Journal
WATER RESOURCES RESEARCH
Volume 51, Issue 1, Pages 716-728Publisher
AMER GEOPHYSICAL UNION
DOI: 10.1002/2014WR015820
Keywords
hydrology; process-based models; model agility; sensitivity analysis
Categories
Funding
- CIRES Graduate Fellowship Award
- Bureau of Reclamation
- U.S. Army Corps of Engineers
- National Science Foundation
- Australian Research Council Centre of Excellence for Climate System Science [CE110001028]
- EU [294947]
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In this commentary we suggest that hydrologists and land-surface modelers may be unnecessarily constraining the behavioral agility of very complex physics-based models. We argue that the relatively poor performance of such models can occur due to restrictions on their ability to refine their portrayal of physical processes, in part because of strong a priori constraints in: (i) the representation of spatial variability and hydrologic connectivity, (ii) the choice of model parameterizations, and (iii) the choice of model parameter values. We provide a specific example of problems associated with strong a priori constraints on parameters in a land surface model. Moving forward, we assert that improving hydrological models requires integrating the strengths of the physics-based modeling philosophy (which relies on prior knowledge of hydrologic processes) with the strengths of the conceptual modeling philosophy (which relies on data driven inference). Such integration will accelerate progress on methods to define and discriminate among competing modeling options, which should be ideally incorporated in agile modeling frameworks and tested through a diagnostic evaluation approach.
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