1887
Volume 12 Number 1
  • ISSN: 1569-4445
  • E-ISSN: 1873-0604

Abstract

ABSTRACT

Permanent geoelectrical monitoring, using the GEOMON4D instrumentation in combination with high resolution displacement monitoring by means of the D.M.S. system, was performed at two active landslide areas: Ampflwang/Hausruck in Austria, and Bagnaschino in Italy. These sites are part of the Austrian geoelectrical monitoring network, which currently comprises six permanently monitored landslides in Europe. Within the observation intervals, several displacement events, triggered by intense precipitation, were monitored and analysed. All of these events were preceded by a decrease of electric resistivity. The application of an innovative 4D inversion algorithm made it possible to investigate the potential processes which led to the triggering of these events. We conclude that resistivity monitoring can significantly help in the investigation of the causes of landslide reactivation. Since the results also contribute to the extrapolation of local displacement monitoring data to a larger scale, resistivity monitoring can definitely support decision‐finding in emergencies.

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2013-09-01
2024-03-28
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References

  1. ArchieG.E.1942. The electrical resistivity log as an aid in determining some reservoir characteristics. Petroleum Transaction of AIME146, 54–62.
    [Google Scholar]
  2. AtkinsE.R. and SmithG.H.1961. The significance of particle shape in formation factor‐porosity relationships. Journal of Petroleum Technology13(3), 285–291.
    [Google Scholar]
  3. BaronI. and SupperR.2010. A general assessment of landslide investigation and monitoring methods in Europe (preliminary results). In: Monitoring Technologies and Early Warning Systems – Current Research and Perspectives for the Future, (eds R.Supper and I.Baron ). Book of extended abstracts, Open Workshop in frame of the EU FP7 “Safeland” Project, February 24th, Vienna. Berichte der Geologischen Bundesanstalt 82, Vienna.
    [Google Scholar]
  4. BellR., ThiebesB., GladeT., BeckerR., KuhlmannH., SchauerteW.et al. 2008. The technical concept within the Integrative Landslide Early Warning System (ILEWS). In: Geotechnologien – Science Report 14.
    [Google Scholar]
  5. ChacónJ., IrigarayC., FernandezT. and El HamdouniR.2006. Engineering geology maps: Landslides and geographical inforation systems. Bulletin of Engineering Geology and the Environment65(4), 341–411.
    [Google Scholar]
  6. ChambersJ.E., MeldrumP.I., GunnD.A., WilkinsonP.B., KurasO., WellerA.L. et al. 2009. Hydrogeophysical monitoring of landslide processes using automated time‐lapse electrical resistivity tomography (ALERT) [extended abstract]. Near Surface 2009,Dublin, Ireland, 7–9 September.
    [Google Scholar]
  7. ChambersJ.E., HobbsP., PenningtonC., JonesL., DixonN., SpriggsM.et al. 2010. Integrated LiDAR, geophysical and geotechnical monitoring of an active inland landslide, UK. Geophysical Research Abstracts12, EGU2010‐5244.
    [Google Scholar]
  8. ChambersJ.E., MeldrumP.I., GunnD.A., WilkinsonP.B., MerrittA., MurphyW. et al. 2011. Geophysical‐geotechnical sensor networks for landslide monitoring. Proceedings of the Second World Landslide Forum,Rome, 3–7 October 2011.
    [Google Scholar]
  9. DailyW., RamirezA., LabrecqueD. and NitaoJ.1992. Electrical‐resistivity tomography of vadose water‐movement. Water Resources Research28, 1429–1442.
    [Google Scholar]
  10. FoglinoL., LovisoloM. and Della GiustaA.2006. Contribution of D.M.S. monitoring systems in the analysis of slide micro‐movements for early warning management, risk assessment and evaluation of mitigating actions. Geophysical Research Abstracts8, 06122.
    [Google Scholar]
  11. GiulianiA., BonettoS., CastagnaS., CominaC. and MandroneG.2010: A Monitoring System for Mitigation Planning: The Case of “Bagnaschino” Landslide in Northern Italy. American Journal of Environmental Sciences6(6), 516–522.
    [Google Scholar]
  12. HayleyK., PidliseckyA. and BentleyL.R.2011. Simultaneous timelapse electrical resistivity inversion. Journal of Applied Geophysics75, 401–411.
    [Google Scholar]
  13. JacksonP., Taylor‐SmithD. and StanfordP.N.1978. Resistivity‐porosity‐particle shape relationships for marine sands. Geophysics43(6), 1250–1268.
    [Google Scholar]
  14. JongmansD. and GaramboisS.2007. Geophysical investigation of landslides: a review. Bulletin de la Societe Geologique de France178(2), 101–112.
    [Google Scholar]
  15. KaraoulisM.C., KimJ.‐H. and TsourlosP.I.2011a. 4D active time constrained resistivity inversion. Journal of Applied Geophysics73, 25–34.
    [Google Scholar]
  16. KaraoulisM., RevilA., WerkemaD.D., MinsleyB.J., WoodruffW.F. and KemnaA.2011b. Time‐lapse three‐dimensional inversion of complex conductivity data using an active time constrained (ATC) approach. Geophysical Journal International187, 2237–251.
    [Google Scholar]
  17. KaraoulisM., RevilA., ZhangJ. and WerkemaD.D.2012. Time‐lapse joint inversion of crosswell DC resistivity and seismic data: A numerical investigation. Geophysics77, D141–D157.
    [Google Scholar]
  18. KimJ.‐H., YiM.‐J., ParkS.‐G. and KimJ.G.2009. 4‐D inversion of DC resistivity monitoring data acquired over a dynamically changing earth model. Journal of Applied Geophysics68, 522–532.
    [Google Scholar]
  19. KimJ.‐H., YiM.‐J., AhnH.‐Y. and KimK.‐S.2010. 4‐D Inversion of Resistivity Monitoring Data Using L1 Norm Minimization. Proceedings of Near Surface 2010,A15, Zurich, Swiss, 6–8 September.
    [Google Scholar]
  20. KimJ.‐H., SupperR., TsourlosP. and YiM.‐J.2012. 4D inversion of resistivity monitoring data through Lp norm minimizations. Proceedings of Near Surface Geoscience 2012,A24, Paris, France, 3–5 September.
    [Google Scholar]
  21. KimJ.‐H., SupperR., TsourlosP. and YiM.‐J.2013. Four‐dimensional inversion of resistivity monitoring data through Lp norm minimizations. Geophysical Journal International (in review).
    [Google Scholar]
  22. LaBrecqueD.J. and YangX.2001. Difference inversion of ERT data: a fast inversion method for 3‐D in situ monitoring. Journal of Environmental and Engineering Geophysics6, 83–89.
    [Google Scholar]
  23. LebourgT., HernandezM., ZeratheS., El BedouiS., JomardH. and FresiaB.2010. Landslides triggered factors analysed by time lapse electrical survey and multidimensional statistical approach. Engineering Geology114(3–4), 238–250
    [Google Scholar]
  24. LokeM.H.1999. Time lapse resistivity imaging inversion. Proceedings of the 5th Meeting of the EEGS European Section,Em1.
    [Google Scholar]
  25. LokeM.H., DahlinT. and RuckerD.F.2013. Smoothness‐constrained time‐lapse inversion of data from 3‐D resistivity surveys. Near Surface Geophysics (in press).
    [Google Scholar]
  26. LovisoloM.2011. Bagnaschino Landslide: From early warning to site‐specific kinematic analysis. Berichte der Geologischen Bundesanstalt82, ISSN 1017–8880 – Landslide Monitoring Technologies & Early Warning Systems, Vienna.
    [Google Scholar]
  27. LuongoR., PerroneA., PiscitelliS., and LapennaV.2012. A Prototype System for Time‐Lapse Electrical Resistivity Tomographies. In: Electrical Imaging for Geohazard and Environmental Monitoring, (eds V.Lapenna , S.Piscitelli and P.Soupios ). International Journal of Geophysics, Article ID 176895, 12 pages. doi:10.1155/2012/176895
    [Google Scholar]
  28. MauritschH.J., SeiberlW., ArndtR., RömerA., SchneiderbauerK. and SendlhoferG.P.2000. Geophysical investigations of a large landslide in the Carnic Region (case study). Engineering Geology56, 373–388.
    [Google Scholar]
  29. MericO., GaramboisS., JongmansD., WatheletM., ChatelainJ.‐L. and VengeonJ.‐M.2005. Application of geophysical methods for the investigation of the large gravitational mass movement of Séchilienne, France. Canadian Geotechnical Journal42, 1105–1115.
    [Google Scholar]
  30. MillerC.R., RouthP., BrostenT. and McNamaraJ.2008. Application of time‐lapse ERT imaging to watershed characterization. Geophysics73, 7–17.
    [Google Scholar]
  31. OldenborgerG.A., KnollM.D., RouthP.S. and LaBrecqueD.J.2007. Time‐lapse ERT monitoring of an injection/withdrawal experiment in a shallow unconfined aquifer. Geophysics72, 177–187.
    [Google Scholar]
  32. PeisinoV., PepeM., BrunamonteF. and BellomaA.2009a. Movimento Franosa in Localita Bagnaschino, Valutazione geologica e geotecnica del movimento franoso sulla SP. 164 e definizione a livello di studio di fattibilità degli interventi tecnici da adottare, Fase 1 Step conoscitivo generale, Ingegneria Geotecnica, Torino, Italy.
    [Google Scholar]
  33. PeisinoV., BrunamonteF., LamponeG.F. and BellomaA.2009b. Movimento Franosa in Localita Bagnaschino, Valutazione geologica e geotecnica del movimento franoso sulla SP. 164 e definizione a livello di studio di fattibilità degli interventi tecnici da adottare, Fase 2 ‐Campagna geognostica integrativa R 2.1 ‐ Relazione sulle indagini geognostiche e geofisiche, Ingegneria Geotecnica, Torino, Italy.
    [Google Scholar]
  34. PeisinoV., BrunamonteF., LamponeG.F. and BellomaA.2009c. Movimento Franosa in Localita Bagnaschino, Valutazione geologica e geotecnica del movimento franoso sulla SP. 164 e definizione a livello di studio di fattibilità degli interventi tecnici da adottare, Fase 3 Monitoraggio di superficie e di sottosuolo, R 3.1 – Risultati acquisiti con le attività di monitoraggio del versante, Ingegneria Geotecnica, Torino, Italy.
    [Google Scholar]
  35. PerroneA.2001. Electrical and Self‐Potential tomographic techniques for landslide monitoring: first results on Southern Apennine Chain (Italy). II international Workshop on Geo‐Electro‐Magnetism / Abstract, Memorie dell’Accademia Lunigianese di Scienze “G. Capellini” Vol. LXXI (2001), Scienze Matematiche, Fisiche e Naturali, La Spezia.
    [Google Scholar]
  36. PerroneA., IannuzziA., LapennaV., LorenzoP., PiscitelliS., RizzoE.et al. 2004. Highresolution electrical imaging of the Varco d’Izzo earthflow (southern Italy). Journal of Applied Geophysics56, 17–29.
    [Google Scholar]
  37. PerroneA., ZeniG., PiscitelliS., PepeA., LoperteA., LapennaV. and LanariR.2006. Joint analysis of SAR interferometry and electrical resistivity tomography surveys for investigationg ground deformation: the case‐study of Satriano di Lucania (Potenza, Italy). Engineering Geology88, 260–273.
    [Google Scholar]
  38. RuckerD.F., FinkaJ.B. and LokeM.H.2011. Environmental monitoring of leaks using timelapsed long electrode electrical resistivity. Journal of Applied Geophysics74, 242–254.
    [Google Scholar]
  39. Schlumberger1987. Log Interpretation Charts, Houston, Schlumberger Educational Services.
    [Google Scholar]
  40. SupperR., HüblG. and JaritzW.2002. Geophysical Surveys for the investigation and monitoring of landslide areas. Proceedings of the Environmental and Engineering Geophysical Society, 8th Meeting Aveiro,Portugal.
    [Google Scholar]
  41. SupperR., AhlA., RömerA., JochumB. and BieberG.2008. A complex geo‐scientific strategy for landslide hazard mitigation – from airborne mapping to ground monitoring. Advances in Geosciences14, 1–6.
    [Google Scholar]
  42. SupperR., RömerA. and JochumB.2009. Geoelectrical measurements for natural hazard monitoring. SEGJ 9th International Symposium, Extended Abstracts, Sapporo.
    [Google Scholar]
  43. SupperR., BaronI., JochumB., ItaA., WinklerE., MotschkaK. and MoserG.2010. From structural investigation towards multi‐parameter early warning systems: geophysical contributions to hazard mitigation at the landslide of Gschliefgraben (Gmunden, Upper Austria), Geophysical Research Abstracts12, EGU2010‐4649‐1.
    [Google Scholar]
  44. SupperR., JochumB., OttowitzD., BaroňI., VecchiottiV., PfeilerS. et al. 2012a. Case histories – Analysis of real monitoring data: Bagnaschino. In: The Safeland Project, Deliverable 4.6, Report on evaluation of mass movement indicators, (eds L.Baron and R.Supper ), Vienna, 191–220.
    [Google Scholar]
  45. SupperR., JochumB., BaroňI., OttowitzD., PfeilerS., RömerA.et al. 2012b. Case histories ‐ Analysis of real monitoring data: Ampflwang‐Hausruck. In: The Safeland Project, Deliverable 4.6, Report on evaluation of mass movement indicators, (eds L.Baron and R.Supper ), Vienna, 150–173.
    [Google Scholar]
  46. WilkinsonP.B., ChambersJ.E., MeldrumP.I., GunnD.A., OgilvyR.D. and KurasO.2010. Predicting the movements of permanently installed electrodes on an active landslide using time‐lapse geoelectrical resistivity data only. Geophysical Journal International183(2), 543–556.
    [Google Scholar]
  47. WinsauerW.O., ShearinH.M., Jr., MassonP.H. and WilliamsM.1952. Resistivity of brine saturated sands in relation to pore geometry. AAPG Bulletin36, 253–277.
    [Google Scholar]
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