Validating interdependent community resilience modeling using hindcasting

John W. Van De Lindt, Hussam Mahmoud, Stephanie Pilkington, Maria Koliou, Navid Attary, Harvey Cutler, Steve Smith, Nathanael Rosenheim, Christopher M. Navarro, Yong Wook Kim, Jong Sung Lee

Research output: Contribution to conferencePaperpeer-review


The resilience of communities prone to natural hazards can be enhanced through the use of risk-informed decision-making tools. These tools can provide community decision-makers key information, allowing them to consider an array of mitigation and/or recovery strategies. To comprehensively assess community resilience, all sectors that have an influence, including physical infrastructure (buildings, bridges, electric power networks, etc.) and the socio-economic systems should be considered. For this purpose, the Center for Risk-Based Community Resilience Planning (hereon referred to as the Center), headquartered at Colorado State University in Fort Collins, Colorado, USA, developed an Interdependent Networked COmmunity Resilience modeling Environment (IN-CORE) capable of simulating the effects of different natural hazards including tornadoes, earthquakes, tsunamis, among others, on physical and socio-economic sectors of a community while accounting for interdependencies between the various sectors. However, such a complex computational environment must be validated with each model being verified as a single component or sub-system. Within the Center, models are verified for accuracy as they are developed, but the combination of all the models must be verified for accuracy and then validated to ensure that it provides the desired output with the accuracy needed for risk-informed decisions. The community of Joplin Missouri in the United States was hit by an EF-5 tornado on May 22, 2011. In this paper, the city of Joplin is modeled in IN-CORE to estimate the building and electrical power network damage, economic disruption and recovery, infrastructure repair and recovery through several metrics, as well as population dislocation. Results are compared with best estimates obtained from collected post-event data, interpreted existing government documentation, and archived literature related to Joplin.

Original languageEnglish (US)
StatePublished - 2019
Event13th International Conference on Applications of Statistics and Probability in Civil Engineering, ICASP 2019 - Seoul, Korea, Republic of
Duration: May 26 2019May 30 2019


Conference13th International Conference on Applications of Statistics and Probability in Civil Engineering, ICASP 2019
CountryKorea, Republic of

ASJC Scopus subject areas

  • Civil and Structural Engineering
  • Statistics and Probability

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