Comparison of Different Multi Criteria Decision-Making Models in Prioritizing Flood Management Alternatives

Abstract

Recent increases in life loss, destruction and property damages caused by flood at global scale, have inevitably highlighted the pivotal considerations of sustainable development through flood risk management. Throughout the paper, a practical framework to prioritize the flood risk management alternatives for Gorganrood River in Iran was applied. Comparison between multi criteria decision making (MCDM) models with different computational mechanisms provided an opportunity to obtain the most conclusive model. Non-parametric stochastic tests, aggregation models and sensitivity analysis were employed to investigate the most suitable ranking model for the case study. The outcomes of these mentioned tools illustrated that ELimination and Et Choice Translating Reality (ELECTRE III), a non-compensatory model, stood superior to the others. Moreover, Eigen-vector’s performance for assigning weights to the criteria was proved by the application of Kendall Tau Correlation Coefficient Test. From the technical point of view, the highest priority among the criteria belonged to a social criteria named Expected Average Number of Casualties per year. Furthermore, an alternative with pre and post disaster effectiveness was determined as the top-rank measure. This alternative constituted flood insurance plus flood warning system. The present research illustrated that ELECTRE III could deal with the complexity of flood management criteria. Hence, this MCDM model would be an effective tool for dealing with complex prioritization issues.

This is a preview of subscription content, access via your institution.

Fig. 1
Fig. 2
Fig. 3

Abbreviations

MCDM:

Multi criteria decision making

VIKOR:

VlseKriterijumska optimizacija I Kompromisno Resenje

TOPSIS:

Technique for order preference by similarity to ideal solution

ELECTRE I and ELECTRE III:

Elimination et choice translating reality

EANC:

Expected average number of casualties per year

SCCT:

Spearman correlation coefficient test

SCC:

Spearman correlation coefficients

SAW:

Simple additive weighing

M-TOPSIS:

Modified TOPSIS

AHP:

Analytical hierarchy process

CP:

Compromise programming

EAD:

Expected annual damage

KTCCT:

Kendall tau correlation coefficient test

KTCC:

Kendall tau correlation coefficient

References

  1. Afshari A, Mojahed M, Yusuff RM (2010) Simple additive weighting approach to personnel selection problem. Int J Innov Manag Technol 1(5):511–515

    Google Scholar 

  2. Antucheviciene J, Zakarevicius A, Zavadskes EK (2011) Measuring congruence of ranking results applying particular MCDM methods. Informatica 22(3):319–338

    Google Scholar 

  3. Ardalan A, Holakouie Naieni K, Kabir MJ, Zanganeh AM, Keshtkar AA, Honarvar MR, Khodaie H, Osooli M (2009) Evaluation of golestan Province’s early warning system for flash floods, Iran, 2006–7. Int J Biometeorol. doi:10.1007/s00484-009-0210-y

    Google Scholar 

  4. Athawale VM, Chakraborty S (2011) A comparative study on the ranking performance of some multi-criteria decision-making methods for industrial robot selection. Int J Ind Eng Comput 2(4):831–850

    Google Scholar 

  5. Azarnivand A, Hashemi-Madani FS, Banihabib ME (2014) Extended fuzzy analytic hierarchy process approach in water and environmental management (case study: Lake Urmia Basin, Iran). Environ Earth Sci. doi:10.1007/s12665-014-3391-6

    Google Scholar 

  6. Brouwer R, Van E (2004) Integrated ecological, economic and social impact assessment of alternative flood control policies in the Netherlands. Ecol Econ. doi:10.1016/j.ecolecon.2004.01.020

    Google Scholar 

  7. Chou SY, Chang YH, Shen CY (2008) A fuzzy simple additive weighting system under group decision-making for facility location selection with objective/subjective attributes. Eu J Oper Res 132–145

  8. De Bruijn KM (2005) Resilience and flood risk management; A systems approach applied to lowland rivers. 216 pp

  9. Duckstein L, Opricovic S (1980) Multi objective optimization in river basin development. Water Resour Res. doi:10.1029/WR016i001p00014

    Google Scholar 

  10. Duckstein L, Bobee B, Ashkar F (1991) A multiple criteria decision modeling approach to selection of estimation techniques for fitting extreme floods. Stoch Hydrol Hydraul. doi:10.1007/BF01544059

    Google Scholar 

  11. Edmund C, Rowsell P, Parker D, Harries T (2008) Systematization, evaluation and context conditions of structural and non-structural measures for flood risk reduction FLOOD-ERA Report for England and Scotland. CRUE Research Report

  12. Elmoustafa AM (2012) Weighted normalized risk factor for floods risk assessment. Ain Shams Eng J 3:327–332

    Article  Google Scholar 

  13. Favardin P, Lepelley D, Serais J (2002) Borda rule, Copeland method and strategic manipulation. Rev Econ Des 7:213–228

    Google Scholar 

  14. Frei FX, Harker PT (1999) Measuring aggregate process performance using AHP. Eur J Oper Res 116(2):436–442

    Article  Google Scholar 

  15. Geng G, Wardlaw R (2013) Application of multi-criterion decision making analysis to integrated water resources management. Water Resour Manag 27:3191–3207

    Article  Google Scholar 

  16. Gibbons JD (1971) Nonparametric Statistical Inference. McGraw-Hill, New York

    Google Scholar 

  17. Hajkowicz S, Higgins A (2008) A comparison of multiple criteria analysis techniques for water resource management. Eur J Oper Res 184(1):255–265

    Article  Google Scholar 

  18. Hansson K, Danielson M, Ekenberg L, Buurman J (2013) Multiple Criteria Decision Making for Flood Risk Management. Integ Catastrophe Risk Model Adv Nat Technol Hazards Res ISSN 1878–9897; 32: 53–72

  19. Hashemi MS, Zare F, Bagheri A, Moridi A (2014) Flood assessment in the context of sustainable development using the DPSIR framework. Int J Environ Protect Policy. doi:10.11648/j.jepp.20140202.11

    Google Scholar 

  20. Hwang CL, Lin MJ (1987) Group decision making under multiple criteria: Methods and applications. Springer

  21. Jahan A, Yusof IM, Shuib S, Nur Fazidah D, Edwards KL (2011) An aggregation technique for optimal decision-making in materials selection. Mater Des. doi:10.1016/j.matdes.2011.05.050

    Google Scholar 

  22. Johnson C, Rowsell EP, Tapsell S (2007) Aspiration and reality: flood policy, economic damages and the appraisal process. Area 39(2):214–223

    Article  Google Scholar 

  23. Kenyon W (2007) Evaluating flood risk management options in Scotland: a participant-led multi-criteria approach. Ecol Econ 64:70–81

    Article  Google Scholar 

  24. Kim Y, Chung ES (2013) Assessing climate change vulnerability with group multi-criteria decision making approaches. Clim Chang. doi:10.1007/s10584-013-0879-0

    Google Scholar 

  25. Kubal C, Haase D, Meyer V, Scheuer S (2009) Integrated urban flood risk assessment – adapting a multi criteria approach to a city. Nat Hazards Earth Syst Sci 9:1881–1895

    Article  Google Scholar 

  26. Kundzewicz ZW (1999) Flood protection sustainability Issues. Hydrol Sci J des Sci Hydrol Special issue: Barriers to Sustainable Management of Water Quantity and Quality 44(4):559–571

  27. Kundzewicz ZW (2005) Is the frequency and intensity of flooding changing in Europe? Springer-V erlag Berlin, Heidelbrg

    Google Scholar 

  28. Kundzewicz ZW, Takeuchi K (1999) Flood protection and management: quo vadimus? Hydrol Sci J 44(3):417–432

    Article  Google Scholar 

  29. Long WJ (2006) Multi-Criteria Decision-Making for water resource management in the BERG water management area. Dissertation presented for the degree of Doctor of Philosophy (Agriculture). University of Stellenbosch

  30. Management and Planning Organization (MPO) (2004) Socio-economical report of Golestan province. Management and Planning Organization Pub

  31. Manokaran E, Subhashini S, Senthilvel S, Muruganandham R, Ravichandran K (2011) Application of multi criteria decision making tools and validation with optimization technique-case study using TOPSIS, ANN & SAW. Int J Manag Bus Stud 1(3): 112–115. ISSN: 2330–9519

  32. Meyer V, Scheuer S, Haase D (2009) A multi criteria approach for flood risk mapping exemplified at the Mulde river, Germany. Nat Hazards 48:17–39

    Article  Google Scholar 

  33. Miettinen K, Salminen P (1999) Decision-aid for discrete multiple criteria decision making problems with imprecise data. Eur J Oper Res 119(1):50–60

    Article  Google Scholar 

  34. Mohaghar A, Fathi MR, Zarchi MK, Omidia A (2012) A combined VIKOR–fuzzy AHP approach to marketing strategy selection. Bus Manag Strat 3(1):13–27

    Google Scholar 

  35. Opricovic S, Tzeng GH (2004) Compromise solution by MCDM methods: a comparative analysis of VIKOR and TOPSIS. Eur J Oper Res 156(2):445–455

    Article  Google Scholar 

  36. Opricovic S, Tzeng GH (2007) Extended VIKOR method in comparison with outranking methods. Eur J Oper Res 178:514–529

    Article  Google Scholar 

  37. Pomerol JC, Barba-Romero S (2000) Multi criterion decision in management: principles and practice. Springer, Netherlands

    Google Scholar 

  38. Pourjavad E, Shirouyehzad H (2011) A MCDM Approach for prioritizing production lines: a case study. Int J Bus Manag 6(10):221–229. Published by Canadian Center of Science and Education. www.ccsenet.org/ijbm

  39. Raju KS, Pillai CRS (1999) Multi criterion decision making in river basin planning and development. Eur J Oper Res 112(2):249–257

    Article  Google Scholar 

  40. Raju KS, Duckstein L, Arnodel C (2000) Multi criterion analysis for sustainable water resources planning: a case study in Spain. Water Resour Manag 14:435–456

    Article  Google Scholar 

  41. Ramanathan R, Ganesh LS (1995) Using AHP for resource allocation problems. Eur J Oper Res 80(2):410–417

    Article  Google Scholar 

  42. Ren, L, Zhang Y, Wang Y, Sun Z (2007) Comparative Analysis of a Novel M-TOPSIS Method and TOPSIS. Appl Math Res Express PP :1–10.

  43. Rogers M, Bruen M, Maystre L (2000) ELECTRE and decision support. Kluwer Academic Publishers, London

    Google Scholar 

  44. Roy B (1968) Classement et choix en pre’sence de points de vues multiples (la me’thode Electre). Cahiers du CERO 8:57–75

    Google Scholar 

  45. Roy B (1978) ELECTRE III: Un algorithme de classement fonde sur une representation floue des preferences en presence de criteres multiples. Cahiers du CERO 20(1):3–24

    Google Scholar 

  46. Roy B (1991) The outranking approach and the foundations of ELECTRE methods. Theor Decis 31:49–73

    Article  Google Scholar 

  47. Roy B, Present M, Silhol D (1986) A programming method for determining which Paris metro stations should be renovated. Eur J Oper Res 24:318–334

    Article  Google Scholar 

  48. Saari D (1995) Mathematical complexity of simple economics. Not Am Math Soc 42(2):222–230

    Google Scholar 

  49. Saaty TL (1977) A scaling method for priorities in hierarchical structures. J Math Psychol 15:59–62

    Article  Google Scholar 

  50. Saaty TL (1980) The Analytic Hierarchy Process. McGraw-Hill, New York, pp 20–25

    Google Scholar 

  51. Saghafian B, Farazjoo H, Bozorgi B, Yazdandoost F (2008) Flood intensification due to changes in land Use. Water Resour Manag 22:1051–1067

    Article  Google Scholar 

  52. Shih HS, Wang CH, Lee ES (2004) A multi attribute GDSS for aiding problem-solving. Math Comput Model 39:1397–1412

    Article  Google Scholar 

  53. Simonovic S (1989) Application of water resources systems concept to the formulation of a water master plan. Water Int. doi:10.1080/02508068908692032

    Google Scholar 

  54. Srdjevic B (2007) Linking analytic hierarchy process and social choice methods to support group decision-making in water management. Decis Support Syst. doi:10.1016/j.dss.2006.08.001

    Google Scholar 

  55. Szmidt E, Kacprzyk J (2011) The Spearman and Kendall rank correlation coefficients between intuitionist fuzzy sets. Atlantis Press, Aix-Les-Bains, pp 521–528

    Google Scholar 

  56. Tecle A, Duckstein L (1994) Concepts of multi criterion decision making. Decision Support System in Water Resources Management. In: J. J. Bogardi and H. P Vatchnebel (eds), pp 33–62

  57. Ustinovichius L, Zavadskas EK, Podvezko V (2007) Application of a quantitative multiple criteria decision making (MCDM-1) approach to the analysis of investments in construction. Control Cybern 36(1):251–268

    Google Scholar 

  58. Yacov Y, Haimes (2011) Harmonizing the Omnipresence of MCDM in Technology, Society, and Policy. Chapter 2. doi: 10.1007/978-3-642-19695-9_2

  59. Yazdandoost F, Bozorgy B (2008) Flood risk management strategies using multi-criteria analysis. Water Manag. doi:10.1680/wama.2008.161.5.261

    Google Scholar 

  60. Yilmaz B, Harmancioglu NB (2010) Multi-criteria decision making for water resource management: a case study of the Gediz River Basin, Turkey. 36(5) p563

  61. Zeleny M, Cochrane JL (1973) A Priori and a posteriori goals in macroeconomic policy making. University of South Carolina Press, Columbia, pp 373–391

    Google Scholar 

Download references

Acknowledgments

The authors would like to acknowledge insightful comments from the anonymous reviewers and the associate editor on the previous version of the manuscript.

Author information

Affiliations

Authors

Corresponding author

Correspondence to Nastaran Chitsaz.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Chitsaz, N., Banihabib, M.E. Comparison of Different Multi Criteria Decision-Making Models in Prioritizing Flood Management Alternatives. Water Resour Manage 29, 2503–2525 (2015). https://doi.org/10.1007/s11269-015-0954-6

Download citation

Keywords

  • Flood risk management
  • Decision making
  • Iran
  • Non-parametric stochastic tests
  • Aggregation methods
  • Sensitivity analysis