Graduation Year

2005

Document Type

Thesis

Degree

M.S.C.E.

Degree Granting Department

Civil Engineering

Major Professor

Dr. Mark A. Ross.

Keywords

Hydrologic models, Nutrient loading, Parameter estimation, Tmdl, Plrg

Abstract

For surface-water resource management studies, it is important to quantify all of the mechanisms that contribute to water quantity and influence water quality. In this regard, various methods have been used to ground-water fluxes in lake systems. These have included physical measurements (e.g., seepage meters), flow-net analyses, water budgets, chemical tracers, ground-water flow models, and statistical analyses. The method developed for this study for calculating ground-water inflow uses a simplified, 1-layer (surficial aquifer) ground-water flow model. The test area was on a set of lakes known as the Winter Haven Chain of Lakes in Polk County, Florida. The technique combines the use of a numerical model (MODFLOW) with an inverse prediction technique (PEST) to determine net surficial recharge rates. Within the model, the lakes were represented as constant-head boundaries.

A general, surficial ground water no-flow boundary was delineated around the entire lake system based on the topographic boundaries. The model used annual average lake elevations to create a constant-head boundary for each lake for each year. Annual average elevations of surficial well heads were used as target well data. Model results generally support previous studies in the region, concluding that the lake chain receives significant inflow from the surficial aquifer and leaks to the Floridan aquifer. As a consequence, ground-water quality constituency was found to be of critical importance. One of the most important observations from this study is the need for accurate ground-water concentrations for ridge lake water quality management. The initial measured values used in this study were highly variable, uncertain, and likely underestimated the effect that ground water has on nutrient loading to the Winter Haven Chain of Lakes.

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