Nonparametric tests for trend detection in water quality time series

Journal Article · Wed Jun 01 04:00:00 EDT 1988 · Water Resour. Bull.; (United States)

DOI:https://doi.org/10.1111/j.1752-1688.1988.tb00904.x· OSTI ID:6606738

Berryman, D; Bobee, B; Cluis, D; Haemmerli, J

A review of nonparametric tests for trend leads to the conclusion that Mann-Whitney, Spearman, and Kendall tests are the best choice for trend detection in water quality time series. Recently these tests have been adapted to account for dependence and seasonality in such series. For monotonic trends, a procedure allowing to select the pertinent tests considering the characteristics of time series is proposed and the practical limitations of the tests are also brought out. This procedure has been applied to identify the appropriate trend detection test for the time series of nine water quality parameters at Lake Laflamme (Quebec). When a time series can be tested with the Mann-Whitney, Kendall, Spearman, or Lettenmaier (1976) test, the number of observations required to detect trends of a given magnitude, for selected significance and power levels can be calculated with the power function of the t test. When the test proposed by Hirsch, et al., Hirsch and Slack, or Farrell need to be used, the number of observations can only be estimated approximately from the results of empirical power studies.

• Research Organization: Ministere de l'Environnement du Quebec, Sainte-Foy (Canada)
• OSTI ID: 6606738
• Journal Information: Water Resour. Bull.; (United States), Journal Name: Water Resour. Bull.; (United States) Vol. 24:3; ISSN WARBA
• Country of Publication: United States
• Language: English

Related Subjects

520200* -- Environment
Aquatic-- Chemicals Monitoring & Transport-- (-1989)
54 ENVIRONMENTAL SCIENCES
CANADA
ENVIRONMENTAL QUALITY
LAKES
MATHEMATICS
MONITORING
NORTH AMERICA
QUEBEC
SEASONAL VARIATIONS
SURFACE WATERS
TIME-SERIES ANALYSIS
VARIATIONS
WATER QUALITY