ASSENSING DISASTER RESILINCE: A CASE STUDY OF THE TR71 REGION

Abstract

The sustainability of any social unit today largely depends on its resilience to disasters. Disaster resilience is the ability of a social unit to cope with an extraordinary impact (earthquake, fire, flood, etc.). Disaster resilience is also defined as the ability and endurance of a society exposed to a disaster to return to its pre-disaster state. Therefore, determining disaster resilience can guide studies such as planning, prioritization and resource allocation in disaster management studies. In this article, an analiysis was conducted to determine the disaster resilience of Kırıkkale, Kırşehir, Nevşehir, Aksaray and Niğde provinces, which are grouped in plans and programs as TR71 provinces. These provinces are located on the central part of Türkiye, with respect to their economic and statistical properties. The disaster resiliences of the provinces were analyzed within the framework of four main criteria by using multi-criteria decision-making methods of Analytical Network Process (ANP), Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) and PROMETHEE. The resiliences of provinces were determined with 11 sub-criteria and 39 indicators under the main criteria of economic, social, infrastructure and natural environment. This study is anticipated to provide substantial insights for decision-makers involved in disaster planning by highlighting the strengths and weaknesses of each province, thereby informing future strategies related to planning, budgeting, and investment. In this paper, it was determined that the provinces with the highest disaster resistance were Nevşehir and Aksaray, and the provinces with the lowest disaster resistance were Kırıkkale and Niğde. Kırşehir ranks in the middle in all methods.

Keywords

• Disaster Management
• Disaster Resilience
• Resilience Indicators
• Multi-Criteria Decision Making
• Multi-Attribute Decision Making

References

1. C. Tuncer, “Kamu Yönetimi Bağlamında Afet Yönetiminde Örnek Bir Uygulama: AYDES,” İletişim Kuram ve Araştırma Dergisi, vol. 59, 158-180. 2022. https://doi.org/10.47998/ikad.1154104
2. T. Eren and H. Gündüz, “Kent Dirençliliği Konusunda Yapılan Lisansüstü Tezlerin Bibliyometrik Analizi.” Resilience,vol. 8, no. 1, pp. 73-82, 2024. https://doi.org/10.32569/resilience.1440796.
3. National Academies Press, “Resilience for Compounding and Cascading Events” {Online], Available: https://nap.nationalacademies.org/read/26659/chapter/3. [Accessed: Sept. 13, 2024].
4. S. Copeland, T. Comes, S. Bach, M. Nagenborg, Y. Schulte and N. Doorn “Measuring social resilience: Trade-offs, challenges and opportunities for indicator models in transforming societies,” International Journal of Disaster Risk Reduction, 2020, https://doi.org/10.1016/j.ijdrr.2020.101799.
5. H. Tariq, “Measuring Community Disaster Resilience at local levels: An adaptable Resilience Framework.” International Journal of Disaster Risk Reduction, 2021, https://doi.org/10.1016/j.ijdrr.2021.102358.
6. H. Xu, S. Li, B. Xing and Y. Tan “Comprehensive Resilience Assessment of Complex Urban Public Spaces: A Perspective of Promoting Sustainability. Land,” vol. 11 no. 6, 2022, https://doi.org/10.3390/land11060842.
7. M. Dağdeviren and E. Eraslan “PROMETHEE Sıralama Yöntemi ile Tedarikçi Seçimi”, Gazi Üniversitesi Mühendislik Mimarlık Fakültesi Dergisi, vol. 23, no. 1, pp. 69-75, 2008.
8. Z. He, H. Chen, H. Yan, Y. Yin, Y. Q. Qiu and T. Wang, “Scenario-Based Comprehensive Assessment for Community Resilience Adapted to Fire Following an Earthquake, Implementing the Analytic Network Process and Preference Ranking Organization Method for Enriched Evaluation II Techniques.” Buildings vol. 11 no. 523 2021, https://doi.org/10.3390/buildings11110523.

9. A. Bucherie, C. Hultquist, S. Adamo, C. Neely, F. Ayala, J. Bazo, and A. Kruczkiewicz, “A comparison of social vulnerability indices specific to flooding in Ecuador: principal component analysis (PCA) and expert knowledge,” International Journal of Disaster Risk Reduction, vol. 73, 2022, https://doi.org/10.1016/j.ijdrr.2022.102897.
10. P. Munpa, S. Kittipongvises, A. Phetrak, W. Sirichokchatchawan, N. Taneepanichskul, J. Lohwacharin, and C. Polprasert, “Climatic and hydrological factors affecting the assessment of flood hazards and resilience using modified UNDRR indicators: Ayutthaya, Thailand.” Water, vol. 14, no.10, 2022.
11. M. A. Salgado-Gálvez, D. Zuloaga Romero, C. Velásquez, M. L. Carreño, O. D. Cardona, and A. H. Barbat, “Urban seismic risk index for Medellín, Colombia, based on probabilistic loss and casualties estimations.” Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, vol. 80, no. 3, pp. 1995–2021, 2016, https://doi.org/10.1007/s11069-015-2056-4.
12. N. Jaramillo, M.L. Carreño, and N. Lantada, “Evaluation of social context integrated into the study of seismic risk for urban areas.” International Journal of Disaster Risk Reduction, vol. 17, pp. 185–198, 2016, https://doi.org/10.1016/j.ijdrr.2016.05.002.
13. M. De Iuliis, O. Kammouh, and G.P. Cimellaro, “Measuring and improving community resilience: a Fuzzy Logic approach," 2022, [Online].Available: https://research.ebsco.com/linkprocessor/plink?id=ed6e5db5-8f34-35e8-bc6b-c4225c5dcf21, [Accessed: Dec. 19, 2023].
14. Ahika, Ahiler Kalkınma Ajansı, . [Online].Available: https://www.ahika.gov.tr/bolgemiz/bir-bakista-tr71-bolgesi. [Accessed: Dec. 24, 2023].
15. L. L. Moreira, M. M. de Brito, and M. Kobiyama, “Review article: A systematic review and future prospects of flood vulnerability indices.” Natural Hazards and Earth System Sciences, vol. 21, pp. 1513–1530, 2021, https://doi.org/10.5194/nhess-21-1513-2021.
16. S. Zhang, J. Zhang, X. Li, X. Du, T. Zhao, Q. Hou, and X. Jin, “Estimating the grade of storm surge disaster loss in coastal areas of China via machine learning algorithms.” Ecological Indicators, no. 136, 2022, https://doi.org/10.1016/j.ecolind.2022.108533.
17. Y. Yang, H. Guo, L. Chen, X. Liu, M. Gu, and W. Pan, “Multiattribute decision making for the assessment of disaster resilience in the three gorges reservoir area.” Ecology and Society, vol. 25, no. 2, pp. 1–14, 2020, https://doi.org/10.5751/ES-11464-250205.
18. N. Lantada., M.L. Carreño, and N. Jaramillo, “Disaster risk reduction: A decision-making support tool based on the morphological analysis.” International Journal of Disaster Risk Reduction, no. 42, 2020, https://doi.org/10.1016/j.ijdrr.2019.101342.
19. W. Xu, L. Xiang, S. Xiong, and D. Proverbs, “The influence of covid-19 on community disaster resilience.” International Journal of Environmental Research and Public Health, vol. 18, no. 1, pp. 1–18, 2021, https://doi.org/10.3390/ijerph18010088.
20. M. Moghadas, A. Asadzadeh, A. Vafeidis, A. Fekete, and T. Kötter, “A multi-criteria approach for assessing urban flood resilience in Tehran, Iran.” International Journal of Disaster Risk Reduction, no. 35, 2019, https://doi.org/10.1016/j.ijdrr.2019.101069.
21. M. Ortiz-Barrios, M. Gul, P. López-Meza, M. Yucesan, and E. Navarro-Jiménez, “Evaluation of hospital disaster preparedness by a multi-criteria decision making approach: The case of Turkish hospitals.” International Journal of Disaster Risk Reduction, no. 49, 2020, https://doi.org/10.1016/j.ijdrr.2020.101748.
22. A. Jamali, M. Robati, H. Nikoomaram, F. Farsad, and H. Aghamohammadi, “Urban Resilience Assessment Using Hybrid MCDM Model Based on DEMATEL-ANP Method (DANP).” Journal of the Indian Society of Remote Sensing, vol. 51, no. 4, pp. 893–915, 2023, https://doi.org/10.1007/s12524-023-01670-8.
23. M.S. Alam and S.M. Haque, “Multi-dimensional earthquake vulnerability assessment of residential neighborhoods of Mymensingh City, Bangladesh: A spatial multi-criteria analysis based approach.” Journal of Urban Management, vol. 11, no. 1, pp. 37–58, 2022, https://research.ebsco.com/linkprocessor/plink?id=81fa517c-51cc-38c9-8537-6200ffafb0ef.
24. X. Xun, and Y. Yuan, “Research on the urban resilience evaluation with hybrid multiple attribute TOPSIS method: an example in China.” Natural Hazards, vol. 103, no. 1, pp. 557–577, 2020, https://research.ebsco.com/linkprocessor/plink?id=45e04e95-553f-37d1-8162-d0ac3d2899a5.
25. S. Marzi, J. Mysiak, A.H. Essenfelder, M. Amadio, S. Giove, and A. Fekete, “Constructing a comprehensive disaster resilience index: The case of Italy.” PLoS ONE, vol. 14, no. 9, 2019), https://doi.org/10.1371/journal.pone.0221585.
26. M. Tayyab, J. Zhang, M. Hussain, X. Liu, B. Al-Shaibah, S. Ullah, S.N. Khan, M.A. Baig, and W. Hassan, “Gis-based urban flood resilience assessment using urban flood resilience model: A case study of peshawar city, khyber pakhtunkhwa, pakistan,” Remote Sensing, vol. 13, no. 10, 2021, https://doi.org/10.3390/rs13101864.
27. C.P.C. Senan, R.S. Ajin, J.H. Danumah, R. Costache, A. Arabameri, A. Rajaneesh, K. Sajinkumar, and S.L. Kuriakose, “Flood vulnerability of a few areas in the foothills of the Western Ghats: a comparison of AHP and F-AHP models.” Stochastic Environmental Research and Risk Assessment, vol. 37, no. 2, pp. 527–556, 2023, https://doi.org/10.1007/s00477-022-02267-2.
28. Y. Park, S. Lee, and J. Lee, “Comparison of fuzzy AHP and AHP in multicriteria inventory classification while planning green infrastructure for resilient stream ecosystems.” Sustainability (Switzerland), vol. 12, no. 21, pp. 1–25, 2020, https://doi.org/10.3390/su12219035.
29. S.M. Parizi, M. Taleai and A. Sharifi, “A GIS-Based Multi-Criteria Analysis Framework to Evaluate Urban Physical Resilience against Earthquakes.” Sustainability (Switzerland), vol. 14, no. 9, 2022, https://doi.org/10.3390/su14095034.
30. K.I. Abdrabo, S.A. Kantoush, A. Esmaiel, M. Saber, T. Sumi, M. Almamari, B. Elboshy,and S. Ghoniem, “An integrated indicator-based approach for constructing an urban flood vulnerability index as an urban decision-making tool using the PCA and AHP techniques: A case study of Alexandria, Egypt.” Urban Climate, no. 48, 2023, https://doi.org/10.1016/j.uclim.2023.101426
31. W. Xu, S. Xiong, Z. Zhong, and D. Proverbs, “Evaluation of humanitarian supply chain resilience in flood disaster,” Water (Switzerland), vol. 13, no. 16, 2021, https://doi.org/10.3390/w13162158
32. A. Bucherie, C. Hultquist, S. Adamo, C. Neely, F. Ayala, J. Bazo, and A. Kruczkiewicz, “A comparison of social vulnerability indices specific to flooding in Ecuador: principal component analysis (PCA) and expert knowledge”, International Journal of Disaster Risk Reduction, https://doi.org/10.1016/j.ijdrr.2022.102897.
33. S. Zhang, J. Zhang, X. Li, X. Du, T. Zhao, Q. Hou, and X. Jin, “Estimating the grade of storm surge disaster loss in coastal areas of China via machine learning algorithms”, Ecological Indicators, https://doi.org/10.1016/j.ecolind.2022.108533.
34. D. Wang, and Y. Wang, “Emergency capacity of small towns to endure sudden environmental pollution accidents: Construction and application of an evaluation model.” Sustainability (Switzerland), vol. 13, no. 10, 2021, https://doi.org/10.3390/su13105511.
35. P. Munpa, S. Kittipongvises, A. Phetrak, W. Sirichokchatchawan, N. Taneepanichskul, J. Lohwacharin and C. Polprasert, “Climatic and Hydrological Factors Affecting the Assessment of Flood Hazards and Resilience Using Modified UNDRR Indicators: Ayutthaya, Thailand”, Water, vol 14, no. 1603, 2022, https://doi.org/10.3390/w14101603.
36. C.L. Zhang, J. Oh, and K. Park, “Evaluation of sewer network resilience index under the perspective of ground collapse prevention,” Water Scıence And Technology, http://dx.doi.org/10.2166/wst.2021.503.