Date of Award
5-2024
Document Type
Thesis
Degree Name
Master of Science (MS)
Department
Civil Engineering
Committee Chair/Advisor
Dr. Weichiang Pang
Committee Member
Dr. Michael Stoner
Committee Member
Dr. Yongjia Song
Committee Member
Prof. Dustin Albright
Abstract
This research introduces an advanced framework which employs parametric wind field models for peak wind speeds, and building fragility curves, loss functions, and demographic data to estimate for estimating housing damage and loss. The uninhabitable units immediate displaced households, short-term and long-term shelter need households are determined. with a particular focus on those eligible for FEMA assistance. The framework's validity is reinforced by a high correlation in the analysis of recent hurricane events between estimated numbers of displaced households and actual FEMA aid recipients, where FEMA aids about 20-60% of the predicted long-term displaced households. A novel application of the model simulates nine 1989 Hugo-like storms passing through Charleston, analyzing Hurricane Hugo as a "below average" event in economic losses over a 125-year period using Mean Return Interval analysis. The model also incorporates multiple time step realizations and an ensemble of 903 potential hurricane tracks for each pre-landfall day, highlighting the variability in storm trajectory and intensity. This research is critical for disaster management practitioners, urban planners, and policymakers, providing actionable insights to improve disaster response strategies and enhance community resilience. The study is structured into six chapters, starting with an introduction, a literature review identifying research gaps, detailed methodology, case studies comparing model predictions with FEMA's responses, analysis of simulated storms, and concluding with recommendations for future research. This comprehensive approach allows stakeholders to understand and manage hurricane impacts more effectively, emphasizing the importance of continuous monitoring and real-time updates in hurricane forecasting.
Recommended Citation
Shakya, Adish Deep, "Quantifying Hurricane Effects on Housing: Evaluating Damage, Loss, And Shelter Demands Using Historical And Simulated Storm Tracks" (2024). All Theses. 4236.
https://open.clemson.edu/all_theses/4236
Author ORCID Identifier
0009-0003-0800-839X
Included in
Civil Engineering Commons, Computational Engineering Commons, Construction Engineering Commons, Construction Engineering and Management Commons, Ocean Engineering Commons, Risk Analysis Commons, Structural Engineering Commons, Urban, Community and Regional Planning Commons, Urban Studies and Planning Commons