The Comparison of Resilience and Resistance Approaches in Flood Risk Management (Case Study of Qezel Ozan River in Mahneshan Basin)

Document Type : علمی - پژوهشی

Authors

1 Ph.D. Student, Faculty of Civil Engineering, K.N. Toosi University Of Technology, Tehran

2 Associate Prof., Faculty of Geodesy & Geomatics, K.N. Toosi University of Technology, Tehran

3 Faculty Member of Geomatics Engineering, University of Bojnord

Abstract

Flood is one of the most common and destructive natural events in the world. Conventional methods which aim to prevent floods, mostly are based on resistance approaches. Considering uncertainties about time and location of flood occurrence and design variables such as discharge, structure resistance and physical characteristics of a basin, resistance methods are not suitable solutions. However, resistance methods for preventing from the flood are effective on lower discharges, they may become less effective or ineffective in extreme-case emergencies. As an example, levees are only effective when flood waters remain below their design capacity. Therefore, in order to manage and reduce human casualties and financial losses, more suitable solutions based on resilience are introduced. Flood resilience is interpreted as the capacity to tolerate flooding to avoid disaster when undergoing- not preventing- flooding, or when physical damage and socioeconomic disruption still occur, the capacity to reorganize and recover quickly. Recovery is defined as assisting of communities affected by flood waters to achieve a proper and effective level of functioning. Resilience approach in water resources management plays an important role in flood risk management. In this study, several strategies of flood risk management with an emphasis on the concept of resilience have been evaluated. A case study was carried out on the Ghezel Ozan river, located in the Mahneshan basin. In order to model the flood, the data related to the topographic conditions of the river are adapted using the HEC GeoRAS extension in the ArcGIS. Then, the flood characteristics in the 25, 50, and 100-year return periods are estimated by the HEC RAS model. Flood flow modeling has been carried out based on eight different management strategies including resistance and resilience strategies based on structural and non-structural approaches. The comparison of these strategies is based on the values of resilient indicators including the amplitude, graduality and recovery rate. Indicators for the amplitude are the expected annual damage (EAD) and the expected annual number of casualties (EANC). The graduality is measured by comparing the relative increase of discharge in a river by the corresponding relative increase of damage. Recovery rate is a function of social, economic and physical condition. In this research, in order to quantify the recovery rate, it is presented as a function of evaporation, transpiration and water penetration into the soil. Finally, after calculating the resilience indicators for each scenario, in order to prioritize the scenarios, the entropy method is used for weighting and TOPSIS is utilized to prioritize the scenarios. According to the results, it has been observed that resilience based methods are preferred to resistance methods and dry farming with flood warning and flood insurance has been determined as the best strategy.

Keywords

References

  1. بزرگی، ب.، 1386، مدیریت پایدار سیلاب با رویکرد انعطاف‌پذیری، پایان‌نامة دکتری، دانشگاه صنعتی خواجه نصیرالدین طوسی، دانشکدة مهندسی عمران.
  2. مؤمنی، م.، 1395، مباحث نوین تحقیق در عملیات، نشر مؤلف، چاپ هفتم، تهران.
  3. Associated Programme on Flood Management (APFM), Integrated Flood Management, Concept Paper, 2004, Technical Document No. 1, WMO & GWP.
  4. De Bruijn, K.M., 2004, Resilience and Flood Risk Management, Water Policy, 6(1), PP. 53–66. ‏
  5. De Bruijn, K.M., 2005, Resilience and Flood Risk Management: A Systems Approach Applied to Lowland Rivers, Published and distributed by DUP Science.
  6. Gersonius, B., van Buuren, A., Zethof, M. & Kelder, E., 2016, Resilient Flood Risk Strategies: Institutional Preconditions for Implementation, Ecology and Society, 21(4), P. 28.‏ https://doi.org/10.5751/ES-08752-210428
  7. Holling, C.S., 1973, Resilience and Stability of Ecological Systems, Annual Review of Ecology and Systematics, 4(1), PP. 1–23. ‏
  8. Hwang, C.L. & Yoon, K., 1981, Multiple Attribute Decision Making: Methods and Application, Springer, New York.
  9. Mens, M. & Klijn, F., 2015, The Added Value of System Robustness Analysis for Flood Risk Management Illustrated by a Case on the IJssel River, Natural Hazards and Earth System Sciences, 15, PP. 213–223.
  10. O'Neill, P., 2004, Developing a Risk Communication Model to Encourage Community Safety from Natural Hazards, State Emergency Services, State Emergency Services, Sydney, N.S.W.
  11. Paramasivam, V., Senthil, V. & Ramasamy, N.R., 2011, Decision Making in Equipment Selection: An Integrated Approach with Digraph and Matrix Approach, AHP and ANP, The International Journal of Advanced Manufacturing Technology, 54(9–12), PP. 1233–1244.‏
  12. Saaty, T.L., 1980, The Analytical Hierarchy Process, Published by McGraw-Hill, New York.
  13. Tagg, A., Laverty, K., Escarameia, M., Garvin, S., Cripps, A., Craig, R. & Clutterbuck, A., 2016, A New Standard for Flood Resistance and Resilience of Buildings: New Build and Retrofit, In: Floodrisk 2016, 18–20 October, Lyon, France.
  14. Wang, P., Zhu, Z. & Wang, Y., 2016, A Novel Hybrid MCDM Model Combining the SAW, TOPSIS and GRA Methods Based on Experimental Design, Information Sciences, 345(C), PP. 27–45

Files

Share

How to cite

Statistics