Radon, Toplam Elektron İçeriği ve Meteorolojik Değişkenlerin Depremlere Bağlı Doğrusal ve Doğrusal Olmayan Değişimlerinin İncelenmesi: ARIMA ve Monte Carlo Modellemesi

Yıl 2024, Cilt: 19 Sayı: 1, 73 - 86, 28.03.2024

Marjan Mohammed Ghafar , Hemn Salh , Fatih Külahcı

https://doi.org/10.55525/tjst.1238962

Cited By: 1

Öz

Kuzey Anadolu Fay Zonu (Türkiye) boyunca meydana gelen bir depremin atmosferik ve yer gazlarındaki anormallikleri analiz etmek ve modellemek için Entegre Otoregresif Hareketli Ortalama (ARIMA) - Monte Carlo Simülasyonu (MCS) önerilmiştir. Depremler, Toprak radon gazı ve Toplam Elektron İçeriği (TEC) eşzamanlı anormallikler gösterdi. Bu üç parametre arasında pozitif ilişkiler vardır. Ayrıca Rn, meteoroloji ve atmosfer arasında da pozitif ilişkiler tespit edilmiştir. Ölçülen verilerin Rn-TEC-Deprem ilişkileri için önerilen ARIMA modeli ve MCS istatistiksel olarak anlamlı sonuçlar vermiştir. Bu model ve simülasyon, tespit edilmesi büyük depremlere göre daha zor olan mikrodepremlerin, özellikle iyonosferik TEC üzerindeki etkilerinde istatistiksel olarak anlamlı değişiklikler olduğunu gösterdi.

Anahtar Kelimeler

Toplam Elektron İçeriği, Deprem öncüleri, ARIMA, Monte Carlo simülasyonu

Investigation of Radon, Total Electron Content and Linear and Nonlinear Variations of Meteorological Variables Due to Earthquakes: ARIMA and Monte Carlo Modelling

Öz

An Integrated Autoregressive Moving Average (ARIMA) - Monte Carlo Simulation (MCS) is proposed to analyze and model the anomalies of atmospheric and ground gases by an earthquake along the North Anatolian Fault Zone (Türkiye). Earthquakes, Soil radon gas and Total Electron Content (TEC) showed simultaneous anomalies. There are positive relationships between these three parameters. Also, positive relations between Rn, meteorology, and atmosphere are detected. The proposed ARIMA model and MCS for the Rn-TEC-Earthquake relationships of the measured data gave statistically significant results. This model and simulation showed statistically significant changes in the effects of microearthquakes, which are more difficult to detect than large earthquakes, especially on the ionospheric TEC.

Anahtar Kelimeler

Total Electron Content, Earthquake precursors, ARIMA, Monte Carlo Simulation

Destekleyen Kurum

Firat University

Teşekkür

Firat University

Kaynakça

• Külahci F, Inceöz M, Doǧru M, Aksoy E, Baykara O. Artificial neural network model for earthquake prediction with radon monitoring. Applied Radiation and Isotopes. 67, 212-219 (2009).
• Anisimov SV, Dmitriev EM, Aphinogenov KV, Guriev AV, Kozmina AS. Variability of radon distribution in the atmospheric surface layer over the land of middle latitudes. IOP Conf Ser Earth Environ Sci. 231, (2019). https://doi.org/10.1088/1755-1315/231/1/012006
• Kulali F, Akkurt I, Özgür N. The effect of meteorological parameters on radon concentration in soil gas. Acta Phys Pol A. 132, 999-1001 (2017). https://doi.org/10.12693/APhysPolA.132.999
• Fuente M, Rábago D, Goggins J, Fuente I, Sainz C, Foley M. Radon mitigation by soil depressurisation case study: Radon concentration and pressure field extension monitoring in a pilot house in Spain. Science of the Total Environment. 695, (2019). https://doi.org/10.1016/j.scitotenv.2019.133746
• MILNE J. The California Earthquake of April 18, 1906. Nature 1910 84:2128. 84, 165-166 (1910). https://doi.org/10.1038/084165a0
• Pulinets S. The Possibility of Earthquake Forecasting: Learning from nature. IOP Publishing Ltd 2018 (2018)
• Mahmood I, M.F. Shahzad MI, Qaiser S. Investigation of atmospheric anomalies associated with Kashmir and Awaran Earthquakes. J Atmos Sol Terr Phys. 154, 75-85 (2017). https://doi.org/10.1016/j.jastp.2016.12.018
• Huang F, Li M, Ma Y, Han Y, Tian L, Yan W, Li X. Studies on earthquake precursors in China: A review for recent 50 years, (2017)
• Akyol AA, Arikan O, Arikan F. A Machine Learning-Based Detection of Earthquake Precursors Using Ionospheric Data. Radio Sci. 55, (2020). https://doi.org/10.1029/2019RS006931
• Nazaroff WW. Radon transport from soil to air. Reviews of Geophysics. 30, 137-160 (1992). https://doi.org/10.1029/92RG00055
• Hosoda M, Tokonami S, Suzuki T, Janik M. Machine learning as a tool for analysing the impact of environmental parameters on the radon exhalation rate from soil. Radiat Meas. 138, (2020). https://doi.org/10.1016/J.RADMEAS.2020.106402
• Ye Q, Singh RP, He A, Ji S, Liu C. Characteristic behavior of water radon associated with Wenchuan and Lushan earthquakes along Longmenshan fault. Radiat Meas. 76, 44-53 (2015). https://doi.org/10.1016/j.radmeas.2015.04.001
• Rikitake T. Predictions and precursors of major earthquakes: the science of macro-scopic anomalous phenomena. Terra Scientific Publishing Company (2001)
• Rikitake T. Earthquake prediction. Earth Sci Rev. 4, 245-282 (1968). https://doi.org/https://doi.org/10.1016/0012-8252(68)90154-2
• Birchard GF. Libby W.F.: Soil radon concentration changes preceding and following four magnitude 4.2–4.7 earthquakes on the San Jacinto Fault in southern California. J Geophys Res Solid Earth. 85, 3100-3106 (1980)
• King CY. Radon emanation on San Andreas Fault. Nature 1978 271:5645. 271, 516-519 (1978). https://doi.org/10.1038/271516a0
• Ulomov VI, Zakharova A.I., Nauk N.V.U.-D.A., undefined 1967. The Tashkent earthquake of April 26, 1966, and its repeated shocks. mathnet.ru.
• Külahcı F, Zeki Ş. On the Correction of Spatial and Statistical Uncertainties in Systematic Measurements of 222Rn for Earthquake Prediction. Geophysics . 35, 449-478 (2014). https://doi.org/10.1007/s10712-013-9273-8
• Tse ST, Rice JR. Crustal earthquake instability in relation to the depth variation of frictional slip properties. J Geophys Res. 91, 9452 (1986). https://doi.org/10.1029/jb091ib09p09452
• Muhammad A, Külahcı F, Salh H, Hama RA. Long Short Term Memory networks (LSTM)-Monte-Carlo simulation of near surface ionization using radon. J Atmos Sol Terr Phys. (2021). https://doi.org/10.1016/j.jastp.2021.105688
• Wattananikorn, K, Wiboolsake S. Soil gas radon as an earthquake precursor: Some considerations on data improvement. Radiat Meas. 29, 593-598 (1998). https://doi.org/10.1016/S1350-4487(98)00079-1
• Ghosh D, Deb A, Sengupta R, Patra KK, Bera S. Pronounced soil-radon anomaly-Precursor of recent earthquakes in India. Radiat Meas. 42, 466-471 (2007). https://doi.org/10.1016/j.radmeas.2006.12.008
• Kuo T, Su C, Chang C, Lin C, Cheng W, Liang H, Lewis C, Chiang C. Application of recurrent radon precursors for forecasting large earthquake near Antung, Taiwan. Radiat Meas. 45, 1049-1054 (2010). https://doi.org/10.1016/j.radmeas.2010.08.009
• Singh M, Kumar M, Jain R, Chatrath R. Radon in ground water related to seismic events. (2019)
• Virk, Walia HS. Helium/radon precursory signals of Chamoli Earthquake, India. Radiat Meas. 34, 379-384 (2001). https://doi.org/https://doi.org/10.1016/S1350-4487(01)00190-1
• Viñas R, Darwich A, Soler V, Martín-Luis MC, Quesada ML, de la Nuez J. Processing of radon time series in underground environments: Implications for volcanic surveillance in the island of Tenerife, Canary Islands, Spain. Radiat Meas. 42, 101-115 (2007). https://doi.org/10.1016/j.radmeas.2006.07.002
• Külahci F, Inceöz M, Doǧru M, Aksoy E, Baykara O. Artificial neural network model for earthquake prediction with radon monitoring. Applied Radiation and Isotopes. 67, 212-219 (2009). https://doi.org/10.1016/J.APRADISO.2008.08.003
• Inyurt S, Peker S, Mekik C. Monitoring potential ionospheric changes caused by the Van earthquake (<i>M</i><sub>w</sub>7.2). Ann Geophys. 37, 143-151 (2019). https://doi.org/10.5194/angeo-37-143-2019
• Arikan F, Arikan O, Erol CB. Regularized estimation of TEC from GPS data for certain midlatitude stations and comparison with the IRI model. Advances in Space Research. 39, 867-874 (2007). https://doi.org/10.1016/j.asr.2007.01.082
• Géodésique, des sciences naturelles. C. Mapping and predicting the Earth’s ionosphere using the Global Positioning System. (1999)
• Langley, RB. Monitoring the Ionosphere and Neutral Atmosphere with GPS.
• Inyurt S, Peker S, Mekik C. Monitoring potential ionospheric changes caused by the Van earthquake . Ann Geophys. 37, 143-151 (2019). https://doi.org/10.5194/angeo-37-143-2019
• Viti M, Mantovani E, Cenni N, Vannucchi A. Interaction of seismic sources in the Apennine belt. Physics and Chemistry of the Earth, Parts A/B/C. 63, 25-35 (2013). https://doi.org/https://doi.org/10.1016/j.pce.2013.03.005
• Hammerstrom JA, Cornely PR. Total Electron Content (TEC) Variations and Correlation with Seismic Activity over Japan. (2016). https://doi.org/10.22186/JYI.31.4.13-16
• Namgaladze AA, Zolotov OV, Karpov MI, Romanovskaya YV. Manifestations of the earthquake preparations in the ionosphere total electron content variations. Nat Sci (Irvine). 4, 848-855 (2012). https://doi.org/10.4236/NS.2012.411113
• Li M, Parrot M. Statistical analysis of the ionospheric ion density recorded by DEMETER in the epicenter areas of earthquakes as well as in their magnetically conjugate point areas. Advances in Space Research. 61, 974-984 (2018). https://doi.org/https://doi.org/10.1016/j.asr.2017.10.047
• Liu J.Y., Chen C.H., Chen Y.I., Yang W.H., Oyama K.I., Kuo K.W. A statistical study of ionospheric earthquake precursors monitored by using equatorial ionization anomaly of GPS TEC in Taiwan during 2001–2007. J Asian Earth Sci. 39, 76-80 (2010). https://doi.org/https://doi.org/10.1016/j.jseaes.2010.02.012
• Li M, Parrot M. Statistical analysis of the ionospheric ion density recorded by DEMETER in the epicenter areas of earthquakes as well as in their magnetically conjugate point areas. Advances in Space Research. 61, 974-984 (2018). https://doi.org/https://doi.org/10.1016/j.asr.2017.10.047
• Şengör AMC, Zabcı C. The North Anatolian Fault and the North Anatolian Shear Zone. World Geomorphological Landscapes. 481-494 (2019). https://doi.org/10.1007/978-3-030-03515-0_27
• Allen CR. Active Faulting in Northern Turkey. (1969)
• Ministry of interior DAEMP. Disaster And Emergency Coordination Board, https://en.afad.gov.tr/disaster-and-emergency-coordination-board
• Thomas D.M., Cotter J.M., Holford D. Experimental design for soil gas radon monitoring. Journal of Radioanalytical and Nuclear Chemistry Articles. 161, 313-323 (1992). https://doi.org/10.1007/BF02040478
• Turkish State Meteorological Service Official Web Sites, https://www.mgm.gov.tr/eng/forecast-cities.aspx
• Boğaziçi University. Earthquake Catalog - BOUN KOERI Regional Earthquake-Tsunami Monitoring Center, http://www.koeri.boun.edu.tr/sismo/2/earthquake-catalog/
• Sezen U, Arikan F, Arikan O, Ugurlu O, Sadeghimorad A. Online, automatic, near‐real time estimation of GPS‐TEC: IONOLAB‐TEC. Space Weather. 11, 297-305 (2013)
• Arikan F, Deviren MN, Lenk O, Sezen U, Arikan O. Observed Ionospheric Effects of 23 October 2011 Van, Turkey Earthquake. Geomatics, Natural Hazards and Risk. 3, (2012). https://doi.org/10.1080/19475705.2011.638027
• Tuna H, Arikan O, Arikan F. Model based Computerized Ionospheric Tomography in space and time. Advances in Space Research. 61, (2018). https://doi.org/10.1016/j.asr.2018.01.031
• Arikan F, Sezen U, Toker C, Artuner H. Improved IONOLAB-TEC Space Weather Service GIM-TEC. (2015)
• Gulyaeva TL, Arikan F, Stanislawska I. Earthquake aftereffects in the Equatorial Ionization Anomaly region under geomagnetic quiet and storm conditions. Advances in Space Research. 60, 406-418 (2017). https://doi.org/10.1016/j.asr.2017.03.039
• Devi̇ren MN, Arikan F. IONOLAB-MAP. An automatic spatial interpolation algorithm for total electron content. Turkish Journal of Electrical Engineering and Computer Sciences. 26, 1933-1945 (2018). https.//doi.org/10.3906/elk-1611-231
• Karatay S, Arikan F, Arikan O. Investigation of total electron content variability due to seismic and geomagnetic disturbances in the ionosphere. Radio Sci. 45, (2010). https://doi.org/10.1029/2009RS004313
• Arikan F, Shukurov S, Tuna H, Arikan O, Gulyaeva TL. Performance of GPS slant total electron content and IRI-Plas-STEC for days with ionospheric disturbance. Geod Geodyn. 7, 1-10 (2016). https://doi.org/10.1016/j.geog.2015.12.009
• Salh H, Külahcı F, Aközcan S. A mobile simulation and ARIMA modeling for prediction of air radiation dose rates. Journal of Radioanalytical and Nuclear Chemistry 2021 328:3. 328, 889-901 (2021). https://doi.org/10.1007/S10967-021-07726-8
• Rycroft MJ, Nicoll KA, Aplin KL, Harrison RG. Recent advances in global electric circuit coupling between the space environment and the troposphere. J Atmos Sol Terr Phys. 90-91, 198-211 (2012). https://doi.org/10.1016/j.jastp.2012.03.015
• Ješkovský M, Javorník A, Breier R, Slučiak J, Povinec PP. Experimental and Monte Carlo determination of HPGe detector efficiency. J Radioanal Nucl Chem. 322, 1863-1869 (2019). https://doi.org/10.1007/s10967-019-06856-4
• Abdolhamidzadeh B, Abbasi T, Rashtchian D, Abbasi SA. A new method for assessing domino effect in chemical process industry. J Hazard Mater. 182, 416-426 (2010). https://doi.org/https://doi.org/10.1016/j.jhazmat.2010.06.049
• Zhao Y, Nielsen CP, Lei Y, McElroy MB, Hao J. Quantifying the uncertainties of a bottom-up emission inventory of anthropogenic atmospheric pollutants in China. Atmos Chem Phys. 11, 2295-2308 (2011). https://doi.org/10.5194/acp-11-2295-2011
• Aalizadeh R, Nika MC, Thomaidis NS. Development and application of retention time prediction models in the suspect and non-target screening of emerging contaminants. J Hazard Mater. 363, 277-285 (2019)
• Külahcı F. Environmental Distribution and Modelling of Radioactive Lead (210). A Monte Carlo Simulation Application. 15-32 (2020). https://doi.org/10.1007/978-3-030-21638-2_2
• Muhammad A, Külahcı F, Salh H, Hama Rashid PA. Long Short Term Memory networks (LSTM)-Monte-Carlo simulation of soil ionization using radon. J Atmos Sol Terr Phys. 221 105688 (2021). https://doi.org/10.1016/j.jastp.2021.105688
• Külahcı F, Aközcan S, Günay O. Monte Carlo simulations and forecasting of Radium-226, Thorium-232, and Potassium-40 radioactivity concentrations. J Radioanal Nucl Chem. 324, 55-70 (2020). https://doi.org/10.1007/s10967-020-07059-y
• Lindmark A, Rosen B. Radon in soil gas Exhalation tests and in situ measurements. Science of The Total Environment. 45, 397-404 (1985). https://doi.org/https.//doi.org/10.1016/0048-9697(85)90243-8
• Schery SD, Gaeddert DH. Measurements of the effect of cyclic atmospheric pressure variation on the flux of 222RN from the soil. Geophys Res Lett. 9, 835-838 (1982). https://doi.org/10.1029/GL009I008P00835
• Baskaran M. Physical, Chemical and Nuclear Properties of Radon: An Introduction. Radon: A Tracer for Geological Geophysical and Geochemical Studies. 1-14 (2016). https://doi.org/10.1007/978-3-319-21329-3_1
• Clements WE, Wilkening MH. Atmospheric pressure effects on 222Rn transport across the Earth-air interface. Journal of Geophysical Research (1896-1977). 79, 5025-5029 (1974). https://doi.org/https://doi.org/10.1029/JC079i033p05025
• Nazaroff W, Nero A. Radon and its decay products in indoor air. (1988)
• Tariq MA, Shah M, Hernández-Pajares M, Iqbal T. Pre-earthquake ionospheric anomalies before three major earthquakes by GPS-TEC and GIM-TEC data during 2015–2017. Advances in Space Research. 63, 2088-2099 (2019). https://doi.org/https://doi.org/10.1016/j.asr.2018.12.028
• Shah MT, Ahmad MA, Naqvi J, Jin S. Seismo ionospheric anomalies before the 2007 M7.7 Chile earthquake from GPS TEC and DEMETER. J Geodyn. 127, 42-51 (2019). https://doi.org/https://doi.org/10.1016/j.jog.2019.05.004