Flood hazard risk evaluation using fuzzy logic and weightage-based combination methods in geographic information system

Document Type : Article


Department of Civil Engineering, Sakarya University, 54187 Sakarya, Turkey


This study addresses the crucial variables contributing highly to the risk of flooding based on the flood characteristics of the Waverly region and develop a fuzzy logic and geographic information based urban flood map with flood zones in Waverly City, Iowa. The methodology emphasizes on weighting crucial variables using spatial analyst tools and fuzzy logic based GIS mapping. Local elevation, distance from Cedar River, land use and population density in Waverly city are recognized as effective variables to risk of flooding in Waverly city. Twenty three calibration tests for determination of weightages of these variables on the risk of flood were performed and compared to previously produced Waverly flood risk maps. Finally, weightages of these variables were assigned as 70 % for elevation, 20 % for distance from Cedar River, 5 % for Manning’s coefficient, and 5 % for population density. In a fuzzy environment they were assigned different fuzzy membership functions, for elevation, fuzzification technique Small was used, for distance, fuzzification technique MS Small was used, for Manning’s coefficient and population density, fuzzification technique Large was used. The flood hazard maps created were overlaid with 100 and 500-year flood maps of Waverly city for calibration and risk evaluation.


Main Subjects


1. Alderman, K., Turner, L.R., and Tong, S. Floods and
human health", A Systematic Review. Environ. Int.,
47, pp. 37{47 (2012).
2. Al-Hanbali, A., Alsaaideh, B., and Kondoh, A. 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), pp. 267{278 (2011).
3. Phong, T., Rajib, S., Guillaume, C., and Norton, J.
GIS and local knowledge in disaster management:
a case study of
ood risk mapping in Viet Nam",
Disasters, 33(1), pp. 152{169 (2009).
4. Chang, H. and Franczyk, J. Climate change, land-use
change and
oods: Toward an integrated assessment",
Geogr. Compass, 5(2), pp. 1549{1579 (2008).
5. Aydi, A., Zairi, M., and Dhia, B.H. Minimization
of environmental risk of land ll site using fuzzy logic,
analytical hierarchy process and weighted linear combination
methodology in a geographic information
system environment", Environ. Earth Sci., 68(5), pp.
1375{1389 (2012).
6. Camarasa B.A.M., Lopez-Garca, M.J., and Soriano-
Garca, J. Mapping temporally-variable exposure to

ooding in small Mediterranean basins using land-use
indicators", Appl. Geogr., 31(1), pp. 136{145 (2011).
7. Malczewski, J., GIS and Multicriteria Decision Analysis,
John Wiley and Son, Toronto (1999).
528 O. Sonmez and H. Bizimana/Scientia Iranica, Transactions A: Civil Engineering 27 (2020) 517{528
8. Mirzapour Al-E-Hashem, S.M.J., Malekly, H., and
Aryanezhad, M.B. 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), pp. 28{42 (2011).
9. Mohd, M.S., Alias, B., and Daud, D. GIS analysis for

ood 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 (2006).
10. Itami, R. and Cotter, M. Application of analytical
hierarchy process to rank issues, projects and sites
in integrated catchment management", In Proc. the
2nd International Conference on Multiple Objective
Decision Support Systems for Land, Water and Environmental
Management, Queensland Department of
Natural Resources and Mines, Brisbane, Australia
11. Tao, Z.H. and Jingdong, W. Application of analytic
hierarchy process in debris
ow risk degree assessment
- a case study of Miyun County, Beijing City", Bulletin
of Soil and Water Conservation, 28(5), pp. 6{10
12. Lawal, D., Matori, A., Hashim, A., Yusof, K., and
Chandio, I. Detecting
ood susceptible areas using
GIS-based analytic hierarchy process", In Proc. International
Conference on Future Environment and
Energy, 28, pp. 3{4 (2015).
13. Federal Emergency Management Agency, 2015/http://
14. Chaochao, L. and Xiaotao, C. A frame work for

ood risk analysis and bene t assessment of
control measures in urban areas", Int. J. of River
Basin Management, 13, pp. 13{15 (2016).
15. Brito, M. and Evers, M. Multi-criteria decisionmaking
ood risk management: a survey of the
current state of the art", Supplement of Natural Hazard
Earth System, 16, pp. 1029{1033 (2016).
16. Das, E. An aggregate fuzzy risk analysis for
incident management", Int. J. of System Assurance
Engineering and Management, 24, pp. 87{93 (2011).
17. Kourgialas, K. Flood management and a GIS modeling
method to assess
ood-hazard areas", Hydrological
Sciences Journal, 11, pp. 123{132 (2016).
18. Li E. Impact assessment of urbanization on
ood risk
in the Yangtze River Delta", Stochastic Environmental
Research and Risk Assessment, 27, pp. 25{37 (2016).
19. Sonmez, O. 2D Flood Modelling and Flood map
production in Rivers", Sakarya University, Institute
of Applied Sciences,Sakarya., pp. 60{80, Sakarya,
Turkey (2013).