Heatmap analysis of modeled coastal tsunamis using different bathymetry data resolutions

Abstract

We examined how variations in the horizontal resolution of bathymetry influence the behavior of modeled tsunamis at shallow depths nearshore. This was done using the Cornell Multi-grid Coupled Tsunami Model (COMCOT) to simulate tsunamis with resampled bathymetric data at resolutions of 5, 10, 20, 30, 40, 50, 100, 200, and 300 meters, derived from 1-m resolution NOAA coastal LiDAR data sets (at water depths of less than or equal to 30 m) and soundings. In total, we utilized 1,080 data sets, comprising 9 resolutions across 30 sets at 4 different sites. In addition, we included the 15-arc second grid ($$\sim$$ ∼ 455 m) 2021 GEBCO data for comparison. We initiated a 5-m high tsunami wave offshore and propagated it towards the coast, then used the resulting maximum wave heights for each resolution to quantify the differences across varying resolutions. Using the 5 m bathymetry as the reference model, we observed that data sets with 10–50 m resolutions can reproduce tsunamis reasonably well. The maximum heights are overestimated by less than or equal to 5% or underestimated by less than or equal to 10%, and the first wave arrival time is $$\sim$$ ∼ 10% earlier than expected. Coarser bathymetries show an increasing trend of height underestimation, with the GEBCO model underestimating it by as much as 70%. Coarser bathymetry models have more variable first wave arrival time, with waves arriving up to 20% later or up to 10% earlier than expected. Overall, a reasonably accurate result can be achieved using a bathymetric resolution in the 10 m–50 m range, and is achievable with reasonable computational efficiency (at least 80% faster than simulations using the 5 m model on high-performance computing). This study highlights the importance of shallow bathymetry data quality in the numerical modeling of tsunami propagation.