Abstract The rainfall-induced earth slope instability is time-dependent as a result of the infiltration process. In order to cater for the uncertainty of geo-material parameters, we conduct a time-dependent reliability analysis of the rainfall-induced landslide, which incorporates discretizing the stochastic process of rainfall infiltration, assigning instantaneous landslide limit state functions at discrete time instants, and calculating the time-dependent slope reliability index within the forecast time as a series system reliability problem. Via the widely used numerical package Python, we adopt a simplified Hasofer-Lind-Rackwitz-Fiessler (HLRF) algorithm to calculate the first-order reliability indices, and the numerical calculations extended to slope reliability analysis are easily implemented. In addition, we account for the spatial variability of soil’s permeability in the water infiltration model, which for simplicity is based on the Karhunen–Loeve (KL) expansion technique. At last, we present extensive parametric studies of an example earth slope using the proposed method, revealing the potential influences of various sources of uncertainties and spatial variability when probabilistically modelling the water infiltration process and the slope instability mechanism, which may be used further for rainfall-induced landslide forecast.

中文翻译：

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考虑土壤渗透性空间变异性的降雨诱发浅层滑坡时效可靠性分析

摘要 作为渗透过程的结果，降雨引起的土坡失稳具有时间依赖性。为了满足地质材料参数的不确定性，我们对降雨诱发的滑坡进行了时间依赖的可靠性分析，其中包括将降雨入渗的随机过程离散化，在离散时刻分配瞬时滑坡极限状态函数，以及计算预测时间内的瞬态边坡可靠度指标作为一个系列系统可靠度问题。通过广泛使用的数值包Python，我们采用简化的Hasofer-Lind-Rackwitz-Fiessler（HLRF）算法来计算一阶可靠性指标，并且可以轻松实现扩展到边坡可靠性分析的数值计算。此外，我们考虑了渗水模型中土壤渗透性的空间变异性，为简单起见，该模型基于 Karhunen-Loeve (KL) 扩展技术。最后，我们使用所提出的方法对一个示例土坡进行了广泛的参数研究，揭示了在对水入渗过程和边坡失稳机制进行概率建模时各种不确定性和空间变异性来源的潜在影响，这些可能进一步用于降雨-诱发滑坡预报。