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Statistical Estimation and Interpretation of Trends in Water Quality Time Series

Zetterqvist, Lena LU (1991) In Water Resources Research 27(7). p.1637-1648
Abstract
Three approaches to trend analysis of water quality time series are discussed: (1) seasonal model, with a test for trend based on ranks of observations, with observations assumed to be m dependent; (2) transfer function noise model, in which covariate series may be included by means of transfer functions, with the remaining noise modeled as a seasonal autoregressive moving average process; and (3) component model, with the noise decomposed into series which describe trends, and irregular and seasonal variation. Models are studied with regards to their ability to include covariate series, possibility of interpretation of trends, treatment of seasonal variation and serial dependence, and robustness for outliers. We regard the component model... (More)
Three approaches to trend analysis of water quality time series are discussed: (1) seasonal model, with a test for trend based on ranks of observations, with observations assumed to be m dependent; (2) transfer function noise model, in which covariate series may be included by means of transfer functions, with the remaining noise modeled as a seasonal autoregressive moving average process; and (3) component model, with the noise decomposed into series which describe trends, and irregular and seasonal variation. Models are studied with regards to their ability to include covariate series, possibility of interpretation of trends, treatment of seasonal variation and serial dependence, and robustness for outliers. We regard the component model being the most realistic and the most informative of the three approaches. Models are applied to series of monthly phosphorus concentration in the Ljungbyån River in Southern Sweden. (Less)
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author
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
Mann-Kendall test, nonparametric statistics, Time series, seasonal models
in
Water Resources Research
volume
27
issue
7
pages
1637 - 1648
publisher
American Geophysical Union
external identifiers
  • scopus:0026266531
ISSN
0043-1397
DOI
10.1029/91WR00478
language
English
LU publication?
yes
id
7965d022-10a7-482a-85a2-840a6033bca4 (old id 1715356)
date added to LUP
2010-11-12 12:34:48
date last changed
2017-10-01 03:55:48
@article{7965d022-10a7-482a-85a2-840a6033bca4,
  abstract     = {Three approaches to trend analysis of water quality time series are discussed: (1) seasonal model, with a test for trend based on ranks of observations, with observations assumed to be m dependent; (2) transfer function noise model, in which covariate series may be included by means of transfer functions, with the remaining noise modeled as a seasonal autoregressive moving average process; and (3) component model, with the noise decomposed into series which describe trends, and irregular and seasonal variation. Models are studied with regards to their ability to include covariate series, possibility of interpretation of trends, treatment of seasonal variation and serial dependence, and robustness for outliers. We regard the component model being the most realistic and the most informative of the three approaches. Models are applied to series of monthly phosphorus concentration in the Ljungbyån River in Southern Sweden.},
  author       = {Zetterqvist, Lena},
  issn         = {0043-1397},
  keyword      = {Mann-Kendall test,nonparametric statistics,Time series,seasonal models},
  language     = {eng},
  number       = {7},
  pages        = {1637--1648},
  publisher    = {American Geophysical Union},
  series       = {Water Resources Research},
  title        = {Statistical Estimation and Interpretation of Trends in Water Quality Time Series},
  url          = {http://dx.doi.org/10.1029/91WR00478},
  volume       = {27},
  year         = {1991},
}