Karst topography comprises a fragile ecological environment with a significant potential for carbon sequestration. It is characterized by severe rocky desertification, particularly in China’s karst fault basin. Therefore, there is a crucial need to scientifically evaluate the variations in carbon storage over time and space in this area to ensure effective land space planning and regional ecological security, especially considering the dual carbon target. Using land use data (1985–2020) from the karst fault basin in Southwest China, the study employed the InVEST model to evaluate temporal and spatial variations in carbon storage. A time span of 35 years was examined, and predictions regarding carbon storage in 2050 were formulated under three different conditions: natural evolution, ecological protection, and cultivated land protection. These predictions were based on natural, social, and economic driving factors. The results revealed a fluctuating downward trend in regards to carbon storage in the study area from 1985 to 2020, with a total decrease of 2.1 × 10⁶ t. After 2000, there has been significant improvement in the dynamic degree of land use for forest land, grassland, and construction land compared to the levels before 2000. Additionally, many land use types with high carbon density transitioned into those with lower carbon density. Spatially, the carbon density in the karst fault basin was higher in the north and lower in the central and southern basins. At the county spatial scale, except for the northern and central parts of the study area, there was a decrease in total carbon storage in the remaining counties. By 2050, under the ecological protection scenario, total carbon storage is projected to increase by approximately 6 × 10⁶ t, whereas under the natural evolution and cultivated land protection scenarios, it is expected to decrease by 2 × 10⁶ t and 3 × 10⁶ t, respectively. Specifically, under the natural evolution scenario, only five counties will experience an increase in carbon storage, while the other counties will witness a decrease. The findings of this study offer a scientific basis for enhancing ecosystem carbon services through land management practices and the control of rocky desertification in the karst fault basin. They can inform decision-making processes regarding carbon sequestration, ecosystem restoration, and sustainable land use planning in the region.

Cantilevered unstable rock masses constitute a prevalent geological hazard, with their stability intrinsically governed by the depth of trailing edge cracks. Traditional stability assessment methods, which largely rely on static calculations or displacement monitoring, often suffer from poor timeliness and insufficient early warning capabilities. To address these limitations, this study employs the Extended Finite Element Method (XFEM) to simulate the natural crack propagation trajectory and investigate the associated dynamic response characteristics under loading. The simulation results demonstrate that XFEM effectively captures the natural “vertical-to-oblique” fracture morphology, overcoming the limitations of pre-defined crack models. A critical correlation is established between crack evolution and natural frequency: the first-order natural frequency exhibits a staged decline, characterized by a precipitous drop of approximately 7 Hz during the late stage of fracture development (80–97% depth). Consequently, a “crack evolution–frequency response” model is proposed. This model confirms that natural frequency is a significantly more sensitive indicator of internal damage than displacement, providing a novel theoretical foundation and technical pathway for the early identification and dynamic evaluation of rock mass stability.

The Guanting Gorge section of the Yongding River features complex terrain and densely distributed hydraulic projects. Under extreme rainstorm conditions, flood disasters are highly likely to occur, triggering secondary disasters such as landslides, barrier lakes, and dam breaks, resulting in prominent chain disaster risks and difficult prevention and control. To accurately evaluate the potential flood disaster chain risks in this region, 12 representative evaluation indicators were selected to establish a flood disaster chain risk evaluation system. The analytic hierarchy process (AHP) and entropy weight method (EW) were adopted to calculate subjective and objective indicator weights, respectively. Game theory was applied to achieve the optimal weight fusion and determine the final indicator weights. On this basis, a variable fuzzy model was constructed to identify flood disaster chain risks, and the Receiver Operating Characteristic-Area Under the Curve (ROC-AUC) was used to verify the accuracy and reliability of the model. The results show that cumulative precipitation, terrain slope, and annual maximum precipitation are the core driving factors inducing regional flood disaster chains, with corresponding weights of 0.2058, 0.1293, and 0.0980, respectively. High- and extremely high-risk areas are mainly concentrated in the western and southern river valleys, among which the Zhaitang–Luopoling river reach and the river section from Luopoling Reservoir to Sanjiadian Hub present the most prominent risks. The spatial distribution of risk zones is highly consistent with the actual disaster sites of the July 2023 Haihe River extreme rainstorm event, and the model achieves an AUC value of 0.901, indicating high accuracy and reliable simulation results. This study accurately identifies the core inducing factors and high-risk sections of flood disaster chains in the Guanting Gorge section of the Yongding River, which can provide scientific references and technical support for regional flood disaster chain prevention and control, hydraulic project operation and management, and disaster prevention and mitigation planning.