Paper No. 8
Presentation Time: 8:00 AM-6:00 PM
SPATIAL RELATIONSHIPS BETWEEN FAULTS AND SPRING LOCALITIES IN THE VALLEY AND RIDGE PROVINCE
MOORE, Johnathan E., Department of Geology & Geography, West Virginia University, Morgantown, WV 26505, VESPER, Dorothy J., Department of Geology & Geography, West Virginia University, Morgantown, WV 26506 and EDENBORN, Harry M., Geosciences Division, National Energy Technology Lab; U.S. Department of Energy, P.O. Box 10940, Pittsburgh, PA 15236, Jmoore42@mix.wvu.edu
Springs in the Valley and Ridge Province of eastern West Virginia and northcentral Virginia are generally reported to be preferentially located near structural features, more specifically faults. A better understanding of that relationship, especially for thermal and mineral springs, will help predict sustainability of springs and regional flow patterns in the province. We used ArcMap® to analyze spatial relationships between springs and faults. Spring data were gathered from the USGS Hydrology Database and literature for 96 springs and fault data were acquired from the USGS National Map Seamless Server. Faults were buffered to 0.5, 1, and 2 miles (0.8, 1.6, and 3.2 km). The intersection tool was used to determine which springs were within each buffer polygon. Temperature data were limited to 60 springs; twenty-two springs with temperatures > 13.5 °C were classified as warm and 38 springs with temperatures <13.5 °C were classified as cold. For comparison, ArcMap® was used to generate three sets of 96 random points.
Analysis for the entire spring set yielded 27% within 0.5 miles of mapped faults, while 45% and 64% of the springs were within 1 and 2 miles of a mapped fault, respectively. Similar results were found when the analysis was conducted for springs classified as cold. Randomly generated points were less likely to plot near faults, with only 9-16%, 17-24%, and 34-42% plotting within 0.5, 1, and 2 miles respectively. Warm springs were anomalous with only 14% mapping within 0.5 miles of a fault, which correlates more closely with random points than the cold springs or the entire dataset. At a distance of 1 and 2 miles, warm springs were similar to the overall dataset, with 45% and 59% plotting near faults, respectively. The data show that the sample springs occur more commonly near faults than they would given a random distribution, although cold springs may be more closely tied to structural features than warm springs. This relationship has larger implications in that it indicates that faults in the Valley and Ridge Province may act as a regional flowpaths for groundwater and other fluids. Future work will include chemical analysis of approximately 25 springs and conducting a similar spatial analysis with specific chemical parameters.
