Streamflow Reconstructions of Southern Appalachian (North Carolina) Headwater Gages Using Tree Rings

Tree rings have been used as a proxy in reconstructing streamflow in the western U.S. for many years, but few reconstructions have been attempted in the eastern United States. Clear limitations exist for streamflow reconstructions in the eastern U.S. compared to the western U.S., but value can be established as demonstrated in this research. The primary goal of this research was to reconstruct streamflow using data from five headwater gages in the Appalachian Mountains of North Carolina. These gages are located on the Valley River, the Oconaluftee River, the Nantahala River, the Little Tennessee River, and the Watauga River. Tree-ring chronologies were used to reconstruct streamflow. Tree-ring chronology predictors were selected using a seasonal correlation analysis. Seasonal correlation analysis revealed May-June-July (MJJ) streamflow variability being highly correlated with tree-ring chronologies in the study region and vicinity. Stepwise linear regression methods were used to reconstruct MJJ streamflow. The reconstructions for the Valley, Oconaluftee, and Nantahala Rivers were considered acceptable reconstructions because the models explained approximately 50% of the total variance in historic period MJJ streamflow records. These three streamflow reconstruction models have predictive skill indicated by a positive reduction of error (RE) values. The root mean square error (RMSE) statistic was 11.5 million cubic meters (MCM) for the Valley River (26% of the mean reconstructed MJJ flow), 15.9 MCM for the Oconaluftee River (16% of the mean reconstructed MJJ flow), and 8.2 MCM for the Nantahala River (20% of the mean reconstructed MJJ flow). Analysis of the reconstructed streamflow data for these three rivers revealed low flow periods from 1710 to 1712 at all three sites. The research presented here shows the potential benefit of using tree-ring chronologies to reconstruct streamflow in the Tennessee Valley region by demonstrating the ability of proxy-based reconstructions to provide useful data beyond the instrumental record. These useful data include identification of extreme wet or dry periods and oscillations in the historical reconstructions that are not visible in the instrumental data.