HR: 0830h
AN: NG41B-0062    [PDF]
TI: Unified Scaling Law for Earthquakes: Implications for Hazard Assessment
AU: Kossobokov, V G
EM: volodya@mitp.ru
AF: International Institute of Earthquake Prediction Theory and Mathematical Geophysics, Russian Academy of Sciences, 79-2 Warshavskoye Shosse, Moscow, 113556 Russian Federation
AU: Kossobokov, V G
EM: volodya@mitp.ru
AF: Institute de Physique du Globe de Paris, 4 Place Jussieu, Cedex 05, Paris, 75252 France
AU: * Turcotte, D L
EM: turcotte@geology.ucdavis.edu
AF: Department of Geology, University of California, One Shields Ave, Davis, CA 95616 United States
AU: Nekrasova, A K
EM: nastia@mitp.ru
AF: International Institute of Earthquake Prediction Theory and Mathematical Geophysics, Russian Academy of Sciences, 79-2 Warshavskoye Shosse, Moscow, 113556 Russian Federation
AB: The confirmed multiplicative scaling of earthquakes changes the traditional view on the recurrence of catastrophic events and helps estimating seismic hazard in an adequate way. The evident patterns of distributed seismicity are apparently scalable according to the Unified Law that generalizes Gutenberg-Richter recurrence relation by accounting for the fractal nature of faulting. The results of the systematic global analysis of the local earthquake size distribution imply that (i) the recurrence of earthquakes in a seismic region, for a wide range of magnitudes and sizes, can be characterized with the following law: Log N(M,L) = A - B (M - 5) + C Log L, where N(M,L) is the expected annual number of earthquakes of magnitude M within an area of liner size L; (ii) for a wide range of control parameter A from under -1.0 to above 0.5, which value determines the average rate of earthquakes that accordingly differs by a factor of 30 or more, the balance between magnitude ranges, B, resides mainly from 0.6 to 1.1, while the fractal dimension of the local seismic prone setting, C, changes from under 1 to 1.4 and larger; (iii) any estimate of earthquake recurrence rate depends on the size of the territory that is used for averaging and, therefore, may differ dramatically if rescaled to the area of interest in a traditional way. For example, the recurrence of a large magnitude earthquake at Los Angeles, an area with L about 40 km, would perhaps be determined from a catalog of the entire southern California, an area with L about 400 km. The estimates for Los Angeles, using SCSN data, 1984-2001, give C = 1.21 and, therefore, imply a traditional assessment of the recurrence in such a case being underestimated by at least a factor of 6. Using the US GS/NEIC Global Hypocenters' Data Base, 1964-2001, and a robust box-counting algorithm, we managed to map values of A, B, and C in every place on the Earth, where the catalog of shallow earthquakes permitted a reliable estimation.
DE: 3220 Nonlinear dynamics
DE: 3240 Chaos
DE: 7209 Earthquake dynamics and mechanics
DE: 7223 Seismic hazard assessment and prediction
DE: 7260 Theory and modeling
SC: Nonlinear Geophysics [NG]
MN: 2003 Fall Meeting