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Nonparametric test performance for trends in water quality with sampling design applications

Olivier Thas UGent, Lieven Van Vooren and Jean-Pierre Ottoy UGent (1998) JOURNAL OF THE AMERICAN WATER RESOURCES ASSOCIATION. 34(2). p.347-357
abstract
In this paper four nonparametric tests for monotonic trend detection are compared with respect to their power and accuracy. The importance of comparing powers at equal empirical significance levels rather than nominal levels is stressed. Therefore, an appropriate graphical method is presented. The effect of the sampling frequency is also assessed using Monte Carlo simulations and a trajectory representation that visualizes the dynamics of the trade-off between the type I and type II errors. These methods are applied to compare four nonparametrical tests (seasonal Mann-Kendall, modified seasonal Mann-Kendall, covariance eigenvalue and covariance inversion) under several conditions. It is concluded with respect to the power that it is not worthwhile for the modified seasonal Mann-Kendall test applied to the AR(1) process considered in this paper to increase the sampling frequency from monthly to biweekly for detecting a monotonic trend of 5 percent, 10 percent, or 15 percent of the process variance. Under these conditions the seasonal Mann-Kendall test is highly liberal, while the covariance inversion and the covariance eigenvalue test are conservative. This research is situated in the development of an efficient sampling design for the Flemish water quality monitoring network.
Please use this url to cite or link to this publication:
author
organization
year
type
journalArticle (original)
publication status
published
subject
keyword
water quality, statistics, trend detection, nonparametric tests, monitoring, TIME-SERIES
journal title
JOURNAL OF THE AMERICAN WATER RESOURCES ASSOCIATION
J. Am. Water Resour. Assoc.
volume
34
issue
2
pages
347 - 357
Web of Science type
Article
Web of Science id
000073273500011
ISSN
0043-1370
DOI
10.1111/j.1752-1688.1998.tb04140.x
language
English
UGent publication?
yes
classification
A1
copyright statement
I have transferred the copyright for this publication to the publisher
id
177682
handle
http://hdl.handle.net/1854/LU-177682
date created
2004-01-14 13:41:00
date last changed
2013-04-26 10:25:28
@article{177682,
  abstract     = {In this paper four nonparametric tests for monotonic trend detection are compared with respect to their power and accuracy. The importance of comparing powers at equal empirical significance levels rather than nominal levels is stressed. Therefore, an appropriate graphical method is presented. The effect of the sampling frequency is also assessed using Monte Carlo simulations and a trajectory representation that visualizes the dynamics of the trade-off between the type I and type II errors. These methods are applied to compare four nonparametrical tests (seasonal Mann-Kendall, modified seasonal Mann-Kendall, covariance eigenvalue and covariance inversion) under several conditions. It is concluded with respect to the power that it is not worthwhile for the modified seasonal Mann-Kendall test applied to the AR(1) process considered in this paper to increase the sampling frequency from monthly to biweekly for detecting a monotonic trend of 5 percent, 10 percent, or 15 percent of the process variance. Under these conditions the seasonal Mann-Kendall test is highly liberal, while the covariance inversion and the covariance eigenvalue test are conservative. This research is situated in the development of an efficient sampling design for the Flemish water quality monitoring network.},
  author       = {Thas, Olivier and Van Vooren, Lieven and Ottoy, Jean-Pierre},
  issn         = {0043-1370},
  journal      = {JOURNAL OF THE AMERICAN WATER RESOURCES ASSOCIATION},
  keyword      = {water quality,statistics,trend detection,nonparametric tests,monitoring,TIME-SERIES},
  language     = {eng},
  number       = {2},
  pages        = {347--357},
  title        = {Nonparametric test performance for trends in water quality with sampling design applications},
  url          = {http://dx.doi.org/10.1111/j.1752-1688.1998.tb04140.x},
  volume       = {34},
  year         = {1998},
}

Chicago
Thas, Olivier, Lieven Van Vooren, and Jean-Pierre Ottoy. 1998. “Nonparametric Test Performance for Trends in Water Quality with Sampling Design Applications.” Journal of the American Water Resources Association 34 (2): 347–357.
APA
Thas, O., Van Vooren, L., & Ottoy, J.-P. (1998). Nonparametric test performance for trends in water quality with sampling design applications. JOURNAL OF THE AMERICAN WATER RESOURCES ASSOCIATION, 34(2), 347–357.
Vancouver
1.
Thas O, Van Vooren L, Ottoy J-P. Nonparametric test performance for trends in water quality with sampling design applications. JOURNAL OF THE AMERICAN WATER RESOURCES ASSOCIATION. 1998;34(2):347–57.
MLA
Thas, Olivier, Lieven Van Vooren, and Jean-Pierre Ottoy. “Nonparametric Test Performance for Trends in Water Quality with Sampling Design Applications.” JOURNAL OF THE AMERICAN WATER RESOURCES ASSOCIATION 34.2 (1998): 347–357. Print.