| چکیده انگلیسی مقاله |
The earthquake phenomenon has been explained by power-law relations with respect to magnitude, time and
space. Fractal is one such power-law relation, which is a two-point spatial correlation function for earthquake
epicenters [1-2]. It reflects the heterogeneity of seismic activity in a fault system. Another power-law relation is bvalue,
which is a frequency-magnitude relation defined by Gutenberg-Richter [3]. The b-value of a region reflects
the frequency-magnitude characteristics of seismogenic structures, stress distribution in space and depth [4-8].
In this paper, the fractal dimension (D) obtained by the box-counting method as the most general approach for
calculating D (Turcott, 1989). According to this method, the study area was initially superimposed on a square grid
size 1 r . The unit square (r) of the area was divided into small squares of linear size 1 1 r / 2, r / 4 and 1 r / 8,
sequentially. The geometry of fractals is calculated by power-law distribution and the potential D, is represented by
the fractal dimension:
Ni=〖C⁄r〗_i^D
where, Ni is the number of objects, characterized by the linear dimension r, C; proportionality constant and Df fractal dimension, which is calculated by (Turcotte, 1992):
D=(Log((Ni+1)/Ni))/(Log(ri/(ri+1)))
At simplest form of Equation (2), the fractal dimension was determined from the slope of the log N (ri)
versus log (1/ri) plot.
Log(N)=C+K log(1/S)
In this paper, b-value, spatial fractal dimension of seismicity and faults D (s and f) are used to
evaluate the seismicity of the Khuzestan zone in Southwestern part of Zagros zone in time interval 1900 to 2018.
The seismicity data of the Zagros zone are extracted from unified seismic catalog of the Iranian Plateau. Spatial
variations of b-value, D(s) and D(f) demonstrate large variations in seismicity behavior along the study area.
The most vulnerable regions for the occurrence of the large earthquakes in the study area considering the
computed lowest b-values and the highest D-values. The relationships among DC -b are used to classify the level of
earthquake hazards for individual seismic source zones, in which the calibration curves illustrate a negative
correlation among the DC and b values. It is observed that the relationship among b and D may be used for
evaluation of seismicity and earthquake hazard assessment because of the high value for correlation coefficients and
limited scattering of the calculated parameters.
The results indicate low b-values and high moderate D(s) and D(f) in the North study area while the Central and southwest is accompanied by low b-values and high D(s) in time interval 1900-2018, which indicates different stress release regimes in northeast and southwest parts of the study area. The Index Regime Stress )R'( in study area is 2.24±0.44, that shows convergent in southwest of Zagros.
Fractal analyses of the active faults and earthquake show increasing values from southwest to northeast. Kriging zoning maps of fractal variations show this content. Fractal dimensions of faults and earthquake in the Khuzestan area show different values, which varied in the NE-SW direction. Based on these variations, the northwestern parts of the study area have more tectonic activity than the southeastern parts.
The lack of faults outcrop in Zagros range, nonequality in faults mechanism, lack of conformity in distribution of earthquake epicenters by faults exist. Consume of many states rate of energy duration of folding process and difference in tectonic and structural style of Sundries part of the study area causes difference in the amount of fractal dimension in southeast Zagros.
According to the zoning maps and the identification of high stress zone in the study area, the cities of Izeh, Baghmalek, Haftkel and in the later stages Masjed Soleiman and Ramhormoz along with the surrounding settlements will be introduced as the main candidate areas for future earthquakes.
References
1. Kagan, Y.Y. and Knopoff, L. (1980) Spatial distribution of earthquakes: the two-point correlation function. Geophysical Journal International, 62(2), 303-320.
2. Mandelbrot, B.B. (1982) The Fractal Geometry of Nature. W.H. Freeman, New York. 468p.
3. Gutenberg, R. and Richter, C.F. (1944) Frequency of earthquakes in California. Bull. Seism. Soc. Am., 34, 185-188.
4. Mogi, K. (1967) Earthquakes and fractures. Tectonophysics, 5(1), 35-55.
5. Mori, J. andAbercrombie, R.E. (1997) Depth dependence of earthquake frequency-magnitude distribution in California: implications for the rupture initiation. Journal of Geophysical Research, 102, 15081-15090.
6. Wiemer, S. and Wyss, M. (1997) Mapping the frequency-magnitude distribution in asperities: an improved technique to calculate recurrence times. Journal of Geophysical Research, 102, 15115-15128.
7. Wiemer, S., Mcnutt, S.R., and Wyss, M. (1998) Temporal and three-dimensional spatial analysis of the frequency magnitude distribution near Long Valley Caldera, California. Geophysical Journal International, 134, 409-421.
8. Wyss, M., Klein, F., Nagamine, K., and Weimer, S. (2001) Anomalously high b-values in the South Flank of Kilauea Hawaii: evidence for the distribution of magma below Kilauea’s East Rift Zone. Geophysical Journal International, 134(2), 409-421. |