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• SWAT-Twn 2.0: Enhanced model with adaptable landslide triggers improves sediment simulation. • Dual triggers (PCP: rainfall and FSW: fraction of soil water content) in SWAT-Twn 2.0 show superior performance. • PCP trigger significantly affects landslide identification accuracy. • Lack of particle size leads to channel deposition overestimation. • Incorporate landslide characteristics into HRU (Hydrologic Response Unit) classification to address limitations. Landslides, 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). [ABSTRACT FROM AUTHOR]

• Contour currents with different physical natures observed over a drift-moat system • High SSC on the drift due to long-range sediment transport by contour currents • High SSC in the moat due to moat wall erosion by tidal-induced secondary flows • Formation of drifts forced by upslope sediment transport of tidal currents Contourite drifts are ubiquitous sedimentary features in the world′s oceans, and their formation are usually ascribed to sedimentation from contour currents. However, in-situ observations of contour currents and their associated sedimentary processes were inadequate. Here, we present mooring observation results from a drift-moat contourite system in the South China Sea to gain insight into its sediment dynamics and formation mechanism. We found that quasi-persistent contour currents develop in the moat, on and below the drift, yet subject to diverse physical oceanographic processes. High suspended sediment concentrations observed on the drift mainly occur in winter, induced by high levels of sediments transported by contour currents from Taiwan. In the moat, however, high suspended sediment concentrations are mostly caused by erosion of the moat wall during periods of strong tidal currents and low shear variance. Such results underscore the complexity of current patterns and sedimentary processes across various topographic units in the drift-moat contourite system. A novel formation mechanism of the contourite drift is thereby proposed, wherein sediment transport by contour currents brings materials for constructing the drift, while its formation is driven by near-critical reflection and upslope transport of sediments by tidal currents. [ABSTRACT FROM AUTHOR]

The change in movable beds is related to the mechanisms of sediment transport and hydrodynamics. Numerical modelling with empirical equations and the simplified momentum equation is the common means to analyze the complicated sediment transport processing in river channels. The optimization of parameters is essential to obtain the proper results. Inadequate parameters would cause errors during the simulation process and accumulate the errors with long-time simulation. The optimized parameter combination for numerical modelling, however, is rarely discussed. This study adopted the ensemble method to simulate the change in the river channel, with a single model combined with multiple parameters. The optimized parameter combinations for a given river reach are investigated. Two river basins, located in Taiwan, were used as study cases, to simulate river morphology through the SRH-2D, which was developed by the U.S. Bureau of Reclamation. The input parameters related to the sediment transport module were randomly selected within a reasonable range. The parameter sets with proper results were selected as ensemble members. The concentration of sedimentation and bathymetry elevation was used to conduct the calibration. Both study cases show that 20 ensemble members were good enough to capture the results and save simulation time. However, when the ensemble members increased to 100, there was no significant improvement, but a longer simulation time. The result showed that the peak concentration and the occurrence of time could be predicted by the ensemble size of 20. Moreover, with consideration of the bed elevation as the target, the result showed that this method could quantitatively simulate the change in bed elevation. With both cases, this study showed that the ensemble method is a suitable approach for river morphology numerical modelling. The ensemble size of 20 can effectively obtain the result and reduce the uncertainty for sediment transport simulation. [ABSTRACT FROM AUTHOR]