Water Resources Management

, Volume 33, Issue 10, pp 3401–3416 | Cite as

Prioritization of Water Allocation for Adaptation to Climate Change Using Multi-Criteria Decision Making (MCDM)

  • Parvin Golfam
  • Parisa-Sadat AshoftehEmail author
  • Taher Rajaee
  • Xuefeng Chu


The complex nature of water resources and the related uncertainty cause decision making to be difficult in practice. In this study, two multi-criteria decision making (MCDM) methods, Analytic Hierarchy Process (AHP) and the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), were applied to determine the best scenario adapting to climate change in agriculture for the Gharanghu basin in Northwest Iran for a 30-year period (2040-2069). Reservoir efficiency indexes were used as evaluation criteria. Specifically, the preference of each criterion relative to the other criteria was determined based on experts’ opinions. Five management scenarios were considered, involving reductions in agricultural water demand by 5, 10, 15, 20, and 25%, respectively. By applying the AHP approach, the consolidated weight of each criterion was calculated; the best adaptation scenario to climate change was determined; the inconsistency rate was calculated; and sensitivity analysis was also performed. The AHP results showed that the fifth scenario (25% demand reduction) with a weight of 33.5% was the best one for agricultural water demand management. The results obtained from the TOPSIS model indicated that the third scenario (15% demand reduction) with a weight of 20.8% was the best management scenario for agriculture in the period of climate change. Thus, estimation of uncertainty related to climate change is critical to choosing the best alternative using the MCDM models. Uncertainty analysis helps address the questions about whether the management scenarios are sustainable under unforeseen changes, and whether they are an ideal response to critical conditions of climate change.


Multi-criteria decision making Analytic hierarchy process Similarity to ideal solution Climate change 


Compliance with ethical standards

Conflict of Interest



  1. Aboutalebi M, Bozorg-Haddad O, Loáiciga HA (2015) Optimal monthly reservoir operation rules for hydropower generation derived with SVR-NSGAII. J Water Resour Plan Manag 141(11).
  2. Abrishamchi A, Ebrahimian A, Tajrishi M, Mariño MA (2005) Case study: Application of multicriteria decision making to urban water supply. j Water Resour Plan Manag 131(4):326–335. CrossRefGoogle Scholar
  3. Afshar A, Bozorg-Haddad O, Mariño MA, Adams BJ (2007) Honey-bee mating optimization (HBMO) algorithm for optimal reservoir operation. J Franklin Inst 344(5):452–462CrossRefGoogle Scholar
  4. Al-Kloub B, Al-Shemmeri T, Pearman A (1997) The role of weights in multi-criteria decision aid, and the ranking of water projects in Jordan. Eur J Oper Res 99(2):278–288. CrossRefGoogle Scholar
  5. Ashofteh P-S, Bozorg-Haddad O, Mariño MA (2013) Scenario assessment of streamflow simulation and its transition probability in future periods under climate change. Water Resour Manag 27(1):255–274. CrossRefGoogle Scholar
  6. Ashofteh P-S, Rajaee T, Golfam P (2017) Assessment of water resources development projects under conditions of climate change using efficiency indexes (EIs). Water Resour Manag.
  7. Azadi F, Ashofteh P-S, Loáiciga HA (2019) Reservoir water-quality projections under climate-change conditions. Water Resour Manag 33(1):401–421. CrossRefGoogle Scholar
  8. Bozorg-Haddad O, Afshar A, Mariño MA (2008) Honey-bee mating optimization (HBMO) algorithm in deriving optimal operation rules for reservoirs. J Hydroinf 10(3):257–264CrossRefGoogle Scholar
  9. Bozorg-Haddad O, Moravej M, Loáiciga HA (2015) Application of the water cycle algorithm to the optimal operation of reservoir systems. J Irrig Drain Eng 141(5).
  10. Fallah-Mehdipour E, Bozorg-Haddad O, Mariño MA (2013) Developing reservoir operational decision rule by genetic programming. J Hydroinf 15(1):103–119CrossRefGoogle Scholar
  11. Garousi-Nejad I, Bozorg-Haddad O (2015) The implementation of developed firefly algorithm in multireservoir optimization in continuous domain. Int J Civ Struct Eng 2(1):104–108Google Scholar
  12. Ghorbannezhad P, Azizi M, Ray C, Yoo C, Ramazani O (2013) Application of sensitivity analysis for assessment of energy and environmental alternatives in the manufacture by using analytic hierarchy process. Environ Prot Eng 39(3):5–20. Google Scholar
  13. Gordon C, Cooper C, Senior CA, Banks HT, Gregory JM, Johns TC, Mitchell JFB, Wood RA (2000) The simulation of SST, sea ice extents and ocean transport in a version of the Hadley Centre coupled model without flux adjustments. Clim Dyn 16:147–168CrossRefGoogle Scholar
  14. Hwang CL, Yoon K (1981) Multiple attributes decision making methods and applications. Springer, BerlinCrossRefGoogle Scholar
  15. Jaber JO, Mohsen MS (2001) Evaluation of non-conventional water resources supply in Jordan. Desalination 136(1-3):83–92. CrossRefGoogle Scholar
  16. Jakeman AJ, Hornberger GM (1993) How Much Complexity Is Warranted in a Rainfall-Runoff Model. Water Resour Res 29(8):2637–2649CrossRefGoogle Scholar
  17. Li YP, Huang GH, Nie SL (2006) An interval-parameter multi-stage stochastic programming model for water resources management under uncertainty. Adv Water Resour 29(5):776–789. CrossRefGoogle Scholar
  18. Moradi-Jalal M, Bozorg-Haddad O, Karney BW, Mariño MA (2007) Reservoir operation in assigning optimal multi-crop irrigation areas. Agric Water Manag 90(1-2):149–159CrossRefGoogle Scholar
  19. Saaty TL (1977) A scaling method for priorities hierarchical structures. J Math Psychol 15(3):234–281. CrossRefGoogle Scholar
  20. Saaty TL (1980) The Analytic Hierarchy Process. McGraw-Hill, New YorkGoogle Scholar
  21. Saaty TL (1990) How to make a decision: The analytic hierarchy process. Eur J Oper Res 48(1):9–26. CrossRefGoogle Scholar
  22. Weng SQ, Huang GH, Li YP (2010) An integrated scenario-based multi-criteria decision support system for water resources management and planning - A case study in the Haihe River Basin. Expert Syst Appl 37(12):8242–8254. CrossRefGoogle Scholar
  23. Zarghami M, Abrishamci A, Ardakanian A (2008) Multi-criteria decision making for integrated urban water management. Water Resour Manag 22(8):1017–1029. CrossRefGoogle Scholar
  24. Zyoud SH, Kaufmann LG, Shaheen H, Samhan S, Fuchs-Hanusch D (2016) A framework for water loss management in developing countries under fuzzy environment: Integration of fuzzy AHP with fuzzy TOPSIS. Expert Syst Appl 61(1):86–105. CrossRefGoogle Scholar

Copyright information

© Springer Nature B.V. 2019

Authors and Affiliations

  1. 1.Department of Civil EngineeringUniversity of QomQomIran
  2. 2.Department of Civil & Environmental EngineeringNorth Dakota State UniversityFargoUSA

Personalised recommendations