Abstract
We describe the uncertainties of altimetry-predicted bathymetry models and then quantify the impact of this uncertainty in tsunami hazard assessments. The study consists of three stages. First, we study the statistics of errors of altimetry-predicted bathymetry models. Second, we employ these statistics to propose a random field model for errors anywhere. Third, we use bathymetry samples to conduct a Monte Carlo simulation and describe the tsunami response uncertainty. We found that bathymetry uncertainties have a greater impact in shallow areas. We also noted that tsunami leading waves are less affected by uncertainties.Recorded Presentation from the vICCE (YouTube Link): https://youtu.be/zzL_XWWAQ7o
Highlights
We describe the uncertainties of altimetry-predicted bathymetry models and quantify the impact of this uncertainty in tsunami hazard assessments
We study the errors of altimetry-predicted bathymetry estimates, which cover ~80% of the earth oceans in massively used models, such as GEBCO and SRTM+
We estimate statistics of the satellite-based bathymetry errors. We employ these statistics to propose a model for the uncertainty anywhere, using a random field conditional to ship measurements, which are assumed to be certain
Summary
We describe the uncertainties of altimetry-predicted bathymetry models and quantify the impact of this uncertainty in tsunami hazard assessments. We study the errors of altimetry-predicted bathymetry estimates, which cover ~80% of the earth oceans in massively used models, such as GEBCO and SRTM+. We estimate statistics of the satellite-based bathymetry errors. We employ these statistics to propose a model for the uncertainty anywhere, using a random field conditional to ship measurements, which are assumed to be certain. We propose a methodology to generate bathymetry error samples. We use the bathymetry samples to conduct a Monte Carlo simulation to quantify the tsunami response uncertainty
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