Issue 8, 2011
From the journal:

Journal of Environmental Monitoring

A statistical approach for the assessment and redesign of the Nile Delta drainage system water-quality-monitoring locations

B. Khalil,*a   T. B. M. J. Ouardabc  and  A. St-Hilairec  

* Corresponding authors

a Irrigation and hydraulics department, Faculty of Engineering, Helwan University, Cairo, Egypt
E-mail: bahaa_khalil@rocketmail.com
Tel: +20 450 667 0447

b Masdar Institute of Science & Technology, PO Box 54224, Abu Dhabi, UAE
E-mail: touarda@masdar.ac.ae

c Canada Research Chair on the Estimation of Hydrometeorological Variables, INRS-ETE, 490 de la Couronne, Quebec, QC, Canada
E-mail: taha.ouarda@ete.inrs.ca, andre.st-hilaire@ete.inrs.ca
Fax: +1 418 654 2600
Tel: +1 418 654 3842

Abstract

There are several deficiencies in the statistical approaches proposed in the literature for the assessment and redesign of surface water-quality-monitoring locations. These deficiencies vary from one approach to another, but generally include: (i) ignoring the attributes of the basin being monitored; (ii) handling multivariate water quality data sequentially rather than simultaneously; (iii) focusing mainly on locations to be discontinued; and (iv) ignoring the reconstitution of information at discontinued locations. In this paper, a methodology that overcomes these deficiencies is proposed. In the proposed methodology, the basin being monitored is divided into sub-basins, and a hybrid-cluster analysis is employed to identify groups of sub-basins with similar attributes. A stratified optimum sampling strategy is then employed to identify the optimum number of monitoring locations at each of the sub-basin groups. An aggregate information index is employed to identify the optimal combination of locations to be discontinued. The proposed approach is applied for the assessment and redesign of the Nile Delta drainage water quality monitoring locations in Egypt. Results indicate that the proposed methodology allows the identification of (i) the optimal combination of locations to be discontinued, (ii) the locations to be continuously measured and (iii) the sub-basins where monitoring locations should be added. To reconstitute information about the water quality variables at discontinued locations, regression, artificial neural network (ANN) and maintenance of variance extension (MOVE) techniques are employed. The MOVE record extension technique is shown to result in a better performance than regression or ANN for the estimation of information about water quality variables at discontinued locations.

Graphical abstract: A statistical approach for the assessment and redesign of the Nile Delta drainage system water-quality-monitoring locations

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Article information

DOI
https://doi.org/10.1039/C0EM00727G
Article type
Paper
Submitted
02 Dec 2010
Accepted
18 Apr 2011
First published
15 Jun 2011

J. Environ. Monit., 2011,13, 2190-2205

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A statistical approach for the assessment and redesign of the Nile Delta drainage system water-quality-monitoring locations

B. Khalil, T. B. M. J. Ouarda and A. St-Hilaire, J. Environ. Monit., 2011, 13, 2190 DOI: 10.1039/C0EM00727G

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