Modeling flood induced interdependencies among hydroelectricity generating infrastructures

Sultana, Sharmin; Chen, Z.

doi:10.1016/j.jenvman.2009.05.019

Cited by 21 publications

(4 citation statements)

References 21 publications

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“…There are models that are capable of performing system‐level vulnerability assessment. For example, Petri nets are among widely used methodologies to assess cyber‐physical attacks to infrastructures (Chen, Sanchez‐Aarnoutse, & Buford, ) and natural hazard‐induced vulnerabilities (Sultana & Chen, ). For example, combining Petri net with Bayesian learning, Chiachío, Chiachío, Prescott, and Andrews (); Pereyra, He, and Mostafavi (); and Taleb‐Berrouane, Khan, and Amyotte () used the integrated method to monitor and analyze the infrastructure system risks.…”

Section: Literature Reviewmentioning

confidence: 99%

Bayesian modeling of flood control networks for failure cascade characterization and vulnerability assessment

Dong

Farahmand

et al. 2019

Computer aided Civil Eng

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This paper presents a Bayesian network model to assess the vulnerability of the flood control infrastructure and to simulate failure cascade based on the topological structure of flood control networks along with hydrological information gathered from sensors. Two measures are proposed to characterize the flood control network vulnerability and failure cascade: (a) node failure probability (NFP), which determines the failure likelihood of each network component under each scenario of rainfall event, and (b) failure cascade susceptibility, which captures the susceptibility of a network component to failure due to failure of other links. The proposed model was tested in both single watershed and multiple watershed scenarios in Harris County, Texas using historical data from three different flooding events, including Hurricane Harvey in 2017. The proposed model was able to identify the most vulnerable flood control network segments prone to flooding in the face of extreme rainfall. The framework and results furnish a new tool and insights to help decision-makers to prioritize infrastructure enhancement investments and actions. The proposed Bayesian network modeling framework also enables simulation of failure cascades in flood control infrastructures, and thus could be used for scenario planning as well as near-real-time inundation forecasting to inform emergency response planning and operation, and hence improve the flood resilience of urban areas. 668 wileyonlinelibrary.com/journal/mice Comput Aided Civ Inf. 2020;35:668-684.

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Section: Literature Reviewmentioning

confidence: 99%

Bayesian modeling of flood control networks for failure cascade characterization and vulnerability assessment

Dong

Farahmand

et al. 2019

Computer aided Civil Eng

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“…Mostly, fragility curves of diverse infrastructures can be obtained from the domain research. For example, the electric transmission station fragility curves under hurricane conditions can be developed from the research in electrical engineering (Ouyang & Wang, ), and the hydropower fragility curve under flood conditions can be developed from the research in hydro technical engineering (Sultana & Chen, ). More recently, some statistical methods have been introduced to obtain the fragility curve/rule of a single building/facility without experimental data.…”

Section: Multiple Hazards Resilience Assessment Methodologymentioning

confidence: 99%

Probabilistic Multiple Hazard Resilience Model of an Interdependent Infrastructure System

Kong

Simonović́

2019

Risk Analysis

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Multiple hazard resilience is of significant practical value because most regions of the world are subject to multiple natural and technological hazards. An analysis and assessment approach for multiple hazard spatiotemporal resilience of interdependent infrastructure systems is developed using network theory and a numerical analysis. First, we define multiple hazard resilience and present a quantitative probabilistic metric based on the expansion of a single hazard deterministic resilience model. Second, we define a multiple hazard relationship analysis model with a focus on the impact of hazards on an infrastructure. Subsequently, a relationship matrix is constructed with temporal and spatial dimensions. Further, a general method for the evaluation of direct impacts on an individual infrastructure under multiple hazards is proposed. Third, we present an analysis of indirect multiple hazard impacts on interdependent infrastructures and a joint restoration model of an infrastructure system. Finally, a simplified two-layer interdependent infrastructure network is used as a case study for illustrating the proposed methodology. The results show that temporal and spatial relationships of multiple hazards significantly influence system resilience. Moreover, the interdependence among infrastructures further magnifies the impact on resilience value. The main contribution of the article is a new multiple hazard resilience evaluation approach that is capable of integrating the impacts of multiple hazard interactions, interdependence of network components (layers), and restoration strategy.

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“…Transitions in multiple directions could occur between the states, not only degradation to a worse state with larger damage and disruption, but also recovery to a better state. [38]. To do so would, however, introduces its own modeling and informational uncertainties.…”

Section: Special Case Of Interdependent Critical Infrastructuresmentioning

confidence: 99%

Risk assessment and management for interconnected critical infrastructure systems at the site and regional levels in California's Sacramento-San Joaquin Delta

Roe

Bea

Jonkman

et al. 2016

IJCIS

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Modeling flood induced interdependencies among hydroelectricity generating infrastructures

Cited by 21 publications

References 21 publications

Bayesian modeling of flood control networks for failure cascade characterization and vulnerability assessment

Bayesian modeling of flood control networks for failure cascade characterization and vulnerability assessment

Probabilistic Multiple Hazard Resilience Model of an Interdependent Infrastructure System

Risk assessment and management for interconnected critical infrastructure systems at the site and regional levels in California's Sacramento-San Joaquin Delta

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