LI-CHI CHIANGLu, Chih MeiChih MeiLu2024-04-152024-04-152024-05-0103418162https://www.scopus.com/inward/record.uri?eid=2-s2.0-85188255665&doi=10.1016%2fj.catena.2024.107948&partnerID=40&md5=88a62737b04468733baabe3bf1bee993https://scholars.lib.ntu.edu.tw/handle/123456789/641913Landslides, caused by heavy rainfall, earthquakes, or human development, are likely occur in steeper slopes, while some occur in moderate slopes (15°– 35°). Although landslides can contribute a significant amount of sediment transport in a watershed, landslides are rarely considered in hydrological models. To conduct a thorough investigation into the influence of landslides on sediment transport within rivers, a detailed analysis of landslide characteristics was performed. Subsequently, a dedicated landslide module was integrated into a hydrological model, known as SWAT-Twn 2.0 – an enhanced version of SWAT-Twn, originally developed by Chiang et al. (2021). This integration allowed for the simulation of sediment transport at the hydrologic response units (HRUs) within the Xiuguluan River Basin, a mountainous watershed located in Taiwan. The study explores multiple threshold values for landslide-triggering factors (PCP: rainfall and FSW: fraction of soil water content), emphasizing the influence of the number and locations of rainfall stations on landslide identification. In comparative scenario simulations (S1: no trigger, S2: single trigger, S3: dual trigger), the integration of dual triggers (PCP + FSW) significantly improves sediment simulation results, particularly for peak total load (S3: R2 = 0.83, NSE = 0.74, PBIAS = 23.69 %). It also emphasizes the importance of specifying the particle size distribution of landslides for accurate sediment deposition calculations. In summary, it is necessary to consider landslide-triggering factors in hydrological models to enhance accuracy in sediment yield simulations. To further improve landslide identification and sediment transport modeling, the study recommends incorporating additional triggering factors into HRU classification (i.e., elevation and aspect).Landslide estimation | Landslide trigger | Sediment simulation | SWAT[SDGs]SDG13journal article10.1016/j.catena.2024.1079482-s2.0-85188255665https://api.elsevier.com/content/abstract/scopus_id/85188255665