تحلیل فضایی مخاطرات محیطی

تحلیل فضایی مخاطرات محیطی

ارزیابی و مقایسه دقت داده‌های گسلی و لرزه‌ای در تحلیل فرکتالی زمین‌ساخت زاگرس شمال غرب

نویسندگان
دانشگاه تهران
چکیده
تغییرات مکانی پارامترهای فرکتالی عامل مهمی برای بررسی وضعیت زمین‌ساختی است. در هندسه فرکتال، بعد‌ فرکتال در هر مقیاسی، حفظ می‌شود که بیانگر خاصیت اصلی فرکتال است. در این تحقیق به منظور بررسی کارایی روش فرکتال در بررسی زمینساخت زاگرس شمال غرب، به مقایسه و آزمون یکسان بودن نتایج ابعاد فرکتالی گسلها در نقشههایی با مقیاسهای مختلف، و زمینلرزههایی با طول دوره و جزئیات و مقیاسهای مختلف بزرگا پرداخته شد. برای این منظور از 6 لایه اطلاعاتی استفاده گردید و ابعاد فرکتالی آنها به روش مربعشمار محاسبه و نتایج بعد فرکتالی آنها مورد تحلیل قرار گرفتهاند. دو دسته داده گسلی مستقیماً و دو دسته داده زمینلرزه (پژوهشگاه بینالمللی زلزله و مؤسسه ژئوفیزیک) یکبار بدون تغییر و دیگر بار برای افزایش دقت با احتساب بزرگای کمال وارد محاسبات شدند. نتایج نشان میدهد که ابعاد هندسی گسلهای منطقه فرکتالی است و تنها تفاوت در ثبت جزئیات گسلها سبب تغییری جزئی در ترتیب مناطق فعال در دو مقیاس شده است و نتایج دو مقیاس تقریباً مشابه است. در مورد دادههای لرزهای نتایج دادههای از 1900 تا 2020 که از تعداد کمتر زمینلرزه و مقیاس مختلف ثبت بزرگا برخوردارند تطبیقی با واقعیت نشان نمیدهند، در صورتی که میتوان به نتایج ابعاد فرکتالی دادههای زمینلرزههای منحصراً سده 20 که از نظر دقت و مقیاس ثبت بزرگا یکسان هستند، اعتماد نمود. نتایج آن، فعالترین منطقه از نظر بعد فرکتالی را محدوده غرب کرمانشاه نشان میدهد و شاهد آن تمرکز زمینلرزههایی با بزرگای بالاتر به ویژه زمین‌لرزه اخیر کرمانشاه با بزرگای 7/3 است که تلفات فراوانی به دنبال داشت.
کلیدواژه‌ها

عنوان مقاله English

Evaluation and comparison of the accuracy of fault and seismic data in fractal analysis of northwest Zagros tectonic

نویسندگان English

Abolghasem Goorabi
Mohammad Zamanzadeh
Mojtaba Yamani
Parisa Pirani
University of Tehran
چکیده English





Evaluation and comparison of the accuracy of fault and seismic data in fractal analysis of northwest Zagros tectonic

Introduction

Complexity of natural processes especially tectonic processes that shape landscapes cannot be evaluated by classic geometry. In comparison with integer dimension of Euclidean space, fractal geometry can analyze features with non-integer dimension (Turcotte, 1977:121). Fractal behavior in such features shows self-similarity that this component is independent of the accuracy of investigation (Baas, 2002, 311). In fact, fractal dimension, is scale-invariant (Phillips, 2002, 144). Spatial variations of fractal parameters are an important factor in studying the tectonic state of regions. By determining the fractal dimension of Linear structures such as faults, it is possible to compare their geometry disorder (Suk moon et al, 1996:5). This parameter affects seismic behavior of fault because earthquake is an event related to faulting (Bachmanov, et al, 2012: 221) and Their concentration in an area indicates tectonic activity. In this research we performed fractal analysis using box counting method on fault and seismic data of northwest of Zagros about different scales of fault and different time periods of earthquake epicenters of two organizations with various detail to find and examine their fractal behavior by fractal dimension.

Methods

Data in this research can be divided to three clusters: 1. Fault lines of two scales of geology maps (1:100000 and 1:250000), 2. Earthquake epicenters of two periods of times prepared by two organizations (20 century data of Institute of Geophysics and 1900-2020 data of International Institute of Earthquake Engineering and Seismology) and 3. The second cluster with exert of Magnitude of completeness of earthquakes that show the minimum magnitude above which the data in the earthquake catalog is complete. Fractal analysis applied on these data by box counting method. To achieve this goal firstly, under study area divided to 6 boxes that contain main fault trends horizontally and vertically (A: folded Zagros in west of Kermanshah, B: faulted Zagros around Kermansha and east of kermansha, C: folded Zagros near mountain front fault, D: An area between faulted and folded Zagros near Khoramabad, E: Area around Balarud fault and F: An area between Balarud and mountain front fault to faulted Zagros). To calculate fractal dimension of fault lines and distribution of earthquake epicenters, box counting method suggested by Turcotte (1997) were applied by using Hausdorff dimension, which in two quantity of size (side length of grids) and number (number of grid boxes containing earthquake epicenter or fault) are used to calculate FD (total fractal dimension) value (Schuller et al, 2001: 3). Relation between reciprocal of side length (quantity of size) and number of boxes containing point and linear features (quantity of Number) was drawn Logarithmically as a linear regression in Excel that shows fractal dimension.

Result and discussion

Larger values of fractal dimension indicate greater geometric disorder (Sukmono et al., 1996: 5). Analysis of faults of two scales represent that faults geometry is fractal and the amount of FD for scale of 1:100000 compared with scale of 1:250,000 is larger but their result approximately is same. The FD values for both scales are locate between 1 and 2 that expresses development of the fractal community of faults has a linear trend. On the other hand, for earthquakes, increase in FD values shows that earthquakes are not clustered and are distributed homogeneously (Oncel & Wilson, 2002: 339) along a line in understudy area. Calculated number-size values for faults and earthquakes represent both partial and popular FD changes. Based on partial FD, two populations can be classified: (a) Background with FD larger than popular FD; (b) Threshold with FD lower than popular FD.

Conclusion

Fractal analysis of faults of two scales of geology maps reveals that the order of active areas with high FD values in both scales are same but due to different details of faults in geology maps of geology survey and oil company, in scale of 1:100000 area labeled B and in scales of 1:250000 area labeled A is the most tectonically active region, however, area labeled E in both scales has lowest value. The order of active areas based on FD values for earthquake epicenters of 1900-2021 data of geophysics institute do not support other results because area labeled C with low density of faults and earthquake epicenters is in the first order and area labeled A is on the contrary of it. However, FD results of 20 century earthquake epicenters with exert of magnitude of completeness are reliable and higher magnitude of earthquakes spatially recent Ezgeleh earthquake in area labeled A is its evidence.

Keywords: Fractal, Tectonic, Northwest Zagros, Fault, Earthquake

کلیدواژه‌ها English

Fractal
Tectonic
Northwest Zagros
Fault
Earthquake
Angeles, G., G. Perillo and J. Pierini. 2004. Fractal analysis of tidal channels in the Bahı́a Blanca Estuary (Argentina). Geomorphology, 57: 263-274. DOI 10.1016/S0169-555X(03)00106-5.
Baas, A.C.W. 2002. Chaos, Fractals and Self-Organization in Coastal Geomorphology: Simulating Dune Landscapes in Vegetated Environments. Geomorphology, 48: 309-328. DOI 10.1016/S0169-555X(02)00187-3
Berberian, M. 1995. Masterblind thrust faults hidden under the Zagros folds: active basement tectonics and surface morphotectonics. Tectonophysics, 241: 193-224. DOI 10.1016/0040-1951(94)00185-C
Bhattacharya, P., B.K. Chakrabarti and Kamal. 2011. A fractal model of earthquake occurrence: Theory, simulations and comparisons with the aftershock data. Journal of Physics: Conference Series, 319: 1-37. DOI 10.1088/1742-6596/319/1/012004
Blanc, E. J. P., M. B. Allen, S. Inger, and H. Hassani. 2003. Structural styles in the Zagros simple folded zone, Iran. Journal of the Geological Society (London), 160: 401–412. DOI 10.1144/0016-764902-110
Bodri, B. 1993. A fractal model for seismicity at Izu-Tokai region, central Japan. Earth Sciences, 1: 539-546. DOI 10.1142/S0218348X93000563
Hessami, K., H.A. Koyi, and C.J. Talbot. 2001. The significance of strike‐slip faulting in the basement of the Zagros fold and thrust belt. Journal of petroleum Geology, 24: 5-28. DOI 10.1111/j.1747-5457.2001.tb00659.x
Hirata, T. 1989. Fractal dimension of fault systems in Japan: Fractal structure in rock fracture geometry at various scales. pure and applied geophysics, 131: 157–170. DOI 10.1007/BF00874485
Hui, C., C. Cheng, L. Ning, and J. Yang. 2020. Multifractal Characteristics of Seismogenic Systems and b Values in the Taiwan Seismic Region. International Journal of Geo-Information, 9: 1-15. DOI 10.3390/ijgi9060384
Jackson, J., and D. Mckenzie. 1984. Active tectonics of the Alpine-Himalayan Belt between western Turkey and Pakistan. Geophysical Journal of the Royal Astronomical Society, 77: 185–264. DOI 10.1111/j.1365-246X.1984.tb01931.x
Lei, X., and K. Kusunose. 1999. Fractal structure and characteristic scale in the distributions of earthquake epicentres, active faults and rivers in Japan. Geophysical Journal International, 39: 754–762. DOI 10.1046/j.1365-246x.1999.00977.x
Mandelbrot, B.B. 1982. The Fractal Geometry of Nature. W.H. Freeman and Company, New York..
Masoudi, P., Y. Asgarinezhad, and B. Tokhmechi. 2015. Feature selection for reservoir characterisation by Bayesian network. Arabian Journal of Geosciences, 8: 3031-3043. DOI 10.1007/s12517-014-1361-7.
Mirzaei, N., M. Gao, and Y.T. Chen. 1997. Seismicity in major seismotectonic provinces of Iran. Earthquake Research in China, 4: 16-26.
Öncel, A.O., and T. Wilson. 2002. Space-time correlations of seismotectonic parameter and examples from Japan and Turkey preceding the izmit earthquake. Bulletin Seismological Society of America, 92: 339–350. DOI. 10.1785/0120000844
Ozturk, S. 2012. Statistical correlation between b-value and fractal dimension regarding Turkish epicentre distribution. Earth science research, 16: 103-108.
Pailoplee, S., and M. Choowong. 2014. Earthquake frequency-magnitude distribution and fractal dimension in mainland Southeast Asia. Earth Planet and Space, 66: 1-10. DOI 10.1186/1880-5981-66-8
Richardson, L.F. 1961. The problem of contiguity: An Appendix to Statistics of Deadly Quarrels. General System Yearbook, 6: 139-187.
Rodriguez-Iturbe, I., and A. Rinaldo. 1997. Fractal River Basin (Chance and Self-Organization). Cambridge University Press, Cambridge. DOI 10.1063/1.882305
Schuller, D.J., A.R. Rao and G.D. Jeong. 2001. Fractal characteristics of dense stream networks. Journal of Hydrology, 243: 1–16. DOI 10.1016/S0022-1694(00)00395-4
Schwartz, D., and K. J. Coopersmith. 1984. Fault Behavior and Characteristic Earthquakes: Examples from the Wasatch and San Andreas Faults, Journal of Geophysics Research. 89: 5681–5698. DOI 10.1029/JB089iB07p05681
Setyawan, B., and B, Sapiie. 2019. Correlation between the fractal of aftershock spatial distribution and active fault on Sumatra. Natural hazards and earth system sciences, 1-11. DOI 10.5194/nhess-2019-215
Strogatz, S.H. 1994. Nonlinear Dynamics and Chaos. Perseus Books publication, New York.
SukMono, S., M. T. Zen, W. G. A. Kadir, L. Hendrajaya, D. Santoso, and J. Dubios. 1996. Fractal Geometry of the Sumatra Active Fault System and its Geodynamical Implications. Journal of Geodynamic, 22: 1–9. DOI 10.1016/0264-3707(96)00015-4
Turcotte, D. L. 1986. Fractals and Fragmentation. Geophysics Research, 91: 1921-1926. DOI 10.1029/JB091iB02p01921
Turcotte, D.L. 1977. Fractal and Chaos in Geology and Geophysics. Cambridge University Press, Cambridge. DOI 10.1017/CBO9781139174695
Vernant, P., F. Nilforushan, D. Hatzfeld, M. Abassi, C. Vigney, F. Mason, H. Nankali, J. Martinod, M. Ashtiany, R. Bayer, F. Tavakoli, and J. Chery. 2004. Present day crustal deformation and plate kinematics in Middle East constrained by GPS measurements in Iran and north Oman. Geophysical Journal International, 157: 381-398. DOI 10.1111/j.1365-246X.2004.02222.x
Wiemer, S., and M. Wyss. 2000. Minimum magnitude of completeness in earthquake catalogs: examples from Alaska, the Western United States,and Japan. Bulletin of the Seismological Society of America, 90: 859-869. DOI 10.1785/0119990114.