Determination of the Initial Sea Surface Deformation Caused by a Tsunami Using Genetic Algorithm

The characteristics of a tsunami is largely determined by its initial source, which can be defined as a perturbation to the equilibrium state of the ocean hydrodynamic. For tsunamis generated by earthquakes, the initial source (as a form of sea surface deformation) is driven by a coseismic vertical displacement of the seabed. Assuming that the rupture process occurs instantaneously, the sea surface deformation can be inferred from recorded tsunami waveforms. Tsunami waveform inversion using the Green’s function technique with least squares optimization is the most widely used method. However, this method can sometimes suffer from ill-posed problems, because of the non-uniqueness of the inversion results. This study proposes a genetic algorithm that helps the traditional least squares method find an optimum solution. We applied the method to an artificial tsunami source with a complex profile. We achieved significant improvements by determining the optimum spatial distribution of the unit sources (the Green’s function) prior to the inversion. In contrast with the regular Green’s function that has equidistant unit sources, our method generates a random spatial distribution. This random characteristic leads to a better approximation of the initial sea surface deformation.