Journal article
Understanding the Impact of Precipitation Bias‐Correction and Statistical Downscaling Methods on Projected Changes in Flood Extremes
Earth's future, Vol.12(3), e2023EF004179
03/2024
DOI: 10.1029/2023EF004179
Abstract
This study evaluates five bias correction and statistical downscaling (BCSD) techniques for daily precipitation and examines their impacts on the projected changes in flood extremes (i.e., 1%, 0.5%, and 0.2% floods). We use climate model outputs from the Coupled Model Intercomparison Project Phase 6 (CMIP6) to conduct hydrologic simulations across watersheds in Iowa and determine historical and future flood extreme estimates based on generalized extreme value distribution fitting. Projected changes in these extremes are examined with respect to four Shared Socioeconomic Pathways (SSPs) alongside five BCSD techniques. We find the magnitude of the estimates of future annual exceedance probabilities (AEPs) are expected to increase under all SSPs, especially for the emission scenarios with higher greenhouse gases concentrations (i.e., SSP370 and SSP585). Our results also suggest the choice of BCSD impacts the magnitude of the projected changes, with the SSPs that play a more limited role compared to the choice of downscaling method. The variability in projected flood changes across Iowa is similar across the downscaling technique but increases as the AEP increases. Our findings provide insights into the impact of downscaling techniques on flood extremes' projections and useful information for climate planning across the state.
Plain Language Summary
This study examines how different methods of spatial downscaling of gridded precipitation by climate model impact the projected changes of extreme flood events under different greenhouse gas emission scenarios. We focus on 44 locations within the state of Iowa (central United States) and use a hydrologic model to estimate the changes in flood extremes under current climate and four future emissions scenarios for different downscaling methods. Our results suggest that the choice of downscaling method impacts the magnitude of the projected changes, while the selected emission scenario plays a smaller role on the projected changes. Therefore, we encourage stakeholders to incorporate the impact of downscaling methods within water resource planning and design when considering climate change.
Key Points
All emission scenarios and downscaling techniques produce a projected increase in flood extremes across Iowa
Discrepancies among downscaling techniques become more pronounced with higher emission scenarios
Projected increases in flood extremes become greater as the annual exceedance probability decreases
Details
- Title: Subtitle
- Understanding the Impact of Precipitation Bias‐Correction and Statistical Downscaling Methods on Projected Changes in Flood Extremes
- Creators
- Alexander T. Michalek - Princeton UniversityGabriele Villarini - Princeton UniversityTaereem Kim - Princeton University
- Resource Type
- Journal article
- Publication Details
- Earth's future, Vol.12(3), e2023EF004179
- DOI
- 10.1029/2023EF004179
- ISSN
- 2328-4277
- eISSN
- 2328-4277
- Number of pages
- 10
- Grant note
- Iowa Department of Transportation (20‐SPR2‐002) Environmental Security Technology Certification Program U.S. Department of Defense
- Language
- English
- Date published
- 03/2024
- Academic Unit
- IIHR--Hydroscience and Engineering; Civil and Environmental Engineering
- Record Identifier
- 9984577111302771
Metrics
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