2015 GSA Annual Meeting in Baltimore, Maryland, USA (1-4 November 2015)

Paper No. 213-4
Presentation Time: 9:00 AM-6:30 PM

GROUND-BASED RADAR INTERFEROMETRY MEASUREMENTS OF THE SLUMGULLION EARTH FLOW (SAN JUAN MOUNTAINS, COLORADO)


LUECKE, Austin and GOMEZ, Francisco, Department of Geological Sciences, University of Missouri, 101 Geology Building, Columbia, MO 65211, atl2p8@mail.missouri.edu

The Slumgullion flow is a large, slow mass movement in the San Juan Mountains of Colorado, often regarded as a “natural laboratory” for earthflows. Studying temporal variations in landslide movement is important for understanding basic flow mechanisms, as well as hazard assessments. Prior studies of the Slumgullion flow have documented temporal variations in the flow velocity, including correlation with tidal periods. The goal of this study is to assess short-term (time periods of hours) movements of the Slumgullion flow using ground-based interferomtric radar (GBIR). GBIR has significant potential for landslide studies owing to spatial completeness and sensitivity to small displacements. The GBIR used in this study is a Gamma Remote Sensing GPRI2 (Ku-band radar). Radar images were acquired with 10 minute sampling intervals throughout a 7+ hour period of observation. Data processing utilizes a multi-interferogram (zero-baseline) approach involving more than 800 interoferometric combinations. Interferograms are subsequently corrected for the atmospheric refractivity based on meteorological data. The data redundancy permits calculating a displacement time series with a standard error better than 0.5 mm, in some cases. Preliminary results suggest that over the 7+ hour observation period, displacements up to 10 mm are apparent. Our GBIR results are also compared with satellite InSAR using data from the Sentinel 1 satellite (C band) over the same time period. With data redundancy and atmospheric corrections, the ground-based interferometric radar appears to be a useful tool for kinematic measurements of mass movements. Using this approach for a longer duration of multiple days may better characterize spatial patterns to the temporal variability.