Shallow landslides are often unpredictable and seriously threaten surrounding infrastructure and the ecological environment. Traditional landslide prediction methods are time-consuming, labor-intensive, and inaccurate. Thus, there is an urgent need to enhance predictive techniques. To accurately predict the runout distance of shallow landslides, this study focuses on a shallow soil landslide in Tongnan District, Chongqing Municipality. We employ a genetic algorithm (GA) to identify the most hazardous sliding surface through multi-iteration optimization. We discretize the landslide body into slice units using the dynamic slicing method (DSM) to estimate the runout distance. The model's effectiveness is evaluated based on the relative errors between predicted and actual values, exploring the effects of soil moisture content and slice number on the kinematic model. The results show that under saturated soil conditions, the GA-identified hazardous sliding surface closely matches the actual surface, with a stability coefficient of 0.9888. As the number of slices increases, velocity fluctuations within the slices become more evident. With 100 slices, the predicted movement time of the Tongnan landslide is 12 s, and the runout distance is 5.91 m, with a relative error of about 7.45%, indicating the model's reliability. The GA-DSM method proposed in this study improves the accuracy of landslide runout prediction. It supports the setting of appropriate safety distances and the implementation of preventive engineering measures, such as the construction of retaining walls or drainage systems, to minimize the damage caused by landslides. Moreover, the method provides a comprehensive technical framework for monitoring and early warning of similar geological hazards. It can be extended and optimized for all types of landslides under different terrain and geological conditions. It also promotes landslide prediction theory, which is of high application value and significance for practical use.

Mudflows are natural phenomena starting from landslides and presenting high impact when they occur. They generate great catastrophes in their path because most of the time there is no indication prior to the failure that triggers them. Understanding how mud is transported is of great importance in infrastructure projects that coincide with hillside areas due to the high risk of occurrence of this phenomenon by cause of the high slopes, which can involve great risks and produce disasters that involve great costs. This work presents the evaluation of mudflows, from the implementation of a laboratory scale experiment in a consistometer with its calibration and validation from numerical models to estimate rheological parameters of the material. Tests were also carried out in an open channel in the laboratory, based on the data previously obtained considering the behavior of the material as a both Newtonian fluid and non-Newtonian fluid. The experiment considered a channel with dimensions of 3 m long, 0.5 m high and 0.7 m wide with slope control, and a mud composition of silty material with 60% moisture. The tests were conducted with slopes of 5%, 10%, 15% and 20%. The numerical models were carried out in ANSYS FLUENT software. In addition, the calibration data of the numerical model were used for a real case study, simulating the slip flow occurred in Yangbaodi, in the southeast of China, occurred on September 18, 2002. The results of the numerical models were compared with the experimental results and show that these have a great capacity to reproduce what is observed in the laboratory when the material is considered as a non-Newtonian fluid. The model reproduced in an appropriate way the movement of the flow at laboratory scale, and for the aforementioned case study, some differences in the final length of deposition were noticed, achieving interesting results that lead the use of the calibrated model towards the estimation of risks due to the mudflow occurrence.

Rapid and long-runout landslides characterized by their high speed, long distance mobility, and huge capacity and volume would pose significant threats to infrastructure and life safety. In this study, a rapid and long-runout landslide that occurred in the Bingda village of the northeastern Tibetan Plateau, which was triggered by heavy rainfall in June 2017, was preliminarily investigated. On the basis of detailed field surveys, high-resolution satellite imagery analysis, and laboratory tests, the morphological and sedimentological features of the landslide were described, and the formation mechanism of hummocky landforms and its insight into the extraordinary movement of the Bingda landslide was deduced. The field investigation and satellite imagery analysis showed that there were nearly 200 hummocks, mostly with normal circular bases and with a height of similar to 0.1 m-7.5 m, distributed in the transfer and accumulation areas of the landslide. The height and number density of the hummocks decreased away from the transfer area to the accumulation area and displayed higher heights at the outer bends of the gully channel than that at the inner bends of it. The characteristics of the spatial distribution and the composition of hummocks indicated that significant generation and dissipation of pore-water pressure within the loose and saturated silty clay layer in the runout path was the most probable reason for the formation of hummocky landforms. This study also provided insights into the hypermobility mechanisms of the Bingda landslide, suggesting that this landslide began with the sliding failure of the weathered colluvium in the source area, and then the landslide debris traveled into the channel and impacted sudden undrained loading and rapid shearing to the underlying silty clay layers in the gully. These processes generated pore-water pressure and reduced the effective stress within the soil particles, resulting in a decrease in the frictional resistance in the substrate, finally facilitating the rapid and long-runout movement of the landslide.