Statistical Estimation and Interpretation of Trends in Water Quality Time Series
(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)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/1715356
- author
- Zetterqvist, Lena LU
- organization
- publishing date
- 1991
- 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 (AGU)
- 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
- 2016-04-01 12:28:50
- date last changed
- 2021-08-15 03:35:52
@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}},
keywords = {{Mann-Kendall test; nonparametric statistics; Time series; seasonal models}},
language = {{eng}},
number = {{7}},
pages = {{1637--1648}},
publisher = {{American Geophysical Union (AGU)}},
series = {{Water Resources Research}},
title = {{Statistical Estimation and Interpretation of Trends in Water Quality Time Series}},
url = {{http://dx.doi.org/10.1029/91WR00478}},
doi = {{10.1029/91WR00478}},
volume = {{27}},
year = {{1991}},
}