Journal of Korea Water Resources Association (한국수자원학회논문집)

Korea Water Resources Association (한국수자원학회)
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Development of regression functions for human and economic flood damage assessments in the metropolises

대도시에서의 인적·물적 홍수피해 추정을 위한 회귀함수 개발

  • Lim, Yeon Taek (Department of Civil Engineering, Yeungnam University) ;
  • Lee, Jong Seok (Department of Civil Engineering, Yeungnam University) ;
  • Choi, Hyun Il (Department of Civil Engineering, Yeungnam University)
  • 임연택 (영남대학교 건설시스템공학과) ;
  • 이종석 (영남대학교 건설시스템공학과) ;
  • 최현일 (영남대학교 건설시스템공학과)
  • Received : 2020.09.18
  • Accepted : 2020.10.26
  • Published : 2020.12.31
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Abstract

Flood disasters have been recently increasing worldwide due to climate change and extreme weather events. Since flood damage recovery has been conducted as a common coping strategy to flood disasters in the Republic of Korea, it is necessary to predict the regional flood damage costs by rainfall characteristics for a preventative measure to flood damage. Therefore, the purpose of this study is to present the regression functions for human and economic flood damage assessments for the 7 metropolises in the Republic of Korea. A comprehensive regression analysis was performed through the total 48 simple regression models on the two types of flood damage records for human and economic costs over the past two decades from 1998 to 2017 using the four kinds of nonlinear equations with each of the six rainfall variables. The damage assessment functions for each metropolis were finally selected by the evaluation of the regression results with the coefficient of determination and the statistical significance test, and then used for the human and economic flood damage assessments for 100-year rainfall in the 7 metropolises. The results of this study are expected to provide the basic information on flood damage cost assessments for flood damage mitigation measures.

기후변화와 기상이변으로 인해 최근 전세계적으로 홍수피해가 증가하고 있다. 우리나라에서는 피해복구가 일반적인 홍수피해 대응방안으로 사용되어 왔기 때문에, 홍수피해에 대한 예방적인 대책을 위해서는 강우특성에 따른 지역적 홍수피해규모를 예측할 필요가 있다. 따라서, 본 연구의 목적은 우리나라 7개 대도시에서의 강우에 의한 인적 및 물적 홍수피해 예측을 위한 회귀함수를 개발하는 것이다. 회귀분석은 1998년부터 2017년까지 최근 20년 동안의 인적 및 물적 손실의 2가지 피해특성자료에 대해 6개의 강우특성 인자를 4가지 형태의 비선형 방정식에 각각 적용한 총 48가지 유형의 단순회귀모형을 통해 종합적으로 수행되었다. 결정계수와 유의성 검정을 통해 회귀분석 결과를 검토하여 각 대도시의 피해추정함수를 최종 선정하였고, 이를 이용하여 100년 빈도 강우량에 대한 7개 대도시의 인적 및 물적 홍수피해 규모를 평가하였다. 본 논문의 결과는 홍수피해 저감대책을 위한 홍수피해 규모 평가에 기초정보를 제공할 수 있을 것으로 기대된다.

Keywords

References

  1. Bentler, P.M., and Chou, C.P. (1987). "Practical issues in structural modeling." Sociological Methods and Research, Vol. 16, No. 1, pp. 78-117. https://doi.org/10.1177/0049124187016001004
  2. Chae, Y.R., Jo, G.J., Lee, S.J., Jun, C.H., Jung, Y.M., Lee, J.H., Park, H.H., and Yoon, D.G. (2016). An analysis of the multiple impacts and policy networks of an extreme flood event in a metropolitan area. Korea Environment Institute, pp. 12-15.
  3. Chang, L.F., Lin, C.H., and Su, M.D. (2008). "Application of geographic weighted regression to establish flood-damage functions reflecting spatial variation." Water SA, Vol. 34, No. 2, pp. 209-216. https://doi.org/10.4314/wsa.v34i2.183641
  4. Choi, C.H., Kim, J.S., Kim, J.H., Kim, H.Y., Lee, W.J., and Kim, H. S. (2016). "Development of heavy rain damage prediction function using statistical methodology." Journal of the Korean Society of Hazard Mitigation, Vol. 17, No. 3, pp. 331-338. https://doi.org/10.9798/KOSHAM.2017.17.3.331
  5. Choi, C.K., Kim, K.T., Kim, G.H., and Kim, H.S. (2017). "Development of damage function for flood damage assessment on single family housing." Journal of the Korean Society of Hazard Mitigation, Vol. 17, No. 6, pp.421-431. https://doi.org/10.9798/KOSHAM.2017.17.6.421
  6. Cortes, M., Turco, M., Llasat-Botija, M., and Llasat, M.C. (2017). "The relationship between precipitation and insurance data for floods in a Mediterranean region (northeast Spain)." Natural hazards and earth system sciences, Vol. 18, No. 3, pp. 857-868.
  7. Doglioni, A., Fiorillo, F., Guadagno, F.M., and Simeone, V. (2011). "Evolutionary polynomial regression to alert rainfall-triggered landslide reactivation." Landslides, Vol. 9, No. 1, pp. 53-62. https://doi.org/10.1007/s10346-011-0274-8
  8. Dorland, C., Tol, R.S.J., and Palutikof, J.P. (1999). "Vulnerability of the Netherlands and Northwest Europe to storm damage under climate change." Climatic Change, Vol. 43, No. 3, pp. 513-535. https://doi.org/10.1023/A:1005492126814
  9. Dormann, C.F., Elith, J., Bacher, S., Buchmann, C., Carl, G., Carre, G., Garcia Marquez, J.R., Gruber, B., Lafourcade, B., Leitao, P.J., Munkemuller, T., McClean, C., Osborne, P.E., Reineking, B., Schroder, B., Skidmore, A.K., Zurell, D., and Lautenbach, S. (2013). "Collinearity: A review of methods to deal with it and a simulation study evaluating their performance." Ecography, Vol. 36, No. 1, pp. 27-46. https://doi.org/10.1111/j.1600-0587.2012.07348.x
  10. Green, S.B. (1991). "How many subjects it take to do a regression analysis?" Multivariate Behavioral Research, Vol. 26, No. 3, pp. 499-510. https://doi.org/10.1207/s15327906mbr2603_7
  11. Haddad, K., and Rahman, A. (2012). "Regional flood frequency analysis in eastern Australia: Bayesian GLS regression-based methods within fixed region and ROI framework - quantile regression vs. parameter regression technique." Journal of Hydrology, Vol. 430-431, pp. 142-161. https://doi.org/10.1016/j.jhydrol.2012.02.012
  12. Halinski, R.S., and Feldt, L.S. (1970). "The selection of variables in multiple regression analysis." Journal of Educational Measurement, Vol. 7, No. 3, pp. 151-157. https://doi.org/10.1111/j.1745-3984.1970.tb00709.x
  13. Harris, R.J. (1975). Primer of multivariate statistics. Academic Press, NY, U.S.
  14. Huang, X., Tan, H., Zhou, J., Yang, T., Benjamin, A., Wen, S.W., Li, S., Liu, A., Li, X., Fen, S., and Li, X. (2008). "Flood hazard in Hunan province of China: An economic loss analysis." Natural Hazards, Vol. 47, No. 1, pp. 65-73. https://doi.org/10.1007/s11069-007-9197-z
  15. Jang, O.J., and Kim, Y.O. (2009). "Flood risk estimation using regional regression analysis." Journal of the Korean Society of Hazard Mitigation, Vol. 9, No. 4, pp. 71-80.
  16. Jun, H.D., Park, M.J., and Kim, G.Y. (2008). "Damage analysis of meteorological disasters for each district considering the characteristics of a district." Journal of the Korean Society of Hazard Mitigation, Vol. 8, No. 2, pp. 75-82.
  17. Kim, J.S., Choi, C.H., Lee, J.S., and Kim, H.S. (2017). "Damage prediction using heavy rain risk assessment: (2) Development of heavy rain damage prediction function." Journal of the Korean Society of Hazard Mitigation, Vol. 17, No. 2, pp. 361-370. https://doi.org/10.9798/KOSHAM.2017.17.2.361
  18. Korea Meteorological Administration (KMA) (2020). Korean Climate Change Assessment Report 2020. p. 5.
  19. Lee, B.H. (2010). "Development of urban flood warning system using regression analysis." Journal of the Korean Society of Civil Engineers, Vol. 30, No. 4B, pp. 347-359.
  20. Lee, H.J., Ryu, S.H., Won, S.H., Jo, E.J., Kim, S.W., and Joe, G.H. (2016). "A study on model of heavy rain risk prediction using influencing factors of flood damage." Journal of the Korean Society of Hazard Mitigation, Vol. 16, No. 3, pp. 39-45. https://doi.org/10.9798/KOSHAM.2016.16.3.39
  21. Lee, J.S., Eo. G., Choi, C.H., Jung, J.W., and Kim, H.S. (2016). "Development of rainfall-flood damage estimation function using nonlinear regression equation." Journal of the Korean Society of Disaster Information, Vol. 12, No. 1, pp. 74-88. https://doi.org/10.15683/kosdi.2016.3.31.74
  22. Miller, D.E., and Kunce, J.T. (1973). "Prediction and statistical overkill revisited." Measurement and Evaluation in Guidance, Vol. 6, No. 3, pp. 157-163. https://doi.org/10.1080/00256307.1973.12022590
  23. Ministry of the Interior and Safety (MOIS). (2017). Statistical yearbook of natural disaster. 2017, pp. 41-42.
  24. Mukaka, M.M. (2012). "Statistics corner: A guide to appropriate use of correlation coefficient in medical research." Malawi Medical Journal, Vol. 24, No. 3, pp. 69-71.
  25. Nunnally, J.C. (1978). Psychometric Theory: Second edition. McGraw Hill, NY, U.S.
  26. Ratner, B. (2009). "The correlation coefficient: Its values range between +1/-1, or do they?" Journal of Targeting, Measurement and Analysis for Marketing, Vol. 17, pp. 139-142. https://doi.org/10.1057/jt.2009.5
  27. Spekkers, M.H., Kok, M., Clemens, F.H.L.R., and ten Veldhuis, J.A.E. (2014). "Decision-tree analysis of factors influencing rainfall-related building structure and content damage." Natural hazards and earth system sciences, Vol. 14, No. 9, pp. 2531-2547. https://doi.org/10.5194/nhess-14-2531-2014
  28. Zhai, G., Fukuzono, T., and Ikeda, S. (2005). "Modeling flood damage: Case of Tokai flood 2000." Journal of the American Water Resources Association, Vol. 41, No. 1, pp. 77-92. https://doi.org/10.1111/j.1752-1688.2005.tb03719.x
  29. Zou, L., and Wei, Y. (2009). "Impact assessment using DEA of coastal hazards on social-economy in Southeast Asia." Natural Hazards, Springer, Vol. 48, No. 2, pp. 167-189. https://doi.org/10.1007/s11069-008-9256-0