Advertisement

Inundation Characteristics in Arida City Due to Overtopping Waves Induced by 2018 Typhoon Jebi

  • Y. Yamanaka
  • R. Shibata
  • Y. Tajima
  • N. Okami
Conference paper

Abstract

This study investigated inundation characteristics at Minatomachi in Arida City, Wakayama Prefecture, Japan, induced by the 2018 Typhoon Jebi. Field surveys were first conducted to capture the inundation area and the inundation depths at a witnessed time. The survey results and interviews of local residents indicated that wave overtopping of the stormy waves, as well as the storm surge, contributed to the inundation. Three numerical simulations for estimating the surge, waves, and inundation were systematically combined to represent the observed inundation characteristics. The simulation result reasonably presented the observed inundation area with the depths and indicated that the wave overtopping was the primary factor for the inundation. The results also implied that infragravity waves, developed under the storm, might have a significant impact on the inundation.

Keywords:

2018 Typhoon Jebi Inundation Overtopping waves Storm surge Infragravity waves 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Notes

Acknowledgements

We appreciate the anonymous residents who provided the pictures and the important information to us, Dr. Lianhui Wu and Mr. Yoshinao Matsuba who helped our field survey, and Mr. Naohiro Hattori who helped us to analyze simulated results. We have obtained the appropriate permissions for use of pictures of Figures 2(a) and (b) and also confirmed that no personal information is included in these pictures. The GSM-GPV data are originally provided by JMA. To access them, the archiving system of Oki/Kanae-Lab and Kitsuregawa-Lab, IIS, Univ. of Tokyo is used. Data accessible at http://dias.tkl.iis.u-tokyo.ac.jp/gpv/. The DIAS dataset is archived and provided under the framework of the Data Integration and Analysis System (DIAS) funded by Ministry of Education, Culture, Sports, Science and Technology (MEXT). Several figures presented in this paper were printed using the Generic Mapping Tools (GMT) software of Wessel et al. (2013). A part of this study was conducted as a research activity of “Enhancement of National Resilience against Natural Disasters,” Cross-ministerial Strategic Innovation Promotion Program (SIP), under supervision of NIED. The program was supported by Council for Science, Technology and Innovation (CSTI).

References

  1. Bertin, X., Li, K., Roland, A. and Nidlot, J.R. (2015) The contribution of short waves in storm surges: Two case studies in the Bay of Biscay. Continental Shelf Research, 96(15): 1-15.CrossRefGoogle Scholar
  2. Geospatial Information Authority of Japan (GSI). Digital Elevation Model, http://www.gsi.go.jp/kiban/, Accessed in December, 2018.
  3. Geospatial Information Authority of Japan (GSI). Basic Map Information, http://www.gsi.go.jp/kiban/, Accessed in March, 2019.
  4. Goda, Y. (1975). Irregular wave deformation in the surf zone. Coastal Engineering in Japan: 13-26.CrossRefGoogle Scholar
  5. Goda, Y. (2008). Overview on the applications of random wave concept in coastal engineering. Proceedings of the Japan Academy, Series B, 84(9): 374-385.CrossRefGoogle Scholar
  6. Ikoma, E. (2010). GPV Data Archive [Data set]. Data Integration and Analysis System (DIAS).  https://doi.org/10.20783/DIAS.161, Accessed in March, 2019.
  7. Japan Meteorological Agency, Typhoon Track Data, https://www.data.jma.go.jp/fcd/yoho/data/typhoon/T1821.pdf, Accessed in December, 2018.
  8. Japan Meteorological Agency, Tide Observations, http://www.data.jma.go.jp/gmd/kaiyou/db/tide/genbo/index.php, Accessed in December, 2018.
  9. Kim, S.Y., Yasuda, T. and Mase, H. (2008). Numerical analysis of effects of tidal variations on storm surges and waves. Applied Ocean Research, 30: 311-322.CrossRefGoogle Scholar
  10. Longuet-Higgins, M.S. and Stewart, R.W. (1964). Radiation stresses in water waves: A physical discussion, with applications. Deep-Sea Research, 11(4), 529-562.CrossRefGoogle Scholar
  11. Mori, N., Yasuda, T., Arikawa, T., Kataoka, T., Nakajo, S., Suzuki, K., Yamanaka, Y. and Webb, A. (2019). 2018 Typhoon Jebi post-event survey of coastal damage in the Kansai Region, Coastal Engineering Journal, 61(3), 278-294.CrossRefGoogle Scholar
  12. Oey, L.Y., Ezer, T., Wang, D.P., Fan, S.J. and Yin, X.Q. (2006). Loop current warming by Hurricane Wilma. Geophysical Research Letters, 33: L08613.Google Scholar
  13. Tajima, Y., Gunasekara, K.H., Shimozono, T. and Cruz, E.C. (2016). Study on local varying inundation characteristics induced by super typhoon Haiyan. Part 1: Dynamic behavior of storm surge and waves around San Pedro Bay. Coastal Engineering Journal, 58(1): 1640002.Google Scholar
  14. Takabatake, T., Mäll, M., Esteban, M., Nakamura, R., Kyaw, T.O., Ishii, H., Valdez, J.J., Nishida, Y., Naya, F. and Shibayama, T. (2018). Field survey of 2018 Typhoon Jebi in Japan: Lessons for disaster risk management. Geosciences, 8(11):412.CrossRefGoogle Scholar
  15. Weatherall, P., Marks, K.M., Jakobsson, M., Schmitt, T., Tani, S., Arndt, J.E., Rovere, M., Chayes, D., Ferrini, V. and Wigley, R. (2015). A new digital bathymetric model of the world’s oceans. Earth and Space Science, 2, 331-345.CrossRefGoogle Scholar
  16. Wessel P., Smith, W.H.F., Scharroo, R., Luis, J.F., and Wobbe, F. (2013). Generic Mapping Tools: improved version released. Eos Trans. AGU 94:409–410.CrossRefGoogle Scholar
  17. WW3DG (The WAVEWATCH III Development Group). (2016). User manual and system documentation of WAVEWATCH III version 5.16., Tech. Note 329, NOAA/NWS/NCEP/MMAB, College Park, MD, USA: 326 pp. + Appendices.Google Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2020

Authors and Affiliations

  • Y. Yamanaka
    • 1
  • R. Shibata
    • 1
  • Y. Tajima
    • 1
  • N. Okami
    • 1
  1. 1.Department of Civil EngineeringThe University of TokyoTokyoJapan

Personalised recommendations