21st Century flood risk projections at select sites for the U.S. National Park Service

Peter Van Dusen, Balaji Rajagopalan, David J. Lawrence, Laura E. Condon, Gary Smillie, Subhrendu Gangopadhyay, Tom Pruitt

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

Assessing flood risk using stationary flood frequency analysis techniques is commonplace. 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.

Original languageEnglish (US)
Article number100211
JournalClimate Risk Management
Volume28
DOIs
StatePublished - 2020
Externally publishedYes

Keywords

  • Flood risk

ASJC Scopus subject areas

  • Global and Planetary Change
  • Geography, Planning and Development
  • Atmospheric Science
  • Management, Monitoring, Policy and Law

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