Granite residual soil is widely distributed in Southeast Fujian. Large-scale engineering construction leads to the exposure of residual soil slopes to the natural environment. Affected by seasonal climate factors, the soil of slopes experiences a dry–wet cycle for a long time. The repeated changes in water content seriously affect the shear strength of soil, and then affect the stability of the slope. In order to explore the influence of the dry–wet cycle on the shear strength of granite residual soil in Fujian, an indoor dry–wet cycle simulation test was carried out for shallow granite residual soil on a slope in Fuzhou, and the relationship between water content, dry–wet cycle times, and the shear strength index, including the cohesion and internal friction angle of the granite residual soil, was discussed. The results show that when the number of dry–wet cycles is constant, the cohesion and internal friction angle of the granite residual soil decrease with an increase in water content. The relationship between the cohesion, internal friction angle, and water content can be described using a power function. Meanwhile, the fitting parameters of the power function are also a function of the number of wet and dry cycles. The prediction formulas of the cohesion and internal friction angle considering the number of dry–wet cycles and water content are established, and then the prediction formula of shear strength is obtained. The ratio of the predicted value of shear strength to the test value shall be within ±15%. An error transfer analysis based on the point estimation method shows that the overall uncertainty of the predicted value of shear strength caused by the combined uncertainty of the predicted value of cohesion and the internal friction angle and the single-variable uncertainty of the predicted value of shear strength caused only by the uncertainty of the predicted value of either the cohesion or internal friction angle increases first and then decreases with an increase in the number of dry–wet cycles. All increase with an increasing water content. The maximum standard deviation of the proposed shear strength prediction model of granite residual soil is less than 9%.

The spatial variability of geotechnical parameters, such as soil shear wave velocity (V_s), exhibits significant nonlinearity and non-stationarity with respect to depth (h) due to the influence of overlying stress. Existing stochastic field models for describing the variability of geotechnical parameters are insufficient for simultaneously capturing both the nonlinearity and non-stationarity of these parameters. In this study, a power function V_s = V_s0[f(h)]ⁿ is proposed to describe the nonlinear trend in soil shear wave velocity (V_s) as a function of depth-related variable f(h). Considering the physical significance and correlation of the power function parameters V_s0 and n, the variability of these parameters is modeled using a random variable model and a stationary stochastic field model, respectively. This leads to the development of a non-stationary stochastic field model that describes the spatial variability of V_s. The proposed method is applied to simulate the random V_s-structure of a seabed site in China, and the obtained V_s results are used to assess the liquefaction probability of the seabed. The results indicate that ignoring the correlation between geotechnical parameters significantly increases the variability of the final simulation results. However, the proposed method accurately captures the nonlinear trend and non-stationary characteristics of soil V_s with depth, and the liquefaction probability predictions are consistent with those derived from in situ V_s measurements in the study area. This approach provides valuable guidance for simulating the spatial variability of depth-dependent geotechnical parameters, particularly those significantly influenced by overlying pressure.

《地球科学》(ISSN 1000-2383;CN42-1874/P) (原刊名《地球科学——中国地质大学学报》ISSN 1000-2383;CN42-1233/P)，创刊于1957年，是由教育部主管、中国地质大学主办的综合性地学学术理论期刊，月刊，2015年改名为《地球科学》,她以反映中国地质大学教学与科研最新的、高水平的基础地质、应用地质、资源与环境地质及地学工程技术研究成果为主要任务。

The spatial variability of soil shear wave velocity (V_s) significantly influences the results of site seismic response analysis. Based on the collected measured V_s values of silty clay in a certain sea area in China, this study divides the V_s data into one set of on-site sample data and six sets of historical data. A power function is used to establish the regression equation between V_s and depth h, and the joint prior distribution of the mean and variance for parameters a and b in the power function is derived using historical data. The joint posterior distribution of parameters a and b is obtained by applying the Bayesian formula to the on-site sample data. Using the maximum a posteriori mean values of a and b combined with the point estimation method, the mean and standard deviation of the predicted V_s values as functions of depth h are derived. The accuracy of the point estimation results is verified using Monte Carlo simulation. Compared to the V_s values predicted using only the mean values of a and b derived from on-site sample data, the V_s values predicted based on the maximum a posteriori mean values of a and b are closer to the measured V_s values. Accordingly, the results of the site seismic response analysis also align more closely with those calculated using the true V_s values.