NDLI: Multi-objective, decision-based assessment of a water quality monitoring network in a river system

Content Provider	Royal Society of Chemistry (RSC)
Author	Ning, S. K. Chang, Ni-Bin
Copyright Year	2002
Abstract	Water quality monitoring network design has historically tended to use experience, intuition and subjective judgement in locating monitoring stations. Better design procedures to optimize monitoring systems need to simultaneously identify significant planning objectives and consider a number of social, economic and environmental constraints. The consideration of multiple objectives may require further decision analysis to determine the preference weights associated with the objectives to aid in the decision-making process. This may require the application of an optimization study to extract such information from decision makers or experts and to evaluate the overall effectiveness of locating strategies. This paper assesses the optimal expansion and relocation strategies of a water quality monitoring network using a two-stage analysis. The first stage focuses on the information retrieval of preference weights with respect to the designated planning objectives. With the aid of a pre-emptive goal programming model, data analysis is applied to obtain the essential information from the questionnaire outputs. The second stage then utilizes a weighted multi-objective optimization approach to search for the optimal locating strategies of the monitoring stations in the river basin. Practical implementation is illustrated by a case study in the Kao-Ping River Basin, south Taiwan.
Starting Page	121
Ending Page	126
Page Count	6
File Format	HTM / HTML PDF
ISSN	14640325
Volume Number	4
Issue Number	1
Journal	Journal of Environmental Monitoring
DOI	10.1039/b107041j
Language	English
Publisher	Royal Society of Chemistry
Access Restriction	Open
Subject Keyword	Ping River Basin Taiwan Decision analysis Mathematical optimization
Content Type	Text
Resource Type	Article
Subject	Public Health, Environmental and Occupational Health Management, Monitoring, Policy and Law

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