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Abstract In the event of near-field tsunamis, vertical evacuation can be an alternative protective action to horizontal evacuation. The objective of this paper is to present an agent-based modeling (ABM) framework to evaluate vertical evacuation behavior and shelter locations for a near-field tsunami hazard from a Magnitude 9.0 Cascadia Subduction Zone (CSZ) earthquake. The expected mortality rate depending on the location of the vertical evacuation shelter (VES) has been chosen as the primary criterion to assess the effectiveness of the vertical evacuation. In addition, maximum tsunami wave height and the vertical evacuation behavior changes with changes in the placement of the VES have been assessed from a constraint point of view. The results revealed that (1) the choice of VES locations will directly impact the proportion of the people who evacuate vertically; (2) The percentage of people who evacuate vertically exponentially drops as the shelter gets farther from the population centroid; (3) the location of shelter significantly impacts the total mortality rates; (4) improvements in evacuees' mobility, such as faster walking speed or shorter milling time, will significantly reduce mortality rate and expand the area of choices for VES locations; and (5) when more people choose to evacuate vertically, the total mortality rate reduces notably. However, wrong placement of VES, and at the same time promoting vertical evacuation behavior can result in catastrophic mortality rates. In addition, a study on the impact of the distance of the VES to the ocean, to the population centroid, and to the horizontal shelters outside of the inundation zone, on the total mortality rate and the evacuation efficiency has been performed. This work reveals the non-linear correlation between the aforementioned characteristics of the VES on the expected mortality rate. The results of this research provide an evidence-driven vertical evacuation modeling framework to guide decision makers at city, state, and federal level to understand the dynamics of vertical evacuation behavior and choice of vertical evacuation shelter locations for a community. [ABSTRACT FROM AUTHOR]

Urban flooding disrupts traffic networks, affecting mobility and disrupting residents' access. Flooding events are predicted to increase due to climate change; therefore, understanding traffic network's flood-caused disruption is critical to improving emergency planning and city resilience. This study reveals the anatomy of perturbed traffic networks by leveraging high-resolution traffic network data from a major flood event and advanced high-order network analysis. We evaluate travel times between every pairwise junction in the city and assess higher-order network geometry changes in the network to determine flood impacts. The findings show network-wide persistent increased travel times could last for weeks after the flood water has receded, even after modest flood failure. A modest flooding of 1.3% road segments caused 8% temporal expansion of the entire traffic network. The results also show that distant trips would experience a greater percentage increase in travel time. Also, the extent of the increase in travel time does not decay with distance from inundated areas, suggesting that the spatial reach of flood impacts extends beyond flooded areas. The findings of this study provide an important novel understanding of floods' impacts on the functioning of traffic networks in terms of travel time and traffic network geometry. • High-order network analysis and reveals anatomy of perturbed traffic networks. • Network-wide persistent travel time increase can last for weeks. • Modest flooding causes significant temporal expansion of network. • Distant trips experience greater percentage increase in travel time. • Flood impacts extend beyond inundated areas. [ABSTRACT FROM AUTHOR]

• Survival models are developed to determine tolerance level for service disruptions. • Empirical data in the aftermath of 3 major hurricane events are used to develop survival models. • Susceptibility curves enable understanding household-level disturbance level from disruptions. In natural hazard engineering, fragility curves are used to determine the likelihood of damage to an engineered system under different magnitudes of hazard intensity. Analogous to fragility curves for engineered systems, survival models developed in the present study determine the extent of disturbances for shelter-in-place households caused by infrastructure service disruptions during disasters. This study used empirical data from household surveys collected in the aftermath of Hurricane Harvey, Hurricane Florence, and Hurricane Michael to create empirical survival models for determining household-level disturbances related to eight infrastructure services: power, water, communication, sewer systems, transportation, solid waste collection, grocery stores, and healthcare facilities. The survival models considered various influencing factors, such as sociodemographic factors, previous experience, risk perception, and access to resources to determine what percentage of households in a community would experience considerable hardship under varying durations of service disruptions. The developed curves suggested that although the susceptibility patterns are similar for short durations of infrastructure service disruptions, prolonged service disruptions pose varying levels of disturbance in different communities based on the household characteristics and contextual factors. Susceptibility curves could be implemented with current tools for assessing the reliability and resilience of infrastructure systems to promote understanding of the societal impacts that disruptions in these services pose to the affected communities. The resulting empirical survival models provide necessary tools and insights for determining the susceptibility of communities to disruptions of various infrastructure services during disasters. Hence, the outcomes of this study provide new empirical insights and models enabling decision-makers to integrate human-centric dimensions into infrastructure retrofit and restoration processes to more equitably reduce societal impacts of service disruptions. Such human-centric approaches enable designing socially resilient cities and contribute to designing sustainable infrastructure systems. [ABSTRACT FROM AUTHOR]

• Bayesian network flood model integrating network structure and empirical flood data. • Failure characterization of road network considering cascading failure from channels. • Simulation of flood propagation on the road network with high accuracy. • Quantitative flood risk measurement in road networks with a tiered representation. • Assist decision-makers to prioritize infrastructure protections for risk reduction. This paper presents a probabilistic model for assessing risk of cascading failures in co-located road and channel networks. The proposed Bayesian network analysis framework integrates network structural properties and empirical flood propagation data to model the spread of flooding. The model was tested in a multiple watershed scenario in Harris County, Texas (USA), using historical flood data from past events. The results show the capability of the proposed Bayesian network model to quantitatively characterize the failure (i.e., inundation) of road network considering the cascading failure (i.e., overflow) from the channel network. The proposed model also enables simulating the risk of flood cascades (i.e., flood propagation) on the road network with high accuracy. The generic design of the algorithm also enables the adaptation of the proposed framework in other cities and regions. Accordingly, the proposed model provides a new tool to help decision-makers prioritize infrastructure protection plans and emergency response actions. [ABSTRACT FROM AUTHOR]

Institutions are important elements in human systems influencing interactions among organizations that contribute to resilience management in interdependent infrastructure systems (IISs). In particular, the existence of institutional congruence among actors across these complex systems is important for the successful operation of such systems. Institutional congruence is the extent to which organizations have similar, agreed upon, or harmonized institutions. Institutional congruence has remained an understudied aspect of the management of resilience in IISs. This paper assesses three significant aspects of resilience management of IISs through the evaluation of organizational institutions: organizations' involvement in hazard mitigation planning and use of hazard mitigation plans; organizations' view regarding the responsibility of hazard mitigations and contributors to hazard; and organizations' support of policies for hazard risk mitigation. Organizational institutions within a sector and across different sectors that are involved in hazard risk mitigation in the context of the Harris County during Hurricane Harvey were investigated. The impacts of the extent to which organizational institutions were congruent on the cooperative management of resilience and the vulnerability of infrastructures were discussed. Findings show that, although the use of non-structural solutions is supported by most of the organizations, the existing plans did not specifically focus on such solutions. Additionally, the results indicate the existence of congruence across sectors about the importance of responsibility sharing among governments at different levels in mitigating the risk of hazard. Different organizations across sectors have varying perceptions regarding suitable approaches for flood risk mitigation that contribute to the vulnerability of physical infrastructures. • Institutional congruence among stakeholders impacts the coordination of resilience management in IISs. • Important components of resilience management examined: hazard mitigation planning, hazard contributors, and policy support. • A stakeholder survey was conducted to assess institutional congruence in Harris County in the context of Hurricane Harvey. • Institutional congruence regarding the importance of responsibility sharing among governments for hazard mitigation is shown. • Organizations across sectors have varying perceptions regarding suitable approaches for mitigating the risk of flooding. [ABSTRACT FROM AUTHOR]