USING PUBLIC DATASETS AND GEOSPATIAL ANALYSES TO INVESTIGATE TECTONIC CONTROLS ON SPRING DISCHARGE LOCATIONS ALONG THE SOUTHERN OZARK DOME, NORTHERN ARKANSAS, USA

Karst aquifers are important sources of water for drinking, irrigation, and industrial use and provide rare ecological habitat for organisms adapted to the subsurface. Groundwater and associated spring discharges are vital resources to communities in northern Arkansas. Identifying geologic factors associated with surface water and groundwater fluxes are key to understanding groundwater movement in the fracture-dominated karst aquifers of the southern Ozark dome in northern Arkansas. Numerous studies have shown faulting to be associated with spring discharge at local scales (< 1 km²); however, a spatial analysis of spring locations and fault geometries at the regional scale (> 100 km²) has not been undertaken. It is shown here that across the southern Ozark dome, spring location geometries generally plot along delineated deep basement faults of the region. A point pattern analysis was then implemented using 307 springs locations derived from USGS 7.5 minute topographic maps and the National Hydrolgraphy Dataset and a ‘continuous sector’ method (Hammer, 2009) was used to generate lineaments across the study area. The results show the generated lineaments reflect similar spatial geometries as nearby faults and in particular, the deep seated basement faults. It is inferred that these deep basement faults therefore likely play a key role in where spring discharges occur in the region and underscore tectonic controls on the hydrologic fluxes along the southern Ozark dome. Moreover, this study highlights the use of publicly available data (i.e. data mining) and publicly available geostatistical tools that greatly aided in both discovering and quantifying the observed geospatial relationships. While the specific mechanisms through which deformation from basement faults affect the deep- and near-surface hydrogeology are not explained by these analyses, the aforementioned data and toolsets can be used to rapidly explore potential spatial relationships between geological and hydrological data, particularly in karst regions.