The Tibetan Plateau (TP), known as the 'Asian Water Tower', poses significant challenges for hydrological modeling due to its complex cryospheric processes and parametric uncertainties. To address these challenges, we developed an integrated evaluation framework that combines spatiotemporal performance metrics with three global sensitivity analysis methods, based on the Variable Infiltration Capacity (VIC) model. Four alpine river basins were used as case studies to assess the impact of 33 parameters on nine hydro-energy variables across daily, seasonal, and spatial scales. Key drivers of spatial heterogeneity in parameter sensitivities were identified. The results indicate that snow albedo, leaf area index, and the soil drainage parameter broadly influence multiple processes. Runoff and baseflow sensitivities vary spatiotemporally. Random Forest-based SHapley Additive Explanations analysis reveals an east-west gradient in parameter sensitivity, driven by temperature, precipitation, and radiation. Two-step parameter optimization improves the average daily simulation efficiency and spatial consistency for land surface temperature and snow cover fraction by 33% and 30%, respectively, without compromising runoff accuracy. Transferring parameter sensitivities to similar basins confirms the framework's robustness and generalizability. This study underscores the importance of non-runoff parameters, enhances simulation performance, and provides insights into seasonal hydrological variability for more robust model applications across the TP.

Slope failures resulting from thaw slumps in permafrost regions, have developed widely under the influence of climate change and engineering activities. The shear strength at the interface between the active layer and permafrost (IBALP) at maximum thawing depth is a critical factor to evaluate stability of permafrost slopes. Traditional direct shear, triaxial shear, and large-scale in-situ shear experiments are unsuitable for measuring the shear strength parameter of the IBALP. Based on the characteristics of thaw slumps in permafrost regions, this study proposes a novel test method of self-weight direct shear instrument (SWDSI), and its principle, structure, measurement system and test steps are described in detail. The shear strength of the IBALP under maximum thaw depth conditions is measured using this method. The results show that under the condition that the permafrost layer is thick underground ice and the active layer consists of silty clay with 20% water content, the test results are in good agreement with the results of field large-scale direct shear tests and are in accordance with previous understandings and natural laws. The above analysis indicates that the method of the SWDSI has a reliable theoretical basis and reasonable experimental procedures, and meets the needs of stability assessment of thaw slumps in permafrost regions. The experimental data obtained provide important parameter support for the evaluation of related geological hazards.

Frozen soils, including seasonally frozen ground and permafrost, are rapidly changing under a warming climate, with cascading effects on water, energy, and carbon cycles. We synthesize recent advances in the physics, observation, and modeling of frozen-soil hydrology, emphasizing freeze-thaw dynamics, infiltration regimes and preferential flow, groundwater-permafrost interactions (including talik development and advective heat), and resulting shifts in streamflow seasonality. Progress in in situ sensing, geophysics, and remote sensing now resolves unfrozen water, freezing fronts, and active-layer dynamics across scales, while land-surface and tracer-aided hydrological models increasingly represent phase change, macropore bypass, and vapor transport. Thaw-induced activation of subsurface pathways alters recharge and baseflow, influences vegetation and biogeochemistry, and modulates greenhouse-gas emissions. Key uncertainties persist in scaling micro-scale processes, parameterizing ice-impeded hydraulics, and representing abrupt thaw and wetland dynamics. We outline a tiered modeling framework, priority observations, and integration of vegetation-hydrology-carbon processes to improve projections of cold-region water resources and climate feedbacks.

Shallow cut-and-cover underground structures, such as subway stations, are traditionally designed as rigid boxes (moment-resisting connections between the main structural members), seeking internal hyperstaticity and high lateral (transverse) stiffness to achieve important seismic capacity. However, since seismic ground motions impose racking drifts, this proved rather prejudicial, with great structural damage and little resilience. Therefore, two previous papers proposed an opposite strategy seeking low lateral (transverse) stiffness by connecting the structural elements flexibly (hinging and sliding). Under severe seismic inputs, these structures would accommodate racking without significant damage; this behaviour is highly resilient. The seismic resilience of this solution was numerically demonstrated in the well-known Daikai station (Kobe, Japan) and a station located in Chengdu (China). This paper is a continuation of these studies; it aims to extend, deepen, and ground this conclusion by performing a numerical parametric study on these two stations in a wide and representative set of situations characterised by the soil type, overburden depth, engineering bedrock position, and high- and lowlateral-stiffness of the stations. The performance indices are the racking displacement and the structural damage (quantified through concrete damage variables). The findings of this study validate the previous remarks and provide new insights.

The ability to predict the soil mechanical parameters swiftly is critical for off-road vehicle mobility. This paper introduces a novel interpretation methodology for determining critical soil mechanical parameters by impact penetration tests, enabling rapid and remote assessment of terramechanics properties. Initially, the method employs the Mohr-Coulomb constitutive model and the Coupled Eulerian-Lagrangian (CEL) finite element method to generate a dataset of soil impact penetration resistance and acceleration responses. Subsequently, a Radial Basis Function (RBF) neural network is employed as a surrogate model and integrated with the Nondominated Sorting Genetic Algorithm II (NSGA-II) to accurately interpret parameters such as density, cohesion, internal friction angle, elastic modulus, and Poisson's ratio. Experimental validation using sand and silty clay from Yangbaijing, Tibet, confirmed the accuracy and robustness of the method. The results indicate that the mean absolute percentage error for interpreted values was below 25%, with relative errors for some key parameters even below 10%. Furthermore, each single-condition calculation was completed on a standard computer in less than one minute. Comparative analyses with other algorithms, including MIGA and POS, demonstrated the superior performance of NSGA-II in avoiding local optima. The proposed interpretation framework offers a rapid, reliable, and remote solution for identifying the soil mechanical properties. Its potential applications range from disaster mitigation and emergency response operations to extraterrestrial soil exploration and other scenarios where in-situ investigations are challenging.

Seismic fragility denotes the probabilities of a system exceeding some prescribed damage levels under a range of seismic intensities. Classical seismic fragility studies in slope engineering usually construct fragility functions by making some assumptions for fragility curve shape, and always neglect spatial variability of soil materials. In this study, an assumption-free method on the basis of probability density evolution theory (PDET) is proposed for seismic fragility assessment of slopes. The random input earthquakes and spatially-variable soil parameters in slope are simultaneously quantified. By the proposed method, assumption-free fragility curves of a slope are established without limiting the fragility curve shape. The obtained fragility results are also compared with those from two classic parametric fragility methods (linear regression and maximum likelihood estimation) and Monte Carlo simulation. The results demonstrate that the proposed assumption-free method has potential to gives more rigorous and accurate fragility results than classical parametric fragility analysis methods. With the proposed method, more reliable fragility results can be obtained for slope seismic risk assessment.

The horizontal displacement of monopile under cyclic loading is subject to uncertainty due to variations in metocean conditions and soil parameters at offshore wind farms. However, the current design for cyclically loaded monopiles relies on the p-y method recommended by API and DNV, which does not accurately capture the horizontal displacement of the monopiles. In this study, finite element simulations are performed using ABAQUS, where the soil is modeled with the Einav-Randolph model to account for soil softening effects. The impact of parameter uncertainties, such as soil stiffness, undrained shear strength, and the pile-soil friction coefficient, on the reliability index of the monopile's horizontal displacement for different length diameter (L/D) ratios is investigated. A case study is provided to assess the horizontal displacement reliability of a monopile under cyclic loading. The results show that the horizontal displacement reliability index decreases as the coefficient of variation (COV) of the random variables, the correlation coefficient, and the monopile's L/D ratio increase. Conversely, the reliability index increases with an increase in the allowable horizontal displacement. The horizontal displacement reliability index is most sensitive to soil stiffness, followed by undrained shear strength and pile-soil friction coefficient. The findings of this study offer valuable insights into how parameter uncertainties influence the horizontal displacement of monopiles under cyclic loading.

To study the degree of strength parameter deterioration (DSPD) of Lushi swelling rock in the high slope area under wetting-drying cycles, 114 samples are remodeled. Wetting-drying cycle and triaxial tests are conducted to comprehensively analyze the influence of dry density, wetting-drying cycle path, and number of wetting-drying cycles on the strength deterioration characteristics of Lushi swelling rock. Using the fitting analysis and function superposition methods, the DSPD model of Lushi swelling rock under wetting-drying cycles is established, which considers the previous four influencing factors. The influence of the DSPD of Lushi swelling rock on the stability of high slopes under rainfall seepage and circulation conditions is studied. Lushi swelling rock exhibits significant strength deterioration characteristics under wetting-drying cycles. The overall DSPD for cohesion is higher than that of the internal friction angle. Under rainstorm conditions, strength deterioration leads to a shallower depth of the critical slip surface of the slope and a smaller safety factor. After eight rounds of rainfall seepage and circulation, the safety factor gradually decreases by approximately 14%-28%. This study provides and verifies the DSPD model of Lushi swelling rock under wetting-drying cycles, and the results could provide a basis for disaster prediction and the optimization design of swelling rock slopes.

Landslides, which are a type of process-based geological hazard, exhibit stagewise characteristics that serve as important guidance for the prevention and mitigation of slope engineering disasters. The cross-correlation and randomness of soil parameters can influence the evolution of landslide characteristics. This paper, based on the spatial variability of slope soil parameters, combines copula theory and the material point method (MPM) to establish a Monte Carlo-random material point method considering the cross-correlation of soil parameters. This resulting method is called copula-RMPM. It investigates the probability distributions of slope instability and landslide large deformation characteristics, such as sliding distance, landslide thickness, collapse range, and volume of sliding mass. The results indicated that in the study of soil parameter characteristics, failure probability increases with increased correlation coefficient. Also, failure probability showed a positive correlation with the variability coefficient of cohesion and internal friction angle, with failure probability being more sensitive to the variability coefficient of the internal friction angle. The landslide large deformation characteristics generally follow the normal distribution; they exhibit significant fluctuations in sliding distance and sliding mass area despite the relatively small variability coefficient. Compared with the results of random field simulation of soil parameters, the probability of landslide large deformation characteristics obtained by deterministic soil parameters is often lower. Therefore, the probability distribution of landslide large deformation characteristics obtained by the Monte Carlo-random material point method considering the cross-correlation of soil parameters is more meaningful for engineering guidance.

Silt is widely utilized as a filling material in transportation construction, However, it frequently suffers from problems, such as excess pore water pressure buildup, settlement, and mud pumping. Wicking geotextiles have emerged as a sustainable solution by improving both drainage and reinforcement capacities, yet their optimal design parameters remain unclear. To address this gap, a series of tests were performed to investigate the effects of compaction degree, reinforcement configuration (number, spacing, position), and specimen geometry on the mechanical and consolidation of silt reinforced with wicking geotextiles. The results reveal that the failure mechanism of reinforced silt progresses through four distinct stages, which the wicking geotextile improved interparticle contact, delays crack initiation, and improves post-peak stability. Wicking geotextiles significantly improve strength, particularly at lower compaction degrees, by restraining crack propagation and promoting uniform stress distribution. Optimal mechanical performance was achieved with three reinforcement layers and compaction degrees of 93-95 %. Mid-depth placement of a single layer or uniform spacing of multiple layers produced the best outcomes. Although non-uniform spacing provided advantages at early deformation stages, it ultimately induced premature failure, whereas uniform spacing (= 1.27 exhibited improved ductility, while larger specimens with multiple layers demonstrated improved post-peak stability. Wicking geotextiles accelerated drainage and void ratio reduction but concurrently decreased the compression modulus. These findings contribute to a more comprehensive understanding of the mechanical and hydraulic responses of wicking geotextile-reinforced silt and provide practical insights for the design and optimization of reinforced subgrades.