Investigation of long-term trends in selected physical and chemical parameters of inflows to Everglades National Park, 1977-2005

Environ Monit Assess. 2011 Jul;178(1-4):525-36. doi: 10.1007/s10661-010-1710-2. Epub 2010 Sep 24.

Abstract

Data of seven water-quality parameters from inflows to the Everglades National Park were collected at three monitoring stations and analyzed for temporal trends. The best-fit models for the existence of trends were evaluated. The Kolmogorov-Smirnov test was used to select the theoretical distribution which best fit the data. Simple regression was used to examine the parameters for concentration-discharge relationships. The power and linear models were found to better describe the concentration-discharge relationships. Loess trend lines indicated a similar trend period of color value change during the selected period at three stations. The sharp decrease in color after 1990 at each station is consistent with the beneficial impacts of control measures, which include Best Management Practices implementation in the Everglades Agricultural Area, water management improvement, and the construction of additional stormwater treatment areas. The existence of trend analysis was performed by using the uncensored seasonal Kendall test. Conductivity and color decreased significantly at two (S12A and S333) of three stations. Alkalinity decreased significantly at S333. A "best-fit" model was selected to describe a trend change with statistical significance; the second-order equation provides a better description of the trend. This study also indicates that by using the routinely measured water-quality parameters, it may be easier to quantify the changes in water quality to aid in making water resources management decisions.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Environmental Monitoring
  • Florida
  • Fresh Water / chemistry*
  • Hydrogen-Ion Concentration
  • Models, Chemical
  • Water Pollutants, Chemical / analysis*
  • Water Pollution, Chemical / statistics & numerical data*
  • Wetlands*

Substances

  • Water Pollutants, Chemical