Report Release: Resilience Through Functionality: Outcome-Driven Quantification Approach with Stakeholders-Based Calibration
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By Michel C. Boufadel, Ph.D., P.E. (New Jersey Institute of Technology), Firas Gerges, Ph.D. (Princeton University), Hani Nassif, Ph.D., P.E. (Rutgers University)
In the face of escalating challenges posed by climate change and rapid urbanization, community resilience is of paramount importance. Quantifying resilience is a crucial step in identifying vulnerabilities and enhancing the capacity of communities to withstand and rebound from adverse events. However, conventional resilience assessments rely on intricate attributes and proxy measures, making them challenging for decision-makers to translate into practical actions, and may not truly capture the resilience of geographic areas.
In this work, we introduce a novel approach to resilience assessment, emphasizing essential functionalities over intricate attributes. Resilience, in this context, means ensuring uninterrupted access to critical services and functions during and after disasters. Rather than navigating through technical complexities and proxy measures, our methodology prioritizes fundamental end variables, offering clarity in resilience assessment. These variables encapsulate the lifelines of communities, including access to electric power, health services, communication, sanitation, transportation, food and water security, economic resilience, as well as biodiversity, and natural ecosystem health. These variables are the linchpins of community functionality in crisis situations. While other variables, such as shelter and evacuation capacity, that directly act to withstand disasters, can be included as end variables.
First, we have leveraged our ARez quantification approach which combines social and engineering resilience concepts to provide true measure of resilience, at various timescales. It tracks the functionality of the end variables before, during, and after disasters, providing a practical view of resilience dynamics.
Second, we sought engagement and feedback from stakeholders to further calibrate the quantification process. While end variables remain consistent across different locations, their relative importance and the factors influencing them can vary significantly. Local demographics, climate conditions, infrastructure setups, and community priorities all contribute to this variability. We gathered input from stakeholders to refine our understanding of the relative importance of end variables and tailor our resilience assessment to the unique characteristics and needs of the community. We collected weights of and feedback on the end variables through a survey that we conducted at a series of in-person meetings and through targeted emails. The results of the survey helped shape the weight distribution for the end variables for the City of Newark, NJ, and generated a set of additional factors and variables that we aim to integrate soon. This survey is a part of continuous effort to update ARez and tailor it for specific locations and priorities.
The results of our survey, combined with our updated ARez approach, provide a robust foundation for resilience assessment that is adaptable and applicable across different locations. By shifting the focus from complex attributes to essential functionalities, our approach bridges the gap between resilience theory and actionable policy implementation, ultimately contributing to the development of more resilient and better-prepared communities in the face of disasters. In addition to its practical utility, our approach has significant policy implications. By providing decision-makers with a clear understanding of community resilience, we empower them to allocate resources more effectively, prioritize resilience-building initiatives, and develop tailored strategies that address the specific needs of each community. Ultimately, our project aims to not only enhance community resilience but also improve the well-being and safety of residents, ensuring a more sustainable and prosperous future for all.