Cluster Computing

, Volume 22, Supplement 5, pp 11723–11740 | Cite as

Fuzzy expert system-based framework for flood management in Saudi Arabia

  • Saad Amin
  • Mohammad Hijji
  • Rahat Iqbal
  • Wayne Harrop
  • Victor ChangEmail author


This paper presents a fuzzy expert system-based framework for flood management in Saudi Arabia that helps the civil defense (CD) authority in both preparing their flood management capabilities and responding to scalable levels of flood risk. One of the most important type of flood management capabilities is training capabilities, the adequacy of training capabilities of emergency responders is a critical factor that influences on flood risk management, even considering other types of capabilities such as equipment and infrastructure. However, due to the lack of adequate training capabilities in place to address dynamic change of flood risk and vulnerabilities in some areas, emergency readiness for floods has been critically affected and resulted in ineffective response and mutual aid. Here, the study aimed to aid decision-makers in the Saudi CD Authority to reduce inappropriate readiness of training capabilities in some critical zones and maintain the levels of readiness using a proposed fuzzy expert system-based framework, which is named the capability evaluation and readiness (CER) framework. The developed CER framework includes a new fuzzy expert system, which is named the intelligent capability evaluation and readiness (ICER) system. CER framework uses three key elements for readiness evaluation and addressing needs related to training capabilities; the records of the provided training and exercises; the targeted standard and policy of readiness and mutual aid; and risk assessment of each zone and existing hazard and vulnerability (HV) factors within a zone. The results of evaluation by interviews indicted high agreement on effectiveness and productivity of the CER framework, however, it is recommended that additional stakeholders are included in order to have comprehensive information regarding others HV factors. In addition, questionnaires shown that more than 60% of the respondents believe that the ICER system is an effective tool for flood response, however, regarding the readiness of the training capabilities, more that 17% of the respondents believe that the ICER system is not effective tool to improving the readiness of the training capabilities.


Fuzzy expert system Flood management Disaster preparedness Training capabilities Saudi civil defense 



This research was supported by the Saudi CD Authority. The authors thank all participants from the Saudi CD Authority who provided insight and knowledge that significantly assisted in this research.


  1. 1.
    Alamri, Y.A.: Emergency management in Saudi Arabia: past, present and future, Un. Of Christchurch report, New Zealand, p. 21. (2010)Google Scholar
  2. 2.
    Momani, N.M., Fadil, A.S.: Changing public policy due to Saudi City of Jeddah flood disaster. J. Soc. Sci. 6, 424 (2010)Google Scholar
  3. 3.
    Abosuliman, S.S., Kumar, A., Alam, F., Rasjidin, R.: Disaster Planning and Management in Jeddah, Saudi Arabia. In: Proceedings of the 2013 International Conference on Economics and Social Science, (2013)Google Scholar
  4. 4.
    General Defense of the KSA, Civil Defence: Number of Injuries Staff, (2007)Google Scholar
  5. 5.
    Hijji, M., Amin, S., Iqbal, R., Harrop, W.: A critical evaluation of the rational need for an IT management system for flash flood events in Jeddah, Saudi Arabia. In: Developments in eSystems Engineering (DeSE), 2013 Sixth International Conference on, IEEE, pp. 209–214 (2013)Google Scholar
  6. 6.
    Hijji, M., Amin, S., Iqbal, R., Harrop, W.: The significance of using, expert system to assess the preparedness of training capabilities against different flash flood scenarios, Lecture Notes on Software Engineering, p. 3 (2015)Google Scholar
  7. 7.
    Deneulin, S., Shahani, L.: An Introduction to the Human Development and Capability Approach: Freedom and Agency. Earthscan, Routledge (2009)CrossRefGoogle Scholar
  8. 8.
    Federal Emergency Management Agency (FEMA): National Preparedness Cycle, (2013)Google Scholar
  9. 9.
    Uricchio, V.F., Giordano, R., Lopez, N.: A fuzzy knowledge-based decision support system for groundwater pollution risk evaluation. J. Environ. Manag. 73, 189–197 (2004)CrossRefGoogle Scholar
  10. 10.
    Dean, J.W., Sharfman, M.P.: Does decision process matter? A study of strategic decision-making effectiveness. Acad. Manag. J. 39, 368–392 (1996)Google Scholar
  11. 11.
    Drennan, L.T., McConnell, A., Stark, A.: Risk and Crisis Management in the Public Sector. Routledge, Abingdon (2014)Google Scholar
  12. 12.
    Liberatore, F., Pizarro, C., de Blas, C.S., Ortuño, M., Vitoriano, B.: Uncertainty in humanitarian logistics for disaster management. A review. In: Decision Aid Models for Disaster Management and Emergencies, Springer, pp. 45–74 (2013)Google Scholar
  13. 13.
    Sprague Jr., R.H., Carlson, E.D.: Building Effective Decision Support Systems. Prentice Hall Professional Technical Reference, New Jersey (1982)Google Scholar
  14. 14.
    Yaqoob, L., Ahmed Khan, N., Subhan, F.: An overview of existing decision support systems for disasters management. CODEN 26, 1765–1776 (2014)Google Scholar
  15. 15.
    Bonczek, R.H., Holsapple, C.W., Whinston, A.B.: Foundations of Decision Support Systems. Academic Press, New York (2014)zbMATHGoogle Scholar
  16. 16.
    Efraim, T., Jay, E.A., Liang, T.-P., McCarthy, R.: Decision Support Systems and Intelligent Systems. Prentice Hall, Upper Saddle River (2001)Google Scholar
  17. 17.
    Zadeh, L.A.: Fuzzy sets. Inf. Control 8, 338–353 (1965)CrossRefGoogle Scholar
  18. 18.
    Doukidis, G.I., Paul, R.J.: Research into expert systems to aid simulation model formulation. J. Oper. Res. Soc. 36, 319–325 (1985)CrossRefGoogle Scholar
  19. 19.
    Lein, J.K.: Applying expert systems technology to carrying capacity assessment: a demonstration prototype. J. Environ. Manag. 37, 63–84 (1993)CrossRefGoogle Scholar
  20. 20.
    Saoud, E.A.: Expert systems for management training in the construction industry, (1996)Google Scholar
  21. 21.
    Simões-Marques, M., Ribeiro, R.A., Gameiro-Marques, A.: A fuzzy decision support system for equipment repair under battle conditions. Fuzzy Sets Syst. 115, 141–157 (2000)CrossRefGoogle Scholar
  22. 22.
    Jia, X.: Fuzzy logic based decision support system for mass evacuation of cities prone to coastal or river flood, Compiègne, (2013)Google Scholar
  23. 23.
    Saudi Geological Survey, About SGS, (2014)Google Scholar
  24. 24.
    Saudi Civil Defense Website, Structure of Saudi Civil Defense in, Saudi Civil Defense, (2016)Google Scholar
  25. 25.
    Haimes, Y.Y.: Risk Modeling, Assessment, and Management. Wiley, New Jersey (2015)zbMATHGoogle Scholar
  26. 26.
    FEMA, Preparedness Cycle, in, FEMA, (2016)Google Scholar
  27. 27.
    Jha, A.K., Bloch, R., Lamond, J.: Cities and Flooding: A Guide to Integrated Urban Flood Risk Management for the 21st Century. World Bank Publications, Washington (2012)CrossRefGoogle Scholar
  28. 28.
    Iqbal, R., Shah, N., James, A., Duursma, J.: ARREST: from work practices to redesign for usability. Int. J. Exp. Syst. Appl. 38(2), 1182–1192 (2011)CrossRefGoogle Scholar
  29. 29.
    Iqbal, R., Sturm, J., Kulyk, O., Wang, C., Terken, J.: User-centred design and evaluation of ubiquitous services. In: Proceedings of the 23rd Annual International Conference on Design of Communication: Documenting and Designing for Pervasive Information, ACM SIGDOC, pp. 138–145, ISBN: 1-59593-175-9 (2005)Google Scholar
  30. 30.
    Qureshi, F.F., Iqbal, R., Asghar, M.N.: Energy efficient wireless communication technique based on cognitive radio for internet of things. J. Netw. Comput. Appl. 89, 14–25 (2017)CrossRefGoogle Scholar
  31. 31.
    Kumar, N., Iqbal, R., Chilamkurti, N.: Capacity and load-aware service discovery with service selection in peer-to-peer grids. J. Fut. Gener. Comput. Syst. 28(7), 1090–1099 (2012)CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2017

Authors and Affiliations

  • Saad Amin
    • 1
  • Mohammad Hijji
    • 1
  • Rahat Iqbal
    • 1
  • Wayne Harrop
    • 1
  • Victor Chang
    • 2
    Email author
  1. 1.Coventry UniversityCoventryUK
  2. 2.IBSS, Xi’an Jiaotong-Liverpool UniversitySuzhouChina

Personalised recommendations