Southeastern Section - 68th Annual Meeting - 2019

Paper No. 18-12
Presentation Time: 1:00 PM-5:00 PM


SUTTON, Collin R.1, LEE, Ming-Kuo1, KUMAR, Sanjiv2 and BURTON, Christopher1, (1)Department of Geosciences, Auburn University, Auburn, AL 36849, (2)School of Forestry and Wildlife Sciences, Auburn University, Auburn, AL 36849

Georgia is located in the southeastern United States and is home to around 10 million people and the country’s 9th most populous metropolitan area according to U.S. census data. The southeastern United States has long been thought to be resilient to the types of groundwater issues that are seen in the western United States and around the world. Global climate trends are expected to cause increases in temperature and variability in precipitation. While climate change trends are expected to affect groundwater, the exact effects are unknown and are likely to vary significantly based on location and local geology.

Preliminary research on streamflow data from 36 gauging stations and statewide precipitation data show decreasing streamflow trend downstream of areas experiencing decreasing precipitation trend. Annual minimum streamflow decreased throughout the entire state while annual maximum streamflow was found to decrease only in the northern areas of the state. The USGS National Water Information System (NWIS) database hosts data for 404 groundwater monitoring wells throughout. 43 of these wells have been identified as having at least 90 percent of daily data available from 1981 to 2017 and will be used. Long-term, decadal, and annual groundwater trends are computed using the Mann—Kendall test. The Mann-Kendall test is also applied to climate and surface water data to explore the relationship between climate, surface water, and groundwater.

Groundwater trends show statistically significant decreasing trend for annual average, while annual range (maximum – minimum) shows significant increasing trend. Both annual maximum and annual minimum ground water levels are decreasing, but a higher rate of decrease in minimum ground water levels are contributing to the increase in annual range. Increasing annual range has huge implication for the water management in the region. Imputing and artificial intelligence methods are applied to the groundwater data prior to trend analysis to determine effectiveness of different techniques for predicting missing data at a given station. This study will provide a regional scale view of groundwater trends in Georgia while considering geologic regimes and climate variation as well as considering the effectiveness of emerging data science techniques.