Click on “Download PDF” for the PDF version or on the title for the HTML version.

If you are not an ASABE member or if your employer has not arranged for access to the full-text, Click here for options.

Multivariate Analysis of Temporal and Spatial Variability of Water Quality in the Southern Indian River Lagoon (IRL), Florida

Published by the American Society of Agricultural and Biological Engineers, St. Joseph, Michigan

Citation:  2007 ASAE Annual Meeting  072107.(doi:10.13031/2013.23413)
Authors:   Yun Qian, Kati W Migliaccio, Yongshan Wan , Yuncong Li
Keywords:   multivariate analysis, water quality index, trend analysis, Indian River Lagoon

Appropriate assessment of long-term water quality monitoring data is essential to correctly interpret data and this often requires use of multivariate techniques. Our objective was to evaluate the temporal and spatial variations in water quality in the Southern Indian River Lagoon (IRL) watershed, Florida using several multivariate techniques as well as a comprehensive water quality index (WQI) based on exploratory water quality constituents greatly contributing to the construction of exploratory factors (EFs) which were derived from exploratory factor analysis (EFA). Trend analysis was conducted on EFs and WQI based on annual and seasonal data sets to estimate time series trends in water quality. Cluster analysis (clustering) was used to cluster the six monitoring stations into three groups. The first five EFs explain around 70% of the total variance and were used to interpret water quality characterized by original constituents for the purpose of data reduction. Nutrient species (P and N) were major variables involved in the construction of the EFs. Seasonal and spatial differences were observed in compositional patterns of EFs. Positive or negative trends were detected for different EF at different monitoring groups during different seasons. The composite WQI showed significant difference among the three clustering groups with the lowest WQI median in station C44S80. At the three monitoring groups, medians of WQI were significantly greater in the wet than in the dry season, which implied that wet season rainfall likely resulted in constituent transport into canals.

(Download PDF)    (Export to EndNotes)