Jia Lan, Cui Yuedi, Cao Lanzhu, Chen Xi, Liu Xishun
Ordos Institute of Liaoning Technical University, Ordos, 017004, Inner Mongolia Autonomous Region, China.
Liaoning Institute of Technology and Equipment for Mineral Resources Development and Utilisation in Higher Educational Institutions, Liaoning Technical University, Fuxin, 123000, Liaoning, China.
Sci Rep. 2025 Jul 1;15(1):21651. doi: 10.1038/s41598-025-04868-7.
Comprehensive landslide risk zoning in open-pit mines is fundamental to precise safety monitoring, early warning, and disaster prevention and control. Existing approaches often rely on single static indicators and exhibit limited capacity for dynamic risk regulation. To address these limitations, this study proposes a scientifically grounded slope zoning method that couples multiple factors across "engineering-geological-environmental (seasonal variations, distribution of infrastructure)". First, a hierarchical structure model comprising four key influencing degree of crack development, slope angle, slope height, and rock and soil properties-is constructed using the Analytic Hierarchy Process (AHP). By computing the weight coefficients of these evaluation indices and deriving a slope hazard index, we classify slope hazard zones. Additionally, the two-dimensional rigid-body Limit Equilibrium Method (LEM) is applied to calculate slope factor of safety for multiple cross-sections, facilitating the delineation of slope stability zones. To integrate these results, we employ a combined cross-matrix analysis and simple weighted averaging method, further refining the comprehensive risk zoning by dynamically incorporating factors such as slope along-strike surface shape, seasonal (climatic) variations, fault characteristics, and distribution of infrastructure. This approach is validated through application to a case study in an open-pit mine, where one higher-risk, five medium-risk, and six low-risk zones are identified. Notably, the higher-risk zone exhibits strong spatial agreement with actual landslide occurrences. The results demonstrate that the proposed method significantly enhances zoning accuracy, providing a theoretical basis for the optimized allocation of monitoring resources, the development of differentiated early-warning models, and the full-lifecycle management of slopes in open-pit mining operations.
露天矿的综合滑坡风险分区是精确安全监测、预警以及防灾减灾的基础。现有方法往往依赖单一静态指标,动态风险调控能力有限。为解决这些局限性,本研究提出一种基于科学的边坡分区方法,该方法结合了“工程-地质-环境(季节变化、基础设施分布)”等多因素。首先,利用层次分析法(AHP)构建了一个包含裂缝发育影响程度、边坡角度、边坡高度以及岩土性质四个关键因素的层次结构模型。通过计算这些评价指标的权重系数并得出边坡危险指数,对边坡危险区进行分类。此外,应用二维刚体极限平衡法(LEM)计算多个横截面的边坡安全系数,便于划分边坡稳定区。为整合这些结果,我们采用交叉矩阵分析和简单加权平均相结合的方法,通过动态纳入边坡走向表面形状、季节(气候)变化、断层特征以及基础设施分布等因素,进一步细化综合风险分区。通过在某露天矿的案例研究中应用该方法进行验证,识别出了一个高风险区、五个中风险区和六个低风险区。值得注意的是,高风险区与实际滑坡发生情况具有很强的空间一致性。结果表明,所提出的方法显著提高了分区精度,为露天采矿作业中监测资源的优化配置、差异化预警模型的开发以及边坡的全生命周期管理提供了理论依据。