Abstract

One of the most significant natural disasters in South-east Asia, is flooding. In Malaysia, for instance, Iskandar Malaysia region as a rapid urbanizing context located in southern peninsula has been affected by several flood events during last decade. Severe rainfall, natural situation, new unplanned developments and insufficient drainage systems mad the situation more considerable. This study seeks to address the crucial variables which contribute to the risk of flooding based on the characteristics of the region and develop a GIS-aided urban flood susceptibility map. The methodology emphasizes on uncertainty and multi-criteria which contribute to the risk of flood and increase the risk. As such, the Fuzzy logic, Multi-criteria ranking and Weighted Linear Combination (WLC) methods in Geographic Information System (GIS) are used to achieve the objectives. Distances from main stream, river and discharge channels, as well as other variables such as elevation, slope and land use are recognized as effective variables within the region. Final susceptibility map indicates that around 658 km2 out of 1,614 km2 within the region is under the high level of flooding risk. Different districts within the region include Pulai, Senai-Kulai, Tebrau and Johor Bahru can be considered as areas with a high risk of flooding. Natural and man-made situation influence the level of risk in each area. Generally the southern part of the region has a high level of risk as the consequence of conjunction between location of stream, lowland and land use type. Finally the situation in 2025 is investigated based on the proposed plan for 2025.

Keywords:

Flood susceptibility, fuzzy logic, GIS , Iskandar Malaysia region, multi-criteria evaluation,

References

1. Alderman, K., L.R. Turner and S. Tong, 2012. Floods and human health: A systematic review. Environ. Int., 47: 37-47.
   CrossRef    PMid:22750033    
2. Al-Hanbali, A., B. Alsaaideh and A. Kondoh, 2011. Using GIS-based weighted linear combination analysis and remote sensing techniques to select optimum solid waste disposal sites within Mafraq City, Jordan. J. Geogr. Inform. Syst., 3(4): 267-278.
   CrossRef    
3. Aydi, A., M. Zairi and B.H. Dhia, 2012. Minimization of environmental risk of landfill site using fuzzy logic, analytical hierarchy process and weighted linear combination methodology in a geographic information system environment. Environ. Earth Sci., 68(5): 1375-1389.
   CrossRef    
4. Camarasa Belmonte, A.M., M.J. López-García and J. Soriano-García, 2011. Mapping temporally-variable exposure to flooding in small Mediterranean basins using land-use indicators. Appl. Geogr., 31(1): 136-145.
   CrossRef    
5. Chang, H. and J. Franczyk, 2008. Climate change, land-use change and floods: Toward an integrated assessment. Geogr. Compass, 5(2): 1549-1579.
   CrossRef    
6. Crosetto, M. and S. Tarantola, 2001. Uncertainty and sensitivity analysis: Tools for GIS-based model implementation. Int. J. Geogr. Inf. Sci., 15(5): 415-437.
   CrossRef    
7. Drobne, S. and A. Lisec, 2009. Multi-attribute decision analysis in GIS: Weighted linear combination and ordered weighted averaging. Informatica, 33: 459-474.
   
8. Fernández, D.S. and M.A. Lutz, 2010. Urban flood hazard zoning in Tucumán Province, Argentina, using GIS and multicriteria decision analysis. Eng. Geol., 111: 90-98.
   CrossRef    
9. He, Y., J. Zhou, P. Kou, N. Lu and Q. Zou, 2011. A fuzzy clustering iterative model using chaotic differential evolution algorithm for evaluating flood disaster. Expert Syst. Appl., 38(80): 10060-10065.
   CrossRef    
10. Hisham, A.S.B., M.I. Marzukhi and A.R. Daud, 2009. The worst flood in 100 years. Somatosens. Mot. Res., 21(2): 145-145.
    
11. Hundecha, Y., A. Bardossy and H.W. Theisen, 2001. Development of a fuzzy logic based rainfall-runoff model. Hydrol. Sci. J., 46(3): 363-377.
    CrossRef    
12. Jian, W., L. Deng, L. Chen, J. Wu and J. Li, 2009. Risk assessment and validation of flood disaster based on fuzzy mathematics. Prog. Nat. Sci., 19(10): 1419-1425.
    CrossRef    
13. Jianfen, L., Z. Xingnan and W. Huimin, 2013. Flood risk mapping for different land use senarios based on RS and GIS. Appl. Mech. Mater., 298: 2415-2419.
    
14. Kainz, W., 2006. Fuzzy Logic and GIS. Department of Geography and Regional Research, University of Vienna, Austria, pp: 1-21.
    
15. Kia, M.B., B. Pradhan, S. Pirasteh, W.N.A. Ulaiman, A.R. Mahmud and A. Moradi, 2012. An artificial neural network model for flood simulation using GIS: Johor River Basin, Malaysia. Environ. Earth Sci., 67(1): 251-264.
    CrossRef    
16. Konrad, C.P., 2003. Effects of Urban Development on Floods. U.S. Department of the interior U.S. Geological Survey, November, pp: 1-4.
    
17. Kubal, C., D. Haase, V. Meyer and S. Scheuer, 2009. Integrated urban flood risk assessment-adapting a multicriteria approach to a city. Nat. Hazard. Earth Sys., 9: 1881-1895.
    CrossRef    
18. Lamond, J., C. Booth, F. Hammond and D. Proverbs, 2012. Flood Hazards Impact and Responses for the Built Environment. CRC Press, Taylor and Francis Group.
    
19. Lawal, D.U., A.N. Matori, A.M. Hashim, I.A. Chandio, S. Sabri, A.L. Balogun and H.A. Abba, 2011. Geographic information system and remote sensing applications in flood hazards management: A review. Appl. Sci. Eng. Technol., 3(9): 933-947.
    
20. Levy, J.K. and J. Hall, 2005. Advances in flood risk management under uncertainty. Stoch. Env. Res. Risk A., 19: 375-377.
    CrossRef    
21. Levy, J.K., J. Hartmann, K.W. Li, Y. An and A. Asgari, 2007. Multi-criteria decision support systems for flood hazard mitigation and emergency response in urban watersheds. J. Am. Water Resour. As., 43(2): 346-358.
    CrossRef    
22. Li, Q., 2013. Fuzzy approach to analysis of flood risk based on variable fuzzy sets atmospheric and improved information diffusion methods. Nat. Hazard. Earth Sys., 13: 239-249.
    CrossRef    
23. Mackenzie, L.D. and A.C. David, 1998. Hydrology. Introduction to Environmental Engineering. 3rd Edn., McGraw Hill, USA.
    
24. Malczewski, J., 1999. GIS and Multicriteria Decision Analysis. John Wiley and Sons, Toronto.
    
25. Mirzapour Al-E-Hashem, S.M.J., H. Malekly and M.B. Aryanezhad, 2011. A multi-objective robust optimization model for multi-product multi-site aggregate production planning in a supply chain under uncertainty. Int. J. Prod. Econ., 134(1): 28-42.
    CrossRef    
26. Mohd, M.S., B. Alias and D. Daud, 2006. GIS analysis for flood hazard mapping: Case study; Segamat, Johor, West Malaysia. Proceeding of National Seminar on Geographic Information System Application for Mitigation in Natural Disaster, pp: 1-15.
    
27. Montz, B.E. and G.A. Tobin, 2011. Natural hazards: An evolving tradition in applied geography. Appl. Geogr., 31(1): 1-4.
    CrossRef    
28. Musungu, K., S. Motala and J. Smit, 2012. Using multi-criteria evaluation and GIS for flood risk analysis in informal settlements of Cape Town: The case of graveyard pond. S. Afr. J. Geomat., 1(1): 77-91.
    
29. Ologunorisa, T.E. and M.J. Abawua, 2005. Flood risk assessment: A review. Appl. Sci. Environ. Mgt., 9(1): 57-63.
    
30. Pandey, G.R. and V.T.V. Nguyen, 1999. A comparative study of regression based methods in regional flood frequency analysis. J. Hydrol., 225: 92-101.
    CrossRef    
31. Paquette, J. and J. Lowry, 2012. Flood hazard modelling and risk assessment in the Nadi River Basin, Fiji, using GIS and MCDA. South Pac. J. Nat. Appl. Sci., 30: 33-43.
    CrossRef    
32. Popovska, C. and D. Ivanoski, 2009. Flood Risk Assessment of Urban Areas. In: Hlavinek, P. (Ed.), Risk Management of Water Supply and Sanitation Systems, Springer Science+Business Media, pp: 101-113.
    CrossRef    
33. Pradhan, B., 2009. Flood susceptible mapping and risk area delineation using logistic regression, GIS and remote sensing. J. Spat. Hydrol., 9(2): 1-18.
    
34. Rizzo, A. and J. Glasson, 2012. Iskandar Malaysia. Cities, 29(6): 417-427.
    CrossRef    
35. Sadeghi-Niaraki, A., M. Varshosaz, K. Kyehyun and J.J. Jason, 2011. Expert systems with applications real world representation of a road network for route planning in GIS. Expert Syst. Appl., 38(10): 11999-12008.
    CrossRef    
36. Saini, S.S. and S.P. Kaushik, 2012. Risk and vulnerability assessment of flood hazard in part of Ghaggar Basin: A case study of Guhla block, Kaithal, Haryana, India. Int. J. Geomat. Geosci., 3(1): 42-54.
    
37. Shaluf, I.M. and F.R. Ahmadun, 2006. Disaster types in Malaysia: An overview. Disaster Prev. Manage., 15(2): 286-298.
    CrossRef    
38. Shimokawa, S. and Y. Takeuchi, 2006. Uncertainty in Flood Risks and Public Understanding of Probable Rainfall. In: Ikeda, S. et al. (Eds.), A Better Integrated Management of Disaster Risks: Toward Resilient Society to Emerging Disaster Risks in Mega-Cities. TERRAPUB Terra Scientific Publishing Co., Tokyo, pp: 109-119.
    
39. Smyth, C.G. and S.A. Royle, 2000. Urban landslide hazards: Incidence and causative factors in Nitero’i, Rio de Janeiro, State, Brazil. Appl. Geogr., 20: 95-117.
    CrossRef    
40. Stefanidis, S. and D. Stathis, 2013. Assessment of flood hazard based on natural and anthropogenic factors using Analytic Hierarchy Process (AHP). Nat. Hazards, 68: 1-17.
    CrossRef    
41. Sulaiman, N.A., H. Faizah, H.K. Afendy and S.A. Manan, 2012. A study on flood risk assessment for Bandar Segamat sustainability using remote sensing and GIS approach. Proceeding of the IEEE Control and System Graduate Research Colloquium (ICSRC). Shah Alam, Selangor, pp: 386-391.
    CrossRef    
42. Tingsanchali, T., 2012. Urban flood disaster management. Proc. Eng., 32: 25-37.
    CrossRef    
43. Zadeh, L.A., 1965. Fuzzy sets. Inform. Control, 8: 338-353.
    CrossRef    
44. Zadeh, L.A., 1988. Fuzzy logic. Computer, 21(4): 83-93.
    CrossRef    

Competing interests

The authors have no competing interests.

Open Access Policy

This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

Copyright

The authors have no competing interests.