Neglecting spatiotemporal rainfall variability misrepresents flood hazard and risk
- 1Department of Earth, Marine, and Environmental Sciences, University of North Carolina at Chapel Hill
- 2Department of Civil and Environmental Engineering, Rice University
- 3Department of Civil and Environmental Engineering, University of Wisconsin-Madison
Abstract
Flood risk assessments underpin flood management and resilience efforts worldwide, including land-use planning, infrastructure design, and insurance requirements. Many of these assessments rely on design storms, which assume a one-to-one relationship between the frequency of storms, flooding, and damage and neglect the spatial and temporal structure of rainfall. Here, we show that these assumptions can lead to systematic misrepresentation of flood hazard and risk. Using a coastal watershed in North Carolina, we compare design storm-based estimates with those from stochastic storm transposition, a probabilistic framework used to generate synthetic events with realistic rainfall fields. Though both methods produce similar basin-averaged rainfall statistics, we find design storms underestimate flood inundation frequency by 31–35% and expected annual damage by 93% relative to SST. These results reveal how complex storm-flood-damage relationships amplify risk from smaller, more frequent storms and illustrate that accounting for spatiotemporal rainfall variability is crucial to risk assessment.
Related
- A 256-year daily rainfall record reveals multiscale rainy-season variability and emerging hydroclimatic hazard over northern East Asia
- Assessment of Rainfall Variability and Its Impact on Soil Erosion Risk Using Rainfall Erosivity in Kwara State, Nigeria
- Year-Wise Refitted Spatiotemporal Landslide Susceptibility Forecasting Driven by IMD Rainfall and SMAP Soil Moisture, Wayanad, India
- A Universal Multifractals perspective into the link between rainfall variability and temperature
- Spatiotemporal trends in temperature and rainfall extremes in central and Northwestern Tigray, Ethiopia
BibTeX
@article{baer2026neglecting,
title = {{Neglecting spatiotemporal rainfall variability misrepresents flood hazard and risk}},
author = {John A. Baer and Antonia Sebastian and Lauren E. Grimley and James Doss-Gollin and Daniel B. Wright and Mohammad Ashar Hussain and Marissa K. Webber},
journal = {npj Natural Hazards},
year = {2026},
month = jun,
doi = {10.1038/s44304-026-00208-5},
url = {https://doi.org/10.1038/s44304-026-00208-5},
note = {CC BY},
}
RIS
TY - JOUR
TI - Neglecting spatiotemporal rainfall variability misrepresents flood hazard and risk
AU - John A. Baer
AU - Antonia Sebastian
AU - Lauren E. Grimley
AU - James Doss-Gollin
AU - Daniel B. Wright
AU - Mohammad Ashar Hussain
AU - Marissa K. Webber
PY - 2026
DA - 2026/06/01
JO - npj Natural Hazards
DO - 10.1038/s44304-026-00208-5
UR - https://doi.org/10.1038/s44304-026-00208-5
AB - Flood risk assessments underpin flood management and resilience efforts worldwide, including land-use planning, infrastructure design, and insurance requirements. Many of these assessments rely on design storms, which assume a one-to-one relationship between the frequency of storms, flooding, and damage and neglect the spatial and temporal structure of rainfall. Here, we show that these assumptions can lead to systematic misrepresentation of flood hazard and risk. Using a coastal watershed in North Carolina, we compare design storm-based estimates with those from stochastic storm transposition, a probabilistic framework used to generate synthetic events with realistic rainfall fields. Though both methods produce similar basin-averaged rainfall statistics, we find design storms underestimate flood inundation frequency by 31–35% and expected annual damage by 93% relative to SST. These results reveal how complex storm-flood-damage relationships amplify risk from smaller, more frequent storms and illustrate that accounting for spatiotemporal rainfall variability is crucial to risk assessment.
SN - 2948-2100
ER -