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Rapid GNSS Source and DART Inversion Models Comparison along the Cascadia Subduction Zone

Session: Advances in the Science and Observation of Tsunamis

Type: Oral

Date: 4/22/2021

Presentation Time: 10:45 AM Pacific

Description: 

Tsunami warning systems have improved significantly since the devastating 2004 Indonesian quake providing coastal communities with the possibility of a rapid tsunami forecast in a timely and more accurate way. One of the problems that needs an improvement is a near-field forecast for the areas located close to the tsunami source. Recent efforts to mitigate the near-field problem have been focused on the computation of rapid GNSS-based (Global Navigation Satellite Systems) seismic solutions. While this technique can generate very fast solutions, its accuracy in forecasting when compared with forecast generated from DART buoy data has yet to be evaluated. In this study we compare the results of GNSS-based source characterization model and DART inversion model using synthetic megathrust ruptures of Cascadia subduction zone for its near-field forecasting potential. The tsunami inundation modeling results demonstrated higher accuracy for the DART-based forecasts in a majority of coastal locations than the GNSS-based forecast. However, the latency in the acquisition of DART data during a real event renders this approach impractical for near-field forecasting. The GNSS-based finite-fault source derived from the Slab 2 characteristics demonstrates its potential as a quick solution in terms of both model accuracy and time contingency of an event.

Presenting Author: Natalia K. Sannikova

Student Presenter: No

Authors