Assessment of repair/reconstruction costs to existing reinforced concrete and masonry buildings following the 2023 Kahramanmaraş earthquakes

The poor seismic performance of substandard building stock in Türkiye has consistently resulted in excessive seismic-induced losses after earthquakes. The catastrophic outcomes of past earthquakes underscore the urgent need to improve the seismic resilience of existing buildings. Most recently, the 2023 Kahramanmaraş earthquakes—among the most devastating seismic events in the history of Türkiye—once again exposed the structural deficiencies of the building stock. This earthquake sequence caused widespread severe damage across 11 provinces and led to an estimated post-earthquake economic loss exceeding 100 billion Euro. In the aftermath, the Turkish Catastrophe Insurance Pool (TCIP) assessed the damage and repair/reconstruction costs of more than 450,000 individual units and provided compensation totaling 33 billion Turkish Lira (approximately 1.6 billion EUR) for post-earthquake repairs and reconstruction. This study presents a detailed evaluation of the post-earthquake repair/reconstruction costs for reinforced concrete and masonry buildings estimated by TCIP experts, analyzing their relationship with several parameters, including soil conditions, distance to the ruptured fault line, peak ground acceleration demand, spectral acceleration demand, number of stories, and year of construction. Based on this analysis, a new empirical relationship for repair costs considering damage state, total floor area, structural system, and spectral acceleration demand of the building, proportional to the reconstruction cost, is proposed, rather than fixed cost ratios. Furthermore, fragility functions are derived for the probabilistic seismic loss estimation frameworks, allowing for the accounting of uncertainties in cost variability. Overall, this study provides scalable and data-driven tools for rapid and large-scale seismic loss estimation, offering a practical alternative to simplified cost ratio approaches.