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MULTIVARIATE NONPARAMETRIC TESTS FOR TREND IN WATER QUALITY 1
Author(s) -
Lettenmaier Dennis P.
Publication year - 1988
Publication title -
jawra journal of the american water resources association
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.957
H-Index - 105
eISSN - 1752-1688
pISSN - 1093-474X
DOI - 10.1111/j.1752-1688.1988.tb00900.x
Subject(s) - nonparametric statistics , statistics , statistic , covariance , multivariate statistics , test statistic , mathematics , econometrics , statistical hypothesis testing , variance (accounting) , trend analysis , contrast (vision) , statistical power , computer science , accounting , artificial intelligence , business
National and state fixed station stream quality monitoring networks have now been in existence for over ten years. The resulting data bases provide opportunities and challenges for statistical trend assessment. Although nonparametric tests have been developed that are well suited to such problems, the interpretation of variations in trend significance between seasons and variables remains a problem. One recently developed test is based on the sum of Mann‐Kendall statistics over seasons or variables, with the test statistic variance computed as the sum of the covariances of the individual Mann‐Kendall statistics. In this method, up‐ and downtrends can cancel, giving an overall indication of no trend. A related test which is sensitive to trend regardless of direction has been shown to behave poorly for typical stream quality record lengths. An alternative formulation which is sensitive to up‐ and downtrends and has power approaching that of the covariance sum method, is described. In addition, a variation of a contrast test for discriminating trend directions and magnitudes among variables or seasons where correlation between seasons or variables is present is described, and tests of its performance reported.