Uncertainty in hydrologic modeling: Toward an integrated data assimilation framework
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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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2Topics & keywords
Topics
Keywords
- Hydrological modelling
- Data assimilation
- Computer science
- Uncertainty analysis
- Identification (biology)
- Key (lock)
- Risk analysis (engineering)
- Data science
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