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Prioritization of non-revenue water reduction scenarios using a risk-based group decision-making approach
- Source :
- Stochastic Environmental Research and Risk Assessment. 34:1713-1724
- Publication Year :
- 2020
- Publisher :
- Springer Science and Business Media LLC, 2020.
-
Abstract
- This study investigates the effectiveness of the reduction policies of the apparent and real losses of non-revenue water. For this purpose, using technique for order of preference by similarity to ideal solution (TOPSIS) model, a decision matrix is proposed, involving apparent and real losses risk reduction values induced by the implementation of each non-revenue water reduction policy. First, decision criteria, including technical, economic, and social criteria, were selected and introduced. Then, the technical criterion was calculated using a fuzzy Bayesian model. In the following, using group decision-making and analytic hierarchy process method, the criteria were weighted. In the next step, the bests of decision criteria were determined by the TOPSIS method. This method was applied in the water distribution network of district 4 of Tehran, Iran. The results indicated that the most basic non-revenue water reduction policy by risk-based group decision-making is to identify unauthorized connections in the apparent water loss sector and increase the speed and quality of maintenance and repairs in the real water loss sector.
- Subjects :
- Environmental Engineering
010504 meteorology & atmospheric sciences
Operations research
Computer science
0208 environmental biotechnology
Analytic hierarchy process
TOPSIS
02 engineering and technology
Multiple-criteria decision analysis
01 natural sciences
Fuzzy logic
020801 environmental engineering
Group decision-making
Reduction (complexity)
Decision matrix
Environmental Chemistry
Non-revenue water
Safety, Risk, Reliability and Quality
0105 earth and related environmental sciences
General Environmental Science
Water Science and Technology
Subjects
Details
- ISSN :
- 14363259 and 14363240
- Volume :
- 34
- Database :
- OpenAIRE
- Journal :
- Stochastic Environmental Research and Risk Assessment
- Accession number :
- edsair.doi...........997f820e3191cf80ab212d987d81cf65