCH

Reconciling theory with observations: elements of a diagnostic approach to model evaluation

(2008) Hoshin V. Gupta et al.   HYDROLOGICAL PROCESSES

Learning from model improvement: On the contribution of complementary data to process understanding

(2008) Fabrizio Fenicia et al.   WATER RESOURCES RESEARCH

Treatment of input uncertainty in hydrologic modeling: Doing hydrology backward with Markov chain Monte Carlo simulation

(2008) Jasper A. Vrugt et al.   WATER RESOURCES RESEARCH

Framework for Understanding Structural Errors (FUSE): A modular framework to diagnose differences between hydrological models

(2008) Martyn P. Clark et al.   WATER RESOURCES RESEARCH