Many uncertainties exist in geotechnical engineering. Spatial variability is a type of uncertainty that has received more and more attention in recent years. Scale of fluctuation (SOF) is a parameter for measuring the spatial variability of soil properties. To investigate the proper method for computing the SOF of soil properties, two types of methods (auto-correlation function method (ACM), and variance reduction method (VRM)) are compared theoretically and numerically, and the influence factors, such as number of data points involved in curve fitting for the auto-correlation function (ACF) or variance reduction function (VRF) and sampling interval, on the SOFs are analyzed. To improve the accuracy of curve fitting for the ACF or VRF, a weighted least squares (WLS) method is proposed, in which the weight of each data point of sample function decreases with the increasing of lag distance between two points in a random field. Three types of soil parameters, including the CPT, the physical, and the hydraulic parameters, are tested by in-situ and laboratory tests, and the SOFs of these parameters are computed. Computation of the SOFs proves that the VRM combined with the suggested WLS is a good method for computing the SOFs of soil properties. Comparison of the SOFs shows that there are negligible differences among the three types of soil parameters of clay layers in Hefei, which is further proved by the Wilcoxon test from a statistical point of view. By using the VRM combine with WLS, the SOFs of clay are computed based on 509 sets of CPT data from 34 sites in Hefei. The statistics of SOFs can give a reference for the selection of SOF for reliability analysis or reliability-based design of geo-structures with spatial variability.

岩土工程存在许多不确定性。空间变异性是一种近年来越来越受到关注的不确定性。波动尺度（SOF）是衡量土壤性质空间变异性的参数。为探讨计算土壤性质 SOF 的合适方法，对两种方法（自相关函数法（ACM）和方差缩减法（VRM））进行了理论和数值比较，以及影响因素，如分析了 SOF 上自相关函数 (ACF) 或方差减少函数 (VRF) 和采样间隔的曲线拟合中涉及的数据点。为了提高 ACF 或 VRF 曲线拟合的准确性，提出了一种加权最小二乘 (WLS) 方法，其中样本函数的每个数据点的权重随着随机场中两点之间滞后距离的增加而减小。通过现场和实验室试验测试了三种土壤参数，包括CPT、物理参数和水力参数，并计算了这些参数的SOF。SOF 的计算证明，VRM 与建议的 WLS 相结合是计算土壤性质 SOF 的好方法。SOFs比较表明，合肥三类黏土层土壤参数差异可忽略不计，Wilcoxon检验从统计学的角度进一步证明了这一点。将VRM与WLS相结合，基于合肥34个站点的509组CPT数据计算粘土的SOF。