Parametric assessment of rainfall-related slope stability through SRM modeling and orthogonal experimental design: insights from the Zhuquedong slope, China

Rainfall-induced slope instability is a major geotechnical hazard in mountainous regions, where slope behavior is governed by the combined effects of geometry, soil mechanical properties, and hydrological conditions. Quantifying the relative influence of these factors remains challenging due to the high dimensionality and computational cost of numerical models. This study presents a parametric numerical–statistical investigation of rainfall-related slope stability by combining the strength reduction method (SRM) with an orthogonal experimental design and statistical analysis. Twenty-eight slope scenarios were generated using an L28 orthogonal array, enabling simultaneous and structured variation of slope geometry, soil strength parameters, and hydrological conditions while limiting computational demand. For each scenario, the factor of safety (Fs) was obtained through SRM-based finite element analysis and subsequently examined using correlation analysis, one-way ANOVA, multiple linear regression, and range analysis to evaluate parameter sensitivity and relative influence. The results indicate that slope geometry, particularly slope height and gradient, exerts the strongest control on stability, while rainfall-related hydrological conditions significantly reduce Fs by amplifying pore-water effects. Soil shear strength parameters provide secondary stabilizing influences, whereas unit weight shows a comparatively minor effect within the investigated range. Rather than proposing a new numerical formulation, this study demonstrates how orthogonal experimental design and statistical post-processing can efficiently support parametric screening of rainfall-related slope stability in engineering applications.