2004 UC Proceedings Abstract

back
   Back



GIS and Groundwater Vulnerability Modeling
Track: Water Resources
Author(s): Sharon Qi, Jason Gurdak

ArcGIS was used to extract geospatial data for input into a statistical model of groundwater vulnerability of the High Plains aquifer. A probability map was generated identifying areas of vulnerability to groundwater contamination that allows water professionals to make decisions regarding groundwater resources. Because the aquifer is large, a GIS was required to efficiently extract data from 20 layers at 6,946 well locations. For some data sets, data were extracted using identity overlays. For other data sets where aggregated information was needed, buffers were created for each well and the information was inventoried using union and map algebra techniques. The site-characteristic variables were used as input for iterative statistical calculations (using logistic regression) that determined which of the variables were significantly correlated with observed water-quality conditions. The variables became part of a probability equation that was solved in GIS using map algebra and then visualized.



Sharon Qi
U.S. Geological Survey
Water Resources
3200 SW Jefferson Way
Corvallis , OR 97331
US
Phone: 541-758-8815
E-mail: slqi@usgs.gov

Jason Gurdak
U.S. Geological Survey
Box 25046, MS 415
Denver Federal Center
Lakewood , CO 80225
US
Phone: 303-236-4882
Fax: 303-236-4912
E-mail: jjgurdak@usgs.gov