In February 2021, severe winter weather conditions associated with Winter Storm Uri triggered an energy infrastructure failure in Texas. Most Texans lost electricity, some lost potable water, natural gas, and suffered other infrastructure-related service disruptions that had profound household consequences. Although several studies have documented the disparities in terms of the types and extent of disruptions Texans experienced during Uri, there is little information about the impact of these disruptions in terms of their burdens on households. Guided by the Capabilities Approach framework, a survey of Texan households was conducted to identify the outage characteristics and capability losses for different household types, as well as the
Agent-Based Modeling Framework for Simulation of Societal Impacts of Infrastructure Service Disruptions during Disasters
The objective of this paper is to model and examine the impacts of different levels of
infrastructure service losses caused by disasters on the households’ well-being residing in a community. An agent-based simulation model was developed to capture complex mechanisms underlying households’ tolerance for the service outages, including household characteristics (e.g., sociodemographic, social capital, resources, and previous disaster experience), physical infrastructure attributes, and extreme disruptive events. The rules governing these mechanisms were determined using empirical survey data collected from the residents of Harris County affected by Hurricane Harvey as well as the existing models for power outages and service restoration times. The analysis results highlighted the spatial diffusion of service risks among households living in affected areas in disasters. The proposed simulation model will provide utility agencies with an analytical tool for prioritization of infrastructure service restoration actions to effectively mitigate the societal impacts of service losses.
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- Award ID(s):
- 1846069
- NSF-PAR ID:
- 10132866
- Date Published:
- Journal Name:
- ASCE Computing in Civil Engineering Workshop
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Abstract burdens that those disruptions posed to households using both objective and subjective measures. Our results indicate that households that endured longer and constant electricity outages suffered more severe impacts across all measures, including more disrupted household capabilities, increased time, and financial costs to cope during the outages, as well as greater declines in reported life satisfaction. We found that low-income households, households with children, and households with disability challenges suffered more severe objective burdens during the storm, although subjective results for these households were mixed. Households with members over the age of 65 fared better in terms of objective measures, yet suffered more in terms of subjective well-being. Moreover, households that had prior experience with a prolonged outage reported significantly smaller reductions in well-being during the storm than other households, despite not showing any difference in objective measures. Ultimately, our results offer context-specific, post-event information about the impacts and needs of different types of households during Uri that are important for informing emergency management and community resilience planning. -
null (Ed.)The objective of this study is to empirically assess household susceptibility to the power disruptions during disasters. In this study, a service gap model is utilized to characterize household susceptibility to infrastructure service disruptions. The empirical household survey data collected from Harris County, Texas, in the aftermath of Hurricane Harvey was employed in developing an appropriate empirical model to specify the significance of various factors influencing household susceptibility. Various factors influencing households’ susceptibility were implemented in developing the models. The step-wise algorithm was used to choose the best subset of variables, and availability of substitutes, previous hazards experience, level of need, access to reliable information, race, service expectations, social capital, and residence duration were selected to be included in the models. Among three classes of models, accelerated failure time (AFT)-loglogistic model yielded the best model fitness for estimating households’ susceptibility to disaster-induced power disruption. The model showed that having a substitute, households’ need for the service, race, and access to reliable information are the most significant factors influencing household susceptibility to the power disruptions. Understanding households’ susceptibility to infrastructure service disruptions provides useful insights for prioritizing infrastructure resilience improvements in order to reduce societal impacts.more » « less
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Natural disasters have devastating effects on the infrastructure and disrupt every aspect of daily life in the regions they hit. To alleviate problems caused by these disasters, first an impact assessment is needed. As such, this paper focuses on a two-step methodology to identify the impact of Hurricane Hermine on the City of Tallahassee, the capital of Florida. The regional and socioeconomic variations in the Hermine’s impact were studied via spatially and statistically analyzing power outages. First step includes a spatial analysis to illustrate the magnitude of customers affected by power outages together with a clustering analysis. This step aims to determine whether the customers affected from outages are clustered or not. Second step involves a Bayesian spatial autoregressive model in order to identify the effects of several demographic-, socioeconomic-, and transportation-related variables on the magnitude of customers affected by power outages. Results showed that customers affected by outages are spatially clustered at particular regions rather than being dispersed. This indicates the need to pinpoint such vulnerable locations and develop strategies to reduce hurricane-induced disruptions. Furthermore, the increase in the magnitude of affected customers was found to be associated with several variables such as the power network and total generated trips as well as the demographic factors. The information gained from the findings of this study can assist emergency officials in identifying critical and/or less resilient regions, and determining those demographic and socioeconomic groups which were relatively more affected by the consequences of hurricanes than others.more » « less
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Extreme weather events have significant economic and social impacts, disrupting essential public services like electricity, phone communication, and transportation. This study seeks to understand the performance and resilience of critical infrastructure systems in Houston, Texas, using Hurricane Harvey (2017) as a case study. We surveyed 500 Houston Metropolitan Statistical Area residents after Hurricane Harvey’s landfall about disruption experience in electricity, water, phone/cellphone, internet, public transportation, workplace, and grocery stores. Our household survey data revealed the proportion and duration of disruption in each system. Approximately 70% of respondents reported experiencing electricity outages, while half (51%) had no access to water for up to six days. Two-thirds of surveyed households lacked internet access, and 50% had their phone services disconnected. Additionally, around 71% of respondents were unable to commute to work, and 73% were unable to purchase groceries for their families during this period. We incorporated the household survey responses into the Dynamic Inoperability Input-Output Model (DIIM) to estimate inoperability and economic losses across interconnected sectors. The projected economic loss was estimated to be in the range of $6.7- $9.7 billion when sensitivity analysis is performed with respect to the number of working days. Understanding the resilience of each sector and the inherent interdependencies among them can provide beneficial insight to policymakers for disaster risk management, notably preparedness and recovery planning for future events.more » « less
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