Beyond The 100-Year Flood
Probabilistic Flood Hazard Assessment For King And Pierce Counties [WA] Under Future Climate Scenarios
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https://doi.org/10.5194/nhess-26-3231-2026 <-- shared #openacess paper
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[part of my old stomping ground as an engineering geologist]
H/T Kees Nederhoff
“Flood maps are usually built from a single design storm. For King and Pierce Counties in the Pacific Northwest (USA), [the authors] tried the opposite - simulate 82 years of actual coastal and river conditions (plus 18 synthetic years) with SFINCS and let the statistics fall out cell by cell. That took about 5,400 yearly simulations and 194,000 CPU hours on USGS’s Hovenweep HPC. Worth it!
The design-event shortcut turns out to hide a real hazard. A deterministic 10-year event underestimated flood depths by up to half a meter compared to the continuous runs.
The bigger surprise [to the authors] was how one-sided the climate signal is. One metre of sea level rise takes King County’s expected annual flooded area from 161 --> 787 hectares, almost a factor of five. Changes in storminess over the same horizon barely register. And somewhere between 100 and 150 cm of SLR, land that never floods today starts flooding fast. If you plan adaptation in Puget Sound, that threshold matters more than any single return-period map.
[They] also propose Expected Annual Flooded Area (EAFA) as a probability-weighted alternative to the binary “inside or outside the 100-year zone” label…”
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“Coastal regions across the globe, including the Salish Sea, are becoming increasingly vulnerable to compound flooding due to the interaction between storm surge, tides, and river outflow. This hazard is anticipated to increase under sea level rise and climate change. This research offers a high-resolution flood hazard mapping approach for King and Pierce Counties of Washington State (United States of America) using the SFINCS (Super-Fast INundation of CoastS) model to facilitate a Continuous Flood Response Modeling (CFRM) framework wherein decades of dynamic coastal and fluvial processes are simulated. By applying a cell-by-cell extreme value analysis, [they] predict flood areas for return periods of 1 to 100 years and compute the Expected Annual Flooded Area (EAFA) as a probability-weighted indicator of flood exposure. Validation of the model against NOAA and USGS gauge data demonstrated good skill (RMSE: 14–17 cm for coastal water levels; unbiased RMSE: 49–116 cm for river water levels), while comparison with FEMA Special Flood Hazard Areas showed high spatial agreement of flooding (hit rates: 0.75–0.83). The statistical analysis of the historical flooding timing showed that the 28 December 2022, event was primarily responsible for the majority of historical flooding in the region. Climate simulations for today indicate an EAFA range of 56–200 ha in King County and 250–644 ha in Pierce County. Projections of future changes show that the primary driver of increasing flood extent is sea level rise (an increase of 80 %–360 % with 1m SLR), while climate change drivers, such as changes to storm patterns, reduce hazards minimally. A threshold was also identified where there is a substantial increase in the area of land that is flooded when sea levels rise above 100–150 cm. Finally, it was found that simple deterministic flood maps may underrepresent flood hazard by approximately 0.5 m if not all contributing factors are considered. Therefore, these findings provide evidence supporting the use of integrated measures of flood hazard, such as EAFA, to inform more rational and spatially responsive flood risk management…”
#USGS #supercomputing #Hovenweep #HPC #coast #coastal #PNW #Seattle #PacificNorthwest #risk #hazard #riskmanagement #model #modeling #CFRM #deterministic #probabilistic #climatechange #extremeweather #fedscience #WA #KingCounty #PierceCounty #WashingtonState #USA #flood #flooding #compoundflooding #floodmaps #SFINCS #storm #weather #climate #climatechange #rainfall #precipitation #sealevel #sealevelrise #SLR #100yearflood #floodhazardmapping #returnperiods #pluvial #fluvial #spatialanalysis #spatiotemporal #remotesensing #streamgage #history #historicflooding #projections #predictions
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