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Did You Feel That? Examining the Transition Between Felt and Not-Felt Shaking

Session: Earthquake Early Warning Live in California! Current Status and Challenges II

Type: Oral

Date: 4/23/2021

Presentation Time: 02:00 PM Pacific

Description: 

We use a dataset of nearly one million individual U.S. Geological Survey (USGS) Did You Feel It? (DYFI) reports from M4.0+ earthquakes in the U.S. ShakeAlert System’s reporting region to examine the transition between felt and not-felt shaking for use in earthquake early warning (EEW) applications. In EEW, alerting strategies must balance the tradeoffs between reducing missed alerts to locations that experience strong shaking and reducing incorrect alerts to regions that do not need to take protective actions. As incorrect alerts to locations where most people do not experience felt shaking may decrease the public’s confidence in EEW, it is necessary to accurately model the probability of felt and not-felt shaking to determine the quality of an EEW alert. The DYFI system provides the most comprehensive dataset of observed earthquake shaking intensities in the United States. These observations have been used as ground-truth for developing the empirical ground-motion-to-intensity conversion equations used in EEW and in rapid-response products such as USGS ShakeMap. However, because the DYFI system is a self-reporting system, reports of not-felt shaking are usually lacking, and as such, our understanding of the transition between felt and not-felt ground motions is limited. Furthermore, the definitions of Modified Mercalli Intensity at low intensities use descriptions like “felt only by few persons at rest” which contributes to the large range of ground motions that correspond to low MMI levels. We investigate the reporting bias of different shaking intensity levels as well as region-specific adjustments to DYFI-based intensities in locations where felt shaking is under-reported relative to population. These adjusted DYFI data will provide improved estimates of the distribution of low-intensity shaking levels, which can then be used to update the ground-motion models used by ShakeAlert and other products.

Presenting Author: Jessie K. Saunders

Student Presenter: No

Authors