Evaluation of seismic migration process before volcanic eruption using modified SARA method

Document Type : Research Article

Authors

1 Department of Physics, Fal.c., Islamic Azad University, Esfahan, Iran.

2 Department of Physics, Na.c., Islamic Azad University, Esfahan, Iran.

Abstract

Volcanic eruptions represent significant natural hazards, posing considerable risks to both the environment and human populations. Accurate prediction of these events remains a complex challenge due to the inherent intricacies of volcanic systems and the uncertainties inherent in their monitoring data. Traditional methods for analyzing seismic activity often necessitate the identification of seismic phases, a process that can be both time-intensive and subject to interpretation errors.
This study presents an advanced approach to the seismic monitoring utilizing Seismic Amplitude Ratio Analysis (SARA), a technique designed to infer seismic activity patterns through the examination of amplitude variations in continuous seismic data recorded across a network of stations. SARA obviates the requirement for phase identification, thereby enhancing the efficiency of volcanic activity monitoring. However, a primary limitation of SARA lies in its reliance on visual and qualitative assessment for determining the onset time and trends of amplitude ratio changes, potentially compromising precision, particularly in cases of subtle variations or low signal-to-noise ratios. To mitigate the effects of these limitations, an enhanced methodology termed Automatic Seismic Amplitude Ratio Analysis (ASARA) has been introduced. This approach leverages a time series of amplitude ratios from all station pairs and incorporates Seasonal Trend Decomposition using Loess (STL) to establish an automated anomaly detection system. ASARA offers the capability to automatically identify the onset time of changes in seismic amplitude ratios and the frequency of these anomalies, thus providing a more robust and quantitative analytical framework. A sudden increase in seismic amplitude ratios across multiple stations suggests a shift in the location of the seismic source and the migratory behavior of seismicity, which can serve as a precursor to volcanic eruptions. This method was applied to seismic data acquired from Mount Etna over a five-year period. Through the analysis of observed anomalies in amplitude ratios, the patterns of seismic activity were successfully identified and the magma migration pathway leading up to an eruption was traced. Findings indicate that an increase in seismic amplitude ratios at specific frequencies is strongly correlated with the movement of magma and the increase in pressure within the volcanic system. These changes were interpreted as evidence of seismic migration toward the surface, indicative of impending volcanic activity. Furthermore, our analyses demonstrate that the refined ASARA method exhibits a high degree of effectiveness in detecting early warning signs of volcanic unrest and forecasting the potential timing of eruptions. This study underscores the potential of ASARA as a valuable tool for enhancing the accuracy and reliability of volcanic eruption forecasts. By automating the detection of seismic anomalies and providing quantitative insights into magma dynamics, ASARA represents a significant advancement in volcanic monitoring and hazard mitigation efforts.
The evaluation results using error metrics including mean square error (MSE), root mean square error (RMSE), mean absolute error (MAE), and coefficient of determination (R2) show that the accuracy of the modified model is improved compared to the original model. Finally, a modified model was introduced to evaluate the pre-eruption seismic migration process for continuous monitoring and surveillance of volcanoes. Considering its advantages and results, this model can serve as a suitable alternative approach, especially in volcanic environments with sparse seismic station distribution, where conventional monitoring infrastructure is limited (Rasaneh et al., 2022).

Keywords

Main Subjects

References

Allard, P., Carbonnelle, J., Dajlevic, D., Le Bronec, J., Morel, P., Robe, M. C., Maurenas, J. M., Faivre-Pierret, R., Martin, D., Sabroux, J. C., & Zettwoog, P. (1991). Eruptive and diffuse emissions of CO2 from Mount Etna. Nature, 351(6325), 387–391.
Angarita, M., Grapenthin, R., Plank, S., Meyer, F. J., & Dietterich, H. (2022). Quantifying large-scale surface change using SAR amplitude images: Crater morphology changes during the 2019–2020 Shishaldin volcano eruption. Journal of Geophysical Research: Solid Earth, 127, e2022JB024344.
Battaglia, J., & Aki, K. (2003). Location of seismic events and eruptive fissures on the Piton de la Fournaise volcano using seismic amplitudes. Journal of Geophysical Research, 108(B8), 2364.
Battaglia, J., Aki, K., & Ferrazzini, V. (2005). Location of tremor sources and estimation of lava output using tremor source amplitude on the Piton de la Fournaise volcano: 1. Location of tremor sources. Journal of Volcanology and Geothermal Research, 147(3), 268–290.
Buono, G., Pappalardo, L., Petrosino, P., Annen, C., & Forni, F. (2022). New insights into the recent magma dynamics under Campi Flegrei caldera (Italy) from petrological and geochemical evidence. Journal of Geophysical Research: Solid Earth, 127, e2021JB023773.
Cabrera, L., Ardid, A., Melchor, I., Ruiz, S., Symmes‐Lopetegui, B., Báez, J. C., Delgado, F., Martinez‐Yáñez, P., Dempsey, D., & Cronin, S. (2024). Eruption forecasting model for Copahue volcano (Southern Andes) using seismic data and machine learning: A joint interpretation with geodetic data (GNSS and InSAR). Seismological Research Letters, 95(5), 2595–2610.
Caudron, C., Taisne, B., Kugaenko, Y., & Saltykov, V. (2015). Magma migration at the onset of the 2012–13 Tolbachik eruption revealed by Seismic Amplitude Ratio Analysis. Journal of Volcanology and Geothermal Research, 307, 60–67.
Chan, H.-P., Chan, Y.-C., & Sun, C.-W. (2023). Thermal pattern of Tatun volcanic system by satellite-observed temperatures and its correlation with earthquake magnitudes. Scientific Reports, 13, 19568.
Chiodini, G., Cioni, R., Guidi, M., Raco, B., & Marini, L. (1998). Soil CO2 flux measurements in volcanic and geothermal areas. Applied Geochemistry, 13(5), 543–552.
Cooper, K. M., & Kent, A. J. (2014). Rapid remobilization of magmatic crystals kept in cold storage. Nature, 506(7489), 480-483.
Coppola, D., Laiolo, M., Cigolini, C., Delle Donne, D., & Ripepe, M. (2015). Enhanced volcanic hot-spot detection using MODIS IR data: Results from the MIROVA system. In A. J. L. Harris, T. De Groeve, F. Garel, & S. A. Carn (Eds.), Detecting, modelling and responding to effusive eruptions. Geological Society.
Eibl, E., Bean, C. J., Vogfjörd, K., & Braiden, A. (2014). Persistent shallow background microseismicity on Hekla volcano, Iceland: A potential monitoring tool. Journal of Volcanology and Geothermal Research, 289, 224–237.
Endo, E. T., & Murray, T. (1991). Real-time seismic amplitude measurement (RSAM): A volcano monitoring and prediction tool. Bulletin of Volcanology, 53(7), 533–545.
Eskandari, A., Amini, S., & Masoudi, F. (2018). Monitoring thermal changes of Damavand Volcano using Landsat images. Scientific Quarterly Journal of Geosciences, 28(109), 43-54.
Farias, C., Lazo, J., Basualto, D., Saavedra, M., Muñoz-Quiroz, F., Zuñiga-Urrea, L., Martínez-Bravo, R., Huentenao-Inostroza, I., & Saéz-Opazo, R. (2023). One decade of b-value variations from volcano-tectonic seismicity as an early indicator of episodes of crisis in a volcano: The case of Copahue, Southern Andes. Frontiers in Earth Science, 11, 1181177.
Franco, L., Palma, J. L., Lara, L. E., Gil-Cruz, F., Cardona, C., Basualto, D., & San Martin, J. (2019). Eruptive sequence and seismic activity of Llaima volcano (Chile) during the 2007–2009 eruptive period: Inferences of the magmatic feeding system. Journal of Volcanology and Geothermal Research, 379, 90–105.
Frankot, R. T., & Chellappa, R. (1990). Estimation of surface topography from SAR imagery using shape from shading techniques. Artificial Intelligence, 43(3), 271–310.
Fu, P., & Rich, P. M. (2002). A geometric solar radiation model with applications in agriculture and forestry. Computers and Electronics in Agriculture, 37, 25–35.
Ganas, A., Lagios, E., Petropoulos, G., & Psiloglou, B. (2010). Thermal imaging of Nisyros volcano (Aegean Sea) using ASTER data: Estimation of radiative heat flux. International Journal of Remote Sensing, 31(15), 4033-4047.
Gudmundsson, M. T., Thordarson, T., Höskuldsson, A., Larsen, G., Björnsson, H., Prata, F., Oddson, B., Magnusson, E., Hognadóttir, T., Petersen, G., Hayward, C. L., Stevenson, J. A., & Jonsdóttir, I. (2012). Ash generation and distribution from April-May 2010 eruption of Eyjafjallajökull, Iceland. Scientific Reports, 2(572), 1-12.
Hajian, A., Nunnari, G., & Kimiaefar, R. (2023). Intelligent methods with applications in volcanology and seismology. Springer Cham. https://doi.org/10.1007/978-3-031-15432-4
Hernández, P. A., Notsu, K., Salazar, J. M., Mori, T., Natale, G., Okada, H., Virgili, G., & Shimoike, Y. (2001). Carbon dioxide degassing by advective flow from Usu volcano, Japan. Science, 292(5514), 83–86.
Howell, S. E., Small, D., Rohner, C., Mahmud, M. S., Yackel, J. J., & Brady, M. (2019). Estimating melt onset over arctic sea ice from time series multi-sensor Sentinel-1 and Radarsat-2 backscatter. Remote Sensing of Environment, 229, 48–59. 
Jaquet, O., Carniel, R., Namar, R., Cecca, M., Renard, P., Demougeot-Renard, H., & Froidevaux, R. (2005). Forecasting volcanic eruptions using geostatistical methods. In Proceedings of a conference (pp. 1-10).  
Kilburn, C. R. (2018). Forecasting volcanic eruptions: Beyond the failure forecast method. Frontiers in Earth Science, 6, 133.
Kumagai, H., Lacson Jr, R., Maeda, Y., Figueroa II, M.S., Yamashina, T., Ruiz, M., Palacios, P., Ortiz, H., & Yepes, H., (2013). Source amplitudes of volcano-seismic signals determined by the amplitude source location method as a quantitative measure of event size. Journal of Volcanology and Geothermal Research, 257, 57–71.
Kurokawa, A., Takeo, M., & Kurita, K. (2016). Two types of volcanic tremor changed with eruption style during 1986 Izu-Oshima eruption. Journal of Geophysical Research: Solid Earth, 121, 2727–2736.
Lecocq, T., Caudron, C., & Brenguier, F. (2014). MSNoise, a Python package for monitoring seismic velocity changes using ambient seismic noise. Seismological Research Letters, 85(3), 715–726.
Manga, M., & Brodsky, E. (2006). Seismic triggering of eruptions in the far field: Volcanoes and geysers. Annual Review of Earth and Planetary Sciences, 34(1), 263–291.
Manley, G. F., Pyle, D. M., Mather, T. A., Rodgers, M., Clifton, D. A., Stokell, B. G., Thompson, G., Londoño, J. M., & Roman, D. C. (2020). Understanding the timing of eruption end using a machine learning approach to classification of seismic time series. Journal of Volcanology and Geothermal Research, 401, 106917.
Marzocchi, W., Sandri, L., & Selva, J. (2008). BET_EF: A probabilistic tool for long- and short-term eruption forecasting. Bulletin of Volcanology, 70, 623–632.
Morioka, H., Kumagai, H., & Maeda, T. (2017). Theoretical basis of the amplitude source location method for volcano-seismic signals. Journal of Geophysical Research: Solid Earth, 122, 6538–6551.
Nakamura, Y. (1989). A method for dynamic characteristics estimation of subsurface using microtremor on the ground surface. Railway Technical Research Institute, Quarterly Reports, 30(1).
Nogoshi, M., & Igarashi, T. (1971). On the amplitude characteristics of microtremor (Part 2). Zisin (Journal of the Seismological Society of Japan. 2nd ser.).
Notsu, K., Mori, T., Vale, S.C.D., Kagi, H., & Ito, T., (2006). Monitoring quiescent volcanoes by diffuse CO2 degassing: Case study of Mt. Fuji, Japan. Pure and Applied Geophysics, 163(5-6), 825–835.
Nunnari, G. (2021). Clustering activity at Mt. Etna based on volcanic tremor: A case study. Earth Science Informatics, 14(6572), 1–23.
Ogiso, M., & Yomogida, K. (2015). Estimation of locations and migration of debris flows on Izu-Oshima Island, Japan, on 16 October 2013 by the distribution of high frequency seismic amplitudes. Journal of Volcanology and Geothermal Research, 298, 15–26.
Pérez, N.M., Padrón, E., Melián, G., et al. (2024). Volcanic soil gas 4He/CO2 ratio: A useful geochemical tool for real-time eruption forecasting. Scientific Reports, 14(1), 7985.
Pu, H.C., Lin, C.H., Lai, Y.C., Shih, M.H., Chang, L.C., Lee, H.F., Lee, P.T., Hong, G.T., Li, Y.H., Chang, W.Y., & Lo, C.H., (2020). Active volcanism revealed from a seismicity conduit in the long-resting Tatun Volcano Group of Northern Taiwan. Scientific Reports, 10(1), 6153.
Rasaneh, G., Hajian, A., Hodhodi, M., Kimiaefar, R., & Gambino, S. (2022). Monitoring magma migration at Mt. Etna using the Seismic Amplitude Ratio Analysis method. Annals of Geophysics, 65(4), VO429.
Richardson, J., Waite, G., & Palma, J. (2014). Varying seismic-acoustic properties of the fluctuating lava lake at Villarrica volcano, Chile. Journal of Geophysical Research: Solid Earth, 119(7), 5560–5573.
Ritz, J. F., Nazari, H., Ghassemi, A., Salamati, R., Shafei, A., Solaymani, S., & Vernant, P. (2006). Active transtension inside Central Alborz: A new insight into northern Iran–southern Caspian geodynamics. Geology, 34(6), 477–480.
Shirokov, V. A., & Zobin, V. M. (1968). Seismic phenomena connected with Piip adventive crater eruption in October-December, 1966. Bulletin of Volcanological Stations, 44. Nauka. (in Russian).
Song, S.-R., Tsao, S., & Lo, H.-J. (2000). Characteristics of the Tatun volcanic eruptions, North Taiwan: Implications for a cauldron formation and volcanic evolution. Journal of the Geological Society of China (Taiwan), 43(2), 361–377.
Taisne, B., Brenguier, F., Shapiro, N. M., & Ferrazzini, V. (2011). Imaging the dynamics of magma propagation using radiated seismic intensity. Geophysical Research Letters, 38, L04304.
Tan, C. T., Taisne, B., Neuberg, J., & Basuki, A. (2019). Real-time assessment of potential seismic migration within a monitoring network using Red-flag SARA. Journal of Volcanology and Geothermal Research, 384, 31–47. https://doi.org/10.1016/j.jvolgeores.2019.07.004.
Thordarson, T., & Self, S. (2003). Atmospheric and environmental effects of the 1783–1784 Laki eruption: A review and reassessment. Journal of Geophysical Research: Atmospheres (1984–2012), 108(AAC-7).
Tokaren, P. I. (1963). On a possibility of forecasting Bezymianniy volcano eruptions according to seismic data. Bulletin of Volcanology, 26, 379–386.
Toutin, T., & Gray, L. (2000). State-of-the-art of elevation extraction from satellite SAR data. ISPRS Journal of Photogrammetry and Remote Sensing, 55(1), 13–33.
Walsh, B., Jolly, A. D., & Procter, J. (2017). Calibrating the amplitude source location (ASL) method by using active seismic sources: An example from Te Maari volcano, Tongariro National Park, New Zealand. Geophysical Research Letters, 44, 3591–3599.
Journal of the Earth and Space Physics
Volume 51, Issue 2
online publication date: 20 September 2025
September 2025
Pages 339-352

Files

Share

How to cite

Statistics