许智隼, 胡五龙. 基于三维X-CT图像的结皮土壤孔隙结构特征与渗透率[J]. 农业工程学报, 2021, 37(14): 89-97. DOI: 10.11975/j.issn.1002-6819.2021.14.010
    引用本文: 许智隼, 胡五龙. 基于三维X-CT图像的结皮土壤孔隙结构特征与渗透率[J]. 农业工程学报, 2021, 37(14): 89-97. DOI: 10.11975/j.issn.1002-6819.2021.14.010
    Xu Zhisun, Hu Wulong. Characteristics of pore structure and permeability in soil crust using 3D X-CT images[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2021, 37(14): 89-97. DOI: 10.11975/j.issn.1002-6819.2021.14.010
    Citation: Xu Zhisun, Hu Wulong. Characteristics of pore structure and permeability in soil crust using 3D X-CT images[J]. Transactions of the Chinese Society of Agricultural Engineering (Transactions of the CSAE), 2021, 37(14): 89-97. DOI: 10.11975/j.issn.1002-6819.2021.14.010

    基于三维X-CT图像的结皮土壤孔隙结构特征与渗透率

    Characteristics of pore structure and permeability in soil crust using 3D X-CT images

    • 摘要: 地表结皮广泛存在于干旱半干旱地区的表层土壤,对水土保持和生态环境有着重要的影响。该研究采用X射线断层扫描成像技术(X-CT)和图像分析方法,获取并分析了3个含表层结皮的土样(孔隙率分别为0.196、0.144和0.093)三维孔隙结构特征,并利用格子玻尔兹曼方法计算了各土样沿深度方向不同土层的渗透率。孔隙结构分析发现,土样的表层与其相邻土层孔隙率具有较大差异,其孔隙变异度E>5%,表层孔隙率较小且连通性更差;而下部土层的孔隙率变化则较为平缓,其孔隙变异度E<5%,且平均孔径随深度的增加而减小,分别由0.43、0.37和0.50 mm降低至0.15、0.14和0.14 mm。渗透率计算结果表明,表层结皮对水分渗流有着明显的阻滞作用,其渗透率最小,分别为7.472、0.006和6.960 μm2;在对土样孔隙结构特征参数与孔隙率相关性分析的基础上,将Kozeny-Carman方程的比表面积替换为孔隙复杂度,提出了一种可靠的渗透率预测模型,较Kozeny-Carman方程及其简化模型而言,该模型具有更高的预测精度,其决定系数R2由0.96提升至0.98,而均方根误差RMSE则由25.06降低至18.31 μm2。该研究可为干旱半干旱地区的水资源管理利用和生态环境保护提供参考。

       

      Abstract: Abstract: Surface crusts are often hardened with the platy surface of soil layers, particularly widely distributed in arid and semi-arid areas. There are also some important influences on the soil and water conservation, as well as the ecological environment, due mainly to the special pore structure and hydraulic characteristics. In this study, three-dimensional images of real soil crust samples were acquired to characterize pore morphology and structure distribution, combining X-ray tomography with pore-scale simulation. The water infiltration process was then simulated in soil samples, thereby to quantitatively analyze the relationship between pore structure and hydraulic characteristics. Three soil samples were collected with the surface crust (the porosity of 0.196, 0.144, and 0.093) using X-ray tomography. Furthermore, a systematic investigation was made on the variation of pore structure along the depth direction of crust soil samples. Specifically, each soil sample was then sliced into 9 layers from the upper surface with each layer of 100 voxels depth. The permeability of each soil layer was then calculated using the lattice Boltzmann method. Subsequently, the correlation analysis was conducted between structural characteristic parameters and permeability. A fractal dimension model was also proposed to calculate the permeability using soil porosity and complexity. The pore structure analysis showed that the porosity and pore connectivity of the surface and bottom layer were smaller than those of the intermediate soil layer in the three soil samples. The maximum pore connectivities of soil layers were 99.21%, 94.64%, and 57.35% in the three soil samples located in the middle of the soil, respectively. The minimum were 45.99%, 27.30%, and 11.74%, respectively, located at both ends of the soil sample. The pore structure of topsoil was different from that of the adjacent soil layer, where the variation coefficient was E>5%. The average pore diameter of each soil layer decreased, with the increase of depth, from 0.43, 0.37, and 0.50 mm to 0.15, 0.14, and 0.14 mm, respectively. More importantly, the soil layer with higher porosity presented better pore connectivity and lower pore complexity, where the correlation coefficient was 0.972. The permeability calculation showed that the surface layer of soil samples behaved low local permeability of 7.472, 0.006, and 6.960 μm2 in the three samples, respectively, indicating there was a blocking effect of crust on soil seepage. Better permeability was achieved in the soil layer with higher porosity, better pore connectivity, and lower pore complexity. As such, a new permeability prediction model was finally proposed, where the specific surface area in the Kozeny-Carman equation was replaced by pore complexity. A higher prediction accuracy was obtained in the improved model, where the determination coefficient R2 increased from 0.96 to 0.98, while the root mean square error (RMSE) decreased from 25.06 to 18.31 μm2, compared with the simplified one. This finding can offer strong support to water resources management and ecological environment protection in arid and semi-arid areas.

       

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