Analysis of the 30 October 2020 İzmir-Samos Tsunami Measurements with Compressive Sensing Method

Öz

Although they do not occur as frequently as other natural disasters, tsunamis can cause tremendous damage to the near-shore ecosystem. On October 30, 2020, at 12:51 p.m. an earthquake with a magnitude of 6.9 Mw occurred at UTC (2:51 p.m. GMT+03:00). The epicenter of the earthquake is located off the Greek island of Samos, approximately 23 km south of Turkey’s İzmir province. This earthquake caused the İzmir-Samos (Aegean) tsunami, which has the same name, on October 30, 2020. In this research, the efficient reconstruction of the hydrodynamic time series of this tsunami with efficient measurements was examined using the Compressive Sensing (CS) algorithm, which is an effective detection technique applied to observational data. For this purpose, tsunami time series records obtained from Kos Marina and Bodrum stations of the UNESCO data portal were used. The potential application of effectively measuring and reconstructing tsunami water surface fluctuation time series and the Fourier spectra of these series with the CS algorithm has been investigated. It has been shown that tsunami parameters such as water surface fluctuations, horizontal and vertical tsunami velocities, and tsunami flood discharge time series can be successfully measured, analyzed, and recorded using CS. In addition, potential future directions and the usefulness and applicability of our findings are also examined.

Anahtar Kelimeler

• 30 October 2020 İzmir-Samos (Aegean) tsunami
• compressive sensing
• time series analysis

30 Ekim 2020 İzmir-Samos Tsunamisi Ölçümlerinin Sıkıştırılabilir Algılama Yöntemiyle Analizi

Öz

Diğer doğal afetler kadar sık meydana gelmeseler de tsunamiler kıyıya yakın ekosisteme çok büyük zararlar verebilir. 30 Ekim 2020’de saat 12:51 p.m. UTC’de (2:51 p.m. GMT+03:00) 6,9 Mw büyüklüğünde bir deprem meydana gelmiştir. Depremin merkez üssü, Türkiye’nin İzmir ilinin yaklaşık 23 km güneyinde, Yunanistan’ın Samos adası açıklarında bulunmaktadır. Bu deprem 30 Ekim 2020’de kendisiyle aynı adı taşıyan İzmir-Samos (Ege) tsunamisine neden olmuştur. Bu araştırmada, gözlemsel verilere uygulanan etkili bir algılama tekniği olan Sıkıştırılabilir Algılama (CS) algoritması kullanılarak bu tsunaminin hidrodinamik zaman serilerinin verimli ölçümlerle geri çatılması incelenmiştir. Bu amaçla UNESCO veri portalının Kos Marina ve Bodrum istasyonlarından elde edilen tsunami zaman serisi kayıtlarından faydalanılmıştır. Tsunami su salınım seviyesi zaman serilerinin ve bu serilerin Fourier spektrumlarının CS algoritmasıyla etkili bir şekilde ölçülerek geri çatılmasının potansiyel uygulaması araştırılmıştır. CS kullanılarak su seviyesi salınımı, yatay ve düşey tsunami hızları, tsunami taşkın debisi zaman serileri gibi tsunami parametrelerinin başarıyla ölçülebileceği, analiz edilebileceği ve kayıt altına alınabileceği gösterilmiştir. Ayrıca gelecekteki potansiyel yönelimler, bulgularımızın kullanışlılığı ve uygulanabilirliği de irdelenmiştir.

Anahtar Kelimeler

• 30 Ekim 2020 İzmir-Samos (Ege) tsunamisi
• sıkıştırılabilir algılama
• zaman serisi analizi

Kaynakça

1. Ward SN. 2002. Tsunamis. In: Meyers RA, editor. The Encyclopedia of Physical Science and Technology. Academic Press, 2002. Vol. 17, 175-191.
2. Chapman C. The Asian tsunami in Sri Lanka: A personal experience. EOS Trans Am Geophys Union 2005; 86: 13–14.
3. Berry MV. Tsunami asymptotics. New J Phys 2005; 7: 129.
4. Röbke B, Vött A. The tsunami phenomenon. Prog Oceanogr 2017; 159: 296–322.
5. Ishihara M, Tadono T. Land cover changes induced by the great east Japan earthquake in 2011. Sci Rep 2017; 7: 45769.
6. Kaiser G, Burkhard B, Römer H, Sangkaew S, Graterol R, Haitook T, Sterr H, Sakuna-Schwartz D. Mapping tsunami impacts on land cover and related ecosystem service supply in Phang Nga, Thailand. Nat Hazards Earth Syst Sci 2013; 13: 3095–3111.
7. Richmond B, Szczucinski W, Chagué-Goff C, Goto K, Sugawara D, Witter R, Tappin DR, Jaffe B, et al. Erosion, deposition and landscape change on the Sendai coastal plain, Japan, resulting from the March 11, 2011 Tohoku-oki tsunami. Sediment Geol 2012; 282: 27–39.
8. Tappin DR, Evans HM, Jordan CJ, Richmond B, Sugawara D, Goto K. Coastal changes in the Sendai area from the impact of the 2011 Tohoku-oki tsunami: Interpretations of time series satellite images, helicopter-borne video footage and field observations. Sediment Geol 2012; 282: 151–174.

9. Bayındır C. Analysis of tsunami and tsunami-structure interaction parameters by compressive sensing. 2nd International Conference on Applied Mathematics in Engineering (ICAME 2021); 1–3 September 2021, Balıkesir, Turkey. 14-19.
10. Sambah AB, Miura F. Remote sensing, GIS, and AHP for assessing physical vulnerability to tsunami hazard. Int J Environ Ecol Eng 2013; 7: 671–679.
11. Yamazaki F, Matsuoka M. Remote sensing technologies in post disaster damage assessment. J Earthquake Tsunami 2007; 1: 193–210.
12. Doğan GG, Yalçıner AC, Yüksel Y, Ulutaş E, Polat O, Güler I, Sahin C, Tarih A, et al. The 30 October 2020 Aegean Sea Tsunami: Post-Event Field Survey Along Turkish Coast. Pure Appl Geophys 2021; 178: 785–812.
13. Alan AR, Bayındır C, Ozaydin F, Altintas AA. The predictability of the 30 October 2020 İzmir-Samos Tsunami hydrodynamics and enhancement of its early warning time by LSTM deep learning network. Water 2023; 15(23): 4195.
14. Triantafyllou I, Gogou M, Mavroulis S, Lekkas E, Papadopoulos GA, Thravalos M. The tsunami caused by the 30 October 2020 Samos (Aegean Sea) Mw7.0 earthquake: Hydrodynamic features, source properties and impact assessment from post-event field survey and video records. J Mar Sci Eng 2021; 9: 68.
15. Evelpidou N, Karkani A, Kampolis I. Relative sea level changes and morphotectonic implications triggered by the Samos earthquake of 30th October 2020. J Mar Sci Eng 2020; 9: 40.
16. Politis D, Potirakis S, Contoyiannis Y, Biswas S, Sasmal S, Hayakawa M. Statistical and criticality analysis of the lower ionosphere prior to the 30 October 2020 Samos (Greece) earthquake (M6.9), based on VLF electromagnetic propagation data as recorded by a new VLF/LF receiver installed in Athens (Greece). Entropy 2021; 23: 676.
17. Mase H, Yasuda T, Mori N. Real-time prediction of tsunami magnitudes in Osaka Bay, Japan, using an artificial neural network. J Waterw Port Coast Ocean Eng 2011; 137: 263–268.
18. Mitra R, Naruse H, Abe T. Estimation of tsunami characteristics from deposits: Inverse modeling using a deep-learning neural network. J Geophys Res: Earth Surf 2020; 125: e2020JF005583.
19. Makinoshima F, Oishi Y, Yamazaki T, Furumura T, Imamura F. Early forecasting of tsunami inundation from tsunami and geodetic observation data with convolutional neural networks. Nat Commun 2021; 12: 2253.
20. Fauzi A, Mizutani N. Machine learning algorithms for real-time tsunami inundation forecasting: A case study in Nankai region. Pure Appl Geophys 2020; 177: 1437–1450.
21. Mulia IE, Ueda N, Miyoshi T, Gusman AR, Satake K. Machine learning-based tsunami inundation prediction derived from offshore observations. Nat Commun 2022; 13: 5489.
22. Wang Y, Imai K, Miyashita T, Ariyoshi K, Takahashi N, Satake K. Coastal tsunami prediction in Tohoku region, Japan, based on S-net observations using artificial neural network. Earth Planets Space 2023; 75: 154.
23. Alan AR, Bayındır C. Analysis of wave runup, overtopping and overwash parameters via compressive sensing. 2nd International Conference on Applied Mathematics in Engineering (ICAME 2021); 1–3 September 2021, Balıkesir, Turkey. 110-115.
24. Kiratzi A, Papazachos C, Özacar A, Pinar A, Kkallas C, Sopaci E. Characteristics of the 2020 Samos earthquake (Aegean Sea) using seismic data. Bull Earthquake Eng 2022; 20: 7713–7735.
25. Sboras S, Lazos I, Bitharis S, Pikridas C, Galanakis D, Fotiou A, Chatzipetros A, Pavlides S. Source modelling and stress transfer scenarios of the October 30, 2020 Samos earthquake: Seismotectonic implications. Turk J Earth Sci 2021; 30: 699–717.
26. Ren C, Yue H, Cao B, Zhu Y, Wang T, An C, Ge Z, Li Z. Rupture process of the 2020 Mw = 6.9 Samos, Greece earthquake on a segmented fault system constrained from seismic, geodetic, and tsunami observations. Tectonophysics 2022; 839: 229497.
27. KRDAE. Boğaziçi Üniversitesi Kandilli Rasathanesi ve Deprem Araştırma Enstitüsü, Bölgesel Deprem-Tsunami İzleme ve Değerlendirme Merkezi 30 Ekim 2020 Ege Denizi Depremi Basın Bülteni. 2020. http://www.koeri.boun.edu.tr/sismo/2/wp-content/uploads/2020/10/20201030_izmir_V1.pdf (Erişim tarihi: 10 Ekim 2023).
28. UNESCO/IOC. UNESCO Intergovernmental Oceanographic Commission Sea Level Station Monitoring Facility. 2020. https://www.ioc-sealevelmonitoring.org/station.php?code=stationcode (Erişim tarihi: 10 Ekim 2023).
29. Candès EJ, Romberg J, Tao T. Robust uncertainty principles: Exact signal reconstruction from highly incomplete frequency information. IEEE Transactions on information theory 2006; 52(2): 489-509.
30. Candès EJ. Compressive sampling. Proceedings of the international congress of mathematicians 2006; 3: 1433-1452.
31. Malara G, Kougioumtzoglou IA, Arena F. Extrapolation of random wave field data via compressive sampling. Ocean Eng 2018; 157: 87-95.
32. Bayındır C. Early detection of rogue waves using compressive sampling. TWMS J App Eng Math 2019; 9(2): 198-205.
33. Bayındır C. Compressive spectral method for the simulation of nonlinear gravity waves. Sci Rep 2016; 22100.
34. Bayındır C, Namlı B. Efficient sensing of the von Karman vortices using compressive sensing. Comput Fluids 2021; 104975.
35. Bayındır C. Compressive spectral renormalization method. TWMS J App Eng Math 2018; 8: 425–437.
36. Bueler-Faudree T, Sam D, Dutykh D, Rybkin A, Suleimani A. Fast shallow water-wave solver for plane inclined beaches. SoftwareX 2021; 17: 100983.
37. Alan AR, Bayındır C. The analytical solutions of long waves over geometries with linear and nonlinear variations in the form of power-law nonlinearities with solid vertical wall. Ocean Eng 2024; 295: 117031.
38. Alan AR, Bayındır C. The analytical solutions of long waves over geometries with linear and nonlinear variations in the form of power-law nonlinearities with solid inclined wall. Dyn Atmos Oceans 2024; 106: 101458.