Mapping permafrost with airborne electromagnetics

Wednesday, 17 December 2014: 4:00 PM
Burke J Minsley1, Lyndsay B Ball1, Benjamin R. Bloss2, Andy Kass1, Neal Pastick3,4, Bruce D Smith1, Clifford I Voss5, David O Walsh6, Michelle A Walvoord1 and Bruce K Wylie7, (1)USGS, Denver, CO, United States, (2)USGS, Baltimore, MD, United States, (3)Stinger Ghaffarian Technologies Sioux Falls, Sioux Falls, SD, United States, (4)University of Minnesota Twin Cities, Department of Forest Resources, Minneapolis, MN, United States, (5)USGS California Water Science Center Menlo Park, Menlo Park, CA, United States, (6)Vista Clara Inc., Mukilteo, WA, United States, (7)USGS, EROS Data Center, Baltimore, MD, United States
Permafrost is a key characteristic of cold region landscapes, yet detailed assessments of how the subsurface distribution of permafrost impacts the environment, hydrologic systems, and infrastructure are lacking. Data acquired from several airborne electromagnetic (AEM) surveys in Alaska provide significant new insight into the spatial extent of permafrost over larger areas (hundreds to thousands of square kilometers) than can be mapped using ground-based geophysical methods or through drilling. We compare several AEM datasets from different areas of interior Alaska, and explore the capacity of these data to infer geologic structure, permafrost extent, and related hydrologic processes. We also assess the impact of fires on permafrost by comparing data from different burn years within similar geological environments. Ultimately, interpretations rely on understanding the relationship between electrical resistivity measured by AEM surveys and the physical properties of interest such as geology, permafrost, and unfrozen water content in the subsurface. These relationships are often ambiguous and non-unique, so additional information is useful for reducing uncertainty. Shallow (upper ~1m) permafrost and soil characteristics identified from remotely sensed imagery and field observations help to constrain and aerially extend near-surface AEM interpretations, where correlations between the AEM and remote sensing data are identified using empirical multivariate analyses. Surface nuclear magnetic resonance (sNMR) measurements quantify the contribution of unfrozen water at depth to the AEM-derived electrical resistivity models at several locations within one survey area. AEM surveys fill a critical data gap in the subsurface characterization of permafrost environments and will be valuable in future mapping and monitoring programs in cold regions.