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Journal of Environmental Quality Abstract - Surface Water Quality

Seasonality of Selected Surface Water Constituents in the Indian River Lagoon, Florida


This article in JEQ

  1. Vol. 36 No. 2, p. 416-425
    Received: May 8, 2006

    * Corresponding author(s): yunli@mail.ifas.ufl.edu
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  1. Y. Qiana,
  2. K. W. Migliaccioa,
  3. Y. Wanb,
  4. Y. C. Li *a and
  5. D. Chinc
  1. a Univ. of Florida, Tropical Research & Education Center, Soil and Water Science Dep. and Biological and Agricultural Engineering Dep., IFAS, Univ. of Florida, 18905 SW 280th St., Homestead, FL 33031
    b South Florida Water Management District, 3301 Gun Club Rd., West Palm Beach, FL 33406
    c Univ. of Miami, Dep. of Civil, Architectural, and Environmental Engineering, Coral Gables, FL 33124


Seasonality is often the major exogenous effect that must be compensated for or removed to discern trends in water quality. Our objective was to provide a methodological example of trend analysis using water quality data with seasonality. Selected water quality constituents from 1979 to 2004 at three monitoring stations in southern Florida were evaluated for seasonality. The seasonal patterns of flow-weighted and log-transformed concentrations were identified by applying side-by-side boxplots and the Wilcoxon signed-rank test (p < 0.05). Seasonal and annual trends were determined by trend analysis (Seasonal Kendall or Tobit procedure) using the U.S. Geological Survey (USGS) Estimate TREND (ESTREND) program. Major water quality indicators (specific conductivity, turbidity, color, and chloride), except for turbidity at Station C24S49, exhibited significant seasonal patterns. Almost all nutrient species (NO2–N, NH4–N, total Kjeldahl N, PO4–P, and total P) had an identical seasonal pattern of concentrations significantly greater in the wet than in the dry season. Some water quality constituents were observed to exhibit significant annual or seasonal trends. In some cases, the overall annual trend was insignificant while opposing trends were present in different seasons. By evaluating seasonal trends separately from all data, constituents can be assessed providing a more accurate interpretation of water quality trends.

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