Liu Qiang, Guo Liang, Miao Jiali, Guo Shangsheng, Shu Jie
College of Earth Science and Engineering, Shandong University of Science and Technology, Qingdao, Shandong, China.
Sci Rep. 2024 Sep 29;14(1):22564. doi: 10.1038/s41598-024-73821-x.
The soil-water characteristic curve (SWCC) is an important basis for describing hydraulic properties, which is closely related to environmental problems such as the migration of toxic substances from groundwater and soil. The SWCC models vary considerably with respect to the void ratio or bulk density. However, the void ratio and bulk density of the same soil change at different depths or positions within a flat space. Accurate simulation or calculation requires a precise SWCC, but measuring every SWCC under each density or void ratio condition is difficult. In this study, two particle packing models, the Kwan model and the modified linear packing density model (MLPDM), were introduced into the van Genuchten (VG) model to predict the SWCC for soil at the minimum void ratio (the maximum dry density). Then, the prediction method of the SWCCs for the same soil with different densities or void ratios was given. A series of laboratory tests using quartz sand mixtures were conducted to verify the accuracy of two extended models (the K-VG model and the M-VG model). For the K-VG model, the average RMSE was 0.020. For the M-VG model, the average RMSE was 0.017. In general, the SWCCs predicted by the two extended models were consistent with the measured values.
土壤水分特征曲线(SWCC)是描述水力特性的重要依据,它与诸如地下水中有毒物质和土壤迁移等环境问题密切相关。SWCC模型在孔隙比或容重方面有很大差异。然而,同一土壤的孔隙比和容重在平坦空间内的不同深度或位置会发生变化。精确的模拟或计算需要精确的SWCC,但在每种密度或孔隙比条件下测量每个SWCC都很困难。在本研究中,将两种颗粒堆积模型,即关模型和改进的线性堆积密度模型(MLPDM),引入van Genuchten(VG)模型,以预测最小孔隙比(最大干密度)下土壤的SWCC。然后,给出了相同土壤在不同密度或孔隙比下SWCC的预测方法。进行了一系列使用石英砂混合物的实验室测试,以验证两个扩展模型(K-VG模型和M-VG模型)的准确性。对于K-VG模型,平均均方根误差(RMSE)为0.020。对于M-VG模型,平均RMSE为0.017。总体而言,两个扩展模型预测的SWCC与测量值一致。