Investigation of Landslide Vulnerability on Prambanan using Vertical Electrical Sounding

Authors

  • Awang Hendriato Pratomo Department of Informatics Engineering, Faculty of Industrial Engineering, UPN “Veteran” Yogyakarta, Jl Babarsari No. 2 Depok, Sleman, Yogyakarta, Indonesia Author
  • Suharsono Department of Geophysics, Faculty Mining Technology, UPN “Veteran” Yogyakarta, Jl SWK 104 Condong Catur, Depok, Sleman, Yogyakarta, Indonesia Author
  • Bambang Pratistho Department of Geology Engineering, Faculty Mining Technology, UPN “Veteran” Yogyakarta, Jl SWK 104 Condong Catur, Depok, Sleman, Yogyakarta, Indonesia Author
  • Dessyanto Boedi Prasetyo Department of Informatics Engineering, Faculty of Industrial Engineering, UPN “Veteran” Yogyakarta, Jl Babarsari No. 2 Depok, Sleman, Yogyakarta, Indonesia Author
  • Yudha Agung Pratama Department of Geophysics, Faculty Mining Technology, UPN “Veteran” Yogyakarta, Jl SWK 104 Condong Catur, Depok, Sleman, Yogyakarta, Indonesia Author
  • Basuki Purnawan Department of Geology Engineering, Faculty Mining Technology, UPN “Veteran” Yogyakarta, Jl SWK 104 Condong Catur, Depok, Sleman, Yogyakarta, Indonesia Author

DOI:

https://doi.org/10.61841/g62ytv32

Keywords:

sliding surface, geoelectricity, Schlumberger configuration, Vertical Electric Sounding, resistivity zone

Abstract

The aims of this research to identify potential weak zone of landslides on Prambanan based on the geoelectric resistivity technique of Vertical Electric Sounding (VES) Schlumberger configuration. Data was collected as much as 7 point sounding ; each Spreading AB has a length of 80 meters. The location of landslide is near from resident house. Therefore evaluation using resistivity method is needed to identification vulnerability of landslide. There are 7 of data acquisition. Based on the inversion result, contrass resistivity zone identified as diferent border of layer. Based on 2D resistivity modeling results indicate that the slip field is at a depth of 1.02-7.8 meters in the form of weathered Tuffaceus Sandstone.

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References

1. Izzati, F. N., Marcelina, B., Hutabarat, S. S., & Widodo. Identifying potential ground movement as a landslide mitigation approach using resistivity method. Conference Proceedings, American Institute of Physics.

2. Nishioka, S. K., Oku, Y., Egusa, N., & Tanouchi, H. (2017). Evaluation of landslide disaster by pseudo global warming experiment rainfall and soil water index on Shingu River Basin, Wakayama with Typhoon T1204. Journal of Japan Society of Civil Engineers, 73(4), 187–192.

3. Zhang, Q., Han, L., Jia, J., Song, L., & Wang, J. (2016). Management of drought risk under global warming. Theoretical and Applied Climatology, 125(1), 187–196.

4. Gariano, S. L., & Guzzetti, F. (2016). Landslides in a changing climate. Earth-Science Reviews, 162, 227–252.

5. Perrone, A., Lapenna, V., & Piscitelli, S. (2014). Electrical resistivity tomography technique for landslide investigation: A review. Earth-Science Reviews, 135, 65–82.

6. Akanbi, E. S., & BJA. (2017). 2-D electrical resistivity imaging for detecting landslide vulnerability of some tin mine sites in Jos South, Plateau State, North Central, Nigeria. IOSR Journal of Applied Geology and Geophysics, 5(2), 17–24.

7. Marsudi, B. P., Saptono, S., Ira, N. P., & Indrajaya, F. (2018). The mitigation of landslide disaster at the area formerly a soil and rock mining in Bukit Permai Singkawang. International Journal of Mining Science, 4(1), 1–10.

8. Bellanova, J., Calamita, G., Giocoli, A., Luongo, R., Macchiato, M., Perrone, A., et al. (2018). Electrical resistivity imaging for the characterization of the Montaguto landslide (Southern Italy). Engineering Geology, 243, 272–281.

9. Kumar, V., Gupta, V., Jamir, I., & Chattoraj, S. L. (2018). Evaluation of potential landslide damming: Case study of Urni landslide, Kinnaur, Satluj Valley, India. Geoscience Frontiers.

10. Ling, C., Xu, Q., Zhang, Q., Ran, J., & Lv, H. (2016). Application of electrical resistivity tomography for investigating the internal structure of a translational landslide and characterizing its groundwater circulation (Kualiangzi landslide, Southwest China). Journal of Applied Geophysics, 131, 154–162.

11. Ko, F. W. Y., & Lo, F. L. C. (2018). From landslide susceptibility to landslide frequency: A territory-wide study in Hong Kong. Engineering Geology, 242, 12–22.

12. Brunetti, M. T., Melillo, M., Peruccacci, S., Ciabatta, L., & Brocca, L. (2018). How far are we from the use of satellite rainfall products in landslide forecasting? Remote Sensing of Environment, 210, 65–75.

13. Mead, S., Magill, C., & Hilton, J. (2016). Rain-triggered lahar susceptibility using a shallow landslide and surface erosion model. Geomorphology, 273, 168–177.

14. Okamoto, T., Matsuura, S., Larsen, J. O., Asano, S., & Abe, K. (2018). The response of pore water pressure to snow accumulation on a low-permeability clay landslide. Engineering Geology, 242, 130–141.

15. Rohadi, S., Masturyono, M., Murjaya, J., Sunardi, B., Ngadmanto, D., Susilanto, P., et al. Ground landslide hazard potency using geoelectrical resistivity analysis and VS30: Case study at Geophysical Station, Lembang, Bandung. Conference Proceedings, AIP Publishing, Vol. 1857.

16. Persichillo, M. G., Bordoni, M., Cavalli, M., Crema, S., & Meisina, C. (2018). The role of human activities on sediment connectivity of shallow landslides. CATENA, 160, 261–274.

17. García-Ruiz, J. M., Beguería, S., Arnáez, J., Sanjuán, Y., Lana-Renault, N., Gómez-Villar, A., et al. (2017). Deforestation induces shallow landsliding in the Urbión Mountains, Iberian Range, Northern Spain. Geomorphology, 296, 31–44.

18. Preuth, T., Glade, T., & Demoulin, A. (2010). Stability analysis of a human-influenced landslide in eastern Belgium. Geomorphology, 120(1), 38–47.

19. Szokoli, K., Szarka, L., Metwaly, M., Kalmár, J., Prácser, E., & Szalai, S. (2018). Characterisation of a landslide by its fracture system using electric resistivity tomography and pressure probe methods. Acta Geodaetica et Geophysica, 53(1), 15–30.

20. Szokoli, K., & Kalmár, J. (2018). Characterisation of a landslide by its fracture system using electric resistivity tomography and pressure probe methods. Acta Geodaetica et Geophysica, 53, 15–30.

21. Destriani, N. (2013). Identifikasi daerah kawasan rentan tanah longsor dalam KSN Gunung Merapi di Kabupaten Sleman. Jurnal Teknik POMITS, 2, 134–138.

22. Fajria, L. (2017). Measuring landslide vulnerability at sub-district of Prambanan, region of Sleman using geographic information system. Geo Educasia, 2, 388–406.

23. Ausilio, E., & Zimmaro, P. (2017). Landslide characterization using a multidisciplinary approach. Measurement, 104, 294–301.

24. Devi, A., Israil, M., Anbalagan, R., & Gupta, P. K. (2017). Subsurface soil characterization using geoelectrical and geotechnical investigations at a bridge site in Uttarakhand Himalayan region. Journal of Applied Geophysics, 144, 78–85.

25. Lesmana, H. K. S. Identifikasi basement rock pada zona longsor dengan menggunakan metode geolistrik (Studi kasus wilayah Kelurahan Selili, Samarinda Ilir, Kota Samarinda, Kalimantan Timur). Conference Proceedings, Vol. 1, pp. 32–36.

26. Muallifah, F., & Faqih. (2009). Perancangan dan pembuatan alat ukur resistivitas tanah. Jurnal Neutrino, 1(2), UIN Malang.

27. Buol, S. W., Southard, R. J., Graham, R. C., & McDaniel, P. A. (2003). Soil Genesis and Classification (5th ed., p. 494). Ames, Iowa: Iowa State Press, Blackwell Publishing. ISBN: 0-8138-2873-2.

28. Soil Survey Staff. (1993). Soil Survey Manual. Washington D.C.: U.S. Government Printing Office. USDA Handbook 18.

29. Horgan, G. W. (1996). A review of soil pore models. Retrieved 2006-11-03.

30. Surono. (2008). Pusat Survei Geologi, Badan Geologi. Jurnal Geologi Indonesia, 3(4), 183–193.

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Published

29.05.2020

How to Cite

Pratomo, A. H., Suharsono, Pratistho, B., Prasetyo, D. B., Pratama, Y. A., & Purnawan , B. (2020). Investigation of Landslide Vulnerability on Prambanan using Vertical Electrical Sounding . International Journal of Psychosocial Rehabilitation, 24(10), 909-925. https://doi.org/10.61841/g62ytv32