Vulnerability Assessment in Urban Areas against Flood with Fuzzy Logic (case study: Tehran District 22)

Subject Areas : environmental management

Elham Esmaeili Alavijeh ¹ , Saeid Karimi ² , Fatemehsadat Alavipoor ³

1 - Ph.D Student in Environmental Planning, University of Tehran .*(Corresponding Author)
2 - Assistant professor of faculty of Environment, University of Tehran
3 - Ph.D Student in Environmental Planning, University of Tehran.

Received: 2015-08-03 Accepted : 2016-04-23 Published : 2020-05-21

Keywords: vulnerability, flood, Tehran District 22, Fuzzy Logic,

Abstract :

Background and Objective: In general, in recent decades, due to urban lives on the sidelines of rivers, dwellers of these areas have been the subject of damages caused by flood. The goal of this research is determining the vulnerability level of urban areas against flood in order to reducing human and financial losses. Method: For this purpose, Chung fuzzy analysis hierarchical process method (fuzzy AHP) is used due to the higher degree of possibility for weighting criteria of gradient, soil, distance from river, geology, height, land usage, and population. After weighting, the criteria of vulnerability in the environment ARCGIS were fuzzy and ultimately fuzzy operators were used for overlapping layers. Findings: To amend the obtained maps, algebraic multiplication and algebraic addition operators, Gamma 0.9, Gamma 0.7 and Gamma 0.5 operators were used. Obtained map from Gamma 0.7 operator was chosen as the final map of vulnerability for obtaining more appropriate result. Discussion and Conclusion: Therefore, considering the final map, and that the percentage of population density is over 1.07 in the eastern north of the area near Kan river, the possibility of vulnerability is proposed to be high in that area. Also it is possible that unpermitted constructions in Kan and Vardavard River limits will lead to water aggregation and its sudden release in the area, and if the process of unpermitted constructions and population increase is continued in the area, it can be resulted that the possibility of vulnerability against flood may be high in Tehran District 22.

References:

1. Green, C. H. (2002). Flood management from the perspective of integrated water resource management. In 2nd International Symposium on Flood Control, Beijing.


2. Ouma, Y. O., & Tateishi, R. (2014). Urban flood vulnerability and risk mapping using integrated multi-parametric AHP and GIS: Methodological overview and case study assessment. Water, 6(6), 1515-1545.


3. Kaźmierczak, A., & Cavan, G. (2011). Surface water flooding risk to urban communities: Analysis of vulnerability, hazard and exposure. Landscape and Urban Planning, 103(2), 185-197.


4. Jiang, W., Deng, L., Chen, L., Wu, J., & Li, J. (2009). Risk assessment and validation of flood disaster based on fuzzy mathematics. Progress in Natural Science, 19(10), 1419-1425


5. Kubal, C., Haase, D., Meyer, V., &Scheuer, S. (2009). Integrated urban flood risk assessment–adapting a multicriteria approach to a city. Natural Hazards and Earth System Science, 9(6), 1881-1895.


6. Kourgialas, N. N., &Karatzas, G. P. (2011). Flood management and a GIS modelling method to assess flood-hazard areas a case study. Hydrological Sciences Journal–Journal des Sciences Hydrologiques, 56(2), 212-225


7. Thieken, A. H., Müller, M., Kreibich, H., & Merz, B. (2005). Flood damage and influencing factors: New insights from the August 2002 flood in Germany. Water resources research, 41(12).


8. Van der Sande, C. J., De Jong, S. M., & De Roo, A. P. J. (2003). A segmentation and classification approach of IKONOS-2 imagery for land cover mapping to assist flood risk and flood damage assessment. International Journal of applied earth observation and geoinformation, 4(3), 217-229.


9. Martinez, J. M., & Le Toan, T. (2007). Mapping of flood dynamics and spatial distribution of vegetation in the Amazon floodplain using multitemporal SAR data. Remote sensing of Environment, 108(3), 209-223.


10. Srinivas, V. V., Tripathi, S., Rao, A. R., & Govindaraju, R. S. (2008). Regional flood frequency analysis by combining self-organizing feature map and fuzzy clustering. Journal of Hydrology, 348(1), 148-166.


11. Chen, J., Zhao, S., & Wang, H. (2011). Risk analysis of flood disaster based on fuzzy clustering method. Energy Procedia, 5, 1915-1919.


12. Qanavati, E., Karam, A., and Agha Alikhani, M., 2012. Flood risk zonation in the farahzad basin (Tehran) using Fuzzy model. Journal of Geography and Environmental Planning. Consecutive 48, No. 4. (In Persian)


13. Habibi, Arash, Ezadyar, Sedigheh and Sarafrazi, Azam, Fuzzy multi-criteria decision making, First Edition, Katebeh Gil Publications, 2014, pp. 75-73. (In Persian)


14. Eastman, J. R. (2012). IDRISI Selva manual. Clark University. Sitio web: www. Clarklabs. org.

3. Salehi, E., Rafie, Y., Farzad Behtash, M., and Aqababai, M., 2013. Urban flood risk zoning using GIS and Fuzzy Hierarchical Analysis Process, Case Study: Tehran. Journal of Environmental Studies. Vol. 39, No. 3.( In Persian)

13. Saffari, A., Sasanpour, F., and Musavand, J., 2011. Assessing the vulnerability of urban areas to flood risk using GIS and fuzzy logic, Case study: District 3 of Tehran. Journal of Applied Research Geographical Sciences. Vol. 11, No.20. (In Persian)

15. Navard. Elham. Presenting Management Solutions for Waste Separation Plan with Emphasis on Education and Public Participation, A Case Study of District 22 of Tehran Municipality, Master Thesis in Environmental Planning, University of Tehran, Faculty of Environment, 2007, pp. 45-44. (In Persian)


16. Asgharpour, Mohammad Javad, Multi-Criteria Decisions, Sixth Edition, University of Tehran Publishers, 2008, page 350. (In Persian)