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Data management of river water quality data: a semi-automatic procedure for data validation

Lieven Clement UGent, Olivier Thas UGent, Jean-Pierre Ottoy UGent and Peter A Vanrolleghem (2007) WATER RESOURCES RESEARCH. 43(8).
abstract
Monitoring networks typically generate large amounts of data. Before the data can be added to the database, they have to be validated. In this paper, a semi-automatic procedure is presented to validate river water quality data. On the basis of historical data, additive models are established to predict new observations and to construct prediction intervals ( PI's). A new observation is accepted if it is located in the interval. The coverage of the prediction intervals and its power to detect anomalous data are assessed in a simulation study. The method is illustrated on two case studies in which the method detected abnormal nitrate concentrations in the water body provoked by a dry summer which was followed by an extreme winter period. The case studies also show that similar to classical multivariate outlier detection tools, the semi-automatic procedure allows the detection of suspicious observations lying at the edges as well as observations lying at the center of the univariate distribution of the observations, but, without having to impose linear relationships typically associated with these classical methods.
Please use this url to cite or link to this publication:
author
organization
year
type
journalArticle (original)
publication status
published
subject
keyword
ADDITIVE-MODELS, NONPARAMETRIC REGRESSION, PREDICTION INTERVALS, TIME-SERIES, AUTOREGRESSION, ESTIMATORS, SMOOTHERS, KERNEL
journal title
WATER RESOURCES RESEARCH
Water Resour. Res.
volume
43
issue
8
article_number
W08429
pages
17 pages
Web of Science type
Article
Web of Science id
000249340000002
JCR category
WATER RESOURCES
JCR impact factor
2.154 (2007)
JCR rank
4/58 (2007)
JCR quartile
1 (2007)
ISSN
0043-1397
DOI
10.1029/2006WR005187
language
English
UGent publication?
yes
classification
A1
copyright statement
I have transferred the copyright for this publication to the publisher
id
380018
handle
http://hdl.handle.net/1854/LU-380018
date created
2007-10-19 10:32:00
date last changed
2013-04-26 10:33:46
@article{380018,
  abstract     = {Monitoring networks typically generate large amounts of data. Before the data can be added to the database, they have to be validated. In this paper, a semi-automatic procedure is presented to validate river water quality data. On the basis of historical data, additive models are established to predict new observations and to construct prediction intervals ( PI's). A new observation is accepted if it is located in the interval. The coverage of the prediction intervals and its power to detect anomalous data are assessed in a simulation study. The method is illustrated on two case studies in which the method detected abnormal nitrate concentrations in the water body provoked by a dry summer which was followed by an extreme winter period. The case studies also show that similar to classical multivariate outlier detection tools, the semi-automatic procedure allows the detection of suspicious observations lying at the edges as well as observations lying at the center of the univariate distribution of the observations, but, without having to impose linear relationships typically associated with these classical methods.},
  articleno    = {W08429},
  author       = {Clement, Lieven and Thas, Olivier and Ottoy, Jean-Pierre and Vanrolleghem, Peter A},
  issn         = {0043-1397},
  journal      = {WATER RESOURCES RESEARCH},
  keyword      = {ADDITIVE-MODELS,NONPARAMETRIC REGRESSION,PREDICTION INTERVALS,TIME-SERIES,AUTOREGRESSION,ESTIMATORS,SMOOTHERS,KERNEL},
  language     = {eng},
  number       = {8},
  pages        = {17},
  title        = {Data management of river water quality data: a semi-automatic procedure for data validation},
  url          = {http://dx.doi.org/10.1029/2006WR005187},
  volume       = {43},
  year         = {2007},
}

Chicago
Clement, Lieven, Olivier Thas, Jean-Pierre Ottoy, and Peter A Vanrolleghem. 2007. “Data Management of River Water Quality Data: a Semi-automatic Procedure for Data Validation.” Water Resources Research 43 (8).
APA
Clement, L., Thas, O., Ottoy, J.-P., & Vanrolleghem, P. A. (2007). Data management of river water quality data: a semi-automatic procedure for data validation. WATER RESOURCES RESEARCH, 43(8).
Vancouver
1.
Clement L, Thas O, Ottoy J-P, Vanrolleghem PA. Data management of river water quality data: a semi-automatic procedure for data validation. WATER RESOURCES RESEARCH. 2007;43(8).
MLA
Clement, Lieven, Olivier Thas, Jean-Pierre Ottoy, et al. “Data Management of River Water Quality Data: a Semi-automatic Procedure for Data Validation.” WATER RESOURCES RESEARCH 43.8 (2007): n. pag. Print.