Assimilating multi-source uncertainties of a parsimonious conceptual hydrological model using hierarchical Bayesian modeling

作者：Wu Wei^*; Clark James S; Vose James M

来源：Journal of Hydrology, 2010, 394(3-4): 436-446.

DOI：10.1016/j.jhydrol.2010.09.017

• Hierarchical Bayesian modeling
• Hydrological modeling
• Soil moisture
• Streamflow

Hierarchical Bayesian (HB) modeling allows for multiple sources of uncertainty by factoring complex relationships into conditional distributions that can be used to draw Inference and make predictions We applied an HB model to estimate the parameters and state variables of a parsimonious hydrological model - GR4J - by coherently assimilating the uncertainties from the model observations and parameters at Coweeta Basin in western North Carolina A state-space model was within the Bayesian hierarchical framework to estimate the daily soil moisture levels and their uncertainties
Results show that the posteriors of the parameters were updated from and relatively insensitive to priors an indication that they were dominated by the data The uncertainties of the simulated streamflow increased with streamflow Increase By assimilating soil moisture data the model could estimate the maximum capacity of soil moisture accounting storage and predict storm events with higher precision compared to not assimilating soil

• 出版日期2010-11-26