Optimizing a Statistics-Based Continuous Rainfall Definition to Represent Soil Saturation Dynamics for Shallow Landslide Prediction

This study proposes and statistically optimizes a definition of “continuous rainfall” that links rainfall records to soil saturation dynamics. The analysis uses hourly rainfall observations and volumetric water content (VWC) measured by eight sensors installed at a 1-m depth at a natural slope monitoring site in Songnisan National Park, Korea, from 2017 through October 2024. After calibrating the initial condition using the mean dry-season VWC (≈ 0.1) and normalizing the observations to represent relative changes in soil saturation, continuous rainfall was formulated using three parameters: (1) the maximum allowable rain-free period (RP_max), (2) the minimum hourly rainfall threshold included in the accumulation (HR_min), and (3) a moving-window duration (MW_dur) that accounts for saturation decay due to drainage. Cumulative continuous rainfall amounts were generated for 27 parameter combinations (RP_max = 12/24/36 h; HR_min = 0/1/2 mm; MW_dur = 48/60/72 h), and the correlations between these amounts and normalized VWC were evaluated. The results show pronounced differences in statistical performance across parameter sets: depending on the chosen combination, the same VWC trajectory was either fragmented into multiple rainfall events or consistently captured as a single continuous rainfall event. These findings indicate that an optimized continuous rainfall metric that represents soil hydrodynamics can improve the interpretation of rainfall inputs for shallow landslide prediction. Future work will extend the approach to diverse slope settings and link it to real-time early-warning systems.