Modeling the combined effects of the 2023 Türkiye-Syria Earthquake and an Atmospheric River event on landslide hazard

Abstract. This study investigates the landslide hazards resulting from the compound effects of the February 6, 2023 Türkiye-Syria earthquakes and a subsequent atmospheric river (AR) event that delivered up to 183 mm of rainfall across the earthquake-impacted region. Using the open-source Landlab modeling toolkit, we integrate global satellite datasets to simulate shallow landslide hazard at a regional scale. Our landslide hazard model incorporates earthquake legacy effects, a seismic driver accounting for post-seismic hillslope weakening, and rainfall drivers into a probabilistic implementation of the infinite slope stability theorem through a Monte Carlo approach. Model validation using landslide inventories and satellite-derived surface change metrics confirms improved performance for rainfall-driven landslide hazards when legacy effects are included. The legacy model reveals an approximately 13° reduction in critical slope angle and identifies high-hazard zones consistent with observed and inferred failures. Additionally, we analyze how the sequence of extreme seismic and rainfall events influences landslide hazard. We find that the scenario where the AR event precedes the earthquakes produces the greatest hazard, with median critical slopes up to 7° lower than other models in high-probability bins (probability of failure, P(F) > 0.6) and nearly double the number of grid cells exceeding P(F) > 0.8 compared to the next closest scenario. We demonstrate how using historical extreme rainfall records can effectively replicate post-seismic landslide hazard maps that use real-time data, offering a rapid approach for hazard forecasting in tectonically active and climate-sensitive regions.