Hurricane Risk Assessment of Petroleum Infrastructure in a Changing Climate

Sichani, Majid Ebad; Anarde, Katherine; Capshaw, Kendall M.; Padgett, Jamie E.; Meidl, Rachel A.; Hassanzadeh, Pedram; Loch-Temzelides, Ted; Bedient, Philip B.

doi:10.3389/fbuil.2020.00104

Cited by 12 publications

(7 citation statements)

References 51 publications

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“…Rita produced 226 mm of total rainfall at Beaumont and a maximum surge of approximately 1.5 m at Sabine Pass (Knabb et al., 2006). Ike made landfall on Galveston Island, TX, on 13 September 2008, as a Category 2 hurricane with maximum sustained winds of 95 knots, R max of 30 nm, and a forward speed of 13.5 mph (Cooperative Institute for Research in the Atmosphere, 2021; Ebad Sichani et al., 2020). Within the study area, Ike produced 138 mm of total rainfall at Beaumont and a maximum storm surge of 3.9 m at Sabine Pass (Berg, 2009).…”

Section: Methodsmentioning

confidence: 99%

Compound Coastal, Fluvial, and Pluvial Flooding During Historical Hurricane Events in the Sabine–Neches Estuary, Texas

Maymandi

Hummel

2022

Water Resources Research

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When storm surge, river discharge, and rainfall occur simultaneously or in succession, they may cause compound flooding and exacerbate impacts in coastal communities. In traditional modeling approaches, these driving processes are simulated separately, leading to discrepancies between simulated and observed data and highlighting the need for coupled modeling frameworks. Here, we develop a coupled coastal–fluvial–pluvial model for the Sabine–Neches Estuary in southeastern Texas using Delft3D to simulate flood extent and depth during Hurricanes Rita, Ike, and Harvey. For each hurricane, four scenarios (i.e., coastal, fluvial, pluvial, and compound) are modeled to determine the relative contribution of each driving force to water levels across the domain. Our results reveal that tropical cyclones such as Harvey that are accompanied by extended periods of rainfall produce the largest extent and longest duration of compound flooding. Such storms also produce highly dynamic and evolving patterns of compound flooding over their duration, with multiple flood peaks that can inhibit response and recovery efforts. When simulating these storms, a coupled model can provide substantial improvements over coastal‐, fluvial‐, and pluvial‐only models, decreasing root mean square error by 69%, 69%, and 79%, respectively. In contrast, storms with short‐duration rainfall and moderate to severe storm surge produce less extensive compound flooding, which is typically dominated by coastal–pluvial interactions. Our results further highlight the potential for compound flooding at the locations of critical water infrastructure assets, suggesting the need for flood adaptation approaches that are robust to multiple types of flooding.

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Section: Methodsmentioning

confidence: 99%

Compound Coastal, Fluvial, and Pluvial Flooding During Historical Hurricane Events in the Sabine–Neches Estuary, Texas

Maymandi

Hummel

2022

Water Resources Research

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“…Galveston Island is located in a hurricane-prone region susceptible to the effects of storm surge and wave loading (FEMA, 2009;Liu and Irish, 2019). To consider the effect of a changing climate on the impact of future storms, the forward velocity of the storm V f and projected increments in the local sea-level are considered, given their influence on surge generation during hurricane events (Liu and Irish, 2019;Moon et al, 2019;Ebad Sichani et al, 2020;Hassanzadeh et al, 2020). In this study, synthetic variations of the scenario storm FEMA 33 (FEMA, 2013;Ebersole et al, 2017) are used to define the hazard as an illustration of the framework.…”

Section: Hazard Analysismentioning

confidence: 99%

“…Storm FEMA 33 is a synthetic storm that results in still-water elevations equivalent to approximately a 100-years return period storm in the Houston-Galveston region per (Ebersole et al, 2017;Melby et al, 2017). The reader can refer to (Ebad Sichani et al, 2020) for details on the hazard model and its outcomes which are adopted in this study. The physics-based numerical model ADCIRC + SWAN was implemented to simulate 19 synthetic variations of storm FEMA 33 by varying the forward velocity of the storm while keeping the spatial characteristics constant (Ebad Sichani et al, 2020).…”

Section: Hazard Analysismentioning

confidence: 99%

“…The reader can refer to (Ebad Sichani et al, 2020) for details on the hazard model and its outcomes which are adopted in this study. The physics-based numerical model ADCIRC + SWAN was implemented to simulate 19 synthetic variations of storm FEMA 33 by varying the forward velocity of the storm while keeping the spatial characteristics constant (Ebad Sichani et al, 2020). The model implements the TX2008 mesh [Federal Emergency Management Agency (FEMA) and U.S. Army Corps of Engineers (USACE), 2011] and comprises 2,500,861 triangular elements and 1,258,550 nodes.…”

Section: Hazard Analysismentioning

confidence: 99%

“…The forward velocity of the storm is defined based on the range proposed by Liu and Irish (2019) for the Galveston region. Given the high uncertainty in the effects of climate change in the forward velocity of tropical cyclones (Ebad Sichani et al, 2020), a uniform distributionV f ∼ U(3, 12) m/s is adopted in this case study. The empirical fragility model proposed by Tomiczek et al (2014) for wood-framed residences in the Galveston area following Hurricane Ike is used in this study to predict the probability of collapse (i.e.…”

Section: Hazard Analysismentioning

confidence: 99%

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Performance-Based Coastal Engineering Framework

González-Dueñas

Padgett

2021

Front. Built Environ.

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The changing dynamics of coastal regions and climate pose severe challenges to coastal communities around the world. Effective planning of engineering projects and resilience strategies in coastal regions must not only address current conditions but also take into consideration the expected changes in the exposure and multi-hazard risk in these areas. However, existing performance-based engineering frameworks generally neglect time-varying factors and miss the opportunity to leverage related evidence as it becomes available. This paper proposes a Performance-Based Coastal Engineering (PBCE) framework that is flexible enough to accommodate uncertain time-varying factors, multi-hazard conditions, and cascading-effects. Furthermore, using a dynamic Bayesian network approach, the framework can incorporate observed evidence into the model to update the prior conditional distribution of the analyzed variables. As a proof of concept, two case studies—a typical elevated residential structure and a two-frame system—are presented, considering the effects of cascading failure, the incorporation of time-varying factors, and the influence of emerging evidence. Results show that neglecting cascading effects significantly underestimates the losses and that the incorporation of evidence reduces the uncertainty under the assumed distribution of evidence. The resulting PBCE framework can support data collection efforts, optimization of retrofitting strategies, integration of experts and community interests by facilitating interactions and knowledge sharing, as well as the identification of vulnerable regions and critical components in coastal multi-hazard regions.

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