HYDROLOGIC MONITORING AND 2-D ELECTRICAL RESISTIVITY IMAGING FOR JOINT GEOPHYSICAL AND GEOTECHNICAL CHARACTERIZATION OF SHALLOW COLLUVIAL LANDSLIDES

Landslide characterization and hazard assessments require multidisciplinary approaches that connect geologic processes with geotechnical parameters. Field monitoring of hydrologic variables such as water content and water potential, coupled with geoelectrical measurements that can establish relationships used for geotechnical and landslide hazard investigations is deficient. This study brings together different techniques to develop a methodology that connects geoelectrical measurements and shear strength. A field-based framework was established that includes (1) analysis of long-term soil moisture fluctuations within different landslides (2) establishment of constitutive and new equations that test the use of electrical conductivity to predict soil-water relationships and shear strength (3) using electrical resistivity tomography (ERT) to support and facilitate the prediction of shear strength in a slope. Hydrologic conditions including volumetric water content, water potential, and electrical conductivity in the soil were measured at three active landslides in Kentucky. The in-situ electrical conductivity used within the framework is valid as a predictor of suction stress and shear strength. The ERT supports interpretations of landslide failure zones, landslide type, lithologic boundaries, and changes in moisture conditions, but also is able to utilize the methodology to calculate shear strength, and provide a spatial view of shear strength in the slope. The practical application of this framework is to support landslide hazard assessment and further understand the long-term influence of moisture conditions in hillslope soils. These parameters are pertinent to investigating the stability of landslides that are often triggered or reactivated by rainfall

Using LiDAR to Map Landslides in Kenton and Campbell Counties, Kentucky

The geology and topography of northern Kentucky and Cincinnati make the area susceptible to landslides. Decades of development and slope modification have contributed to the area being prone to landslides and having one of the highest costs per capita in the United States for landslide damage. The slow nature of some landslides and incremental damage that can span several decades often result in lack of awareness of the problem, however. Many of the landslides go unreported, and citizens do not take advantage of resources to become educated about mitigating the problem. Research at the Kentucky Geological Survey developed a methodology using high-resolution light detection and ranging (LiDAR) data optimal for the terrain of Kenton and Campbell Counties to document landslides and enter them into an inventory. Potential landslide locations were mapped and the resulting new data were digitized. Hillshade DEM maps were the primary data set used. Locations were field verified, where possible. Continued use of high-resolution LiDAR to identify potential landslides will provide a framework for analyzing landslide data that is crucial to understanding the nature of landslide-prone areas and reducing long-term losses

Kentucky Geological Survey Landslide Inventory: From Design to Application

The Kentucky Geological Survey is compiling a landslide inventory database to better document the distribution and geologic context of Kentucky’s landslides. The database provides users with easy access to landslide information, raises awareness of landslide causes, and will help prevent property damage or injury. The database was used to create an online landslide information map, which provides online access to landslide data and gives users the ability to customize the map using other data layers pertinent to landslides. The database design is based on common attributes collected by other states with active inventories and landslide hazard programs, as well as attributes necessary to document landslides in Kentucky and help with future research goals. A comprehensive landslide inventory database serves as a foundation for understanding landslide distribution, assisting land-use planning decisions, creating hazard maps, and modeling landslide susceptibility

Geology of Cumberland Gap National Historical Park

Cumberland Gap National Historical Park is located in parts of Kentucky, Virginia, and Tennessee. The park was authorized by President Franklin Roosevelt on June 11, 1940, and is now the largest historical park in the National Park System. It contains 24,000 acres along Cumberland Mountain near Ewing, Va., proceeding southwest toward Fern Lake in Tennessee, a distance of approximately 20 miles. The average width of the park is only 1.6 miles. The park hosts a distinctive range of geologic processes and features. Unique structural geology, caves and karst, surface and groundwater erosion, and mass wasting are just a few of the processes that shape the scenic landscape of the park. This publication illustrates the relationship between the geology of Cumberland Gap and the historical and cultural issues that are important to the park and its visitors. It is intended for park visitors, educators, park staff, and anyone interested in the geology of Cumberland Gap National Historical Park. It was produced using digital geologic mapping and geographic information system technology, which also help the National Park Service with resource management and meeting federal mandates, while also providing informative perspectives that are valuable to all citizens who enjoy national parks. For more information, please visit the Cumberland Gap National Historical Park Web site at www.nps.gov/cuga. To obtain digital geologic and other GIS data, visit the National Park Service Data Portal at nrinfo.nps.govtReference.mvc/Search

Polarization dOTF: on-sky focal plane wavefront sensing

The differential Optical Transfer Function (dOTF) is a focal plane wavefront sensing method that uses a diversity in the pupil plane to generate two different focal plane images. The difference of their Fourier transforms recovers the complex amplitude of the pupil down to the spatial scale of the diversity. We produce two simultaneous PSF images with diversity using a polarizing filter at the edge of the telescope pupil, and a polarization camera to simultaneously record the two images. Here we present the first on-sky demonstration of polarization dOTF at the 1.0m South African Astronomical Observatory telescope in Sutherland, and our attempt to validate it with simultaneous Shack-Hartmann wavefront sensor images.Comment: 11 pages, 9 figures, Proc. SPIE Vol. 991

Geologic, Geotechnical, and Geophysical Investigation of a Shallow Landslide, Eastern Kentucky

In eastern Kentucky, landslides occur in colluvial soils or at the colluvium-bedrock contact, and are commonly triggered by heavy rainfall. These slides occur particularly where steep slopes and weak rocks combine with various methods of slope modification. Landslides can damage roadways, infrastructure, and residences, and mitigation costs can exceed $10 million per year. The Meadowview landslide in Boyd County was investigated to assess the geologic conditions, extent, and behavior of a rainfall-triggered landslide in eastern Kentucky and evaluate the use of electrical resistivity as a tool to characterize a shallow colluvial landslide. Although this type of landslide is common in Kentucky, there are few comprehensive landslide characterization studies combining geologic, geotechnical, and geophysical assessment. This study successfully used traditional geologic and geotechnical data to characterize an active landslide and electrical resistivity to interpret landslide stratigraphy, moisture regimes, and depth to the slide plane. The surface and borehole electrical-resistivity arrays across the Meadowview landslide resulted in inverted resistivity sections with distinct resistivity contrasts that correlate to landslide stratigraphy, depth of slide plane, and groundwater regimes

Seismic Velocity Database for the New Madrid Seismic Zone and Its Vicinity

Over the last 20 years, researchers at the University of Kentucky have collected seismic-reflection and refraction data to characterize seismic velocity models of the soil-sediment overburden throughout the central United States. The data are in different forms, such as published reports, theses, and journal articles, and in digital form. In order to construct a unified database for easier management, access, and use, Microsoft Access was used to design the data structure and field properties. The database consists of four tables with unified field names, data type, and units. An ArcGIS geodatabase with the same data structure as the Access database was then created for visualization and querying capability. The compiled seismic velocity data used the same data types and units, and were stored in both databases. The databases are flexible, so that new data and data types can be added and joined with existing databases at the Kentucky Geological Survey

Landslide Susceptibility Map of Floyd County, Kentucky

The purpose of this map is to identify landslide-prone areas in Floyd County in order to provide the public, as well as local and state government agencies, with information about where landslides are likely to occur. This map represents geomorphic-based susceptibility modeling that focuses on physical slope characteristics and morphology, the quality of which is dependent on data accuracy and resolution of terrain models. The availability of high-resolution (5-ft digital elevation model) lidar derived datasets allows for the generation of terrain elevation derivatives such as hillshades, slope, aspect, curvature, and roughness, as well as identification of existing landslide deposits. These high-resolution lidar derived datasets, coupled with landslide inventory mapping, enable us to produce detailed, high-resolution landslide susceptibility maps

Landslide Susceptibility Map of Johnson County, Kentucky

The purpose of this map is to identify landslide-prone areas in Johnson County in order to provide the public, as well as local and state government agencies, with information about where landslides are likely to occur. This map represents geomorphic-based susceptibility modeling that focuses on physical slope characteristics and morphology, the quality of which is dependent on data accuracy and resolution of terrain models. The availability of high-resolution (5-ft digital elevation model) lidar derived datasets allows for the generation of terrain elevation derivatives such as hillshades, slope, aspect, curvature, and roughness, as well as identification of existing landslide deposits. These high-resolution lidar derived datasets, coupled with landslide inventory mapping, enable us to produce detailed, high-resolution landslide susceptibility maps