21st Century flood risk projections at select sites for the U.S. National Park Service
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Van Dusen, PeterRajagopalan, Balaji
Lawrence, David J.
Condon, Laura E.
Smillie, Gary
Gangopadhyay, Subhrendu
Pruitt, Tom
Affiliation
Univ Arizona, Dept Hydrol & Atmospher SciIssue Date
2020-02-04Keywords
Flood risk
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Van Dusen, P., Rajagopalan, B., Lawrence, D. J., Condon, L. E., Smillie, G., Gangopadhyay, S., & Pruitt, T. (2020). 21st Century flood risk projections at select sites for the US National Park Service. Climate Risk Management, 28, 100211.Journal
CLIMATE RISK MANAGEMENTRights
Copyright © 2020 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/BY-NC-ND/4.0/).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
Assessing flood risk using stationary flood frequency analysis techniques is commonplace. Flood risk However, it is increasingly evident that the stationarity assumption of these analyses does not hold as anthropogenic climate change could shift a site's hydroclimate beyond the range of historical behaviors. We employ nonstationary flood frequency models using the generalized extreme value (GEV) distribution to model changing flood risk for select seasons at twelve National Parks across the U.S. In this GEV model, the location and/or scale parameters of the distribution are allowed to change as a function of time-variable covariates. We use historical precipitation and modeled flows from the Variable Infiltration Capacity model (VIC), a land-surface model that simulates land-atmosphere fluxes using water and energy balance equations, as covariates to fit a best nonstationary GEV model to each site. We apply climate model projections of precipitation and VIC flows to these models to obtain future flood probability estimates. Our model results project a decrease in flood risk for sites in the southwestern U.S. region and an increase in flood risk for sites in northern and eastern regions of the U.S. for the selected seasons. The methods and results presented will enable the NPS to develop strategies to ensure public safety and efficient infrastructure management and planning in a nonstationary climate.Note
Open access journalISSN
2212-0963Version
Final published versionae974a485f413a2113503eed53cd6c53
10.1016/j.crm.2020.100211
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Except where otherwise noted, this item's license is described as Copyright © 2020 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/BY-NC-ND/4.0/).