Quantitative Characterization of Macropore Structure of Granite Residual Soil

QUE Yun; CAI Pei-chen; LI Xian

doi:10.11988/ckyyb.20200987

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Journal of Changjiang River Scientific Research Institute ›› 2022, Vol. 39 ›› Issue (2) : 82-88. DOI: 10.11988/ckyyb.20200987

ROCK-SOIL ENGINEERING

Quantitative Characterization of Macropore Structure of Granite Residual Soil

QUE Yun, CAI Pei-chen, LI Xian

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Abstract

In order to reveal the distribution law and shape characteristics of the macropore structure of granite residual soil, we quantified the round ratio, flatness, overall silhouette coefficient and fractal dimension of undisturbed granite residual soil in Fuzhou by using industrial CT scanning and ImageJ software. Our findings revealed that 1) over 80% of the macropores ranged 0.15-1 mm in diameter, and less than 20% of the macropores had a diameter greater than 1 mm. Ranging between 5.8%-22.7%, the macroporosity of granite residual soil first augmented and then reduced with the increase of soil depth. 2) Larger diameter of macropore resulted in a smaller round ratio. 3) The overall silhouette coefficient of four samples changed within 0.81-0.87, and such change attenuated with the increase of soil depth. 4) The macroporosity of granite residual soil is correlated with the fractal dimension; but the coefficients of such correlation of different samples varied distinctly. In summary, granite residual soil is of large porosity, small toughness, wide distribution of macropores, large difference in pore structure, and large dispersion of local pore flatness.

Key words

granite residual soil / CT scan / macropores / meso-scale / fractal dimension

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QUE Yun, CAI Pei-chen, LI Xian. Quantitative Characterization of Macropore Structure of Granite Residual Soil[J]. Journal of Changjiang River Scientific Research Institute. 2022, 39(2): 82-88 https://doi.org/10.11988/ckyyb.20200987

References

[1] 吴能森. 花岗岩残积土开挖边坡的工程特性[J]. 山地学报, 2006, 24(4): 431-436.
[2] 阙云, 林登辉, 陈嘉. 强降雨条件下含大孔隙土柱水分非平衡运移特性[J]. 同济大学学报:自然科学版, 2017, 45(4): 488-496.
[3] 吕捷,樊秀峰,吴振祥.基于降雨染色示踪试验的大孔隙流特性研究[J].长江科学院院报,2021,38(5):109-114,122.
[4] 潘网生, 许玉凤, 卢玉东, 等. 基于非均匀性和分形维数的黄土优先流特征定量分析[J]. 农业工程学报, 2017, 33(3): 140-145.
[5] 曾强. 植被发育斜坡非饱和带优先流及根-土环隙流研究[D]. 昆明:昆明理工大学, 2016.
[6] 李同川. 黄土高原土壤大孔隙特征及其对土壤水分的影响[D]. 杨凌:西北农林科技大学, 2017.
[7] 徐宗恒. 植被发育斜坡非饱和带土体大孔隙研究[D]. 昆明:昆明理工大学, 2014.
[8] WARNER G S,NIEBER J L,MOORE I D,et al.Characterizing Macropores in Soil by Computed Tomography[J].Soil Science Society of America Journal,1989,53(3):653-660.
[9] 石辉, 陈凤琴, 刘世荣. 岷江上游森林土壤大孔隙特征及其对水分出流速率的影响[J]. 生态学报, 2005, 25(3): 507-512.
[10]吴华山, 陈效民, 陈粲. 利用 CT 扫描技术对太湖地区主要水稻土中大孔隙的研究[J]. 水土保持学报, 2007, 21(2): 175-178.
[11]时忠杰, 王彦辉, 徐丽宏, 等. 六盘山典型植被下土壤大孔隙特征[J]. 应用生态学报, 2007, 18(12): 2675-2680.
[12]曾强, 徐则民, 官琦, 等. 不同植被条件下斜坡土体大孔隙特征分析[J]. 岩石力学与工程学报, 2016, 35(增刊1):3343-3352.
[13]EHLER W. Observation on Earthworm Channels and Infiltration on Tilled and Untilled Loess Soil[J]. Soil Science, 1975, 119(3): 242-249.
[14]冯杰, 郝振纯. CT扫描确定土壤大孔隙分布[J]. 水科学进展, 2002,13(5): 611-617.
[15]高宙,胡霞.基于CT扫描研究灌丛根系对土壤大孔隙的影响[J].水土保持研究,2020,27(3):315-319.
[16]鞠忻倪, 贾玉华, 甘淼, 等. 黄土沟壑区不同地形部位土壤大孔隙特征研究[J]. 土壤学报, 2018, 55(5): 1098-1107.
[17]蔡沛辰,阙云,李显.围压条件下原状花岗岩残积土细观渗流数值模拟[J].福州大学学报:自然科学版,2021,49(3):400-406.
[18]蔡园园, 房怀英, 余文, 等. 采用数字图像处理的机制砂粒度级配检测方法[J]. 华侨大学学报:自然科学版, 2019, 40(5): 567-573.
[19]李伟莉, 金昌杰, 王安志, 等. 长白山北坡两种类型森林土壤的大孔隙特征[J]. 应用生态学报, 2007, 18(6): 1213-1218.
[20]冯杰, 于纪玉. 利用CT扫描技术确定土壤大孔隙分形维数[J]. 灌溉排水学报, 2005, 24(4): 26-28,40.
[21]张丽萍, 陈儒章, 邬燕虹, 等. 风化花岗岩坡地土壤剖面大孔隙特性的空间分布[J]. 土壤学报, 2018, 55(3): 620-632.
[22]ZHANG Z B, PENG X, ZHOU H, et al. Characterizing Preferential Flow in Cracked Paddy Soils Using Computed Tomography and Breakthrough Curve[J]. Soil & Tillage Research, 2015, 146: 53-65.