DOI QR코드

DOI QR Code

Development and Application of a Coastal Disaster Resilience Measurement Model for Climate Change Adaptation: Focusing on Coastal Erosion Cases

기후변화 적응을 위한 연안 재해 회복탄력성 측정 모형의 개발 및 적용: 연안침식 사례를 중심으로

  • Received : 2023.11.27
  • Accepted : 2023.12.29
  • Published : 2023.12.31

Abstract

Climate change is significantly affecting coastal areas, and its impacts are expected to intensify. Recent studies on climate change adaptation and risk assessment in coastal regions increasingly integrate the concepts of recovery resilience and vulnerability. The aim of this study is to develop a measurement model for coastal hazard recovery resilience in the context of climate change adaptation. Before constructing the measurement model, a comprehensive literature review was conducted on coastal hazard recovery resilience, establishing a conceptual framework that included operational definitions for vulnerability and recovery resilience, along with several feedback mechanisms. The measurement model for coastal hazard recovery resilience comprised four metrics (MRV, LRV, RTSPV, and ND) and a Coastal Resilience Index (CRI). The developed indices were applied to domestic coastal erosion cases, and regional analyses were performed based on the index grades. The results revealed that the four recovery resilience metrics provided insights into the diverse characteristics of coastal erosion recovery resilience at each location. Mapping the composite indices of coastal resilience indicated that the areas along the East Sea exhibited relatively lower coastal erosion recovery resilience than the West and South Sea regions. The developed recovery resilience measurement model can serve as a tool for discussions on post-adaptation strategies and is applicable for determining policy priorities among different vulnerable regional groups.

기후변화는 연안지역에 심각한 영향을 미치고 있으며 그 영향이 점점 증가할 것이라고 예상되는 바, 최근 기후변화 적응 및 리스크 평가에 있어 많은 연구들이 취약성과 함께 회복탄력성 개념을 이용하고 있다. 본 연구의 목적은 기후변화 적응을 위한 연안재해 회복탄력성 측정 모형을 개발하는 것이다. 측정 모형 개발에 앞서 연안재해 회복탄력성에 대한 광범위한 문헌검토를 통해 취약성과 회복탄력성에 대한 조작적 정의와 함께 여러 피드백 메커니즘이 포함된 개념적 프레임워크를 작성하였다. 연안재해 회복탄력성 측정 모형은 네 가지 측정값(MRV, LRV, RTSPV, ND)과 연안재해 회복탄력성 복합 지수(CRI)를 포함하고 있으며, 개발된 지수는 국내 연안침식 사례에 적용되었다. 또한 지수 등급에 따른 지역적 분석이 수행되었다. 연구 결과, 네 가지 회복탄력성 측정값을 통해 각 지점이 가지는 연안침식 회복탄력성의 다양한 특성을 파악할 수 있음을 확인하였다. 연안 회복탄력성 복합 지수의 매핑 결과 서해안 및 남해안 지역에 비해 동해안 지역들은 연안침식 회복탄력성이 상대적으로 떨어지는 것으로 나타났다. 본 연구의 회복탄력성 측정 모형은 적응 이후의 이행전략에 대한 논의를 제공하는 도구로 활용될 수 있으며, 서로 다른 취약 지역 그룹 간 정책지원에 대한 우선순위를 결정하는 데 이용 가능하다.

Keywords

Acknowledgement

이 논문은 2023년도 해양수산부 재원으로 해양수산과학기술진흥원의 지원을 받아 수행된 연구임(20220431, 해양공간 정책시뮬레이터 기술개발).

References

  1. Anjos, L. J. and P. M. de Toledo(2018), Measuring resilience and assessing vulnerability of terrestrial ecosystems to climate change in South America, PLoS One, Vol. 13, No. 3, e0194654.
  2. Birgani, Y. T. and F. Yazdandoost(2016), Resilience in urban drainage risk management systems, In proceedings of the institution of civil engineers-water management, Vol. 169, No. 1, pp. 3-16. https://doi.org/10.1680/wama.14.00043
  3. Bruneau, M., S. E. Chang, R. T. Eguchi, G. C. Lee, T. D. O'Rourke, A. M. Reinhorn, ... and D. Von Winterfeldt(2003), A framework to quantitatively assess and enhance the seismic resilience of communities, Earthquake spectra, Vol. 19, No. 4, pp. 733-752. https://doi.org/10.1193/1.1623497
  4. Chang, S. E. and M. Shinozuka(2004), Measuring improvements in the disaster resilience of communities, Earthquake spectra, Vol. 20, No. 3, pp. 739-755. https://doi.org/10.1193/1.1775796
  5. Chen, J., S. T. Yang, H. W. Li, B. Zhang, and J. R. Lv(2013), Research on geographical environment unit division based on the method of natural breaks (Jenks), The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol. 40, pp. 47-50.
  6. Cutter, S. L., L. Barnes, M. Berry, C. Burton, E. Evans, E. Tate, and J. Webb(2008), A place-based model for understanding community resilience to natural disasters, Global environmental change, Vol. 18, No. 4, pp. 598-606.
  7. Cutter, S. L., K. D. Ash, and C. T. Emrich(2014), The geographies of community disaster resilience, Global environmental change, Vol. 29, pp. 65-77. https://doi.org/10.1016/j.gloenvcha.2014.08.005
  8. Field, C. B. and V. R. Barros(Eds.)(2014), Climate change 2014-Impacts, adaptation and vulnerability: Regional aspects, Cambridge University Press.
  9. Ingrisch, J. and M. Bahn(2018), Towards a comparable quantification of resilience, Trends in Ecology & Evolution, Vol. 33, No. 4, pp. 251-259. https://doi.org/10.1016/j.tree.2018.01.013
  10. Keating, A., K. Campbell, M. Szoenyi, C. McQuistan, D. Nash, and M. Burer(2017), Development and testing of a community flood resilience measurement tool, Natural Hazards and Earth System Sciences, Vol. 17, No. 1, pp. 77-101. https://doi.org/10.5194/nhess-17-77-2017
  11. Klein, R. J., R. J. Nicholls, and F. Thomalla(2003), Resilience to natural hazards: How useful is this concept?, Global environmental change part B: environmental hazards, Vol. 5, No. 1, pp. 35-45. https://doi.org/10.1016/j.hazards.2004.02.001
  12. Kythreotis, A. P. and G. I. Bristow(2017), The 'resilience trap': exploring the practical utility of resilience for climate change adaptation in UK city-regions, Regional Studies, Vol. 51, No. 10, pp. 1530-1541. https://doi.org/10.1080/00343404.2016.1200719
  13. Laboy, M. and D. Fannon(2016), Resilience theory and praxis: a critical framework for architecture, Enquiry The ARCC Journal for Architectural Research, Vol. 13, No. 1.
  14. McClymont, K., D. Morrison, L. Beevers, and E. Carmen (2020), Flood resilience: a systematic review. Journal of Environmental Planning and Management, Vol. 63, No. 7, pp. 1151-1176. https://doi.org/10.1080/09640568.2019.1641474
  15. Manyena, B., G. O'Brien, P. O'Keefe, and J. Rose(2011), Disaster resilience: a bounce back or bounce forward ability?, Local Environment: The International Journal of Justice and Sustainability, Vol. 16, No. 5, pp. 417-424.
  16. Miguez, M. G. and Verol, A. P.(2017), A catchment scale Integrated Flood Resilience Index to support decision making in urban flood control design, Environment and Planning B: Urban Analytics and City Science, Vol. 44, No. 5, pp. 925-946. https://doi.org/10.1177/0265813516655799
  17. Mugume, S. N., D. E. Gomez, G. Fu, R. Farmani, and D. Butler(2015), A global analysis approach for investigating structural resilience in urban drainage systems, Water research, Vol. 81, pp. 15-26. https://doi.org/10.1016/j.watres.2015.05.030
  18. Owotoki, P., N. Manojlovic, F. Mayer-Lindenberg, and E. Pasche(2006), A data mining approach for capacity building of stakeholders in integrated flood management, In Sixth International Conference on Data Mining (ICDM'06), pp. 446-455.
  19. Qasim, S., M. Qasim, R. P. Shrestha, A. N. Khan, K. Tun, and M. Ashraf(2016), Community resilience to flood hazards in Khyber Pukhthunkhwa province of Pakistan, International Journal of Disaster Risk Reduction, Vol. 18, pp. 100-106. https://doi.org/10.1016/j.ijdrr.2016.03.009
  20. Schinke, R., A. Kaidel, S. Golz, T. Naumann, J. S. Lopez-Gutierrez, and S. Garvin(2016), Analysing the effects of flood-resilience technologies in urban areas using a synthetic model approach, ISPRS international journal of geo-information, Vol. 5, No. 11, 202.
  21. Simonovic, S. P. and A. Peck(2013), Dynamic resilience to climate change caused natural disasters in coastal megacities quantification framework, British Journal of Environment and Climate Change, Vol. 3, No. 3, pp. 378-401. https://doi.org/10.9734/BJECC/2013/2504
  22. Simonovic, S. P.(2018), From risk management to quantitative disaster resilience: A new paradigm for catastrophe modeling, In Risk modeling for hazards and disasters, pp. 281-297.
  23. Singh, R. R., M. Bruneau, A. Stavridis, and K. Sett(2022), Resilience deficit index for quantification of resilience, Resilient Cities and Structures, Vol. 1, No. 2, pp. 1-9.
  24. Timmermann, P.(1981), Vulnerability, resilience and the collapse of society, Environmental Monograph, Vol. 1, pp. 1-42.
  25. Torresan, S., A. Critto, J. Rizzi, A. Zabeo, E. Furlan, and A. Marcomini(2016), DESYCO: A decision support system for the regional risk assessment of climate change impacts in coastal zones, Ocean & Coastal Management, Vol. 120, pp. 49-63. https://doi.org/10.1016/j.ocecoaman.2015.11.003
  26. Toimil, A., I. J. Losada, R. J. Nicholls, R. A. Dalrymple, and M. J. Stive(2020), Addressing the challenges of climate change risks and adaptation in coastal areas: A review, Coastal Engineering, Vol. 156, 103611.
  27. Wong, P. P., I. J. Losada, J. P. Gattuso, J. Hinkel, A. Khattabi, K. L. McInnes, ... and A. Sallenger(2014), Coastal systems and low-lying areas. Climate change, Vol. 2104, pp. 361-409.
  28. Woodruff, S. C. and M. Stults(2016), Numerous strategies but limited implementation guidance in US local adaptation plans, Nature Climate Change, Vol. 6, No. 8, pp. 796-802. https://doi.org/10.1038/nclimate3012
  29. Zevenbergen, C., B. Gersonius, and M. Radhakrishan(2020), Flood resilience. Philosophical Transactions of the Royal Society A, Vol. 378, No. 2168, 20190212.