Elsevier

Journal of Hydrology

Volume 517, 19 September 2014, Pages 700-714
Journal of Hydrology

Large scale climate oscillations and mesoscale surface meteorological variability in the Apalachicola-Chattahoochee-Flint River Basin

https://doi.org/10.1016/j.jhydrol.2014.06.002Get rights and content

Highlights

  • We analyze climatological circumstances leading to low flows in the ACF.

  • We use canonical correlation analysis to review relationships.

  • This study uses temperature data and four, multi-temporal, computed SPI values.

  • Climate oscillations in this study include AMO, NAO, PDO, and SOI.

  • Study establishes a need for appropriate temporal SPI and subbasin study.

Summary

The “water wars” between Alabama, Georgia, and Florida over water restrictions and allocation in the Apalachicola-Chattahoochee-Flint River Basin (ACF) stem, in part, from the occurrence of several droughts in the 1980s, the dramatic increase in water use in the northern basin around Atlanta, and increased agricultural usage in the central basin. This study examines relationships between available surface climatological variables connected to evapotranspiration and climatic oscillations using canonical correlation analysis (CCA).

Canonical loadings and cross loadings from CCA are evaluated in two tests using temperature and precipitation data and four climate oscillations – the Atlantic Multidecadal Oscillation (AMO), North Atlantic Oscillation (NAO), Pacific Decadal Oscillation (PDO), and Southern Oscillation Index (SOI). In the first test, the six-month Standardized Precipitation Index (SPI) and all four seasons of the four climate oscillations from every subbasin in the ACF are evaluated, revealing relationships mostly with the AMO and NAO, and primarily with temperatures. In order to focus more on precipitation and the variance among the different temporal scales of the SPI, Test Two looks at the relationship between all four SPI variations and all four seasons of the climate oscillations from the extreme northern and southern subbasins. Test Two shows the twenty-four month SPI has the largest loadings and variance explained, which may be contributed to the longer frequencies in the AMO and PDO. The southern part of the basin is largely influenced by SOI, while the northern subbasin the AMO and PDO. Concurrent relationships between the same season of the climate oscillation and meteorological variable confirm previously researched directions of the relationships between the oscillation and precipitation or temperature in both Test One and Test Two.

Introduction

Water is increasingly recognized as a vital and limited resource in many regions of the world. The “water wars” of the ACF began in the 1980s when a series of droughts in the southeastern United States significantly reduced flows in the three named rivers. Water restrictions and allocation became a source of debate between the states of Alabama, Georgia, and Florida, who share the integral resources provided by the highly managed waters of the ACF.

The ACF river basin originates in northern Georgia with the Chattahoochee River draining from Lake Sidney Lanier near Atlanta, flowing down the Georgia and Alabama border before eventually joining with the Flint River at Lake Seminole at the Georgia/Florida border. From here the Apalachicola River drains from Lake Seminole down to the Gulf of Mexico into Apalachicola Bay (Fig. 1). The ACF is nearly 385 miles (619 km) long and 50 miles (80 km) wide, covering approximately 50,800 km2. The majority of the basin lies within Georgia (74%), with the remainder in western Alabama (15%) and the western panhandle of Florida (11%) (USACE, 1998). Its annual average discharge ranks it 21st in magnitude among river systems of the conterminous United States (USACE, 1998).

The waters in the basin are heavily managed for a variety of uses including agriculture, recreation, industry, and hydropower production. The ACF currently contains 16 dams and main-stem reservoirs, 14 of which are associated with hydropower operations (Frick et al., 1998). Management introduces water-use agendas and technology that may ultimately generate long-term, unintended consequences for the environment, exacerbating initial conflicts or leading to worse conditions (Carey et al., 2012). The ACF is sensitive to the uses and management of the different sections of the basin, as more drawdown in Atlanta and irrigation along the Flint causes lower flows to the Apalachicola Bay, one of the planet’s “biodiversity hotspots” (Ruhl, 2005).

For these reasons, the ACF has a complex legal history. Legal battles flared between Georgia, Alabama, and Florida over water reallocations granted by the United States Army Corps of Engineers (Corps), the responsible water management agency of the ACF. Despite the use of an Interstate Water Compact, protective orders, numerous lawsuits, and court-issued deadlines for agreements, the three states remain in battle over the appropriate water allocation, minimum streamflows, and Atlanta access to drawdown of Lake Lanier. As of January 2014, the Supreme Court is reviewing a request from Florida to hear the most recent lawsuit against Georgia on ACF water use.

High interest in this issue has inspired several other studies to be conducted on the ACF or parts of it, particularly concerning streamflow and drought indicators. One such study by Light et al. (2006) focuses on the water-level decline in the Apalachicola and the associated effects on the floodplain in the last half century. Another study by Steinemann (2003) uses a probabilistic framework to evaluate different drought indicators for the ACF as part of the developed drought plan between the three feuding states. Morey et al. (2009) evaluates variability in the Apalachicola River flow rates and discharge to the Gulf of Mexico linked to precipitation anomalies. Despite these efforts, an elaborate study has yet to be conducted for the ACF with a larger climatological theme investigating the variance and relationships of mesoscale surface climatological variability with global scale climate oscillations.

Important prior work on hydroclimatology includes studies by Ropelewski and Halpert, 1986, Enfield et al., 2001, McCabe et al., 2004, Barlow et al., 2000, Vincente-Serrano et al., 2011, Stambaugh et al., 2011, Keyan et al., 2010, Smith et al., 1998. The findings and relationships from these studies are complex and tend to focus on regional results that sometimes conflict. Analysis by Mishra and Singh (2010) concluded that drought occurrences around the world are related to large-scale climate oscillations, and further that understanding drought at the local scale is generally missing and potentially important to understanding the spatial and temporal heterogeneity of typical hydrometeorological variables.

Arrocha and Ruscher (2005) completed work assessing precipitation patterns in the last century using annual precipitation data from representative cooperative and first order stations in the ACF. Using a climatological “norm” value computed from 1931–1980 data, precipitation anomalies were examined from 1885 to 2002 using standard deviation and percentile calculations at 50 key stations throughout the ACF. They found extreme dry event years tended to be associated with extensive dry periods; however, there were also a few solitary drought years identified. The drought analysis found “no obvious pattern” for the return of drought periods, however a La Niña event occurred during about 30% of the below normal precipitation years. Their study suggested further investigation into the relationship between climate trends and other multidecadal oscillations such as the AMO and the PDO.

The purpose of this study is to extend the previous research and better describe climatological conditions in the ACF basin over the last century and conduct further investigation of surface variables and other possible climate links to drought in the ACF. Instead of focusing on precipitation percentiles, this study utilizes SPI values of three, six, twelve, and twenty-four month indices. Along with the SPI, monthly minimum and maximum temperature data is used for a more complete description of the variance in the mesoscale meteorological variables possibly linked to climate patterns. The temperature data is provided through cooperative first order and Automated Surface Observing Stations (ASOS) and the Parameter-elevation Regressions on Independent Slopes Model (PRISM dataset) (Daly et al., 2002). Our final dataset is a subset of those used by Arrocha and Ruscher (2005), consisting of 24 stations covering several different climate divisions in the ACF basin, as shown in Fig. 1.

Based on previous research, we investigate the impacts of the AMO, NAO, PDO, and El Niño Southern Oscillation (ENSO) on observed climate state. These have all been suggested by other authors to be connected to precipitation patterns in the southeastern United States. While other studies of this nature have been performed on the southeast in general, no study has specifically focused on the ACF and the possible variations throughout the ACF.

Temperature data, as well as precipitation, are associated with changes in climatic oscillations. Both of these climatological variables influence streamflow variability by contributing to evapotranspiration (Hornberger et al., 1998) and therefore hydrological drought (Mishra and Singh, 2010). Research on multiple climate oscillations suggests that some climate oscillations may influence the strength or signal of other climate indices, which could possibly be relevant to our results (Gershunov and Barnett, 1998, Rajagopalan et al., 2000, Sutton and Hodson, 2003, Tootle et al., 2005). This uncertainty regarding coupling or competing effects by multiple climate oscillations requires a more fuzzy modeling approach, combining the effects of multiple oscillations and looking at grades of membership from dry to wet, and hot to cold (Şen, 2010).

While streamflow is an important variable in basin-specific drought studies, we did not include it as a variable in our study because the ACF is significantly managed by the Corps through federal reservoirs, dams, and other control structures (Carriker, 2000). There is also no streamflow data available prior to 1930 to correspond to the full range of our climatological dataset. Other relevant variables such as relative humidity (or dew point temperature) and soil moisture and temperature are not as widely available in National Climatic Data Center (NCDC) records and so cannot be utilized in this manner.

This study is organized into sections as follows – a review of the data, then discussion of the potential teleconnections to considered climate oscillations, followed by evaluation of two tests using CCA to determine relationships between four climate oscillations, temperature, and four temporal variations of SPI, drawing and summarizing conclusions at the end.

Section snippets

Climatological variables

For the intended climate study, a long and consistent record of monthly precipitation and temperature data is needed to reduce the potential for error (e.g. Mishra and Singh, 2010). Most of the data is provided by cooperative and first-order stations within the ACF by NCDC. Missing and flagged data values were replaced with the PRISM data, as discussed later in this section. A total of 24 stations were used, 4 of these stations being in Florida and 20 stations in Georgia. A map of the stations

Climatic oscillations overview

Our study evaluates four climate oscillations that have been most frequently attributed to precipitation variability in the southeast United States. This section describes the data, characteristics, and mechanisms behind the oscillations, as well as the relationships to temperature and precipitation from previous literature for each oscillation. These oscillations can be seen in Fig. 4.

Methodology

Classical discrete Fourier transforms were carried out on all climate and precipitation indices used in this study to elucidate a fundamental understanding of any periodicities and interdependencies. However, these did not indicate any significant findings, most likely because the occurrence of drought (and wet) periods were aperiodic. The relatively long periods of time between pronounced drought provides for only a few important events. The most revealing time series analysis conducted was

Test One results: SPI6 and temperature

The goal of Test One is to collectively describe the relationships between the climatological surface variables and climate oscillations for all subbasins for a multivariate approach to understanding drought in the ACF.9 A summary of the canonical correlations and proportion of variance explained for both tests is provided in Table 4.

Test One reveals the strongest canonical relationships occur in the

Summary and conclusions

Canonical correlation analysis (CCA) is utilized to develop a complex, multivariate approach to analyze the climate oscillation and surface climatology relationships in the ACF basin. Canonical correlation analysis uses two sets of variables, dependent (surface climatological variables) and independent (climate oscillations), to create canonical variates for each set of data that maximize the correlations between the variates. Two tests are developed using CCA for the analysis. Test One

Acknowledgement

The authors acknowledge Dr. Henry Fuelberg, Dr. Jon E. Ahlquist, Helen M. Light, and Dr. John Hanley for reviewing the preliminary work for this study.

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