Rainfall-induced shallow slope instability is a significant global hazard, often triggered by water infiltration that affects soil stability and involves dynamic changes in the hydraulic behavior of unsaturated soils. This study employs a hydro-mechanical coupled analysis model to assess the impact of rainfall on slope stability, focusing on the dynamic hydraulic behavior of unsaturated soils. By simulating the soil water content and slope stability under four different rainfall scenarios based on observational data and historical thresholds, this study reveals that higher rainfall intensity significantly increases the soil water content, leading to reduced slope stability. The results show a strong correlation between the soil water content and slope stability, with a 20 mm/h rainfall intensity threshold emerging as a reliable predictor of potential slope instability. This study contributes to a deeper understanding of slope stability dynamics and emphasizes the importance of proactive risk management in response to changing rainfall patterns while also validating current management practices and providing essential insight for improving early warning systems to effectively mitigate landslide risk.

In geotechnical engineering, the soil water retention curve (SWRC) is key to solving problems arising from unsaturated soil, and the methodology used to obtain the SWRC parameters is crucial for investigating rainfall infiltration and slope stability. However, on-site measurements of soil data are expensive and time-consuming, and therefore, there is high uncertainty in the SWRC parameters due to the limited amount of data available. This study explores the impact of uncertainty in SWRC parameters on unsaturated soil slope seepage and stability under rainfall conditions. Bayesian updating was initially used to update the posterior distribution of the SWRC parameters of the model and in situ soil. Subsequently, a Markov Chain Monte Carlo (MCMC) method was used to generate random samples, and the uncertainty of the parameters was analyzed. Additionally, SWRC parametric models with different confidence intervals were created, and a hydraulic coupled model was used to evaluate the influence of the SWRC parameters (with different confidence intervals) on slope seepage and stability under rainfall conditions. The results indicated that the parameters and affecting the air entry value of the soil and the pore size distribution, respectively, increased as the confidence interval percentile increased. The changes in these two parameters increased the effect of rainfall on the pressure head and volumetric water content of the soil. After rainfall infiltrated the slope, the soil volumetric water content and the internal suction stress of the soil increased, resulting in a reduction in the local factor of safety (LFS) and, hence, a decrease in the stability of the slope. These results show that the predictions for the pressure head and volumetric water content were affected by the uncertainty in the SWRC parameters, leading to errors in the slope stability analysis.

Owing to active orogenic movement and the monsoon climate, rainfall-induced landslide disasters often occur in Taiwan. Hence, hillslope hydrology and stability have received considerable research attention. However, it remains difficult to accurately estimate the duration and consequences of hillslope instability induced by hillslope hydrology. Research on hillslope hydrology and stability is complicated by spatial heterogeneity, hydrological processes operating at various scales, spatiotemporal evolution, and geomorphological properties. Recent advances in critical zone science have provided an approach to extend geoscience studies. The “deep coupling” concept is essential for integrating physical, chemical, and biological processes on various spatiotemporal scales and for providing a macro and unified framework for evaluating internal properties and processes. Critical zone science and hillslope hydrology and stability both depend on interdisciplinary perspectives and approaches, monitoring strategies, and model analysis of integrating and coupling processes. They both share the characteristics of spatial heterogeneity, continuous evolution, and relevance to ecosystem services. To address the challenges related to hillslope hydrology and stability in Taiwan, we reviewed the progress in, relevance between, and common challenges to hillslope hydrology, stability, and critical zone science. We then presented a process-based integrated monitoring strategy, an interdisciplinary perspective, and a coupling analysis framework and model. The aim of this study was to promote the advancement of research on hillslope stability and hydrology in Taiwan.

The soil water characteristic curve (SWCC) is a key foundation in unsaturated soil mechanics describing the relationship between matric suction and water content, which is crucial for studies on effective stress, permeability coefficients, and other soil properties. In natural environments, colluvial and residual soils typically exhibit high pore heterogeneity, and previous studies have shown that the SWCC is closely related to the distribution of pore sizes. The SWCC of soils may display either a unimodal or bimodal distribution, leading to different hydraulic behaviors. Past unsaturated slope stability analyses have used the unimodal SWCC model, but this assumption may result in evaluation errors, affecting the accuracy of seepage and slope stability analyses. This study proposes a novel bimodal hydro-mechanical coupling model to investigate the influence of bimodal SWCC representations on rainfall-induced seepage behavior and stability of unsaturated slopes. By fitting the unimodal and bimodal SWCCs with experimental data, the results show that the bimodal model provides a higher degree of fit and smaller errors, offering a more accurate description of the relationship between matric suction and effective saturation, thus improving the accuracy of soil hydraulic property assessment. Furthermore, the study established a hypothetical slope model and used field data of landslides to simulate the collapse of Babaoliao in Chiayi County, Taiwan. The results show that the bimodal model predicts slope instability 1 to 3 h earlier than the unimodal model, with the rate of change in the safety factor being about 16.6% to 25.1% higher. The research results indicate the superiority of the bimodal model in soils with dual-porosity structures. The bimodal model can improve the accuracy and reliability of slope stability assessments.

This study established a study framework to quantify the safety factors of unsaturated shallow slopes at different temperatures. This study is based on a non-isothermal soil water characteristic curve model quantifying the temperature-dependent hydraulic properties of soils. The hydraulic coupling analysis models HYDRUS 2D and The Slope Cube Module were used for finite element modeling. A slope stability analysis was performed based on the local factor of safety (LFS) theory. An increased temperature decreased the soil matric suction, suction stress, effective stress, and LFS, weakening the soil strength. Slope modeling analysis showed that soils were dominated by different water retention mechanisms before and after rainfall infiltration, and the trends caused by temperature changes also changed accordingly. This study provides insights into the relationship between soil mechanical properties and temperature, which is valuable for maintaining soil stability and preventing geological hazards.