Main Title |
Multivariate Trend Testing of Lake Water Quality. |
Author |
Loftis, J. C. ;
Taylor, C. H. ;
Newell, A. D. ;
Chapman, P. L. ;
|
CORP Author |
Colorado State Univ., Fort Collins. Dept. of Agricultural and Chemical Engineering. ;Merrell Dow Research Inst., Cincinnati, OH. ;ManTech Environmental Technology, Inc., Corvallis, OR. Environmental Research Lab.;Corvallis Environmental Research Lab., OR. |
Publisher |
cJun 91 |
Year Published |
1991 |
Report Number |
EPA-68-03-3439; EPA/600/J-94/510; |
Stock Number |
PB95-148722 |
Additional Subjects |
Lakes ;
Water quality ;
Trends ;
Multivariate analysis ;
Water pollution sampling ;
Acid rain ;
Long term effects ;
Air pollution ;
Air water interactions ;
Statistical analysis ;
Reprints ;
Acid precipitation
|
Internet Access |
|
Holdings |
Library |
Call Number |
Additional Info |
Location |
Last Modified |
Checkout Status |
NTIS |
PB95-148722 |
Some EPA libraries have a fiche copy filed under the call number shown. |
|
07/26/2022 |
|
Collation |
15p |
Abstract |
Multivariate methods of trend analysis offer the potential for higher power in detecting gradual water quality changes as compared to multiple applications of univariate tests. Simulation experiments were used to investigate the power advantages of multivariate methods for both linear model and Mann-Kendall based approaches. The experiments focused on quarterly observations of three water quality variables with no serial correlation and with several different intervariable correlation structures. The multivariate methods were generally more powerful than the univariate methods, offering the greatest advantage in situations where water quality variables were positively correlated with trends in opposing directions. For illustration, both the univariate and multivariate versions of the Mann-Kendall based tests were applied to case study data from several lakes in Maine and New York which had been sampled as part of EPA's long term monitoring study of acid precipitation effects. |