Abstract
Climate change, population dynamics, the aging of built infrastructure, and their growing complexity have gradually increased the vulnerability of coastal communities around the world. Among the many critical coastal infrastructures, the residential coastal building stock has exhibited significant vulnerabilities in past storm and hurricane events. Beyond the initial impact of these hurricane events on the built environment, coastal communities struggle to recover even years after landfall. Moreover, the initial shock as well as the recovery phase do not evenly affect all sectors of the population and frequently uncover social vulnerabilities and inequalities in the preparedness, response, and recovery from disasters. This study explores and expands a performance-based coastal engineering (PBCE) framework that allows for consideration of time-varying aspects of the hazard, depreciation, and aging or deterioration of coastal structures and infrastructure systems by applying it to evaluate the future performance and recovery of a portfolio of residential structures subjected to surge and wave loads. Using the residential building stock of Galveston, Texas as a case study, a Bayesian network framework is leveraged to evaluate the uncertain damage and subsequent recovery of the portfolio for the years 2030 and 2050, and correlations with representative social vulnerability factors are drawn. The correlation analysis between immediate damage and social vulnerability factors, as well as between the recovery index and social vulnerability factors up to six years following the storm landfall, is pursued to expose potential disparities in the impact of the storm to different sectors of the community in the short- and long-term. Results show that changing climate conditions exacerbate the probability of failure of the building stock and associated housing recovery. Also, the correlations in the short- and long-terms show that the elderly and women might be most at risk in future hurricane events. The incorporation of multi-structure systems and time-varying factors in the performance assessment framework is of great importance to inform resilience and adaptation engineering models, in particular, when the effects of chronic hazards, a growing population, and increases in asset values are expected to grow in the future. The methodology and case study also provide useful tools to inform planning and decision-making, resilience assessment, and facilitate recovery efforts in coastal settings while accounting for the impact of the hazard on vulnerable populations.
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Data Availability Statement
Some or all data, models, or code that support the findings of this study are available from the corresponding author upon reasonable request.
Acknowledgments
The authors gratefully acknowledge the support of this research by the National Science Foundation under awards OISE-1545837 and CMMI- 2002522. In addition, the second author is supported in part by the NIST Center of Excellence for Risk-Based Community Resilience Planning under Cooperative Agreement 70NANB15H044 between the National Institute of Standards and Technology (NIST) and Colorado State University. Any opinions, findings, and conclusions, or recommendations expressed in this paper are those of the authors and do not necessarily reflect the views of the sponsors. In addition, helpful discussions with authors whose published models were adopted in this study are also gratefully acknowledged, including Profs. Tori Tomiczek and Sara Hamideh. Rice University’s Fondren Library GIS center is acknowledged for their support in identifying the data used in the testbed analysis, along with the resources of the NHERI DesignSafe Cyberinfrastructure CMMI- 2022469. Maps throughout this paper were created using ArcGIS software by Esri. ArcGIS and ArcMap are the intellectual property of Esri.
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Journal of Structural Engineering
Volume 148 • Issue 8 • August 2022
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© 2022 American Society of Civil Engineers.
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Received: Jul 31, 2021
Accepted: Mar 16, 2022
Published online: Jun 9, 2022
Published in print: Aug 1, 2022
Discussion open until: Nov 9, 2022
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