Efficient Quantification of Risk for Linear Engineering Projects under Landslide Hazards: A Novel Proposal Based on Slope Unit

Traditional methods for assessing the risk to linear engineering projects (e.g., pipelines, railways, power transmission lines, etc.) from landslides are constrained by the need for prior prediction of specific landslide geometries. This leads to complex processes and uncertain outcomes. This study proposes a fundamental paradigm shift: employing slope units as stable assessment units and directly evaluating their probability of overall instability as the hazard indicator. Furthermore, for the linear engineering segment traversing a given unit, its vulnerability and failure consequences can be predetermined and uniquely defined within the unit based on engineering attributes (e.g., crossing type, structural design parameters, socio-economic value), forming a "fixed-parameter" system. Consequently, the risk to linear engineering projects under landslide influence is simplified into a standardized formula: Unit Risk = Unit Landslide Probability (predicted) × Unit Linear Engineering Vulnerability (fixed) × Unit Linear Engineering Failure Consequence (fixed). The core advantages of this model lie in its generality and efficiency: 1) It is applicable to all types of mountainous linear engineering projects including pipelines, roads, railways, and transmission lines; 2) It is equally suitable for forward-looking risk assessment during the planning and design phase as well as for rapid risk screening during operation and maintenance; 3) By encapsulating complex uncertainties within the probabilistic assessment of the slope unit while standardizing vulnerability and consequence parameters, it transforms the evaluation process from "case-by-case judgment" to "standardized calculation". This method offers a promising novel pathway toward standardized and rapid assessment for managing the risk to linear engineering projects under landslide influence, holding significant application potential, particularly for the preliminary screening and systematic comparison of risks to long-distance projects under the influence of geohazards.