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WITHDRAWN Evaluating Scaling Relationships From Insar-Derived Earthquake Source Parameters

Description: 

WITHDRAWN Scaling relationships are key to understanding which earthquake source parameters – quantities that describe the earthquake source (e.g. fault length, fault width, slip, and seismic moment) – are key to producing large earthquakes. Proposed scaling relationships include the presence or absence of scaling breaks and the existence of a power law (or not), in length-moment scaling, or area-length scaling (Scholz, 1982, 1994; Romanowicz, 1982, 1992, Leonard, 2010). Better constraints on scaling relationships of source parameters will allow for improved estimates of potential future earthquake sizes and improved forecasts of earthquake hazards.

In this work, we aim to bring a new perspective to scaling relationships by using an InSAR-derived source parameter dataset. InSAR can provide robust constraints on key parameters such as fault length by direct measurements and on other fault parameters by modeling. To compile our dataset, we simultaneously mine the literature for source parameters for InSAR-based studies and also model recent earthquakes not present in the literature ourselves. For our own models, we estimate the source parameters (e.g. strike, slip, length) using a rectangular elastic dislocation model, fitted to downsampled InSAR data from the Sentinel-1 satellites, whose parameters are estimated using a Powell algorithm with multiple Monte Carlo restarts. To evaluate scaling relationships, we use statistical approaches (e.g. regression analyses) to quantify the relationships between the source parameters (e.g. length, width, seismic moment). Our preliminary results, based on over 200 earthquakes studied with InSAR, are consistent with a length squared-moment scaling (L2 ∝ Mo), suggesting that slip may be proportional to fault length.

The value of the scaling relationships obtained in this way are only as robust as the earthquake models and the modeled source parameters. To assess the likely impact of uncertainties in these parameters, we examine a few well-studied events, such as the 2015 Gorkha, Nepal and 2019 Ridgecrest, CA earthquakes, to quantify the variability in published models.

Session: Understanding and Quantifying the Variability in Earthquake Source Parameter Measurements [Poster Session]

Type: Poster

Date: 5/3/2024

Presentation Time: 08:00 AM (local time)

Presenting Author: Karlee

Student Presenter: Yes

Invited Presentation: 

Authors