Application of Dense Offshore Tsunami Observations from Ocean Bottom Pressure Gauges (OBPGs) for Tsunami Research and Early Warnings

  • Mohammad HeidarzadehEmail author
  • Aditya R. Gusman
Part of the Springer Natural Hazards book series (SPRINGERNAT)


We introduce a new data source of dense deep-ocean tsunami records from Ocean Bottom Pressure Gauges (OBPGs) which are attached to Ocean Bottom Seismometers (OBS) and apply them for far-field and near-field tsunami warnings. Tsunami observations from OBPGs are new sources of deep-ocean tsunami observations which, for the first time, provide dense tsunami data with spacing intervals in the range of 10–50 km. Such dense data are of importance for tsunami research and warnings and are capable of providing new insights into tsunami characteristics. Here, we present a standard procedure for the processing of the OBPG data and extraction of tsunami signals out of these high-frequency data. Then, the procedure is applied to two tsunamis of 15 July 2009 Mw 7.8 Dusky Sound (offshore New Zealand) and 28 October 2012 Mw 7.8 Haida Gwaii (offshore Canada). We successfully extracted 30 and 57 OBPG data for the two aforesaid tsunamis, respectively. Numerical modeling of tsunami was performed for both tsunamis in order to compare the modeling results with observation and to use the modeling results for the calibration of some of the OBPG data. We successfully employed the OBPG data of the 2012 Haida Gwaii tsunami for tsunami forecast by applying a data assimilation technique. Our results, including two case studies, demonstrate the high potential of OBPG data for contribution to tsunami research and warnings. The procedure developed in this study can be readily applied for the extraction of tsunami signals from OBPG data.


Tsunami Ocean Bottom Pressure Gauge Ocean Bottom Seismometer Tsunami warning system Numerical simulation 2009 Dusky Sound earthquake 



We acknowledge NOAA (National Oceanic and Atmospheric Administration of the US) for providing the DART data (, the IOC (Intergovernmental Oceanographic Commission) for the tide gauge records ( and the Incorporated Research Institutions for Seismology Data Management Center for the OBPG records ( Authors would like to thank Kenji Satake (The University of Tokyo, Japan), Tomohiro Takagawa (Port and Airport Research Institute, Japan), Shingo Watada (The University of Tokyo, Japan) and Anne Sheehan (University of Colorado, US) for their collaboration on the analysis of the OPBG records. Parts of this study were previously presented at the AGU (American Geophysical Union) fall meeting in San Francisco (US) in December 2016. The lead author (MH) was funded by the Brunel University London through the Brunel Research Initiative and Enterprise Fund 2017/18 (BUL BRIEF).


  1. 1.
    Beavan J, Samsonov S, Denys P, Sutherland R, Palmer N, Denham M (2010) Oblique slip on the Puysegur subduction interface in the 2009 July MW 7.8 Dusky Sound earthquake from GPS and InSAR observations: implications for the tectonics of southwestern New Zealand. Geophys J Int 183(3):1265–1286CrossRefGoogle Scholar
  2. 2.
    Geist EL, Titov VV, Synolakis CE (2006) Tsunami: wave of change. Sci Am 294(1):56–63CrossRefGoogle Scholar
  3. 3.
    Gonzalez FI, Milburn HM, Bernard EN, Newman JC (1998) Deep-ocean assessment and reporting of tsunamis (DART®): brief overview and status report. In: Proceedings of the international workshop on tsunami disaster mitigation, Tokyo, Japan, 19–22 January 1998Google Scholar
  4. 4.
    Gusman AR, Murotani S, Satake K, Heidarzadeh M, Gunawan E, Watada S, Schurr B (2015) Fault slip distribution of the 2014 Iquique, Chile, earthquake estimated from ocean-wide tsunami waveforms and GPS data. Geophys Res Lett 42:1053–1060CrossRefGoogle Scholar
  5. 5.
    Gusman AR, Sheehan A, Satake K, Heidarzadeh M, Mulia IE, Maeda E (2016a) Tsunami data assimilation of Cascadia seafloor pressure gauge records from the 2012 Haida Gwaii earthquake. Geophys Res Lett 43(9):4189–4196Google Scholar
  6. 6.
    Gusman A, Mulia IE, Satake K, Watada S, Heidarzadeh M, Sheehan AF (2016b) Estimate of tsunami source using optimized unit sources and including dispersion effects during tsunami propagation: the 2012 Haida Gwaii earthquake. Geophys Res Lett 43(18):9819–9828Google Scholar
  7. 7.
    Heidarzadeh M, Satake K (2013) The 21 May 2003 Tsunami in the Western Mediterranean sea: statistical and wavelet analyses. Pure Appl Geophys 170(9):1449–1462CrossRefGoogle Scholar
  8. 8.
    Heidarzadeh M, Satake K (2013) Waveform and spectral analyses of the 2011 Japan tsunami records on tide gauge and DART stations across the Pacific Ocean. Pure Appl Geophys 170(6):1275–1293CrossRefGoogle Scholar
  9. 9.
    Heidarzadeh M, Satake K (2014) Excitation of basin-wide modes of the Pacific Ocean following the March 2011 Tohoku Tsunami. Pure Appl Geophys 171(12):3405–3419CrossRefGoogle Scholar
  10. 10.
    Heidarzadeh M, Satake K, Murotani S, Gusman AR, Watada S (2015) Deep-water characteristics of the Trans-Pacific Tsunami from the 1 April 2014 M w 8.2 Iquique, Chile Earthquake. Pure Appl Geophys 172(3–4):719–730CrossRefGoogle Scholar
  11. 11.
    Heidarzadeh M, Harada T, Satake K, Ishibe T, Gusman A (2016) Comparative study of two tsunamigenic earthquakes in the Solomon Islands: 2015 Mw 7.0 normal-fault and 2013 Santa Cruz Mw 8.0 megathrust earthquakes. Geophys Res Lett 43(9):4340–4349CrossRefGoogle Scholar
  12. 12.
    Kalnay E (2003) Atmospheric modeling, data assimilation, and predictability. Cambridge University Press, Cambridge, UKGoogle Scholar
  13. 13.
    Kao H, Shan SJ, Farahbod AM (2015) Source characteristics of the 2012 Haida Gwaii earthquake sequence. Bull Seismol Soc Am 105(2B):1206–1218CrossRefGoogle Scholar
  14. 14.
    Leonard LJ, Bednarski JM (2014) Field survey following the 28 October 2012 Haida Gwaii tsunami. Pure Appl Geophys 171(12):3467–3482CrossRefGoogle Scholar
  15. 15.
    Maeda T, Obara K, Shinohara M, Kanazawa T, Uehira K (2015) Successive estimation of a tsunami wavefield without earthquake source data: a data assimilation approach toward real-time tsunami forecasting. Geophys Res Lett 42(19):7923–7932CrossRefGoogle Scholar
  16. 16.
    Rabinovich AB, Eblé MC (2015) Deep-ocean measurements of tsunami waves. Pure Appl Geophys 172:3281–3312CrossRefGoogle Scholar
  17. 17.
    Satake K (1995) Linear and nonlinear computations of the 1992 Nicaragua earthquake tsunami. Pure Appl Geophys 144:455–470CrossRefGoogle Scholar
  18. 18.
    Sheehan AF, Gusman AR, Heidarzadeh M, Satake K (2015) Array observations of the 2012 Haida Gwaii tsunami using Cascadia Initiative absolute and differential seafloor pressure gauges. Seismol Res Lett 86(5):1278–1286CrossRefGoogle Scholar
  19. 19.
    Synolakis CE, Bernard EN (2006) Tsunami science before and beyond Boxing Day 2004. Philos Trans R Soc Lond A 364(1845):2231–2265MathSciNetCrossRefGoogle Scholar
  20. 20.
    Titov VV, Gonzalez FI, Bernard EN, Eble MC, Mofjeld HO, Newman JC, Venturato AJ (2005) Real-time tsunami forecasting: challenges and solutions. In: Developing tsunami-resilient communities. Springer, Netherlands, pp 41–58Google Scholar
  21. 21.
    Weatherall P, Marks KM, Jakobsson M, Schmitt T, Tani S, Arndt JE, Rovere M, Chayes D, Ferrini V, Wigley R (2015) A new digital bathymetric model of the world’s oceans. Earth Space Sci 2:331–345CrossRefGoogle Scholar

Copyright information

© Springer Nature Singapore Pte Ltd. 2019

Authors and Affiliations

  1. 1.Department of Civil and Environmental EngineeringBrunel University LondonUxbridgeUK
  2. 2.GNS ScienceLower HuttNew Zealand

Personalised recommendations