Hydrologic Drought Reconstruction Potential in the Southeast US

Abstract:

The western US has long been challenged with the need to manage surface water systems due to the reoccurrence of drought. Most observers associate challenges with western water with two factors. First, the growth and development of large population centers including Las Vegas, Phoenix and southern California (San Diego, Los Angeles) and second, these population centers are in arid regions where precipitation and water supply is limited. However, research has revealed that the Colorado River, which supplies water for over 25 million people, was significantly over allocated when the “Law of the River” (Colorado River Compact of 1922) was implemented. This over allocation of the river was due to a lack of historic (observed) streamflow data and was discovered when paleo streamflow reconstructions (using tree ring data) were developed. In the southeast US, tree ring data has been used to reconstruct the Palmer Drought Severity Index (PDSI). However, very limited research has been performed in the southeast US on developing paleo reconstructions of hydrologic variables such as streamflow, precipitation and soil moisture. The reconstruction of streamflow would allow drought to be quantified (duration, magnitude, severity, return period) and thus put into perspective the 2007-2009 drought that impacted Lake Lanier (Chattahoochee River) and much of the southeast. This research will investigate hydrologic data sources (unimpaired streamflow, precipitation, soil moisture) in the southeast US in conjunction with available tree ring datasets. A preliminary evaluation relating these hydrologic datasets to moisture sensitive tree ring datasets will be performed to determine the potential success of developing paleo reconstructions of hydrologic variables. Results of this research may include determining which hydrologic variable (unimpaired streamflow, precipitation, soil moisture) results in the best skill; the best (most skillful) hydrologic season or seasons to reconstruct; which species of tree is most effective (retained) in reconstruction models; and where is there a need for additional data (tree ring chronology) collections.