Resilience-Informed Guidance through Modeling and Interdisciplinary Field Studies


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Webinar Date

19 Apr 2021, 11:00 am


The study of community resilience requires modeling of each sector across a community, but the sectors must interact, often representing contributions from different scientific disciplines. This type of complex modeling requires the analyst to not only have an understanding of disciplines outside of engineering but to actively work and engage with key experts in sociology/planning and economics. This presentation will begin with an overview of the Center for Risk-Based Community Resilience Planning’s approach to merge engineering, social science/planning, and economics to form the Interdependent Networked Community Resilience Modeling Environment (IN-CORE). This includes learning from an interdisciplinary longitudinal field study beginning in 2016 to present for flooding in Lumberton, NC, including challenges posed by a second hurricane and the pandemic on data collection and interpretation. The presentation will close with an illustrative example application of a community planning for tornado hazard and an example of resilience-informed policy guidance.


Dr. John W. van de Lindt is the Harold H. Short Endowed Chair Professor in the Department of Civil and Environmental Engineering at Colorado State University. Over the last two decades van de Lindt’s research program has focused on performance-based engineering and test bed applications of building and other systems for earthquakes, hurricanes, tsunamis, tornadoes and floods. Professor van de Lindt is the Co-director for the National Institute of Standards and Technology-funded Center of Excellence (COE) for Risk-Based Community Resilience Planning headquartered at Colorado State University entering its seventh year. He has published more than 400 technical articles and reports including more than 200 journal papers, and currently serves as the Editor-in-Chief for the ASCE Journal of Structural Engineering.


Civil, Architectural and Environmental Engineering

Research Center/Lab(s)

Center for Intelligent Infrastructure

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Final Version

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