articleWater Resources ResearchJul 1, 2007BRONZE OA

Uncertainty in hydrologic modeling: Toward an integrated data assimilation framework

University of Arizona

Indexed incrossrefdoaj

Abstract

Despite significant recent developments in computational power and distributed hydrologic modeling, the issue of how to adequately address the uncertainty associated with hydrological predictions remains a critical and challenging one. This issue needs to be properly addressed for hydrological modeling to realize its maximum practical potential in environmental decision‐making processes. Arguably, the key to properly addressing hydrologic uncertainty is to understand, quantify, and reduce uncertainty involved in hydrologic modeling in a cohesive, systematic manner. Although general principles and techniques on addressing hydrologic uncertainty are emerging in the literature, there exist no well‐accepted…

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884
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35.04
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100%
References
101
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Authors

2

Topics & keywords

Keywords
  • Hydrological modelling
  • Data assimilation
  • Computer science
  • Uncertainty analysis
  • Identification (biology)
  • Key (lock)
  • Risk analysis (engineering)
  • Data science
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