Probabilistic assessment of soil liquefaction-induced failures during the 2023 Kahramanmaras earthquakes in Türkiye: A case study from Iskenderun city

Abstract

The February 6 2023 Kahramanmarasearthquakes and their aftershocks caused devastating destruction across T & uuml,rkiye and Syria. Widespread liquefaction-induced damage-particularly in regions such as Iskenderun Ad & imath,yaman-Golbas& imath, Hatay-Dortyol and Reyhanl & imath,-was reported along with general structural damage throughout the affected areas. This study addresses the critical issue of soil liquefaction within a probabilistic earthquake-soil-structure interaction framework and provides a comprehensive assessment of its impacts. An empirical methodology is proposed for estimating liquefaction-induced settlements near buildings by integrating post-earthquake reconnaissance observations with analytical results within a Performance-Based Design (PBD) framework. The analysis focuses on three regions within the Iskenderun district which were selected based on observed evidence of liquefaction and underlying geotechnical characteristics. Geotechnical investigation reports and recorded ground motion data were employed to evaluate the influence of local soil conditions. Site effects were evaluated using one-dimensional site response analyses which allowed for the simulation of ground motion amplification. The resulting surface acceleration time histories served as the basis for the damage assessment. To quantify liquefaction susceptibility a data-driven classification of the Liquefaction Potential Index (LPI) was conducted using K-Means clustering facilitating the derivation of optimized thresholds for damage severity. Based on this classification empirical fragility functions were developed to relate the Liquefaction Potential Index (LPI) to the Damage Severity Index (DSI) enabling the estimation of exceedance probabilities for different damage states. The findings highlight the importance of probabilistic fragility modeling in enhancing seismic hazard mitigation strategies and informing risk-based engineering decisions.