Improved treatment of uncertainty in hydrologic modeling: Combining the strengths of global optimization and data assimilation

Jasper A. Vrugt, Cees G H Diks, Hoshin Vijai Gupta, Willem Bouten, Jacobus M. Verstraten

Research output: Contribution to journalArticle

383 Citations (Scopus)

Abstract

Hydrologic models use relatively simple mathematical equations to conceptualize and aggregate the complex, spatially distributed, and highly interrelated water, energy, and vegetation processes in a watershed. A consequence of process aggregation is that the model parameters often do not represent directly measurable entities and must therefore be estimated using measurements of the system inputs and outputs. During this process, known as model calibration, the parameters are adjusted so that the behavior of the model approximates, as closely and consistently as possible, the observed response of the hydrologic system over some historical period of time. In practice, however, because of errors in the model structure and the input (forcing) and output data, this has proven to be difficult, leading to considerable uncertainty in the model predictions. This paper surveys the limitations of current model calibration methodologies, which treat the uncertainty in the input-output relationship as being primarily attributable to uncertainty in the parameters and presents a simultaneous optimization and data assimilation (SODA) method, which improves the treatment of uncertainty in hydrologic modeling. The usefulness and applicability of SODA is demonstrated by means of a pilot study using data from the Leaf River watershed in Mississippi and a simple hydrologic model with typical conceptual components.

Original languageEnglish (US)
Pages (from-to)1-17
Number of pages17
JournalWater Resources Research
Volume41
Issue number1
DOIs
StatePublished - Jan 2005

Fingerprint

Global optimization
data assimilation
uncertainty
modeling
hydrologic models
Watersheds
calibration
parameter uncertainty
Calibration
model uncertainty
watershed
Model structures
Uncertainty
Agglomeration
Rivers
vegetation
rivers
prediction
energy
methodology

ASJC Scopus subject areas

  • Environmental Science(all)
  • Environmental Chemistry
  • Aquatic Science
  • Water Science and Technology

Cite this

Improved treatment of uncertainty in hydrologic modeling : Combining the strengths of global optimization and data assimilation. / Vrugt, Jasper A.; Diks, Cees G H; Gupta, Hoshin Vijai; Bouten, Willem; Verstraten, Jacobus M.

In: Water Resources Research, Vol. 41, No. 1, 01.2005, p. 1-17.

Research output: Contribution to journalArticle

Vrugt, Jasper A. ; Diks, Cees G H ; Gupta, Hoshin Vijai ; Bouten, Willem ; Verstraten, Jacobus M. / Improved treatment of uncertainty in hydrologic modeling : Combining the strengths of global optimization and data assimilation. In: Water Resources Research. 2005 ; Vol. 41, No. 1. pp. 1-17.
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