GSA Annual Meeting in Phoenix, Arizona, USA - 2019

Paper No. 114-15
Presentation Time: 9:00 AM-6:30 PM


KELNER, Gary M., Department of Geosciences, Fort Hays State University, 600 Park Street, Hays, KS 67601-2040, GAUVEY, Kaitlyn, Fort Hays State University, 3021 Sherman Ave, Hays, KS 67601-2040 and SUMRALL, Jonathan B., Department of Geosciences, Fort Hays State University, 600 Park St., Hays, KS 67601

The Gypsum Hills in Barber County Kansas is known to have karst features such as caves and sinkholes. This study created a predictive model for karst features. Features that were previously identified were used to aid in the creation of this model as well as Light Detection and Ranging (LiDAR) and WorldView-3 imagery. Two privately owned ranches in Barber County were used for this study due to ease of access. The predictive model for karst features will be useful for future exploration of karst features in Barber County. Understanding the distribution and occurrence of karst features will help landowners mitigate risk such as collapse leading to structural damage and aquifer contamination.

This karst feature predictability model encompasses the use of the ESRI ArcGIS software platform. The data for this model consists of a topographic wetness index, slope and aspect, nearest neighbor elevation, Normalized Density Vegetation Index (NDVI), land cover/land use, distance to geomorphic features and subsurface geology. Other software platforms will be used in the creation of this model as needed such as MicroDEM, SAGA GIS and ENVI for imagery analysis. To test the relationship of geology to karst formation, rock samples were collected from various features to document the lithology and perform petrographic analyses. On these properties, the geologic contact between the Permian Medicine Lodge Gypsum and Flowerpot Shale appears to be a control on the formation of karst features, and may play an important role in predicting the location of unknown features.

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