Abstract: Strong earthquakes can easily trigger co-seismic debris accumulation, which, under subsequent heavy rainfall conditions, can easily transform into debris flows, posing a significant risk to life and property safety.Rainfall is the main trigger for post-earthquake debris flows, and constructing an accurate and effective rainfall threshold model is of great importance.Currently, post-earthquake debris flow rainfall thresholds often rely on the rainfall intensity-duration (I-D) empirical model, which has a relatively high misjudgment rate.To address this issue, the study focuses on a small watershed prone to debris flow in the Luding earthquake zone, specifically the Mogangling watershed.Using meteorological and hydrological in-situ monitoring data, a post-earthquake debris flow database is established.The concept of Absolute Energy (AE) is introduced to improve the traditional I-D model.Considering the key role of extreme hydrodynamic conditions in triggering post-earthquake debris flows, the study utilizes a HEC-HMS hydrological model to simulate the hydrological processes in the Mogangling watershed under different rainfall conditions, constructing a rainfall threshold model based on hydrological processes.The calculation results indicate that compared to the traditional I-D model, the newly constructed rainfall threshold model significantly improves accuracy, with a misjudgment rate lower than of the I-D model.Meanwhile, it is found that the improved rainfall threshold model (CR-AE) exhibits misjudgments in the cases of short-duration heavy rainfall and low-intensity long-duration rainfall.To reduce the misjudgment rate, AE and D are added as supplementary judgment conditions while maintaining the misjudgment rate unchanged, thereby enhancing the model's ability to recognize these types of rainfall events.The results can provide a reference for post-earthquake debris flow risk assessment.