Towards a 3D model of the Cascadia Subduction Zone

Conveners: Anne Trehu, Suzanne Carbotte, Doug Toomey

Location: Oregon State University

Date of Workshop: June 18 (afternoon) to June 20 (all day), 2018

Workshop Summary Report

Through EarthScope, GeoPRISMS and the Cascadia Initiative, a wealth of new data have been acquired to image the electrical resistivity and the seismic reflectivity, velocity and attenuation structure of the Cascadia subduction zone, including the structure of the plate boundary and the connection between subducted material and the output of the volcanoes. This work builds on an earlier network of onshore/offshore controlled source and natural source seismic and electromagnetic profiles funded by NSF and USGS over the past 3 decades. The results emerging from these studies are, in some cases, seemingly inconsistent. For example, different studies infer quite different degrees of hydration of the downgoing plate and different magnitude and direction of anisotropy in the underlying mantle. In other cases, different datasets (e.g. seismic velocity and electrical resistivity) and may indicate spatially coincident variations in structure, but the geologic implications of the observations have not yet been explored. In yet other cases, the depth to reflective structure depends on the frequency content of the reflections for reasons that have not been clearly identified. To date, there is no comprehensive synthesis of the many models generated from these data. Published models and models currently in preparation cover a wide range of scales and have been derived using a variety of different techniques.

The purposes of this workshop will be:

(1) to evaluate differences between models based on similar data sets;

(2) to integrate models derived for the same region from data sets with different imaging resolutions with potential field data in order to extrapolate from regions with high resolution data sets to tectonically or morphologically similar regions with less data;

(3) to develop geological models that satisfy the multiple constraints provided by the different geophysical data sets from the region; and

(4) to identify gaps in understanding and discuss the data needed to fill those gaps.