Skip to page content
USDA Forest Service

Research & Development Treesearch

Treesearch Home
About Treesearch
Contact Us
Research & Development
Forest Products Lab
International Institute of Tropical Forestry
Pacific Northwest
Pacific Southwest
Rocky Mountain
Southern Research Station
Help - We Participate  Government Made Easy

Global Forest Information Service

US Forest Service
P.O. Box 96090
Washington, D.C.

(202) 205-8333

You are here: Home / Search / Publication Information
Bookmark and Share

Publication Information

View PDF (1.5 MB)

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

Author: Wu, Wei; Clark, James S.; Vose, James M.;

Date: 2010

Source: Journal of Hydrology 394(3-4):436-446

Publication Series: Scientific Journal (JRNL)

Description: 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 moisture data. This study has shown that hierarchical Bayesian model is a useful tool in water resource planning and management by acknowledging stochasticity.

Keywords: Hierarchical Bayesian modeling, Hydrological modeling, Soil moisture, Streamflow

Publication Notes:

  • We recommend that you also print this page and attach it to the printout of the article, to retain the full citation information.
  • This article was written and prepared by U.S. Government employees on official time, and is therefore in the public domain.



Wu, Wei; Clark, James S.; Vose, James M. 2010. Assimilating multi-source uncertainties of a parsimonious conceptual hydrological model using hierarchical Bayesian modeling. Journal of Hydrology 394(3-4):436-446.


 [ Get Acrobat ]  Get the latest version of the Adobe Acrobat reader or Acrobat Reader for Windows with Search and Accessibility

USDA logo which links to the department's national site. Forest Service logo which links to the agency's national site.