بررسی فرونشست شمال شرق ایران از طریق برآورد بردار سرعت و عدم‌قطعیت ایستگاه‌های دائمی GPS

نوع مقاله : مقاله پژوهشی

نویسندگان

1 نویسنده مسئول، گروه مهندسی نقشه‌برداری، دانشکده علوم پایه و فنی مهندسی، واحد تاکستان، دانشگاه آزاد اسلامی، تاکستان، ایران. رایانامه: sa.ghasemi@iau.ac.ir

2 گروه ژئودزی و هیدروگرافی، دانشکده مهندسی نقشه‌برداری و اطلاعات مکانی، پردیس دانشکده‌های فنی، دانشگاه تهران، تهران، ایران. رایانامه: ardalan@ut.ac.ir

3 گروه ژئودزی و مهندسی نقشه‌برداری، دانشکده مهندسی عمران، دانشگاه تفرش، تفرش، ایران. رایانامه: karimi@tafreshu.ac.ir

چکیده

این پژوهش ارائه دهنده برآوردی جدید برای فرونشست شمال شرق ایران از طریق آنالیز سری‌های زمانی 31 ایستگاه GPS شبکه خراسان به‌عنوان بخشی از شبکه ایستگاه‌های دائمی ژئودینامیک و GNSS ایران (IPGN) واقع در شمال شرق ایران از ابتدای سال 2006 تا پایان سال 2016 است. برآورد یاد شده، حاصل از بردار سرعت ایستگاه‌های شبکه در چارچوب ITRF2014 بر مبنای آنالیز سری زمانی در دو بخش مدل تابعی و مدل تصادفی است. آنالیز مدل تابعی طی مراحل کشف پرش‌ها، تعیین مدل حرکت، کشف اشتباهات و آزمون آماری در قالب یک فرآیند تکرار انجام شده است. در آنالیز مدل تصادفی، همبستگی مکانی به روش پشته‌سازی وزن‌دار و همبستگی زمانی به روش برآورد ماکزیمم درست‌نمایی (MLE) و در نظر گرفتن مدل نویزی ترکیب نویز سفید و نویز فلیکر بررسی می‌شود. نتایج تحقیق نشان می‌دهد که: (1) هر یک از ایستگاه‌های این شبکه در بازه زمانی 11 ساله به‌طور متوسط دارای 9 پرش غیر لرزه‌ای بوده‌اند. (2) فیلترینگ مکانی، میانگین نرم بردار باقیمانده‌های مؤلفه‌های شرقی، شمالی و قائم را به ترتیب 17/30، 40/29 و 90/17 درصد کاهش می‌دهد. (3) پنج ایستگاه GOLM، GRGN، NFRD، NISH و SHRN دارای فرونشست غیرطبیعی بوده و سه ایستگاه GOLM، NFRD و NISH که به یکدیگر نزدیک‌اند نشان از یک فرونشست منطقه‌ای دارند. (4) در ایستگاه GRGN علاوه بر فرونشست زیاد، حرکت شتاب‌دار و سیگنال‌های پریودیک بزرگ نیز در مؤلفه قائم ایستگاه مشاهده شده و لذا لازم است برای آگاهی از علت این رفتار ارتفاعی پوسته زمین، در محدوده این ایستگاه داده‌های بیشتری از طریق نصب ایستگاه‌های دائمی جدید، جمع‌آوری شود.

کلیدواژه‌ها

موضوعات

عنوان مقاله [English]

Investigation of subsidence in the northeastern of Iran by estimating the velocity vector and uncertainty of permanent GPS stations

نویسندگان [English]

  • Seyed Amin Ghasemi Khalkhali 1
  • Alireza Azmoudeh Ardalan 2
  • Roohollah Karimi 3
1 Corresponding Author, Department of Surveying Engineering, Faculty of Basic Sciences and Technical Engineering, Takestan Branch, Islamic Azad University, Takestan, Iran. E-mail: sa.ghasemi@iau.ac.ir
2 Department of Geodesy and Hydrography, School of Surveying and Geospatial Engineering, College of Engineering, University of Tehran, Tehran, Iran. E-mail: ardalan@ut.ac.ir
3 Department of Geodesy and Surveying Engineering, Faculty of Civil Engineering, Tafresh University, Tafresh, Iran. E-mail: karimi@tafreshu.ac.ir
چکیده [English]

This study presents a new estimate for subsidence in the northeast of the country through the time series analysis of 11-year (from the beginning of 2006 till the end of 2016) of 31 stations of the Khorasan network, as part of the Iranian Permanent Geodynamic & GNSS Network (IPGN), located in northeastern Iran. The mentioned estimation is obtained from the velocity vector of network stations in the International Terrestrial Reference Frame of ITRF2014 based on time series analysis in two realms, i.e., deterministic model analysis and stochastic model analysis. The deterministic model analysis is comprised of jump detection, determination of station motion model parameters, the study of station trend, outlier detection, and statistical significance test to check the jumps magnitude. Due to the interdependence of these steps, the related calculations are performed iteratively. Noise analysis includes two phases, namely, spatial filtering and temporal filtering. In the first phase, the Common Mode Error (CME) parameter is calculated using the weighted stacking method and taking into account the data correlation coefficient and stations distance. In the second phase, using the maximum likelihood estimation (MLE) method, the optimal noise model is derived as a combination of white noise and flicker noise. As a result, the reliable velocities of the stations (resulting from a complete analysis of the deterministic model) and their realistic uncertainties (resulting from the selection of optimal stochastic models) are calculated. Based on this study we found that: (1) Each station during the 11-year study period has on average nine jumps, all of which are of non-seismic origin. (2) Including the data from all IPGN stations in spatial filtering, leads to better results and on average reduces the norm of post-fit residual vectors for east, north, and up coordinate components by 30.17%, 29.40%, and 17.90%, respectively. (3) Concerning the temporal filtering, we found that the noise of the up-component is significantly higher than the noise of the horizontal components. (4) Stochastic model analysis showed the realistic uncertainties of the east, north, and up components are 4.33, 4.44, and 3.70 times, respectively, greater than the uncertainties which are derived without application of stochastic modeling (optimistic uncertainties). (5) The vertical velocity of most of stations was found to be in the normal range of -5 to 5 mm/yr. (6) Five stations, namely, GOLM, GRGN, NFRD, NISH, and SHRN are having anomalous subsidence (up to 9 mm/yr). (7) The proximity of the three stations GOLM, NFRD, and NISH allows us to infer a regional subsidence for the area of their location. (8) The station GRGN, in addition to anomalous subsidence, shows distinctive features such as the nonlinear trend as well as large periodic signals in the up component of the station. Therefore, to find the reason for such vertical behavior of the earth's crust more permanent GNSS stations must be established in that area. (9) The estimated parameters of periodic signal of the stations demonstrate that the annual and draconitic year signals have the largest amplitudes in the three coordinate components. In addition, amplitude of the periodic signals of the up component is significantly larger than the other components.

کلیدواژه‌ها [English]

  • Subsidence
  • Time series Analysis
  • Northeastern of Iran
  • Spatial Filtering
  • Jump detection

مراجع

Altamimi, Z., Rebischung, P., Métivier, L., & Collilieux, X. (2016). ITRF2014: A new release of the International Terrestrial Reference Frame modeling nonlinear station motions. Journal of Geophysical Research: Solid Earth, 121(8), 6109-6131.
Amiri-Simkooei, A. (2016). Non-negative least-squares variance component estimation with application to GPS time series. Journal of Geodesy, 90(5), 451-466.
Amiri-Simkooei, A., Hosseini-Asl, M., Asgari, J., & Zangeneh-Nejad, F. (2019). Offset detection in GPS position time series using multivariate analysis. GPS solutions, 23(1), 13.
Amiri-Simkooei, A., Mohammadloo, T., & Argus, D. (2017). Multivariate analysis of GPS position time series of JPL second reprocessing campaign. Journal of Geodesy, 91(6), 685-704.
An, J., Zhang, B., Ai, S., Wang, Z., & Feng, Y. (2021). Evaluation of vertical crustal movements and sea level changes around Greenland from GPS and tide gauge observations. Acta Oceanologica Sinica, 40(1), 4-12.
Barzaghi, R., & Borghi, A. (2018). Theory of second order stationary random processes applied to GPS coordinate time-series. GPS Solutions, 22(3), 86.
Borghi, A., Aoudia, A., Riva, R. E., & Barzaghi, R. (2009). GPS monitoring and earthquake prediction: a success story towards a useful integration. Tectonophysics, 465(1-4), 177-189.
Bevis, M., & Brown, A. (2014). Trajectory models and reference frames for crustal motion geodesy. Journal of Geodesy, 88(3), 283-311.
Birhanu, Y., Williams, S., Bendick, R., & Fisseha, S. (2018). Time dependence of noise characteristics in continuous GPS observations from East Africa. Journal of African Earth Sciences, 144, 83-89.
Blewitt, G., Hammond, W. C., & Kreemer, C. (2018). Harnessing the GPS data explosion for interdisciplinary science. Eos, 99, 1-2.
Bogusz, J., Gruszczynski, M., Figurski, M., & Klos, A. (2015). Spatio-temporal filtering for determination of common mode error in regional GNSS networks. Open Geosciences, 7(1).
Bogusz, J., & Klos, A. (2016). On the significance of periodic signals in noise analysis of GPS station coordinates time series. GPS solutions, 20(4), 655-664.
Bogusz, J., Klos, A., & Pokonieczny, K. (2019). Optimal Strategy of a GPS Position Time Series Analysis for Post-Glacial Rebound Investigation in Europe. Remote Sensing, 11(10), 1209.
Bruni, S., Zerbini, S., Raicich, F., Errico, M., & Santi, E. (2014). Detecting discontinuities in GNSS coordinate time series with STARS: case study, the Bologna and Medicina GPS sites. Journal of Geodesy, 88(12), 1203-1214.
Dehghani, M., Valadan Zoej, M. J., Entezam, I., Mansourian, A., & Saatchi, S. (2009). InSAR monitoring of progressive land subsidence in Neyshabour, northeast Iran. Geophysical Journal International, 178(1), 47-56.
Gazeaux, J., Williams, S., King, M., Bos, M., Dach, R., Deo, M., Moore, A.W., Ostini, L., Petrie, E., Roggero, M., & Teferle, F.N. (2013). Detecting offsets in GPS time series: First results from the detection of offsets in GPS experiment. Journal of Geophysical Research: Solid Earth, 118(5), 2397-2407.
Graham, S. E., Loveless, J. P., & Meade, B. J. (2018). Global plate motions and earthquake cycle effects. Geochemistry, Geophysics, Geosystems, 19(7), 2032-2048.
Gruszczynski, M., Klos, A., & Bogusz, J. (2016). Orthogonal transformation in extracting of common mode errors from continuous GPS networks. Acta Geodynamica et Geomaterialia, 13(3), 291-298.
Hammond, W. C., Blewitt, G., Kreemer, C., & Nerem, R. S. (2021). GPS imaging of global vertical land motion for studies of sea level rise. Journal of Geophysical Research: Solid Earth, 126(7), e2021JB022355.
He, X., Hua, X., Yu, K., Xuan, W., Lu, T., Zhang, W., & Chen, X. (2015). Accuracy enhancement of GPS time series using principal component analysis and block spatial filtering. Advances in Space Research, 55(5), 1316-1327.
He, X., Montillet, J.-P., Fernandes, R., Bos, M., Yu, K., Hua, X., & Jiang, W. (2017). Review of current GPS methodologies for producing accurate time series and their error sources. Journal of Geodynamics, 106, 12-29.
Herring, T., King, R., & McClusky, S. (2015). Introduction to GAMIT/GLOBK, release 10.6. Mass. Inst. of Technol., Cambridge.
https://ncc.gov.ir/
Jiang, W., Ma, J., Li, Z., Zhou, X., & Zhou, B. (2018). Effect of removing the common mode errors on linear regression analysis of noise amplitudes in position time series of a regional GPS network & a case study of GPS stations in Southern California. Advances in Space Research, 61(10), 2521-2530.
Khalkhali, S. A. G., Ardalan, A. A., & Karimi, R. (2021). A time series analysis of permanent GNSS stations in the northwest network of Iran. Annals of Geophysics, 64(2), GD218-GD218.
Khorrami, F., Vernant, P., Masson, F., Nilfouroushan, F., Mousavi, Z., Nankali, H., Saadat, S.A., Walpersdorf, A., Hosseini, S., Tavakoli, P., & Aghamohammadi, A. (2019). An up-to-date crustal deformation map of Iran using integrated campaign-mode and permanent GPS velocities. Geophysical Journal International, 217(2), 832-843.
Khorrami, M., Abrishami, S., & Maghsoudi, Y. (2020). Mashhad subsidence monitoring by interferometric synthetic aperture radar technique. Amirkabir Journal of Civil Engineering, 51(6), 1187-1204.
Klos, A., & Bogusz, J. (2017). An evaluation of velocity estimates with a correlated noise: case study of IGS ITRF2014 European stations. Acta Geodynamica et Geomaterialia, 14(3), 255-265.
Klos, A., Bos, M. S., & Bogusz, J. (2018a). Detecting time-varying seasonal signal in GPS position time series with different noise levels. GPS solutions, 22(1), 21.
Klos, A., Olivares, G., Teferle, F. N., Hunegnaw, A., & Bogusz, J. (2018b). On the combined effect of periodic signals and colored noise on velocity uncertainties. GPS solutions, 22(1), 1.
Li, W., Li, F., Zhang, S., Lei, J., Zhang, Q., & Yuan, L. (2019). Spatiotemporal Filtering and Noise Analysis for Regional GNSS Network in Antarctica Using Independent Component Analysis. Remote Sensing, 11(4), 386.
Mao, A., Harrison, C. G., & Dixon, T. H. (1999). Noise in GPS coordinate time series. Journal of Geophysical Research: Solid Earth, 104(B2), 2797-2816.
Motagh, M., Walter, T. R., Sharifi, M. A., Fielding, E., Schenk, A., Anderssohn, J., & Zschau, J. (2008). Land subsidence in Iran caused by widespread water reservoir overexploitation. Geophysical Research Letters, 35(16).
Mousavi, Z., Walpersdorf, A., Walker, R.T., Tavakoli, F., Pathier, E., Nankali, H.R.E.A., Nilfouroushan, F., & Djamour, Y. (2013). Global Positioning System constraints on the active tectonics of NE Iran and the South Caspian region. Earth and Planetary Science Letters, 377, 287-298.
Nikolaidis, R. (2004). Observation of geodetic and seismic deformation with the Global Positioning System.
Ostanciaux, E., Husson, L., Choblet, G., Robin, C., & Pedoja, K. (2012). Present-day trends of vertical ground motion along the coast lines. Earth-Science Reviews, 110(1-4), 74-92.
Ray, J., Altamimi, Z., Collilieux, X., & van Dam, T. (2008). Anomalous harmonics in the spectra of GPS position estimates. GPS solutions, 12(1), 55-64.
Riddell, A. R. (2021). Vertical land motion of the Australian plate (Doctoral dissertation, University of Tasmania).
Santamaría‐Gómez, A., Bouin, M. N., Collilieux, X., & Wöppelmann, G. (2011). Correlated errors in GPS position time series: Implications for velocity estimates. Journal of Geophysical Research: Solid Earth, (116(B1.
Shirzaei, M., Freymueller, J., Törnqvist, T. E., Galloway, D. L., Dura, T., & Minderhoud, P. S. (2021). Measuring, modelling and projecting coastal land subsidence. Nature Reviews Earth & Environment, 2(1), 40-58.
Teferle, F. N., Williams, S. D., Kierulf, H. P., Bingley, R. M., & Plag, H.-P. (2008). A continuous GPS coordinate time series analysis strategy for high-accuracy vertical land movements. Physics and Chemistry of the Earth, Parts A/B/C, 33(3-4), 205-216.
Tobita, M. (2016). Combined logarithmic and exponential function model for fitting postseismic GNSS time series after 2011 Tohoku-Oki earthquake. Earth, Planets and Space, 68(1), 1-12.
Tourani, M., Caglayan, A., Saber, R., Isik, V., & Chitea, F. (2021). Determination of land subsidence in gorgan plain with insar method (Golestan, NE Iran). book: geoscience for society, education and environment.
Varbla, S., Ågren, J., Ellmann, A., & Poutanen, M. (2022). Treatment of tide gauge time series and marine GNSS measurements for vertical land motion with relevance to the implementation of the Baltic Sea Chart Datum 2000. Remote Sensing, 14(4), 920.
Vernant, P., Nilforoushan, F., Hatzfeld, D., Abbassi, M., Vigny, C., Masson, F., . . . Bayer, R. (2004). Present-day crustal deformation and plate kinematics in the Middle East constrained by GPS measurements in Iran and northern Oman. Geophysical Journal International, 157(1), 381-398.
Walpersdorf, A., Manighetti, I., Mousavi, Z., Tavakoli, F., Vergnolle, M., Jadidi, A., Hatzfeld, D., Aghamohammadi, A., Bigot, A., Djamour, Y., & Nankali, H. (2014). Present-day kinematics and fault slip rates in eastern Iran, derived from 11 years of GPS data. Journal of Geophysical Research: Solid Earth, 119(2), 1359-1383.
Wdowinski, S., Bock, Y., Zhang, J., Fang, P., & Genrich, J. (1997). Southern California permanent GPS geodetic array: Spatial filtering of daily positions for estimating coseismic and postseismic displacements induced by the 1992 Landers earthquake. Journal of Geophysical Research: Solid Earth, 102(B8), 18057-18070.
Williams, S.D., Bock, Y., Fang, P., Jamason, P., Nikolaidis, R.M., Prawirodirdjo, L., Miller, M., & Johnson, D.J. (2004). Error analysis of continuous GPS position time series. Journal of Geophysical Research: Solid Earth, 109(B3).
Zhu, Z., Zhou, X., Deng, L., Wang, K., & Zhou, B. (2017). Quantitative analysis of geophysical sources of common mode component in CMONOC GPS coordinate time series. Advances in Space Research, 60(12), 2896-2909.
فیزیک زمین و فضا
دوره 49، شماره 1
تاریخ انتشار الکترونیکی: 24 خرداد 1402
خرداد 1402
صفحه 35-51

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