Adaptive multistart Gauss–Newton approach for geodetic data inversion of earthquake source parameters

Abstract

We present an adaptive multistart Gauss–Newton approach (AMGNA) to inverse earthquake source parameters with multiple geodetic data sets. The AMGNA can be combined with uniform and nonuniform sampling schemes to generate initial parameters. The AMGNA searches for the improved solution with an adaptively determined number of initial parameters based on a given stable level represented by a target probability; this process involves a first-order approximate uncertainty calculation and performs a joint inversion involved variance component estimation. We test the efficiency and reliability of the AMGNA with synthetic global positioning system and interferometric synthetic aperture radar data and apply the proposed approach to the 2009 Mw 6.3 L’Aquila earthquake and 2017 Mw 6.6 Bodrum–Kos earthquake. The results show that the AMGNA can retrieve well the designed source parameters by several simulated cases and estimate source parameters and uncertainties comparable to those of previous studies for real applications. The AMGNA can quickly estimate the source parameters and uncertainties within 0.5–25 min using six processes in parallel computing. Considering the easily implemented property of the nonuniform sampling scheme, our algorithm has potential applications in the fast and automatic inversion of earthquake source parameters.