Science for a risky world—A U.S. Geological Survey plan for risk research and applications

Ludwig, K. R.; Ramsey, David W.; Wood, Nathan J.; Pennaz, Alice; Godt, Jonathan W.; Plant, Nathaniel G.; Luco, Nicolas; Koenig, Todd A.; Hudnut, K. W.; Davis, Donyelle K.; Bright, Patricia R.

doi:10.3133/cir1444

Cited by 14 publications

(13 citation statements)

References 3 publications

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“…The model reproduced the enhanced transfer in the storm band at Mantoloking during 2012, suggesting a physical mechanism for the change that the model was able to capture but remains unexplained. The likely explanation is that the location of the Azores-Bermuda high-pressure system over the Atlantic in 2012 (Mattingly et al, 2015), associated with the negative phase of the North Atlantic Oscillation, resulted in average winds that lined up with the axis of the bay and caused enhanced wind setup in the northern part of the bay. The model overestimated the transfer at ETH in the storm band and underestimated the low-frequency transfer at Waretown.…”

Section: Offshore Transfer To Baymentioning

confidence: 99%

“…As part of the general needs for hazard assessment (Ludwig et al, 2018), the important hazard characteristics that decision makers require include spatial extent, duration, and magnitude. The proposed methodology provides an approximation to both the extent of the area and the magnitude and also variations based on storm duration.…”

Section: Validity For Flooding Hazard Assessmentsmentioning

confidence: 99%

“…Hazard assessments consist of a characterization of the spatial and temporal extent of damaging physical events and the determination of the specific characteristics of those events (Ludwig et al, 2018). While flooding on the mainland side of back-barrier bays has severe socioeconomic implications, most coastal hazard evaluations (Gornitz et al, 1994;Thieler and Hammar-Klose, 1999;Klein and Nicholls, 1999;Kunreuther et al, 2000;Neumann et al, 2015;Vitousek et al, 2017) have focused on open-coast areas.…”

Section: Introductionmentioning

confidence: 99%

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Spatial distribution of water level impacting back-barrier bays

Aretxabaleta

Ganju

Defne

et al. 2019

Nat. Hazards Earth Syst. Sci.

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Abstract. Water level in semi-enclosed bays, landward of barrier islands, is mainly driven by offshore sea level fluctuations that are modulated by bay geometry and bathymetry, causing spatial variability in the ensuing response (transfer). Local wind setup can have a complementary role that depends on wind speed, fetch, and relative orientation of the wind direction and the bay. Bay area and inlet geometry and bathymetry primarily regulate the magnitude of the transfer between open ocean and bay. Tides and short-period offshore oscillations are more damped in the bays than longer-lasting offshore fluctuations, such as a storm surge and sea level rise. We compare observed and modeled water levels at stations in a mid-Atlantic bay (Barnegat Bay) with offshore water level proxies. Observed water levels in Barnegat Bay are compared and combined with model results from the Coupled Ocean–Atmosphere–Wave–Sediment Transport (COAWST) modeling system to evaluate the spatial structure of the water level transfer. Analytical models based on the dimensional characteristics of the bay are used to combine the observed data and the numerical model results in a physically consistent approach. Model water level transfers match observed values at locations inside the bay in the storm frequency band (transfers ranging from 50 %–100 %) and tidal frequencies (10 %–55 %). The contribution of frequency-dependent local setup caused by wind acting along the bay is also considered. The wind setup effect can be comparable in magnitude to the offshore transfer forcing during intense storms. The approach provides transfer estimates for locations inside the bay where observations were not available, resulting in a complete spatial characterization. An extension of the methodology that takes advantage of the ADCIRC tidal database for the east coast of the United States allows for the expansion of the approach to other bay systems. Detailed spatial estimates of water level transfer can inform decisions on inlet management and contribute to the assessment of current and future flooding hazard in back-barrier bays and along mainland shorelines.

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Section: Offshore Transfer To Baymentioning

confidence: 99%

Section: Validity For Flooding Hazard Assessmentsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Spatial distribution of water level impacting back-barrier bays

Aretxabaleta

Ganju

Defne

et al. 2019

Nat. Hazards Earth Syst. Sci.

View full text Add to dashboard Cite

show abstract

“…As part of the general needs for hazard assessment (Ludwig et al, 2018), the important hazard characteristics that decision makers require include spatial extent, duration, and magnitude. The proposed methodology provides an approximation to both the area extent and magnitude, and also variations based on storm duration.…”

Section: Validity For Flooding Hazard Assessmentsmentioning

confidence: 99%

“…Hazard assessments consist of a characterization of the spatial and temporal extent of damaging physical events and the determination of the specific characteristics of those events (Ludwig et al, 2018). While flooding in the mainland side of back-barrier bays has severe socio-economic implications, most of the coastal hazard evaluations (Gornitz et al, 1994;Thieler and Hammar-Klose, 1999;Klein and Nicholls, 1999;Kunreuther et al, 2000) have focused in open-coast areas.…”

mentioning

confidence: 99%

Spatial distribution of water level impact to back-barrier bays

Aretxabaleta¹,

Ganju²,

Defne³

et al. 2018

Preprint

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Abstract. Water level in semi-enclosed bays, landward of barrier islands, is mainly driven by offshore sea level fluctuations that are modulated by bay geometry and bathymetry, causing spatial variability in the ensuing response (transfer). Local wind setup can have a secondary role that depends on wind speed, fetch, and relative orientation of the wind direction and the bay. Inlet geometry and bathymetry primarily regulate the magnitude of the transfer between open ocean and bay. Tides and short-period offshore oscillations are more damped in the bays than longer-lasting offshore fluctuations, such as storm surge and sea level rise. We compare observed and modeled water levels at stations in a mid-Atlantic bay (Barnegat Bay) with offshore water level proxies. Observed water levels in Barnegat Bay are compared and combined with model results from the Coupled Ocean–Atmosphere–Wave–Sediment Transport (COAWST) modeling system to evaluate the spatial structure of the water level transfer. Analytical models based on the dimensional characteristics of the bay are used to combine the observed data and the numerical model results in a physically consistent approach. Model water level transfers match observed values at locations inside the Bay in the storm frequency band (transfers ranging from 70–100 %) and tidal frequencies (10–55 %). The contribution of frequency-dependent local setup caused by wind acting along the bay is also considered. The approach provides transfer estimates for locations inside the Bay where observations were not available resulting in a complete spatial characterization. The approach allows for the study of the Bay response to alternative forcing scenarios (landscape changes, future storms, and rising sea level). Detailed spatial estimates of water level transfer can inform decisions on inlet management and contribute to the assessment of current and future flooding hazard in back-barrier bays and along mainland shorelines.

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Changes in wildfire occurrence and risk to homes from 1990 through 2019 in the Southern Rocky Mountains,USA

et al. 2023

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Wildfires and housing development have increased since the 1990s, presenting unique challenges for wildfire management. However, it is unclear how the relative influences of housing growth and changing wildfire occurrence have altered risk to homes, or the potential for wildfire to threaten homes. We used a random forests model to predict burn probability in relation to weather variables at 1-km resolution and monthly intervals from 1990 through 2019 in the Southern Rocky Mountains ecoregion. We quantified risk by combining the

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Science for a risky world—A U.S. Geological Survey plan for risk research and applications

Cited by 14 publications

References 3 publications

Spatial distribution of water level impacting back-barrier bays

Spatial distribution of water level impacting back-barrier bays

Spatial distribution of water level impact to back-barrier bays

Changes in wildfire occurrence and risk to homes from 1990 through 2019 in the Southern Rocky Mountains,USA

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