Graduation Year

2010

Document Type

Dissertation

Degree

Ph.D.

Degree Granting Department

Civil Engineering

Major Professor

Mark A. Ross, Ph.D.

Committee Member

Jeffrey A. Cunningham, Ph.D.

Committee Member

Jeffrey S. Geurink, Ph.D.

Committee Member

Terrie M. Lee, M.S.E.

Committee Member

Rafael A. Perez, Ph.D.

Committee Member

Mark C. Rains, Ph.D.

Keywords

analytical techniques, bathymetry, frequency analysis, hydrologic models, water storage, wetlands

Abstract

Wetlands are important elements of watersheds that influence water storage, surface water runoff, groundwater recharge/discharge processes, and evapotranspiration. To understand the cumulative effect wetlands have on a watershed, one must have a good understanding of the water-level fluctuations and the storage characteristics associated with multiple wetlands across a region. An improved analytical method is presented to describe the storage characteristics of wetlands in the absence of detailed hydrologic and bathymetric data. Also, a probabilistic approach based on frequency analysis is developed to provide insight into surface and groundwater interactions associated with isolated wetlands. The results of the work include: 1) a power-function model based on a single fitting parameter and two physically based parameters was developed and used to represent the storage of singular or multiple wetlands and lakes with acceptable error, 2) a novel hydrologic characterization applied to 56 wetlands in west-central Florida provided new information about wetland hydroperiods which indicated standing water was present in the wetlands 62% of the time and these wetlands were groundwater recharge zones 59% of the time over the seven year study, 3) the smallest extreme value probability distribution function was identified as the best-fit model to represent the water levels of five wetland categories in west-central Florida, 4) representative probability models were developed and used to predict the water levels of specific wetland categories, averaging less than 10% error between the predicted and recorded water levels, and 5) last, based on this probability analysis, the various wetland categories were shown to exhibit similar means, extremes and ranges in water-level behavior but unique slopes in frequency distributions, a here to for new finding. These results suggest that wetland types may best be differentiated by the regular variability in water levels, not by the mean and/or extreme water levels. The methods and analytical techniques presented in this dissertation can be used to help understand and quantify wetland hydrology in different climatological or anthropogenic stress conditions. Also, the methods explored in this study can be used to develop more accurate and representative hydrologic simulation models.

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