ABSTRACT: The isotope mass-balance approach was used to estimate ground-water inflow to 81 lakes in the central highlands and coastal lowlands of central Florida. The study area is characterized by a subtropical climate and numerous lakes in a mantled karst terrain. Ground-water inflow was computed using both steady-state and transient formulations of the isotope mass-balance equation. More detailed data were collected from two study lakes, including climatic, hydrologic, and isotopic (hydrogen and oxygen isotope ratio) data. For one of these lakes (Lake Starr), ground-water inflow was independently computed from a water-budget study. Climatic and isotopic data collected from the two lakes were similar even though they were in different physiographic settings about 60 miles apart. Isotopic data from all of the study lakes plotted on an evaporation trend line, which had a very similar slope to the theoretical slope computed for Lake Starr. These similarities suggest that data collected from the detailed study lakes can be extrapolated to the rest of the study area.
Ground-water inflow computed using the isotope mass-balance approach ranged from 0 to more than 260 inches per year (or 0 to more than 80 percent of total inflows). Steady-state and transient estimates of ground-water inflow were very similar. Computed ground-water inflow was most sensitive to uncertainty in variables used to calculate the isotopic composition of lake evaporate (isotopic compositions of lake water and atmospheric moisture and climatic variables). Transient results were particularly sensitive to changes in the isotopic composition of lake water. Uncertainty in ground-water inflow results is considerably less for lakes with higher ground-water inflow than for lakes with lower ground-water inflow. Because of these uncertainties, the isotope mass-balance approach is better used to distinguish whether ground-water inflow quantities fall within certain ranges of values, rather than for precise quantification.
The lakes fit into three categories based on their range of ground-water inflow: low (less than 25 percent of total inflows), medium (25-50 percent of inflows), and high (greater than 50 percent of inflows). The majority of lakes in the coastal lowlands had low ground-water inflow, whereas the majority of lakes in the central highlands had medium to high ground-water inflow.
Multiple linear regression models were used to predict ground-water inflow to lakes. These models help identify basin characteristics that are important in controlling ground-water inflow to Florida lakes. Significant explanatory variables include: ratio of basin area to lake surface area, depth to the Upper Floridan aquifer, maximum lake depth, and fraction of wetlands in the basin. Models were improved when lake water-quality data (nitrate, sodium, and iron concentrations) were included, illustrating the link between ground-water geochemistry and lake chemistry. Regression models that considered lakes within specific geographic areas were generally poorer than models for the entire study area. Regression results illustrate how more simplified models based on basin and lake characteristics can be used to estimate ground-water inflow.
Although the uncertainty in the amount of ground-water inflow to individual lakes is high, the isotope mass-balance approach was useful in comparing the range of ground-water inflow for numerous Florida lakes. Results were also helpful in understanding differences in the geographic distribution of ground-water inflow between the coastal lowlands and central highlands. In order to use the isotope mass-balance approach to estimate inflow for multiple lakes, it is essential that all the lakes are sampled during the same time period and that detailed isotopic, hydrologic, and climatic data are collected over this same period of time. Isotopic data for Florida lakes can change over time, both seasonally and interannually, primarily because of differences in net precipitation. The isotope mass-balance approach was most successful for lakes in the central highlands, where lakes have higher ground-water inflow, are deeper, and undergo less isotopic variability, compared to lakes in the coastal lowlands. Results from this study illustrate the large range in ground-water inflow to Florida lakes and underscore the importance of ground water in the water budget of many of Florida's lakes.
A. Isotopic composition of rainwater at Lake Starr and Halfmoon Lake
B. Isotopic composition of atmospheric moisture at Lake Starr and Halfmoon Lake
C. Isotopic composition of ground water at selected study lakes
D. Isotopic composition of surface-water inflow
E. Isotopic composition of lake water from summer 1999 and winter 2000 samplings
F. Basin characteristics used in final multiple regression models for the entire study area
1. Map showing location of study lakes and relation to geomorphic regions
2. Photograph of aerial view of lakes in Polk County near Winter Haven, Florida
3. Schematic of generalized hydrogeologic section through a central Florida lake
4. General relation between dD and d18O for global meteoric water and water that has undergone evaporation
5. Schematic illustrating differences in isotopic composition between two lakes with different amounts of ground-water inflow
6-22. Graphs showing:
1. Location and size of study lakes
2. Annual water budget for Lake Starr (1996-2000) and Halfmoon Lake (June 1996-May 2000)
3. Instantaneous discharge in inflow channels to Crooked Lake, Clinch Lake, and Lake Lotela
4. Average isotopic composition of rainwater and ground water at Lake Starr and Halfmoon Lake
5. Variables used to back-calculate the isotopic composition of atmospheric moisture from the Lake Starr water budget
6. Comparison of ground-water inflow to Lake Starr from water-budget and isotope mass-balance approaches
7. Ground-water inflow results using steady-state and transient isotope mass-balance approaches
8. Summary of sensitivity analysis of ground-water inflow computed from the isotope mass-balance approach for Lake Starr
9. Potential explanatory variables with statistically significant correlation coefficients (p<0.05) with ground-water inflow
10. Multiple linear regression models to predict ground-water inflow