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.

In deep foundation pit engineering, the soil undergoes a complex stress path, encompassing both loading and unloading phases. The Shanghai model, an advanced constitutive model, effectively accounts for the soil's deformation characteristics under these varied stress paths, which is essential for accurately predicting the horizontal displacement and surface settlement of the foundation pit's enclosure structure. This model comprises eight material parameters, three initial state parameters, and one small-strain parameter. Despite its sophistication, there is a scarcity of numerical studies exploring the correlation between these parameters and the deformation patterns in foundation pit engineering. This paper initially establishes the superiority of the Shanghai model in ultra-deep circular vertical shaft foundation pit engineering by examining a case study of a nursery circular ultra-deep vertical shaft foundation pit, which is part of the Suzhou River section's deep drainage and storage pipeline system pilot project in Shanghai. Subsequently, utilizing an idealized foundation pit engineering model, a comprehensive sensitivity analysis of the Shanghai model's multi-parameter values across their full range was performed using orthogonal experiments. The findings revealed that the parameter most sensitive to the lateral displacement of the underground continuous wall was kappa, with an increase in kappa leading to a corresponding increase in displacement. Similarly, the parameter most sensitive to surface subsidence outside the pit was lambda, with an increase in lambda resulting in greater subsidence. Lastly, the parameter most sensitive to soil uplift at the bottom of the pit was also kappa, with an increase in kappa leading to more significant uplift.