Multivariate statistical and trend analyses of surface water quality in the central Indian River Lagoon area, Florida

Abstract

The Indian River Lagoon (IRL) estuary system is of concern to environmental scientists, because its water quality has been deteriorating in the past several decades. To understand spatial variability and temporal changes of surface water quality in the central IRL area, cluster analysis, principle component analysis, and nonparametric trend analysis were conducted for a dataset of 27,648 observations, collected for twelve parameters of surface water quality over the period of 1998–2013 at twelve monitoring stations. The cluster analysis separated the data into four groups, which are closely related to the locations of the monitoring stations. The principal component analysis was applied to each of the four groups to determine the important water quality parameters. In each group, five principal components explain 75–85% of the total data variance, and the components include the following water quality parameters: nutrient species (nitrogen and phosphorus), physicochemical parameters (salinity, specific conductivity, pH, and DO), and erosion factors (total suspended solids and turbidity). Statistically significant trends in these water quality parameters were detected by applying the Mann–Kendall trend test, and abrupt trend shifts were detected by applying the sequential Mann–Kendall trend test. The trends and trend shifts are attributed to land use changes, projects of lagoon restoration, and the 2006 drought conditions in the study area. The results of this study can be of direct use to management projects for improving surface water quality at the central IRL area.