4.7 Article

Development of fuzzy multi-criteria approach to prioritize locations of treated wastewater use considering climate change scenarios

Journal

JOURNAL OF ENVIRONMENTAL MANAGEMENT
Volume 146, Issue -, Pages 505-516

Publisher

ACADEMIC PRESS LTD- ELSEVIER SCIENCE LTD
DOI: 10.1016/j.jenvman.2014.08.013

Keywords

Fuzzy TOPSIS; Robust prioritization; Representative concentration pathway; Treated wastewater use

Funding

  1. Advanced Water Management Research Program [11-TI-006]
  2. Ministry of Land, Infrastructure and Transport of Korean Government
  3. Basic Science Research Program of the National Research Foundation of Korea [2010-0010609]
  4. National Research Foundation of Korea [2010-0010609] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)

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This study proposed a robust prioritization framework to identify the priorities of treated wastewater (TWW) use locations with consideration of various uncertainties inherent in the climate change scenarios and the decision-making process. First, a fuzzy concept was applied because future forecast precipitation and their hydrological impact analysis results displayed significant variances when considering various climate change scenarios and long periods (e.g., 2010-2099). Second, various multi-criteria decision making (MCDM) techniques including weighted sum method (WSM), Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) and fuzzy TOPSIS were introduced to robust prioritization because different MCDM methods use different decision philosophies. Third, decision making method under complete uncertainty (DMCU) including maximin, maximax, minimax regret, Hurwicz, and equal likelihood were used to find robust final rankings. This framework is then applied to a Korean urban watershed. As a result, different rankings were obviously appeared between fuzzy TOPSIS and non-fuzzy MCDMs (e.g., WSM and TOPSIS) because the inter-annual variability in effectiveness was considered only with fuzzy TOPSIS. Then, robust prioritizations were derived based on 18 rankings from nine decadal periods of RCP4.5 and RCP8.5. For more robust rankings, five DMCU approaches using the rankings from fuzzy TOPSIS were derived. This framework combining fuzzy TOPSIS with DMCU approaches can be rendered less controversial among stakeholders under complete uncertainty of changing environments. (C) 2014 Elsevier Ltd. All rights reserved.

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