Resilience zoning of Shiraz city against floods using VIKOR_AHP model

Document Type : Research Paper

Authors

• Mohammad Hadi Fattahi
• Mohammad Behroozi

Department of Civil Engineering, Marvdasht Branch, Islamic Azad University, Marvdasht, Iran

10.30495/wej.2023.31164.2369

Abstract

Abstract
Introduction: Flooding in urban areas is increasing due to population growth with improper land use planning and climate change-induced increase in extreme rainfall events. Flood risks have affected the largest proportion of the world's population (45%) compared to other natural disasters and caused 5424 recorded deaths between 2000 and 2017, and if our cities are to be resilient and better able to deal with the consequences of floods. city to cope, it is expected that they will adopt sustainable strategies to adapt to the new climatic and socio-economic conditions. Accordingly, the purpose of this research is to evaluate the resilience of Shiraz city against floods in order to identify areas of low resilience and take the necessary measures to increase it. Their resilience should be done.
Methods: The research method of this research is descriptive-analytical and practical in terms of purpose. Based on the background of the research and refinement of the variables based on the conditions of the research area, four dimensions and 24 criteria were determined, including demographic (8 variables), economic (3 variables), environmental (4 variables) and infrastructure (9 variables).
Findings: AHP method was used for weighting and access to critical infrastructure for action and recovery has the highest weight with a weight of 0.115, and infrastructure with a weight of 0.395 has the highest weight. The estimated CR of the model is equal to 0.07, which it shows the acceptable accuracy of the model. For zoning, the Vikor model has been used, and based on the output of the model, 9.92% of the area is in the zone with low resilience, where about 16.63% of the population of Shiraz lives in this zone, and about 75.43% of the area is in the zone with medium resilience. 74.56% of the population lives in it, and the area with high resilience is 14.65%, where 8.81% of the population of Shiraz lives.

Keywords

• Zoning
• Resilience
• Flood
• Vikor_AHP model
• Shiraz

20.1001.1.20086377.1402.16.58.1.1

---

References

1. Hammond MJ, Chen AS, Djordjević S, Butler D, Mark O. Urban flood impact assessment: A state-of-the-art review. Urban Water J. 2015;12(1):14–29.
2. Recanatesi F, Petroselli A, Ripa MN, Leone A. Assessment of stormwater runoff management practices and BMPs under soil sealing: A study case in a peri-urban watershed of the metropolitan area of Rome (Italy). J Environ Manage. 2017;201:6–18.
3. Chen Y, Samuelson HW, Tong Z. Integrated design workflow and a new tool for urban rainwater management. J Environ Manage. 2016;180:45–51.
4. Sperotto A, Torresan S, Gallina V, Coppola E, Critto A, Marcomini A. A multi-disciplinary approach to evaluate pluvial floods risk under changing climate: The case study of the municipality of Venice (Italy). Sci Total Environ. 2016;562:1031–43.
5. Olsen AS, Zhou Q, Linde JJ, Arnbjerg-Nielsen K. Comparing methods of calculating expected annual damage in urban pluvial flood risk assessments. Water. 2015;7(1):255–70.
6.  Bhattarai R, Yoshimura K, Seto S, Nakamura S, Oki T. Statistical model for economic damage from pluvial floods in Japan using rainfall data and socioeconomic parameters. Nat Hazards Earth Syst Sci. 2016;16(5):1063–77.
7.  Karamouz M, Zahmatkesh Z, Nazif S. Quantifying resilience to coastal flood events: a case study of New York City. In: World Environmental and Water Resources Congress 2014. 2014. p. 911–23.
8. Poussin JK, Botzen WJW, Aerts JCJH. Factors of influence on flood damage mitigation behaviour by households. Environ Sci Policy. 2014;40:69–77.
9.  Serre D, Heinzlef C. Assessing and mapping urban resilience to floods with respect to cascading effects through critical infrastructure networks. Int J Disaster Risk Reduct. 2018;30:235–43.
10.  Dankers R, Feyen L. Climate change impact on flood hazard in Europe: An assessment based on high‐resolution climate simulations. J Geophys Res Atmos. 2008;113(D19).
11.  Roosta M, Javadpoor M, Ebadi M. A study on street network resilience in urban areas by urban network analysis: comparative study of old, new and middle fabrics in shiraz. Int J Urban Sci. 2022;26(2):309–31.
12.  Leitner H, Sheppard E, Webber S, Colven E. Globalizing urban resilience. Urban Geogr. 2018;39(8):1276–84.
13.  Glaeser EL. Urban resilience. Urban Stud. 2022;59(1):3–35.
14.  Motta M, de Castro Neto M, Sarmento P. A mixed approach for urban flood prediction using Machine Learning and GIS. Int J disaster risk Reduct. 2021;56:102154.
15.  Guptha GC, Swain S, Al-Ansari N, Taloor AK, Dayal D. Evaluation of an urban drainage system and its resilience using remote sensing and GIS. Remote Sens Appl Soc Environ 23: 100601. 2021.
16.  Haghighi Fard SM, Doratli N. Evaluation of Resilience in Historic Urban Areas by Combining Multi-Criteria Decision-Making System and GIS, with Sustainability and Regeneration Approach: The Case Study of Tehran (IRAN). Sustain 2022, Vol 14, Page 2495 [Internet]. 2022;14(5):2495.
17.  Munpa P, Kittipongvises S, Water AP, 2022 Climatic and Hydrological Factors Affecting the Assessment of Flood Hazards and Resilience Using Modified UNDRR Indicators: Ayutthaya, Thailand. Water. 2022;14(10):1603.
18.  Tayyab M, Zhang J, Hussain M, Ullah S, Liu X, Khan SN, et al. Gis-based urban flood resilience assessment using urban flood resilience model: A case study of peshawar city, khyber pakhtunkhwa, pakistan. Remote Sens. 2021;13(10):1864.
19.  Zare N. Evaluation and Modeling Urban Resilience to Floods and Methods to Increase Its Resiliency, a Case Study of Metropolitan Shiraz. Shiraz university; 2018.
20.  Mirasadollahi shamsi sadat, motavali  sadraldin, janbaz ghobadi  gholam reza. Resilience analysis of urban settlements against the flood with emphasis on  Social and economic indicators Case study :  ( Gorgan city). jgs [Internet]. 2021;20(59):137–55.
21.  Nazmfar H, Pashazadeh A. Evaluation of urban tolerability in the face of natural hazards (Case study: the city of Ardabil). 2018;
22.  Serre D. DS3 model testing: assessing critical infrastructure network flood resilience at the neighbourhood scale. Urban Disaster Resil Secur Addressing Risks Soc. 2018;207–20.
23.  Fritsch K, Assmann A, Tyrna B. Long-term experiences with pluvial flood risk management. Lang M, Klijn F, Samuels P, editors. E3S Web Conf [Internet]. 2016;7:4017.
24.  Fekete A, Tzavella K, Armas I, Binner J, Garschagen M, Giupponi C, et al. Critical data source; tool or even infrastructure? Challenges of geographic information systems and remote sensing for disaster risk governance. ISPRS Int J Geo-Information. 2015;4(4):1848–69.
25.  Mohamed SA, El-Raey ME. Vulnerability assessment for flash floods using GIS spatial modeling and remotely sensed data in El-Arish City, North Sinai, Egypt. Nat Hazards. 2020;102(2):707–28.
26.  Lavell A, Oppenheimer M, Diop C, Hess J, Lempert R, Li J, et al. Climate change: new dimensions in disaster risk, exposure, vulnerability, and resilience. In: Managing the risks of extreme events and disasters to advance climate change adaptation: Special report of the intergovernmental panel on climate change. Cambridge University Press; 2012. p. 25–64.
27.  Holling CS. Resilience and Stability of Ecological Systems. 2003;4(1):1–23.
28. Shaw R, Team I. Climate disaster resilience: focus on coastal urban cities in Asia. asian J Environ disaster Manag. 2009;1(1):101–16.
29.  Orencio PM, Fujii M. A localized disaster-resilience index to assess coastal communities based on an analytic hierarchy process (AHP). Int J Disaster Risk Reduct. 2013;3:62–75.
30.  Garcia-Dia MJ, DiNapoli JM, Garcia-Ona L, Jakubowski R, O’Flaherty D. Concept analysis: resilience. Arch Psychiatr Nurs. 2013;27(6):264–70.
31.  Dictionary MWC. Merriam-Webster Dictionary. Merriam-Webster Dictionary.
32.  Meerow S, Newell JP, Stults M. Defining urban resilience: A review. Landsc Urban Plan. 2016;147:38–49.
33.  Reghezza M. Face aux crues parisiennes, entre résilience et adaptation. Résilience, vulnérabilité des Territ génie urbain, Press des Ponts, Paris. 2016;175–84.
34.  Detrembleur S, Stilmant F, Dewals B, Erpicum S, Archambeau P, Pirotton M. Impacts of climate change on future flood damage on the river Meuse, with a distributed uncertainty analysis. Nat Hazards. 2015;77:1533–49.
35.  Ghosh A, Kar SK. Application of analytical hierarchy process (AHP) for flood risk assessment: a case study in Malda district of West Bengal. India Nat Hazards 94 (1): 349–368. 2018.
36.  Khosravi K, Pourghasemi HR, Chapi K, Bahri M. Flash flood susceptibility analysis and its mapping using different bivariate models in Iran: a comparison between Shannon’s entropy, statistical index, and weighting factor models. Environ Monit Assess. 2016;188:1–21.
37.  Charlton R, Fealy R, Moore S, Sweeney J, Murphy C. Assessing the impact of climate change on water supply and flood hazard in Ireland using statistical downscaling and hydrological modelling techniques. Clim Change. 2006;74(4):475–91.
38.  Khosravi K, Panahi M, Golkarian A, Keesstra SD, Saco PM, Bui DT, et al. Convolutional neural network approach for spatial prediction of flood hazard at national scale of Iran. J Hydrol. 2020;591:125552.
39.  Jonkman SN, Dawson RJ. Issues and challenges in flood risk management—editorial for the special issue on flood risk management. Water 4 (4): 785-792. 2012.
40.  Ouma YO, Tateishi R. Urban flood vulnerability and risk mapping using integrated multi-parametric AHP and GIS: methodological overview and case study assessment. Water. 2014;6(6):1515–45.
41.  Directive 2007/60/EC of the European Parliament and of the Council of 23 October 2007 on the assessment and management of flood risks [Internet]. EU Flood Directive
42.  Naulin JP, Payrastre O, Gaume E. Spatially distributed flood forecasting in flash flood prone areas: Application to road network supervision in Southern France. J Hydrol. 2013;486:88–99.
43.  Guo E, Zhang J, Ren X, Zhang Q, Sun Z. Integrated risk assessment of flood disaster based on improved set pair analysis and the variable fuzzy set theory in central Liaoning Province, China. Nat hazards. 2014;74:947–65.
44.  Zhang J, Chen Y. Risk assessment of flood disaster induced by typhoon rainstorms in Guangdong province, China. Sustainability. 2019;11(10):2738.
45.  Soltani A, Javadpoor M, Shams F, Mehdizadeh M. Street network morphology and active mobility to school: Applying space syntax methodology in Shiraz, Iran. J Transp Heal. 2022;27:101493.
46. Javadpoor M, Soltani A, Fatehnia L, Soltani N. How the Built Environment Moderates Gender Gap in Active Commuting to Schools. Int J Environ Res Public Heal 2023, Vol 20, Page 1131 [Internet]. 2023;20(2):1131.
47.  Abdolazimi H, Roshun SH, Shamsnia SA, Shahinifar H. Identification of Potential Areas to Flood Inundation in Shiraz City Using TOPSIS-GIS. Hydrogeomorphology. 2021;7(25):139-159.
48.  Yazdanbakhsh M, Jamshidi Z, Ranjbar H, Ranjbaran Z, Nikzad NK. Statistical Yearbook 2011 Fars province. Shiraz: Deputy of planning and employment of the Fars province Statistics Office.; 2012.
49.  Hong CY, Chang H. Residents’ perception of flood risk and urban stream restoration using multi-criteria decision analysis. River Res Appl. 2020;36(10):2078–88.
50.  Mihunov V V, Lam NSN, Zou L, Rohli R V, Bushra N, Reams MA, et al. Community Resilience to Drought Hazard in the South-Central United States. Ann Am Assoc Geogr. 2018;108(3):739–55.
51.  Links JM, Schwartz BS, Lin S, … NKD medicine and, 2018 COPEWELL: a conceptual framework and system dynamics model for predicting community functioning and resilience after disasters. cambridge.orgJM Links, BS Schwartz, S Lin, N Kanarek, J Mitrani-Reiser, TK Sell, CR Watson, D WardDisaster Med public Heal Prep 2018•cambridge.org [Internet].
52.  Cutter SL, Ash KD, Emrich CT. The geographies of community disaster resilience. Glob Environ Chang. 2014;29:65–77.
53.  Javadpoor M, Sharifi A, Roosta M. An adaptation of the Baseline Resilience Indicators for Communities (BRIC) for assessing resilience of Iranian provinces. Int J Disaster Risk Reduct. 2021;66:102609.
54.  Siebeneck L, Arlikatti S, Andrew SA. Using provincial baseline indicators to model geographic variations of disaster resilience in Thailand. Nat Hazards [Internet]. 2015;79(2):955–75.
55.  Cutter SL, Barnes L, Berry M, Burton C, Evans E, Tate E, et al. A place-based model for understanding community resilience to natural disasters. Glob Environ Chang. 2008;18(4):598–606.
56.  Cutter SL, Burton CG, Emrich CT. Disaster resilience indicators for benchmarking baseline conditions. J Homel Secur Emerg Manag. 2010;7(1).
57.  Sharifi A, Roosta M, Javadpoor M. Urban form resilience: A comparative analysis of traditional, semi-planned, and planned neighborhoods in Shiraz, Iran. Urban Sci. 2021;5(1):18.
58.  Assarkhaniki Z, Rajabifard A. The conceptualisation of resilience dimensions and comprehensive quantification of the associated indicators: A systematic approach. International Journal of Disaster Risk Reduction. 2020;51:101840.
59.  Bagheri MN, Motamedi M, Mafi E. Assessing the resilience of Shirvan city in the face of earthquakes. 2022
60.  Kammouh O, Zamani Noori A, Cimellaro GP, Mahin SA. Resilience Assessment of Urban Communities. ASCE-ASME J Risk Uncertain Eng Syst Part A Civ Eng. 2019;5(1).
61.  Song J, Huang B, Li R. Assessing local resilience to typhoon disasters: A case study in Nansha, Guangzhou. Dias JM, editor. PLoS One [Internet]. 2018 Mar 9;13(3):e0190701.
62.  Song J, Huang B, Water RL, 2017 Measuring recovery to build up metrics of flood resilience based on pollutant discharge data: A case study in East China. Water. 2017;9(8):619.
63.  Yu PL. A Class of Solutions for Group Decision Problems. Manage Sci. 1973;19(8):936–46.
64.  Multiple Criteria Decision Making. undefined Compromise programming [Internet]. 1973.
65.  Opricovic S, Tzeng GH. Extended VIKOR method in comparison with outranking methods. Eur J Oper Res. 2007;178(2):514–29.
66.  Chang CL. A modified VIKOR method for multiple criteria analysis. Environ Monit Assess. 2010;168(1-4):339–44.
67.  Jahan A, Mustapha F, Ismail MY, Sapuan SM, Bahraminasab M. A comprehensive VIKOR method for material selection. Mater Des. 2011;32(3):1215–21.