Accurate delineation of compound flood hazard requires joint simulation of rainfall‐runoff and storm surges within high‐resolution flood models, which may be computationally expensive. There is a need for supplementing physical models with efficient, probabilistic methodologies for compound flood hazard assessment that can be applied under a range of climate and environment conditions. Here we propose an extension to the joint probability optimal sampling method (JPM‐OS), which has been widely used for storm surge assessment, and apply it for rainfall‐surge compound hazard assessment under climate change at the catchment‐scale. We utilize thousands of synthetic tropical cyclones (TCs) and physics‐based models to characterize storm surge and rainfall hazards at the coast. Then we implement a Bayesian quadrature optimization approach (JPM‐OS‐BQ) to select a small number (∼100) of storms, which are simulated within a high‐resolution flood model to characterize the compound flood hazard. We show that the limited JPM‐OS‐BQ simulations can capture historical flood return levels within 0.25 m compared to a high‐fidelity Monte Carlo approach. We find that the combined impact of 2100 sea‐level rise (SLR) and TC climatology changes on flood hazard change in the Cape Fear Estuary, NC will increase the 100‐year flood extent by 27% and increase inundation volume by 62%. Moreover, we show that probabilistic incorporation of SLR in the JPM‐OS‐BQ framework leads to different 100‐year flood maps compared to using a single mean SLR projection. Our framework can be applied to catchments across the United States Atlantic and Gulf coasts under a variety of climate and environment scenarios.
- NSF-PAR ID:
- 10330331
- Date Published:
- Journal Name:
- Nature Climate Change
- Volume:
- 12
- Issue:
- 2
- ISSN:
- 1758-678X
- Page Range / eLocation ID:
- 171 to 178
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Abstract Over the next century, model projections suggest that river run‑off in the Pacific Northwest will increase during the winter season and that sea‐level rise (SLR) may exceed a meter. To investigate the resulting changes in flood hazard, we numerically model the February 1996 and January 1923 floods (the largest and third‐largest Willamette River floods since 1900) under present and potential future run‐off and sea level scenarios. First, we reproduce the actual February 1996 flood to within a root‐mean‐square error of 0.05 m (
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1038/s41558-021-01272-7
