Optimizing logic-tree branches for improved seismic hazard mapping in Egypt

Abstract

The development of a comprehensive Probabilistic Seismic Hazard Analysis (PSHA) framework for Egypt marks a pivotal advancement in seismic hazard assessment, with significant implications for critical infrastructure, large-scale developments, and the revision of the Egyptian Building Code. This study generates Peak Ground Acceleration (PGA) and Spectral Acceleration (SA) maps, addressing the inherent complexities and uncertainties of PSHA through robust quantitative methodology. The research utilizes Kullback-Leibler Divergence (KLD) to assess the importance of logic-tree branches and evaluate the performance of the implemented models. By incorporating updated seismicity catalogs, refined seismotectonic models, and advanced ground motion prediction equations (GMPEs), the study optimizes logic-tree branch weights through rigorous statistical evaluation and sensitivity analyses. The results obtained using KLD show that the most effective seismic hazard model integrates recent seismotectonic models, GMPEs designed for shallow active crustal seismic sources, and those suited for seismic sources within the subduction zones of the Mediterranean Sea. This data-driven approach, leveraging the KLD-weighting scheme, effectively minimizes uncertainties in PSHA and enhances the reliability of parameter selection for site-specific seismic hazard analysis. The results obtained using the KLD exhibit a strong alignment with findings from previous PSHA studies conducted for Egypt. This concordance underscores the robustness and reliability of the KLD-based approach in evaluating and ranking seismic hazard models. By effectively capturing the statistical similarities and divergences among logic-tree branches, the KLD methodology not only validates the current framework against established studies but also demonstrates its capacity to refine and enhance the understanding of seismic hazard distributions in Egypt.