Random field theory is often used to model spatial variability of geo-material boundary and property. The results of random field generation based on different theories are quite different; however, few studies discuss the effects of adopting different random field approaches on the established stratigraphic models and their influence on engineering analysis. This article compares two random field approaches for evaluating liquefaction potential at a selected site. Here, based on the results of cone penetration tests (CPTs) at the study site, stratigraphic models are constructed using a continuous random field (conditional random field, CRF) and a discontinuous random field (Markov random field, MRF). Note that the MRF parameters were calibrated with the statistical parameters used in CRF. A series of geological profiles representing realizations of the derived CRF-based and MRF-based stratigraphic models are generated. Then, the liquefaction potential index (LPI) is calculated using the simplified procedure with a simulated geological profile and associated soil parameters. Finally, by repeating the analysis for all realizations of random stratigraphic models, the mean and the coefficient of variation of LPI are determined. Meanwhile, the uncertainty of stratigraphic models generated by CRF and MRF approaches is quantified and expressed as information entropy. Next, the relationship between stratigraphic model uncertainty (as an entropy) and LPI variation (or uncertainty) is established. The results show that: (1) the generation of the stratigraphic model is affected by the chosen random field approach, and the distribution of MRF-based strata is more continuous compared with that of CRF-based strata; (2) due to this effect, the strata uncertainty of CRF simulation is more uniform compared with that of MRF; (3) the information entropy and LPI uncertainty obtained using CRF exhibit moderate correlation, while these parameters obtained using MRF exhibit a strong positive correlation.

随机场理论通常用于模拟地质材料边界和属性的空间变异性。基于不同理论的随机场生成结果大相径庭；然而，很少有研究讨论采用不同随机场方法对已建立的地层模型的影响及其对工程分析的影响。本文比较了在选定地点评估液化潜力的两种随机场方法。在这里，根据研究现场的锥入试验（CPTs）结果，使用连续随机场（conditional random field，CRF）和不连续随机场（Markov random field，MRF）构建地层模型。请注意，MRF 参数是使用 CRF 中使用的统计参数校准的。生成了一系列地质剖面，代表了基于 CRF 和基于 MRF 的地层模型的实现。然后，液化潜力指数 (LPI) 使用简化的程序与模拟的地质剖面和相关的土壤参数计算。最后，通过对随机地层模型的所有实现重复分析，确定了 LPI 的均值和变异系数。同时，CRF和MRF方法生成的地层模型的不确定性被量化并表示为信息熵。接下来，建立地层模型不确定性（作为熵）与 LPI 变化（或不确定性）之间的关系。结果表明：（1）地层模型的生成受所选择的随机场方法的影响，与基于CRF的地层相比，基于MRF的地层分布更连续；(2)由于这种影响，CRF模拟的地层不确定性比MRF更均匀；(3) 使用 CRF 得到的信息熵和 LPI 不确定性表现出中等相关性，而使用 MRF 得到的这些参数表现出很强的正相关性。