Rainfall distributional properties control hydrologic model parameter importance.
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Author
Meles, M.B.Goodrich, D.C.
Unkrich, C.L.
Gupta, H.V.
Burns, I.S.
Hirpa, F.A.
Razavi, S.
Guertin, D.P.
Affiliation
Department of Hydrology and Atmospheric Sciences, University of ArizonaSchool of Natural Resources and the Environment, University of Arizona
Issue Date
2024-01-10Keywords
Dynamic parameter importanceKINEROS2
Sensitivity analysis
VARS
Walnut gulch
Watershed modeling
Zonal calibration
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Elsevier B.V.Citation
Menberu B. Meles, Dave C. Goodrich, Carl L. Unkrich, Hoshin V. Gupta, I. Shea Burns, Feyera A. Hirpa, Saman Razavi, D. Phillip Guertin, Rainfall distributional properties control hydrologic model parameter importance., Journal of Hydrology: Regional Studies, Volume 51, 2024, 101662, ISSN 2214-5818, https://doi.org/10.1016/j.ejrh.2024.101662 (https://www.sciencedirect.com/science/article/pii/S2214581824000107).Rights
Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license.Collection Information
This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at repository@u.library.arizona.edu.Abstract
Study region: Semi-arid region of the Western United States of America in 16.6 km2 WS10 watershed using data from the highly instrumented Walnut Gulch Experimental Watershed managed by the USDA-Agricultural Research Services. Study focus: Hydrologic model parameters are generally designed to represent watershed physiographic properties. This study investigates the possible impact of climate forcing, particularly precipitation across a watershed, on model parameter identification – a topic that has historically received minimal attention. To address this gap, we conducted time-varying and time-aggregate sensitivity analysis of a physically based distributed hydrologic model on a heavily instrumented watershed under various observed and synthetic storm events to assess how the distributional properties of rainfall in space and time influence the importance model parameters. Particularly, we focused on a semi-arid watershed with an area larger than the typical convective storms in the region. New hydrologic insight: Results show that there is a significant variation in parameter importance following rainfall spatial and temporal properties and that characterizing the relationship between parameter importance and rainfall properties is essential for identifying parameter values that adequately capture the watershed behaviors. We further showed that a power-law function linking parameter importance to precipitation properties can extrapolate results to other climate regimes. More analyses across different watersheds, climate forcing, and models are required to improve our understanding and strategies for parametrization and calibration of watershed models. © 2024Note
Open access journalISSN
2214-5818Version
Final Published Versionae974a485f413a2113503eed53cd6c53
10.1016/j.ejrh.2024.101662
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Except where otherwise noted, this item's license is described as Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license.