Real-time tsunami forecasting system with nonlinear effects using Green's functions: application to near-shore tsunami behavior in complex bay topography

In this study, a real-time tsunami estimation method was developed using the linear superposition of Green's functions, which account for nonlinear tsunami effects around coastal areas. To this end, first, the nonlinear effects associated with the inundation and bottom friction and advection terms in a nonlinear long-wave model were investigated, focusing on large tsunamis around Urado Bay in Kochi Prefecture, Japan, which is at risk of future damage from tsunamis produced by the Nankai Trough earthquake. The results indicate that the effects of advection play a more significant role than those of the inundation and bottom friction in terms of accurately estimating near-shore tsunami propagation. Then, based on these results, Green's functions were modified to account for the linearly approximated effects of the advection terms. By applying the developed method to tsunamis around Urado Bay, it was demonstrated that accurate estimations of the water surface level and flow velocity changes could be quickly obtained at any location around the bay. The developed method can be applied to real-time tsunami inundation forecasting and off-shore evacuation simulations of vessels to support optimal evacuation decisions.

Automated summary

In this study, a real-time tsunami estimation method using Green's functions was developed to account for nonlinear tsunami effects in coastal areas. The study focused on large tsunamis in Urado Bay, Japan and investigated the effects of advection, inundation, and bottom friction in accurately estimating near-shore tsunami propagation. The modified Green's functions based on the linearly approximated effects of advection were applied to accurately estimate water surface level and flow velocity changes around Urado Bay. The developed method has potential applications in real-time tsunami inundation forecasting and vessel evacuation simulations.