Quantification of macropores of Malan loess and the hydraulic significance on slope stability by X-ray computed tomography Original Article First Online: 13 August 2019 Abstract
The accurate identification and quantitative characterization of loess structural properties at the pore scale are important in the study of macroscopic permeability. To characterise the macropore structure of Malan loess systematically, a non-destructive detecting method, that is, X-ray computed tomography (CT), was adopted for scanning five undisturbed specimens. A series of processing steps, including image filtering by a novel compositing image filter, image segmentation with the effective combination of threshold and top hat method, and three-dimensional (3D) reconstruction and visualisation by marching cube algorithm and volume-rendering technique were finished in AVIZO
® software to acquire the 3D pore network model and to extract the two-dimensional (2D) and 3D structural parameters, such as porosity, equal diameter, aspect ratio, shape factor (SF), node density, number of terminal and branching nodes, coordinate number, dip angle, dip direction angle and tortuosity. Results show that (1) Malan loess is a kind of porous geological material with strong verticality and spatial anisotropy reflected by the 2D parameters including porosity, equal diameters and aspect ratio as well as the 3D dip angle and 3D-visualised loess macropores; (2) Malan loess has higher permeability in the vertical direction than that in the horizontal direction so that prone to induce excessive infiltration and preferential flow, thereby threatening the loess slope stability; (3) SF is an effective parameter for pore classification in both 2D and 3D scales; (4) the macropores with a large diameter have a larger volume fraction, better connectivity (effective porosity) and greater contribution to water permeability; (5) the larger the coordinate number, the greater the hydraulic conductivity, nevertheless other than the aggregates for the water repellency caused by organic matter. In conclusion, the combination of CT and AVIZO ® is excellent for quantifying the key macropore structural parameters (e.g., shape factor and tortuosity) and their hydraulic significance on slope stability. Keywords Malan loess Macropore X-ray computed tomography 3D structural model Shape factor Tortuosity Preferential flow Notes Acknowledgements
This research was supported by the National Natural Science Foundation of China (Grant number: 41630634) and the Major Research Project for Creative Group of Guizhou Provincial Department of Education (Grant numbers QJH-KY 054 and QJH-KY 055).
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Artur D, Zbigniew K, Maciej M (2011) Hydraulic tortuosity in arbitrary porous media flow. Phys Rev E Stat Nonlinear Softw Matter Phys 84:036319.
https://doi.org/10.1103/PhysRevE.84.036319 CrossRef Google Scholar
Beckers E, Plougonven E, Roisin C, Hapca S, Léonard A, Degré A (2014) X-ray microtomography: a porosity-based thresholding method to improve soil pore network characterization? Geoderma 219–220:145–154.
https://doi.org/10.1016/j.geoderma.2014.01.004 CrossRef Google Scholar
Boudreau BP, Meysman FJR (2006) Predicted tortuosity of muds. Geology 34:693–696.
https://doi.org/10.1130/g22771.1 CrossRef Google Scholar
Calistru AE, JităReanu G (2015) Applications of X-ray computed tomography for examining soil structure: a review. Bull Univ Agric Sci Vet Med Cluj-Napoca Agric 72:30–36.
https://doi.org/10.15835/buasvmcn-agr:11145 CrossRef Google Scholar
Carey GR, McBean EA, Feenstra S (2016) Estimating tortuosity coefficients based on hydraulic conductivity. Groundwater 54:476–487.
https://doi.org/10.1111/gwat.12406 CrossRef Google Scholar
Carmignato S, Dewulf W, Leach R (2018) Industrial X-ray computed tomography. Springer International Publishing, Cham.
https://doi.org/10.1007/978-3-319-59573-3 CrossRef Google Scholar
Chen T, Xie Q, Xu H, Chen J, Ji J, Lu H, Balsam W (2010) Characteristics and formation mechanism of pedogenic hematite in Quaternary Chinese loess and paleosols. CATENA 81:217–225.
https://doi.org/10.1016/j.catena.2010.04.001 CrossRef Google Scholar
Chen G, Meng X, Qiao L, Zhang Y, Wang S (2018) Response of a loess landslide to rainfall: observations from a field artificial rainfall experiment in Bailong River Basin, China. Landslides 15:1–17.
https://doi.org/10.1007/s10346-017-0924-6 CrossRef Google Scholar
China SAotPsRo (2008) Pore size distribution and porosity of solid materials by mercury porosimetry and gas adsorption—part 1: mercury porosimetry. Standards Press of China, Beijing
Cnudde V, Boone MN (2013) High-resolution X-ray computed tomography in geosciences: a review of the current technology and applications. Earth Sci Rev 123:1–17.
https://doi.org/10.1016/j.earscirev.2013.04.003 CrossRef Google Scholar
Cristiano E, Bogaard T, Barontini S (2016) Effects of anisotropy of preferential flow on the hydrology and stability of landslides. Proc Earth Planet Sci 16:204–214.
https://doi.org/10.1016/j.proeps.2016.10.022 CrossRef Google Scholar
Deng J, Wang LM, Zhang ZZ, Bing H (2010) Microstructure characteristics and forming environment of late Quaternary Period loess in the Loess Plateau of China. Environ Earth Sci 59:1807–1817.
https://doi.org/10.1007/s12665-009-0162-x CrossRef Google Scholar
Elliot TR, Reynolds WD, Heck RJ (2010) Use of existing pore models and X-ray computed tomography to predict saturated soil hydraulic conductivity. Geoderma 156:133–142.
https://doi.org/10.1016/j.geoderma.2010.02.010 CrossRef Google Scholar
FEI, Sas (2016) Avizo
920 User’s Guide. FEI, Berlin
Gao G (1980) Chinese loess microstructure. Chin Sci Bull 25:945–948.
https://doi.org/10.1360/csb1980-25-20-945 (in Chinese)
CrossRef Google Scholar
Gharedaghloo B, Price JS, Rezanezhad F, Quinton WL (2018) Evaluating the hydraulic and transport properties of peat soil using pore network modeling and X-ray micro computed tomography. J Hydrol 561:494–508.
https://doi.org/10.1016/j.jhydrol.2018.04.007 CrossRef Google Scholar
Goldstein L, Prasher SO, Ghoshal S (2007) Three-dimensional visualization and quantification of non-aqueous phase liquid volumes in natural porous media using a medical X-ray Computed Tomography scanner. J Contam Hydrol 93:96–110.
https://doi.org/10.1016/j.jconhyd.2007.01.013 CrossRef Google Scholar
Guo P (2012) Dependency of tortuosity and permeability of porous media on directional distribution of pore voids. Transp Porous Media 95:285–303.
https://doi.org/10.1007/s11242-012-0043-8 CrossRef Google Scholar
Ichikawa K, Kawashima H, Shimada M, Adachi T, Takata T (2019) A three-dimensional cross-directional bilateral filter for edge-preserving noise reduction of low-dose computed tomography images. Comput Biol Med.
https://doi.org/10.1016/j.compbiomed.2019.103353 CrossRef Google Scholar
Ivanov AL, Shein EV, Skvortsova EB (2019) Tomography of soil pores: from morphological characteristics to structural-functional assessment of pore space. Eurasian Soil Sci 52:50–57.
https://doi.org/10.1134/S106422931901006X CrossRef Google Scholar
Jiang J, Wei X, Zhang X (2011) Research on mechanical parameters of intact sliding zone soils of Huangtupo landslide based on CT scanning and simulation tests. Chin J Rock Mech Eng 25:438–439 doi:
http://www.rockmech.org/CN/Y2011/V30/I5/1025 (in Chinese)
Jiang M, Zhang F, Hu H, Cui Y, Peng J (2014) Structural characterization of natural loess and remolded loess under triaxial tests. Eng Geol 181:249–260.
https://doi.org/10.1016/j.enggeo.2014.07.021 CrossRef Google Scholar
Jiang M, Sima J, Cui Y, Hu H, Zhou C, Lei H (2017) Experimental investigation of the deformation characteristics of natural loess under the stress paths in shield tunnel excavation. Int J Geomech 17:1–10.
https://doi.org/10.1061/(ASCE)GM.1943-5622.0000972 CrossRef Google Scholar
Karpyn ZT, Alajmi A, Radaelli F, Halleck PM, Grader AS (2009) X-ray CT and hydraulic evidence for a relationship between fracture conductivity and adjacent matrix porosity. Eng Geol 103:139–145.
https://doi.org/10.1016/j.enggeo.2008.06.017 CrossRef Google Scholar
Koponen A, Kataja M, Timonen J (1996) Tortuous flow in porous media. Phys Rev E Stat Phys Plasmas Fluids Relat Interdiscip Top 54:406–410.
https://doi.org/10.1103/PhysRevE.54.406 CrossRef Google Scholar
Landis EN, Keane DT (2010) X-ray microtomography. Mater Charact 61:1305–1316
CrossRef Google Scholar
Lanfrey PY, Kuzeljevic ZV, Dudukovic MP (2010) Tortuosity model for fixed beds randomly packed with identical particles. Chem Eng Sci 65:1891–1896.
https://doi.org/10.1016/j.ces.2009.11.011 CrossRef Google Scholar
Latifi N, Eisazadeh A, Marto A, Meehan CL (2017a) Tropical residual soil stabilization: a powder form material for increasing soil strength. Constr Build Mater 147:827–836.
https://doi.org/10.1016/j.conbuildmat.2017.04.115 CrossRef Google Scholar
Latifi N, Vahedifard F, Ghazanfari E, Horpibulsuk S, Marto A, Williams J (2017b) Sustainable improvement of clays using low-carbon nontraditional additive. Int J Geomech 18:04017162.
https://doi.org/10.1061/(ASCE)GM.1943-5622.0001086 CrossRef Google Scholar
Latifi N, Vahedifard F, Ghazanfari E, Rashid ASA (2018) Sustainable usage of calcium carbide residue for stabilization of clays. J Mater Civ Eng 30:04018099.
https://doi.org/10.1061/(ASCE)MT.1943-5533.0002313 CrossRef Google Scholar
Lei S, Tang W (2004) Analysis of Microstructure Change for Loess in the Process of Loading and Collapse with CT Scanning. Chin J Rock Mech Eng 23:4166–4169.
https://doi.org/10.3321/j.issn:1000-6915.2004.24.013 (in Chinese)
CrossRef Google Scholar
Leue M, Uteau-Puschmann D, Peth S, Nellesen J, Kodešová R, Gerke HH (2019) Separation of soil macropore types in three-dimensional X-ray computed tomography images based on pore geometry characteristics. Vadose Zone J.
https://doi.org/10.2136/vzj2018.09.0170 CrossRef Google Scholar
Li Y (1990) Quantitative analysis on Luochuan loess porosity using micropicture and microcomputer. Site Investig Sci Technol 8:6–9
Li XA, Li L (2017) Quantification of the pore structures of Malan loess and the effects on loess permeability and environmental significance, Shaanxi Province, China: an experimental study. Environ Earth Sci 76:522–535.
https://doi.org/10.1007/s12665-017-6855-7 CrossRef Google Scholar
Li X, Zhang D (1999) Application of CT in analysis of structure of compacted soil. Rock Soil Mech 20:62–66.
https://doi.org/10.16285/j.rsm.1999.02.014 (in Chinese)
CrossRef Google Scholar
Li Y, Zhao J (2017) Loess and Loess Geohazards in China. CRC Press, London.
https://doi.org/10.1201/9781315177281 CrossRef Google Scholar
Li J, Chen Z, Huang X (2010) CT-triaxial test for collapsability of undisturbed Q3 loess. Chin J Rock Mech Eng 29:1288–1296.
http://www.rockmech.org/CN/Y2010/V29/I06/1288 (in Chinese)
Li TC, Shao MA, Jia YH (2016) Application of X-ray tomography to quantify macropore characteristics of loess soil under two perennial plants. Eur J Soil Sci 67:266–275.
https://doi.org/10.1111/ejss.12330 CrossRef Google Scholar
Li T, Ma Shao, Jia Y, Jia X, Huang L (2018a) Using the X-ray computed tomography method to predict the saturated hydraulic conductivity of the upper root zone in the Loess Plateau in China. Soil Sci Soc Am J.
https://doi.org/10.2136/sssaj2017.08.0268 CrossRef Google Scholar
Li X, Lu Y, Zhang X, Lu Y, Yang Y (2018b) Pore-fissure identification and characterization of paleosol based on X-ray computed tomography. Bull Soil Water Conserv 38:224–230.
https://doi.org/10.13961/j.cnki.stbctb.20181024.001 (in Chinese)
CrossRef Google Scholar
Li Y, He S, Deng X, Xu Y (2018c) Characterization of macropore structure of Malan loess in China based on 3D pipe models constructed by using computed tomography technology. J Asian Earth Sci 154:271–279.
https://doi.org/10.1016/j.jseaes.2017.12.028 CrossRef Google Scholar
Li Y, Zhang T, Zhang Y, Xu Q (2018d) Geometrical appearance and spatial arrangement of structural blocks of the Malan loess in NW China and the implications for the formation of loess columns. J Asian Earth Sci 158:18–28.
https://doi.org/10.1016/j.jseaes.2018.02.007 CrossRef Google Scholar
Li P, Xie W, Pak RYS, Vanapalli SK (2019a) Microstructural evolution of loess soils from the Loess Plateau of China. CATENA 173:276–288.
https://doi.org/10.1016/j.catena.2018.10.006 CrossRef Google Scholar
Li X, Lu Y, Fan W, Pan W, Zhang X, Lu Y (2019b) Current status and prospects of research on mechanism of preferential flow-induced sliding in loess slope. Bull Soil Water Conserv 39:294–301+324.
https://doi.org/10.13961/j.cnki.stbctb.2019.01.046 (in Chinese)
CrossRef Google Scholar
Lipiec J, Turski M, Ma Hajnos, Wieboda R (2015) Pore structure, stability and water repellency of earthworm casts and natural aggregates in loess soil. Geoderma 243–244:124–129.
https://doi.org/10.1016/j.geoderma.2014.12.026 CrossRef Google Scholar
Liu Z et al (2015) Collapsibility, composition, and microstructure of loess in China. Can Geotech J 53:673–686.
https://doi.org/10.1139/cgj-2015-0285 CrossRef Google Scholar
Liu XM, Mingming MA, Haibin WU, Zhou ZB (2017) Identification of aeolian loess deposits on the Indo-Gangetic Plain (India) and their significance. Sci China Earth Sci 60:428.
https://doi.org/10.1007/s11430-016-5167-1 CrossRef Google Scholar
Luo L, Lin H, Halleck P (2008) Quantifying soil structure and preferential flow in intact soil using X-ray computed tomography. Soil Sci Soc Am J 72:1058–1069.
https://doi.org/10.2136/sssaj2007.0179 CrossRef Google Scholar
Luo L, Lin H, Li S (2010a) Quantification of 3-D soil macropore networks in different soil types and land uses using computed tomography. J Hydrol 393:53–64.
https://doi.org/10.1016/j.jhydrol.2010.03.031 CrossRef Google Scholar
Luo LF, Lin H, Schmidt J (2010b) Quantitative relationships between soil macropore characteristics and preferential flow and transport. Soil Sci Soc Am J 74:1929–1937.
https://doi.org/10.2136/sssaj2010.0062 CrossRef Google Scholar
Luo H, Wu F, Chang J, Xu J (2018) Microstructural constraints on geotechnical properties of Malan Loess: a case study from Zhaojiaan landslide in Shaanxi province, China. Eng Geol 236:60–69.
https://doi.org/10.1016/j.enggeo.2017.11.002 CrossRef Google Scholar
Maciej M, Arzhang K, Zbigniew K (2008) Tortuosity-porosity relation in porous media flow. Phys Rev E Stat Nonlinear Softw Matter Phys 78:026306.
https://doi.org/10.1103/PhysRevE.78.026306 CrossRef Google Scholar
Manickam SS, Gelb J, McCutcheon JR (2014) Pore structure characterization of asymmetric membranes: non-destructive characterization of porosity and tortuosity. J Membr Sci 454:549–554.
https://doi.org/10.1016/j.memsci.2013.11.044 CrossRef Google Scholar
Muhammad N, Siddiqua S, Latifi N (2018) Solidification of subgrade materials using magnesium alkalinization: a sustainable additive for construction. J Mater Civ Eng 30:04018260.
https://doi.org/10.1061/(ASCE)MT.1943-5533.0002484 CrossRef Google Scholar
Olsen PA, Binley A, Henry-Poulter S, Tych W (2015) Characterizing solute transport in undisturbed soil cores using electrical and X-ray tomographic methods. Hydrol Process 13:211–221.
https://doi.org/10.1002/(sici)1099-1085(19990215)13:2%3c211:aid-hyp707%3e3.0.co;2-p CrossRef Google Scholar
Pawlowski S, Nayak N, Meireles M, Portugal CAM, Velizarov S, Crespo JG (2018) CFD modelling of flow patterns, tortuosity and residence time distribution in monolithic porous columns reconstructed from X-ray tomography data. Chem Eng J 350:757–766.
https://doi.org/10.1016/j.cej.2018.06.017 CrossRef Google Scholar
Pot V et al (2015) Three-dimensional distribution of water and air in soil pores: comparison of two-phase two-relaxation-times lattice-Boltzmann and morphological model outputs with synchrotron X-ray computed tomography data. Adv Water Resour 84:87–102.
https://doi.org/10.1016/j.advwatres.2015.08.006 CrossRef Google Scholar
Saboorian-Jooybari H, Ashoori S, Mowazi G (2012) Development of an analytical time-dependent matrix/fracture shape factor for countercurrent imbibition in simulation of fractured reservoirs. Transport Porous Media 92:10.
https://doi.org/10.1007/s11242-011-9928-1 CrossRef Google Scholar
Saravanathiiban DS, Kutay ME, Khire MV (2014) Effect of macropore tortuosity and morphology on preferential flow through saturated soil: a Lattice Boltzmann study. Comput Geotech 59:44–53.
https://doi.org/10.1016/j.compgeo.2014.02.006 CrossRef Google Scholar
Schmitt M, Halisch M, Müller C, Fernandes CP (2016) Classification and quantification of pore shapes in sandstone reservoir rocks with 3-D X-ray micro-computed tomography. Solid Earth 7:285–300.
https://doi.org/10.5194/se-7-285-2016 CrossRef Google Scholar
Shanti NO, Chan VWL, Stock SR, Carlo FD, Thornton K, Faber KT (2014) X-ray micro-computed tomography and tortuosity calculations of percolating pore networks. Acta Mater 71:126–135.
https://doi.org/10.1016/j.actamat.2014.03.003 CrossRef Google Scholar
Shao W (2017) Numerical modeling of the effect of preferential flow on hillslope hydrology and slope stability. Doctoral thesis, Delft University of Technology.
Taina IA, Heck RJ, Elliot TR (2008) Application of x-ray computed tomography to soil science: a literature review. Can J Soil Sci 88:1–19.
https://doi.org/10.4141/CJSS06027 CrossRef Google Scholar
Wang ZY, Xu Q, Ni WK (2010) Study of undisturbed loess stress-strain relation during CT test. Rock Soil Mech 31:387–391 + 396.
https://doi.org/10.3969/j.issn.1000-7598.2010.02.010 (in Chinese)
CrossRef Google Scholar
Wang J-D, Li P, Ma Y, Vanapalli SK (2019a) Evolution of pore-size distribution of intact loess and remolded loess due to consolidation. J Soils Sediments 19:1226–1238.
https://doi.org/10.1007/s11368-018-2136-7 CrossRef Google Scholar
Wang L, Yuan K, Luan X, Li Z, Feng G, Wu J (2019b) 3D characterizations of pores and damages in C/SiC composites by using X-Ray computed tomography. Appl Compos Mater 26:493–505.
https://doi.org/10.1007/s10443-018-9712-2 CrossRef Google Scholar
Wei T, Fan W, Yuan W, Wei Y-n, Yu B (2019) Three-dimensional pore network characterization of loess and paleosol stratigraphy from South Jingyang Plateau, China. Environ Earth Sci 78:333.
https://doi.org/10.1007/s12665-019-8331-z CrossRef Google Scholar
Xu J, Li Y, Lan W, Wang S (2019) Shear strength and damage mechanism of saline intact loess after freeze-thaw cycling. Cold Reg Sci Technol 164:102779.
https://doi.org/10.1016/j.coldregions.2019.05.005 CrossRef Google Scholar
Yan G, Wei C, Song Y, Zhang J, Yang H (2018a) Quantitative Characterization of Shale Pore Structure Based on Ar-SEM and PCAS. Earth Sci 43:1602–1610.
https://doi.org/10.3799/dqkx.2017.525 CrossRef Google Scholar
Yan K, Gu TF, Wang JD, Liu YM, Wang X, Wang CX (2018b) A study of the micro-configuration of loess based on micro-CT images. Hydrogeol Eng Geol 45:71–77.
https://doi.org/10.16030/j.cnki.issn.1000-3665.2018.03.09 (in Chinese)
CrossRef Google Scholar
Yao Z, Chen Z, Li J, Wei F, Liu J (2017) Meso-structure dynamic evolution characteristic of undisturbed loess based on CT technology. Trans Chin Soc Agric Eng 10:10.
https://doi.org/10.11975/j.issn.1002-6819.2017.13.018 (in Chinese)
CrossRef Google Scholar
Yu B, Li J (2004) A geometry model for tortuosity of flow path in porous media. Chin Phys Lett 21:1569–1571.
https://doi.org/10.1088/0256-307X/21/8/044 CrossRef Google Scholar
Yu X, Peng G, Lu S (2018a) Characterizing aggregate pore structure by X-ray micro-computed tomography and a network model. Soil Sci Soc Am J 82:744–756.
https://doi.org/10.2136/sssaj2017.11.0385 CrossRef Google Scholar
Yu Y-S et al (2018b) Three-dimensional localization of nanoscale battery reactions using soft X-ray tomography. Nat Commun 9:921
CrossRef Google Scholar
Zhang J-M, Ze-min F, Ru-ji H (2017) Quantification of 3D macropore networks in forest soils in Touzhai valley (Yunnan, China) using X-ray computed tomography and image analysis. J Mountain Sci 14:474–491.
https://doi.org/10.1007/s11629-016-4150-9 CrossRef Google Scholar
Zhang X, Lu Y, Li X, Lu Y, Pan W (2019a) Microscopic structure changes of Malan loess after humidification in South Jingyang Plateau, China. Environ Earth Sci 78:287.
https://doi.org/10.1007/s12665-019-8290-4 CrossRef Google Scholar
Zhang Z, Liu K, Zhou H, Lin H, Li D, Peng X (2019b) Linking saturated hydraulic conductivity and air permeability to the characteristics of biopores derived from X-ray computed tomography. J Hydrol 571:1–10.
https://doi.org/10.1016/j.jhydrol.2019.01.041 CrossRef Google Scholar
Zhao D, Xu M, Liu G, Ma L, Zhang S, Xiao T, Peng G (2017a) Effect of vegetation type on microstructure of soil aggregates on the Loess Plateau, China. Agric Ecosyst Environ 242:1–8.
https://doi.org/10.1016/j.agee.2017.03.014 CrossRef Google Scholar
Zhao D et al (2017b) Quantification of soil aggregate microstructure on abandoned cropland during vegetative succession using synchrotron radiation-based micro-computed tomography. Soil Tillage Res 165:239–246.
https://doi.org/10.1016/j.still.2016.08.007 CrossRef Google Scholar
Zhong R, Xu M, Netto RV, Wille K (2016) Influence of pore tortuosity on hydraulic conductivity of pervious concrete: characterization and modeling. Constr Build Mater 125:1158–1168.
https://doi.org/10.1016/j.conbuildmat.2016.08.060 CrossRef Google Scholar
Zhu YQ, Chen ZH (2009) Experimental study on dynamic evolution of meso-structure of intact Q_3 loess during loading and collapse using CT and triaxial apparatus. Chin J Geotechn Eng 31:1219–1228
Zong Y, Yu X, Zhu M, Lu S (2015) Characterizing soil pore structure using nitrogen adsorption, mercury intrusion porosimetry, and synchrotron-radiation-based X-ray computed microtomography techniques. J Soils Sediments 15:302–312.
https://doi.org/10.1007/s11368-014-0995-0 CrossRef Google Scholar Copyright information
© Springer-Verlag GmbH Germany, part of Springer Nature 2019