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Landslides pose significant and serious geological threat disasters worldwide, threatening human lives and property; China is particularly susceptible to these disasters. This paper focuses on Pengyang County, which is situated in the Ningxia Hui Autonomous Region of China, an area prone to landslides. This study investigated the application of machine learning techniques for analyzing landslide susceptibility. To construct and validate the model, we initially compiled a landslide inventory comprising 972 historical landslides and an equivalent number of non-landslide sites (Data sourced from the Pengyang County Department of Natural Resources). To ensure an impartial evaluation, both the landslide and non-landslide datasets were randomly divided into two sets using a 70/30 ratio. Next, we extracted 15 landslide conditioning factors, including the slope angle, elevation, profile curvature, plan curvature, slope aspect, TWI (topographic wetness index), TPI (topographic position index), distance to roads and rivers, NDVI (normalized difference vegetation index), rainfall, land use, lithology, SPI (stream power index), and STI (sediment transport index), from the spatial database. Subsequently, a correlation analysis between the conditioning factors and landslide occurrences was conducted using the certainty factor (CF) method. Three landslide models were established by employing logistic regression (LR), functional trees (FTs), and random subspace functional trees (RSFTs) algorithms. The landslide susceptibility map was categorized into five levels: very low, low, medium, high, and very high susceptibility. Finally, the predictive capability of the three algorithms was assessed using the area under the receiver operating characteristic curve (AUC). The better the prediction, the higher the AUC value. The results indicate that all three models are predictive and practical, with only minor discrepancies in accuracy. The integrated model (RSFT) displayed the highest predictive performance, achieving an AUC value of 0.844 for the training dataset and 0.837 for the validation dataset. This was followed by the LR model (0.811 for the training dataset and 0.814 for the validation dataset) and the FT model (0.776 for the training dataset and 0.760 for the validation dataset). The proposed methods and resulting landslide susceptibility map can assist researchers and local authorities in making informed decisions for future geohazard prevention and mitigation. Furthermore, they will prove valuable and be useful for other regions with similar geological characteristics features. [ABSTRACT FROM AUTHOR]

Tectonically active mountain regions such as Southwestern China are frequently hit by catastrophic floods caused by the breach of landslide dams. However, how these extreme events influence the morphodynamics of bedrock‐alluvial rivers is not well understood. More specifically, during a landslide dam outburst flood, bedrock can be eroded by intensive transport of sediment (i.e., tools effect), but can also be buried under thick alluvial cover (i.e., cover effect). Here, we implement the MRSAA‐c (Corrected Macro‐Roughness‐based Saltation‐Abrasion‐Alluviation) model to simulate the morphodynamics of bedrock‐alluvial rivers subject to landslide dam outburst flood(s). For a single dam breach event, the evolution of a bedrock‐alluvial river shows different characteristics at different time scales. At flood time scale (within one day), bedrock is eroded by about 10 mm. The landslide deposit then mainly provides a cover effect in the decadal‐century scale, which leads to a net uplift of the bedrock underneath, and thus the formation of a bedrock "bump." The bedrock profile returns to its initial equilibrium state at a millennial time scale, after the bedrock bump migrates upstream beyond the inlet. When subject to repeated dam breach events, the bedrock‐alluvial river can reach a dynamic equilibrium after sufficient time (tens of thousands of years). The equilibrium is characterized by sharply increased bedrock slope around the dam site, and gently decreased slope downstream. The impact of dam breach events is constrained within a scale of hundreds of kilometers, indicating the existence of a sedimentograph boundary layer. Plain Language Summary: Both seasonal floods and outburst floods (caused by e.g., breaching of landslide dams) contribute to bedrock channel downcutting in mountain rivers. Since outburst floods may carry much more water and sediment than seasonal floods, their impacts are important to understand how bedrock channels change in time. We implement a numerical model to simulate landslide dam outburst floods and associated channel evolution. Results show that a landslide dam outburst flood cuts into the bedrock channel during the flood event. In subsequent decades or centuries, landslide deposits can cover the channel and thus hinder bedrock downcutting, leading to a net rising of the bedrock surface. Eventually a bedrock bump moves upstream and beyond the river reach in tens of thousands of years. When outburst floods at a single site occur repeatedly, a dynamic balance is reached, with steeply increased bedrock slope near the dam site and gently decreased slope in the downstream. Our results show the great influence of landslide dam outburst floods on the behavior of bedrock channels. Key Points: A single dam breach event leads to bedrock incision over flood time scale, then forms a bedrock bump at decadal‐century scaleThe wave of alluvium from a dam breach shows diffusion when the bed is alluviated, and also advection when the bedrock is partially exposedUnder repeated dam breach events, the equilibrium profile of a bedrock‐alluvial river is characterized by a boundary layer and a knickpoint [ABSTRACT FROM AUTHOR]

• The dam-break induced cascading hazard chain leading to a catastrophic event. • This paper used a typical outburst debris flow to describe the catastrophe process. • The flow amplification effect was analyzed based on the obstructive coefficient. • The movement process of outburst debris flow was simulated and validated. • Different scenario simulations were performed under the new mitigation projects. Strong earthquakes can induce large amounts of loose solid materials, forming landslide dams and blocking narrow flow channels. Under extreme rainfall conditions, instability can lead to an outburst of debris flow once the landslide dam has formed it. On July 10, 2013, a volume of 4.5 × 104 m3 of debris flow occurred in the Yangling gully, Wenchuan County, China. This event can be categorized as an outburst of the debris flow that might seriously threaten valley residents, existing sediment transport countermeasure works, and road infrastructures. This paper describes a typical outburst of debris flow, calculates its obstructive coefficient, simulates the process under various recurrence intervals, and analyzes the efficacy of a new mitigation project. Related research results have laid the foundation for further study of the risk assessment and early warning of debris flow due to landslide dam failure. In this paper, an accurate computational model for the obstructive coefficient, closely related to the flow amplification effect, is established based on a dam break's physical experiments. Combined with the numerical calculation method, the movement process of the Yangling gully was simulated under the old artificial dam and the flow channel engineering conditions. By comparing the measured and the simulated accumulation area, the verification results illustrate that the accumulation area considering the obstructive coefficient model is closer to the measured value. Based on the obstructive coefficient computational model, the results illustrate the outburst of debris flow discharge for various recurrence intervals (50, 100, and 200 years respectively) to perform scenario simulations of Yangling gully under the new mitigation project conditions. [ABSTRACT FROM AUTHOR]

• A landslide sediment supply capacity assessment model was developed for applications in debris flow basins. • Spatial and temporal variability of landslide sediment supply capacity is significant. • Decay of landslide sediment supply capacity to the pre-earthquake level is expected within 17 years. • The evolution of landslide activity has a positive effect on the landslide sediment transport capacity. After the Wenchuan earthquake, a large number of landslides in debris flow basins continued to provide loose debris for channels and further affected the occurrence of debris flows. Evaluating the landslide sediment supply capacity in debris flow basins requires understanding the landslide activity and the coupled relationship between the landslide and the channel. In this study, we proposed a model based on the landslide area density index (P Als) and the landslide connectivity (IC l) to evaluate the capacity of the landslide sediment supply for channels in 46 sub-catchments in the study area. The capacity of the landslide sediment supply for channels generally decreased from 2008 to 2018, but due to the influence of heavy rainfall, the actual capacity of the landslide sediment supply for channels in the study area may gradually diminish in an unstable way, and it may arrive at the pre-earthquake level by 2025 without the influence of extreme rainfall. However, higher debris flow activity may last longer than 2025 because sufficient gully materials are still accumulated in the channel. The sediment transport capacity of landslides was divided into five levels: extremely, high, moderate, slight and low. The capacity of the landslide sediment supply for channels changed from extreme levels and high levels to moderate levels and slight levels after the first 5 years of the Wenchuan earthquake and was then dominated by low levels. Simultaneously, the regions with higher landslide sediment supply capacities gradually changed from along the Minjiang River regions to the upper and middle reaches of the debris flow basin from 2008 to 2018. Hongchun gully, which is in the study area, was chosen as an example to compare the assessment results and field investigation. The long-term evolution of landslides is an important reason for the decrease in the sediment supply capacity of landslides. [ABSTRACT FROM AUTHOR]