RAPID: Deploying a dense network to record seismicity at the Rattlesnake Ridge landslide

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In October of 2017, a series of cracks were discovered on Rattlesnake Ridge south of Yakima, WA. At that time, they were ~1 m deep. As of late December 2017, just two months later, those same cracks had grown to over 80 m deep. These cracks represent the lateral margin of the Rattlesnake Ridge landslide, which consists of an estimated 4 million cubic meters of material that is making its way downhill slowly. The slowly moving rock mass sits atop a (weak) sedimentary rock layer between thicker layers of Columbia River flood basalt. The best case (and most likely scenario) is that this material continues to move south slowly and fall into an asphalt quarry. However, an alternative (unlikely) scenario involves catastrophic failure which could block Highway 82, and dam the Yakima River flooding the surrounding area. The objective of this RAPID proposal is to deploy 40 nodal seismometers in the surrounding area to continuously monitor seismic signals coming from the slide. Nodal seismometers (or nodes) are small, lightweight, cable free, three-component seismometers. This state-of-the-art technology was developed for oil and gas exploration, however, nodes can also be used to study a variety of other seismic processes, such as earthquakes and landslides. The size and (relatively) low cost of individual sensors allows for easily deployable, dense observation networks that produce high-quality data. The resulting dataset can be used to determine the location, timing and nature of seismic signals coming from the slide. The spatial and temporal evolution of slide related seismicity can be used to better characterize the landslide and potentially to predict when failure may occur.Forty nodal seismometers will be deployed around the Rattlesnake Ridge landslide near Yakima, WA. These instruments will be "hot swapped" every 30 days until the landslide fails or until the landslide reaches steady-state. These deployments will result in three component seismic data from which travel times will be computed to form a 3D grid of potential sources. A network beamforming approach will be followed to detect, locate, and characterize seismic signals coming from the landslide. This information will provide new insight into the size and nature of the slide of this rock block as well as the degree of internal deformation. This project has a potential broad societal impact and will help quantify and understand the landslide process in general.