A surge response function approach to coastal hazard assessment – part 1: basic concepts

Resio, Donald T.; Irish, Jennifer L.; Cialone, Mary A.

doi:10.1007/s11069-009-9379-y

Cited by 124 publications

(110 citation statements)

References 14 publications

Supporting

Mentioning

110

Contrasting

Order By: Relevance

“…For instance, historical hurricanes (see Table 2 for select examples) are often associated with a return period when in fact, a region should define return periods for particular storm attributes as they contribute to inundation hazards within the given region. Further, this should be done on a spatially dependent basis, be it discrete as is the case here or continuous as shown in Irish et al (2009) and Resio et al (2009). On the other hand, the top 5 storms (numbers 65, 83, 84, 64, and 66) contributing to the 0.2% flooding surface yield 76% (coverage) of the flooding surface.…”

Section: Recap and Discussionmentioning

confidence: 99%

“…In this comparison, the HHI is more reflective of the hazard potential than is the SSHS. Resio et al (2009) developed a surge response function approach, a variant of the standard Joint Probability Method (JPM) approach to coastal hazard assessment. A basic concept of the approach is to maximize the information content in the sample set of storms to be simulated and introduced into the JPM surge matrices.…”

Section: Hurricane Intensity Index and Hurricane Hazard Indexmentioning

confidence: 99%

See 1 more Smart Citation

Coastal Flooding in Florida’s Big Bend Region with Application to Sea Level Rise Based on Synthetic Storms Analysis

Hagen¹,

Bacopoulos²

2012

Terr. Atmos. Ocean. Sci.

View full text Add to dashboard Cite

Flooding is examined by comparing maximum envelopes of water against the 0.2% (= 1-in-500-year return-period) flooding surface generated as part of revising the Federal Emergency Management Agency's flood insurance rate maps for Franklin, Wakulla, and Jefferson counties in Florida's Big Bend Region. The analysis condenses the number of storms to a small fraction of the original 159 used in production. The analysis is performed by assessing which synthetic storms contributed to inundation extent (the extent of inundation into the floodplain), coverage (the overall surface area of the inundated floodplain) and the spatially variable 0.2% flooding surface. The results are interpreted in terms of storm attributes (pressure deficit, radius to maximum winds, translation speed, storm heading, and landfall location) and the physical processes occurring within the natural system (storms surge and waves); both are contextualized against existing and new hurricane scales.The approach identifies what types of storms and storm attributes lead to what types of inundation, as measured in terms of extent and coverage, in Florida's Big Bend Region and provides a basis in the identification of a select subset of synthetic storms for studying the impact of sea level rise. The sea level rise application provides a clear contrast between a dynamic approach versus that of a static approach.

show abstract

Section: Recap and Discussionmentioning

confidence: 99%

Section: Hurricane Intensity Index and Hurricane Hazard Indexmentioning

confidence: 99%

Coastal Flooding in Florida’s Big Bend Region with Application to Sea Level Rise Based on Synthetic Storms Analysis

Hagen¹,

Bacopoulos²

2012

Terr. Atmos. Ocean. Sci.

View full text Add to dashboard Cite

show abstract

“…In spite of this somewhat questionable form, objective testing by Houston et al [29] concluded parametric winds at landfall reasonably represented the maximum winds in most storms studied. Estimated errors in each of the remaining five parameters can be scaled to approximate the magnitude of the associated errors in surges using response surface concepts [33,67,68]. Official forecast cross-track errors averaged over last 5-years are 85 and 151 km at 24 and 48 h, respectively.…”

Section: Estimating Tropical Cyclone Surge Hazard On the Scale Of Daysmentioning

confidence: 99%

“…Hurricane Katrina provided direct evidence that there could be large discrepancies between these two types of information. As a result, since 2005, the USACE and FEMA adopted the JPM with some modifications to reduce the number of storms in the sample required for surge simulation, while maintaining good accuracy for planning purposes-sometimes termed the JPM-OS approach for Boptimal sampling^ [33,67,68,80]. Irish et al [34] showed the estimation power of the JPM significantly exceeds that of the HSM, and that the use of historical surge data alone for planning could introduce substantial local errors into design and planning decision-making.…”

Section: Estimating Tropical Cyclone Surge Hazard On a Multi-year Scalementioning

confidence: 99%

“…Two primary methods have been developed to reduce the number of storms (i.e., samples) needed in surge simulations, while maintaining adequate sampling resolution and integration domain for representing the full JPM integral accurately: Surface Response Functions (SRF) ( [33,67,68]; others) and Bayesian Quadrature [63,80]. Both methods produce good results when compared to results using a larger number of samples; however, some assumptions initially developed for application in the central Gulf of Mexico are in need of additional review.…”

Section: Estimating Tropical Cyclone Surge Hazard On a Multi-year Scalementioning

confidence: 99%

See 1 more Smart Citation

Tropical Cyclone Storm Surge Risk

Resio

Irish

2015

Curr Clim Change Rep

Self Cite

View full text Add to dashboard Cite

Tropical cyclone storm surge represents a significant threat to communities around the world. These surge characteristics vary spatially and temporally over a range of scales; therefore, conceptual frameworks for understanding and mitigating them must be cast within a context of risk that covers the complete range of hazards, their consequences, and methods for mitigation. A review of primary overlapping time scales and associated spatial scales for tropical cyclone surge hazards covers two scales of particular interest: (1) synopticscale predictions used for warnings and evacuation decisions and (2) long-term estimation of hazards and related risks needed for coastal planning and decision-making. Factors that can affect these estimates, such as episodic variations in tropical cyclone characteristics and longer-term climate change and sea-level rise are then examined in the context of their potential impacts on hazards and risks related to tropical cyclone surges.

show abstract

Heightened hurricane surge risk in northwest Florida revealed from climatological‐hydrodynamic modeling and paleorecord reconstruction

et al. 2014

View full text Add to dashboard Cite

Historical tropical cyclone (TC) and storm surge records are often too limited to quantify the risk to local populations. Paleohurricane sediment records uncover long‐term TC activity, but interpreting these records can be difficult and can introduce significant uncertainties. Here we compare and combine climatological‐hydrodynamic modeling (including a method to account for storm size uncertainty), historical observations, and paleohurricane records to investigate local surge risk, using Apalachee Bay in northwest Florida as an example. The modeling reveals relatively high risk, with 100 year, 500 year, and “worst case” surges estimated to be about 6.3 m, 8.3 m, and 11.3 m, respectively, at Bald Point (a paleorecord site) and about 7.4 m, 9.7 m, and 13.3 m, respectively, at St. Marks (the head of the Bay), supporting the inference from paleorecords that Apalachee Bay has frequently suffered severe inundation for thousands of years. Both the synthetic database and paleorecords contain a much higher frequency of extreme events than the historical record; the mean return period of surges greater than 5 m is about 40 years based on synthetic modeling and paleoreconstruction, whereas it is about 400 years based on historical storm analysis. Apalachee Bay surge risk is determined by storms of broad characteristics, varies spatially over the area, and is affected by coastally trapped Kelvin waves, all of which are important features to consider when accessing the risk and interpreting paleohurricane records. In particular, neglecting size uncertainty may induce great underestimation in surge risk, as the size distribution is positively skewed. While the most extreme surges were generated by the uppermost storm intensities, medium intensity storms (categories 1–3) can produce large to extreme surges, due to their larger inner core sizes. For Apalachee Bay, the storms that induced localized barrier breaching and limited sediment transport (overwash regime; surge between 3 and 5 m) are most likely to be category 2 or 3 storms, and the storms that inundated the entire barrier and deposited significantly more coarse materials (inundation regime; surge > 5 m) are most likely to be category 3 or 4 storms.

show abstract

A surge response function approach to coastal hazard assessment – part 1: basic concepts

Cited by 124 publications

References 14 publications

Coastal Flooding in Florida’s Big Bend Region with Application to Sea Level Rise Based on Synthetic Storms Analysis

Coastal Flooding in Florida’s Big Bend Region with Application to Sea Level Rise Based on Synthetic Storms Analysis

Tropical Cyclone Storm Surge Risk

Heightened hurricane surge risk in northwest Florida revealed from climatological‐hydrodynamic modeling and paleorecord reconstruction

Contact Info

Product

Resources

About