Application of a generalised MPK model with data fusion approaches for landslide risk assessment

Chathurika Jayasundara, Ravin N. Deo, Jayantha Kodikara

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

Abstract

The constitutive modelling of unsaturated soil behaviour within the MPK framework using data fusion approaches are discussed to envisage a practical approach for the evaluation and monitoring of landslide-prone areas. The present study focuses on improvements in subsurface suction distribution estimations via electrical resistivity tomography (ERT), which can be used to generate quasi-continuous suction profiles (QCSP) for numerical modelling. An explicit petro geophysical transfer function between suction and resistivity is presented herein, which was derived from the Waxman-Smits electrical resistivity model and the Van Genuchten equation for soil water retention curves. For efficient numerical modelling, a selective correction approach (SCA) is presented for petro geophysical transfer function updating procedure. The data acquisition and analysis architecture are envisaged within a data cloud platform, which is highly attractive within the context of internet-of-things (IoT). Although the focus of this work is on suction estimations, a similar approach can be used for estimation of other constitutive variables required within the MPK framework.

Original languageEnglish
Title of host publicationInformation Technology in Geo-Engineering - Proceedings of the 3rd International Conference ICITG 2019
EditorsAntónio Gomes Correia, Joaquim Tinoco, Paulo Cortez, Luís Lamas
PublisherSpringer
Pages635-643
Number of pages9
ISBN (Print)9783030320287
DOIs
Publication statusPublished - 2020
EventInternational Conference on Information Technology in Geo-Engineering 2019 - Guimarães, Portugal
Duration: 29 Sep 20192 Oct 2019
Conference number: 3rd
http://www.3rd-icitg2019.civil.uminho.pt/

Publication series

NameSpringer Series in Geomechanics and Geoengineering
PublisherSpringer
ISSN (Print)1866-8755
ISSN (Electronic)1866-8763

Conference

ConferenceInternational Conference on Information Technology in Geo-Engineering 2019
Abbreviated titleICITG 2019
CountryPortugal
CityGuimarães
Period29/09/192/10/19
Internet address

Keywords

  • Data fusion
  • MPK framework
  • Suction

Cite this

Jayasundara, C., Deo, R. N., & Kodikara, J. (2020). Application of a generalised MPK model with data fusion approaches for landslide risk assessment. In A. G. Correia, J. Tinoco, P. Cortez, & L. Lamas (Eds.), Information Technology in Geo-Engineering - Proceedings of the 3rd International Conference ICITG 2019 (pp. 635-643). (Springer Series in Geomechanics and Geoengineering). Springer. https://doi.org/10.1007/978-3-030-32029-4_53
Jayasundara, Chathurika ; Deo, Ravin N. ; Kodikara, Jayantha. / Application of a generalised MPK model with data fusion approaches for landslide risk assessment. Information Technology in Geo-Engineering - Proceedings of the 3rd International Conference ICITG 2019. editor / António Gomes Correia ; Joaquim Tinoco ; Paulo Cortez ; Luís Lamas. Springer, 2020. pp. 635-643 (Springer Series in Geomechanics and Geoengineering).
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abstract = "The constitutive modelling of unsaturated soil behaviour within the MPK framework using data fusion approaches are discussed to envisage a practical approach for the evaluation and monitoring of landslide-prone areas. The present study focuses on improvements in subsurface suction distribution estimations via electrical resistivity tomography (ERT), which can be used to generate quasi-continuous suction profiles (QCSP) for numerical modelling. An explicit petro geophysical transfer function between suction and resistivity is presented herein, which was derived from the Waxman-Smits electrical resistivity model and the Van Genuchten equation for soil water retention curves. For efficient numerical modelling, a selective correction approach (SCA) is presented for petro geophysical transfer function updating procedure. The data acquisition and analysis architecture are envisaged within a data cloud platform, which is highly attractive within the context of internet-of-things (IoT). Although the focus of this work is on suction estimations, a similar approach can be used for estimation of other constitutive variables required within the MPK framework.",
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Jayasundara, C, Deo, RN & Kodikara, J 2020, Application of a generalised MPK model with data fusion approaches for landslide risk assessment. in AG Correia, J Tinoco, P Cortez & L Lamas (eds), Information Technology in Geo-Engineering - Proceedings of the 3rd International Conference ICITG 2019. Springer Series in Geomechanics and Geoengineering, Springer, pp. 635-643, International Conference on Information Technology in Geo-Engineering 2019 , Guimarães, Portugal, 29/09/19. https://doi.org/10.1007/978-3-030-32029-4_53

Application of a generalised MPK model with data fusion approaches for landslide risk assessment. / Jayasundara, Chathurika; Deo, Ravin N.; Kodikara, Jayantha.

Information Technology in Geo-Engineering - Proceedings of the 3rd International Conference ICITG 2019. ed. / António Gomes Correia; Joaquim Tinoco; Paulo Cortez; Luís Lamas. Springer, 2020. p. 635-643 (Springer Series in Geomechanics and Geoengineering).

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

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AU - Kodikara, Jayantha

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N2 - The constitutive modelling of unsaturated soil behaviour within the MPK framework using data fusion approaches are discussed to envisage a practical approach for the evaluation and monitoring of landslide-prone areas. The present study focuses on improvements in subsurface suction distribution estimations via electrical resistivity tomography (ERT), which can be used to generate quasi-continuous suction profiles (QCSP) for numerical modelling. An explicit petro geophysical transfer function between suction and resistivity is presented herein, which was derived from the Waxman-Smits electrical resistivity model and the Van Genuchten equation for soil water retention curves. For efficient numerical modelling, a selective correction approach (SCA) is presented for petro geophysical transfer function updating procedure. The data acquisition and analysis architecture are envisaged within a data cloud platform, which is highly attractive within the context of internet-of-things (IoT). Although the focus of this work is on suction estimations, a similar approach can be used for estimation of other constitutive variables required within the MPK framework.

AB - The constitutive modelling of unsaturated soil behaviour within the MPK framework using data fusion approaches are discussed to envisage a practical approach for the evaluation and monitoring of landslide-prone areas. The present study focuses on improvements in subsurface suction distribution estimations via electrical resistivity tomography (ERT), which can be used to generate quasi-continuous suction profiles (QCSP) for numerical modelling. An explicit petro geophysical transfer function between suction and resistivity is presented herein, which was derived from the Waxman-Smits electrical resistivity model and the Van Genuchten equation for soil water retention curves. For efficient numerical modelling, a selective correction approach (SCA) is presented for petro geophysical transfer function updating procedure. The data acquisition and analysis architecture are envisaged within a data cloud platform, which is highly attractive within the context of internet-of-things (IoT). Although the focus of this work is on suction estimations, a similar approach can be used for estimation of other constitutive variables required within the MPK framework.

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PB - Springer

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Jayasundara C, Deo RN, Kodikara J. Application of a generalised MPK model with data fusion approaches for landslide risk assessment. In Correia AG, Tinoco J, Cortez P, Lamas L, editors, Information Technology in Geo-Engineering - Proceedings of the 3rd International Conference ICITG 2019. Springer. 2020. p. 635-643. (Springer Series in Geomechanics and Geoengineering). https://doi.org/10.1007/978-3-030-32029-4_53