Spatial Analysis of Environmental Hazards

Spatial Analysis of Environmental Hazards

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

Authors
Abolghasem Goorabi
Mohammad Zamanzadeh
Mojtaba Yamani
Parisa Pirani
University of Tehran
10.52547/jsaeh.8.3.107
Abstract




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
Keywords
Fractal
Tectonic
Northwest Zagros
Fault
Earthquake
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Spatial Analysis of Environmental Hazards
Volume 8, Issue 3 - Serial Number 31
Autumn 2021
Pages 107-122