Skip to main content

Advertisement

SpringerLink
Log in

Geospatial-based approach for susceptibility assessment of expansive soils using a new multicriteria classification model

  • Original Paper
  • Published:
Arabian Journal of Geosciences Aims and scope Submit manuscript

Abstract

Geotechnical spatial distribution was applied using the geostatistical interpolation approach to improve the accuracy of spatial prediction of geotechnical data throughout the study area and characterize the expansive soil for highways and structure projects. The cross-validation method was used to calibrate the digital models (DM) and to determine their level of accuracy, during the process of establishing the optimal geotechnical classification strategy through 187 samples, including their water content (w), dry bulk density (γd), plasticity index (PI), methylene blue value (MBV), carbonate content (CaCO3), and free swelling pressure (Ps). The spatial interpolation was performed by applying sequential spherical, Gaussian, and exponential simulations. Following calibration, a new multicriteria soil classification (MSC) formula was developed using a statistical approach to estimate the classes of expansive soil susceptibility indirectly. The susceptibility (DM) indicated a high correlation coefficient (R2) of 0.99. A susceptibility map was created based on the new developed formula, and it revealed that the study area could be divided into four principal parts: extremely susceptible, susceptible, moderate, and safe. The swelling soil associated with prospective pavements and building damage can be estimated based on spatial zoning maps considering geotechnical and geological parameters and comparing the spatial correlations of geotechnical site classes. These maps could develop soil improvement strategies in civil and geotechnical engineering fields.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7

Similar content being viewed by others

Data availability

The data presented in this study are available from the corresponding author.

References

  • Achour Y, Boumezbeur A, Hadji R, Chouabbi A, Cavaleiro V, Bendaoud EA (2017) Landslide susceptibility mapping using analytic hierarchy process and information value methods along a highway road section in Constantine, Algeria. Arab J Geosci 10. https://doi.org/10.1007/s12517-017-2980-6

  • Adam J, Saleh S, Olowosulu AT et al (2018) Mapping of soil properties using geographical information system (GIS ): a case study of Hassan Usman Katsina Polytechnic. Open J Civ Eng 8:544–554. https://doi.org/10.4236/ojce.2018.84039

    Article  Google Scholar 

  • Al-Mukhtar M, Lasledj A, Alcover JF (2010) Behaviour and mineralogy changes in lime-treated expansive soil at 20° C. Appl Clay Sci 50:191–198

    Article  Google Scholar 

  • Allo OJ, Ayolabi EA, Oladele S (2019) Investigation of near-surface structures using seismic refraction and multi-channel analysis of surface waves methods — a case study of the University of Lagos main campus. Arab J Geosci 12:257. https://doi.org/10.1007/s12517-019-4397-x

    Article  Google Scholar 

  • Anis Z, Wissem G, Riheb H et al (2019) Effects of clay properties in the landslides genesis in flysch massif: case study of Aïn Draham, North Western Tunisia. J African Earth Sci 151:146–152. https://doi.org/10.1016/j.jafrearsci.2018.12.005

    Article  Google Scholar 

  • Arétouyap Z, Njandjock Nouck P, Nouayou R, Ghomsi Kemgang FE, Piépi Toko AD, Asfahani J (2016) Lessening the adverse effect of the semivariogram model selection on an interpolative survey using kriging technique. Springerplus 5. https://doi.org/10.1186/s40064-016-2142-4

  • ASTM D2487–11 (2011) Standard practice for classification ofsoils for engineering purposes (unified soil classificationsystem). Annual Book of ASTM Standards, ASTM International,West Conshohocken

  • Blés JL, Fleury JJ (1970) Carte géologique de l’Algérie au 1/50000, feuille n_178, Morsott, avec notice explicative détaillée. Service de cartes Géologique et Sonatrach, Division d’hydrocarbure. Direction des explorations, Alger

  • Belkhiri L, Tiri A, Mouni L (2020) Spatial distribution of the groundwater quality using kriging and Co-kriging interpolations. Groundw Sustain Dev 11:100473. https://doi.org/10.1016/j.gsd.2020.100473

    Article  Google Scholar 

  • Bencharef MH, Boubaya D, Aboud E, Ayfer S (2022) Role of an advanced gravity data analysis in improving the geologic understanding of the northern Tebessa region, Northeastern Algeria. J Afr Earth Sci 104693. https://doi.org/10.1016/j.jafrearsci.2022.104693

  • BS EN ISO 17892–5 (2017) Geotechnical investigation and testing. Laboratory testing of soil - Part 5: Incremental loading oedometer test

  • Cawley GC, Talbot NLC (2010) On over-fitting in model selection and subsequent selection bias in performance evaluation. J Mach Learn Res 11:2079–2107

    Google Scholar 

  • Concha-Riedel J, Antico FC, López-Querol S (2021) Mechanical strength, mass loss and volumetric changes of drying adobe matrices combined with kaolin and fine soil particles. Constr Build Mater 312:125246. https://doi.org/10.1016/j.conbuildmat.2021.125246

    Article  Google Scholar 

  • Chen FH (1988) Foundations on expansive soils. American Elsevier Sci. Pub. Com, New York

  • Dahoua L, Usychenko O, Savenko VY, Hadji R (2018) Mathematical approach for estimating the stability of geotextile-reinforced embankments during an earthquake. Min Sci 25:207–217

    Google Scholar 

  • Dahoua L, Yakovitch SV, Hadji R, Farid Z (2017) Landslide susceptibility mapping using analytic hierarchy process method in BBA-Bouira Region, case study of east-west highway, NE Algeria. In: Kallel A., Ksibi M., Ben Dhia H., Khélifi N. (eds) Recent Advances in Environmental Science from the Euro-Mediterranean and Surrounding Regions. EMCEI 2017. Advances in Science, Technology & Innovation (IEREK Interdisciplinary Series for Sustainable Development). Springer, Cham

  • Djellali A, Ounis A, Saghafi B (2013) Behavior of flexible pavements on expansive soils. Int J Transp Eng 1:1–16

    Google Scholar 

  • Djellali A, Houam A, Saghafi B et al (2017a) Static analysis of flexible pavements over expansive soils. Int J CivEng 15:391. https://doi.org/10.1007/s40999-016-0058-6

    Article  Google Scholar 

  • Djellali A, Houam A, Saghafi B (2017b) Indirect estimation of swelling pressure of clayey subgrade under pavement structures. Arab J Sci Eng 42:3991. https://doi.org/10.1007/s13369-017-2546-7

    Article  Google Scholar 

  • Diodato N, Esposito L, Bellocchi G, Vernacchia L, Fiorillo F, Guadagno FM (2013) Assessment of the spatial uncertainty of nitrates in the aquifers of the Campania plain (Italy). Am J Clim Change 2:128–137. https://doi.org/10.4236/ajcc.2013.22013

    Article  Google Scholar 

  • Doostmohammadi M, Jafari A, Asghari O (2014) Geostatistical modeling of uniaxial compressive strength along the axis of the Behesht-Abad tunnel in Central Iran. Bull Eng Geol Environ 74(3):789–802

    Article  Google Scholar 

  • El Mekki A, Hadji R, Chemseddine F (2017) Use of slope failures inventory and climatic data for landslide susceptibility, vulnerability, and risk mapping in souk Ahras region. Min Sci 24:237–249

    Google Scholar 

  • EN ISO 10693 (2014) Soil quality - determination of carbonate content - volumetric method (ISO 10693:1995)

  • EN ISO 17892–12 (2018) Geotechnical investigation and testing - laboratory testing of soil - part 12: determination of liquid and plastic limits (ISO 17892–12:2018)

  • EN 17542–3 (2020) Earthworks - geotechnical laboratory tests - part 3: methylene blue value VBS on soils and rocks

  • Fehdi C, Rouabhia A, Mechai A et al (2014) Hydrochemical and microbiological quality of groundwater in the Merdja area, Tébessa, North-East of Algeria. Appl Water Sci. https://doi.org/10.1007/s13201-014-0209-3

    Article  Google Scholar 

  • Gangodagamage C, Zhou X, Lin H (2008) Autocorrelation, spatial. In: Shekhar S, Xiong H (eds) Encyclopedia of GIS. Springer, Boston

    Google Scholar 

  • Garnero G, Godone D (2013) Comparisons between different interpolation techniques. Int Arch Photogramm Remote Sens Spat Inf Sci - ISPRS Arch 40:139–144. https://doi.org/10.5194/isprsarchives-XL-5-W3-139-2013

    Article  Google Scholar 

  • GTR (2000) Guide technique pour la réalisation des remblais et des couches de forme. Edition du SETRA-LCPC, Bagneux, Fascicule I&II, Paris

  • Hadji R, Limani Y, Boumazbeur A, DemdoumA ZK, Zahri F, Chouabi A (2014) Climate change and their influence on shrinkage - swelling clays susceptibility in a semi - arid zone: a case study of Souk Ahras municipality, NE-Algeria. Desalin Water Treat 52(10–12):2057–2072

    Article  Google Scholar 

  • Hadji R, Chouabi A, Gadri L et al (2016) Application of linear indexing model and GIS techniques for the slope movement susceptibility modeling in Bousselam upstream basin, Northeast Algeria. Arab J Geosci 9:192. https://doi.org/10.1007/s12517-015-2169-9

    Article  Google Scholar 

  • Hadji R, Rais K, Gadri L, Chouabi A, Hamed Y (2017) Slope failure characteristics and slope movement susceptibility assessment using GIS in a medium scale: a case study from Ouled Driss and Machroha municipalities, northeast Algeria. Arab J Sci Eng 42:281–300. https://doi.org/10.1007/s13369-016-2046-1

    Article  Google Scholar 

  • Hamad A, Hadji R, Bâali F et al (2018) Conceptual model for karstic aquifers by combined analysis of GIS, chemical, thermal, and isotopic tools in Tuniso-Algerian transboundary basin. Arab J Geosci 11:409. https://doi.org/10.1007/s12517-018-3773-2

    Article  Google Scholar 

  • Hosseini E, Gholami R, Hajivand F (2018) Geostatistical modeling and spatial distribution analysis of porosity and permeability in the Shurijeh-B reservoir of Khangiran gas field in Iran. J Pet Explor Prod Technol 9(2):1051–1073. https://doi.org/10.1007/s13202-018-0587-4

    Article  Google Scholar 

  • Houmadi Y, Mohammed S, Mamoune A, Belakhdar K (2009) Swelling and geotechnical cartography of Saida soils. Jordan J Civ Eng 3:32–40

    Google Scholar 

  • Ilori AO (2019) Extracting some soil parameters and estimating elastic settlements from Direct shear box data for a granular C- Ø soil. SN Appl Sci 1(10):1–13. https://doi.org/10.1007/s42452-019-1347-x

    Article  Google Scholar 

  • ISO 17892–1 (2004) Geotechnical investigation and testing — laboratory testing of soil — part 1: determination of water content

  • ISO 17892–2 (2004) Geotechnical investigation and testing — laboratory testing of soil — part 2: determination of dry bulk density

  • Kearsey T, Williams J, Finlayson A, Williamson P, Dobbs M, Marchant B, Kingdon A, Campbell D (2015) Testing the application and limitation of stochastic simulations to predict the lithology of glacial and fluvial deposits in Central Glasgow. UK Eng Geol 187:98–112

    Article  Google Scholar 

  • Karim Z, Hadji R, Hamed Y (2019) GIS-based approaches for the landslide susceptibility prediction in Setif Region (NE Algeria). Geotech Geol Eng 37:359–374. https://doi.org/10.1007/s10706-018-0615-7

    Article  Google Scholar 

  • Kim HS, Kim HK (2019) Optimizing site-specific geostatistics to improve geotechnical spatial information in Seoul, South Korea. Arab J Geosci 12:104. https://doi.org/10.1007/s12517-018-4171-5

    Article  Google Scholar 

  • Kim M, Kim HS, Chung CK (2020) A three-dimensional geotechnical spatial modeling method for borehole dataset using optimization of geostatistical approaches. KSCE J Civ Eng 24:778–793. https://doi.org/10.1007/s12205-020-1379-1

    Article  Google Scholar 

  • King J, Mulder T, Essink GO, Bierkens MFP (2022) Joint estimation of groundwater salinity and hydrogeological parameters using variable-density groundwater flow, salt transport modelling and airborne electromagnetic surveys. Adv Water Resour 160:104118. https://doi.org/10.1016/j.advwatres.2021.104118

    Article  Google Scholar 

  • Krige DG (1951) A statistical approach to some basic mine valuation problems on theWitwatersrand. J Chem Metall Min Eng Soc S Afr 52(6):119–139

    Google Scholar 

  • Lan TN (1977) Nouvel essai d’identification des sols : l’essai au bleu de méthylène. Bull LPC 88:136–137

    Google Scholar 

  • Liu WF, Leung YF, Lo MK (2017) Integrated framework for characterization of spatial variability of geological profiles. Can Geotech J 54(1):47–58

    Article  Google Scholar 

  • Manchar N, Benabbas C, Hadji R, Bouaicha F, Grecu F (2018) Landslide susceptibility assessment in Constantine Region (NE Algeria) by means of statistical models. Studia Geotechnica Et Mechanica 40(3):208–219

    Article  Google Scholar 

  • Mendes A, Galvão P, de Sousa J et al (2019) Relations of the groundwater quality and disorderly occupation in an Amazon low-income neighborhood. Environ Dev Sustain 21:353–368. https://doi.org/10.1007/s10668-017-0040-8

    Article  Google Scholar 

  • Mitchell JK, Soga K (2005) Fundamentals of soil behaviour, 3rd edn. Wiley, Hoboken

    Google Scholar 

  • Ncibi K, Chaar H, Hadji R, Baccari N, Sebei A, Khelifi F, ... Hamed Y (2020) A GIS-based statistical model for assessing groundwater susceptibility index in shallow aquifer in Central Tunisia (Sidi Bouzid basin). Arab J Geosci 13(2): 98

  • Nekkoub A, Baali F, Hadji R, Hamed Y (2020) The EPIK multi-attribute method for intrinsic vulnerability assessment of karstic aquifer under semi-arid climatic conditions, case of Cheria Plateau, NE Algeria. Arab J Geosci 13(15):1–15

    Article  Google Scholar 

  • Pająk M, Halecki W, Gąsiorek M (2017) Accumulative response of Scots pine (Pinus sylvestris L.) and silver birch (Betula pendula Roth) to heavy metals enhanced by Pb-Zn ore mining and processing plants: explicitly spatial considerations of ordinary kriging based on a GIS approach. Chemosphere 168:851–859. https://doi.org/10.1016/j.chemosphere.2016.10.125

    Article  Google Scholar 

  • Qi X, Liu H (2019) An improved global zonation method for geotechnical parameters. Eng Geol 248:185–196. https://doi.org/10.1016/j.enggeo.2018.11.013

    Article  Google Scholar 

  • Sacks J, Schiller S (1988) Spatial designs. In: Gupta SS, Berger JO (eds) Statistical decision theory and related topics IV. Springer, New York, pp 385–399

    Chapter  Google Scholar 

  • Schenková Z, Schenk V, Kalogeras I et al (2007) Isoseismal maps drawing by the kriging method. J Seismol 11:121–129. https://doi.org/10.1007/s10950-006-9023-1

    Article  Google Scholar 

  • Seed HB, Woodward RJ, Lundgren R (1962) Prediction of swellingpotential for compacted clays. J Soil Mech Found Div ASCE 88(SM3):53–87

    Article  Google Scholar 

  • Sagar CP, Badiger M, Mamatha KH, Dinesh SV (2022) Prediction of CBR using dynamic cone penetrometer index. Mater Today Proc. https://doi.org/10.1016/j.matpr.2021.12.467

    Article  Google Scholar 

  • Takagi H, Pratama MB, Kurobe S et al (2019) Analysis of generation and arrival time of landslide tsunami to Palu City due to the 2018 Sulawesi earthquake. Landslides 16:983–991. https://doi.org/10.1007/s10346-019-01166-y

    Article  Google Scholar 

  • Tamani F, Hadji R, Hamad A, Hamed Y (2019) Integrating remotely sensed and GIS data for the detailed geological mapping in semi-arid regions: case of Youks les Bains Area, Tebessa Province, NE Algeria. Geotech Geol Eng 2. https://doi.org/10.1007/s10706-019-00807-2

  • USDA (2005) Estimating soil moisture by feel and appearance (Program Aid 1619). United. States Department of Agriculture, Natural Resource conservation service

  • Vila JM (1980) La chaîne alpine d’Algérie orientale et des confins algérotunisiens. Thèse Doctorat, Université Paris, Travaux du département de géotectonique, Laboratoire de géologie structurale, Paris 665

  • Wang X, Zhang J, Sun Y et al (2022) Stiffness identification of deteriorated PC bridges by a FEMU method based on the LM-assisted PSO-Kriging model. Structures 43:374–387. https://doi.org/10.1016/j.istruc.2022.06.060

    Article  Google Scholar 

  • Wang Y, Akeju OV, Zhao T (2017) Interpolation of spatially varying but sparsely measured geo-data: a comparative study. Eng Geol 231:200–217

    Article  Google Scholar 

  • XP P 94–091 (1995b) Sols : Essai de gonflement à l’oedomètre. Détermination des déformations par chargement de plusieurs éprouvettes. Normalisation Française

  • Yang S, Kang Y-E, Yee K (2023) Multi-fidelity modeling via regression-based hierarchical kriging BT - The Proceedings of the 2021 Asia-Pacific International Symposium on Aerospace Technology (APISAT 2021), Volume 1. In: Lee S, Han C, Choi J-Y, et al. (eds). Springer Nature Singapore, Singapore, pp 643–652

  • Zaltsberg E (2013) Development of regional hydrogeological mapping in Russia. Hydrogeol J 21:525–528. https://doi.org/10.1007/s10040-012-0946-z

    Article  Google Scholar 

  • Zereg S, Boudoukha A, Benaabidate L (2018) Impacts of natural conditions and anthropogenic activities on groundwater quality in Tebessa plain, Algeria. Sustain Environ Res 28:340–349. https://doi.org/10.1016/j.serj.2018.05.003

    Article  Google Scholar 

  • Zerzour O, Gadri L, Hadji R et al (2020) Semi-variograms and kriging techniques in iron ore reserve categorization: application at Jebel Wenza deposit. Arab J Geosci 13:1–10. https://doi.org/10.1007/s12517-020-05858-x

    Article  Google Scholar 

  • Zha F, Liu S, Du Y, Cui K (2008) Behavior of expansive soils stabilized with fly ash. Nat Hazards 47:509–523. https://doi.org/10.1007/s11069-008-9236-4

    Article  Google Scholar 

  • Zhang B, Wang H, Ye Y et al (2019) Potential hazards to a tunnel caused by adjacent reservoir impoundment. Bull Eng Geol Environ 78:397–415. https://doi.org/10.1007/s10064-017-1110-8

    Article  Google Scholar 

  • Zhao H, Gao Z-H, Xia L (2022) Efficient aerodynamic analysis and optimization under uncertainty using multi-fidelity polynomial chaos-Kriging surrogate model. Comput Fluids 246:105643. https://doi.org/10.1016/j.compfluid.2022.105643

    Article  Google Scholar 

  • Zymnis DM, Whittle AJ, Cheng X (2019) Simulation of long-term thermo-mechanical response of clay using an advanced constitutive model. Acta Geotech 14:295. https://doi.org/10.1007/s11440-018-0726-6

    Article  Google Scholar 

Download references

Acknowledgements

The Environmental Laboratory, Larbi Tebessi University, Algeria, supported this study. The authors wish to thank the anonymous reviewers for their valuable comments on the manuscript. The authors are indebted to the LTP Est laboratory, Tebessa, Algeria, for help in analyzing soil samples.

Author information

Authors and Affiliations

  1. Environmental Laboratory, Mining Institute, Echahid Cheikh Larbi Tebessi University, 12002, Tebessa, Algeria

    Adel Djellali, Zied Benghazi & Khaled Rais

  2. Department of Civil Engineering, Texas State University, San Marcos, Texas, 78666, USA

    Debojit Sarker

Authors
  1. Adel Djellali
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Debojit Sarker
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Zied Benghazi
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Khaled Rais
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Adel Djellali.

Ethics declarations

Conflict of interest

The authors declare that they have no competing interests.

Additional information

Responsible Editor: Zeynal Abiddin Erguler

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Djellali, A., Sarker, D., Benghazi, Z. et al. Geospatial-based approach for susceptibility assessment of expansive soils using a new multicriteria classification model. Arab J Geosci 15, 1742 (2022). https://doi.org/10.1007/s12517-022-11024-2

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s12517-022-11024-2

Keywords

Search

Navigation