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Long-term flood risk assessment of watersheds under climate change based on the game cross-efficiency DEA

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  • Qingmu Su

    (National Cheng Kung University)

Abstract

Climate change has significantly increased extreme precipitation and altered regional hydrological cycle, aggravating flood in the watershed. The effective measurement of the risk brought by climate change is an effective way to cope with flood hazard in the future. At the same time, the quality of the simulation of climate change scenarios will also affect the accuracy of flood risk assessment. Therefore, a comprehensive method is needed to measure the long-term disaster risk. However, the current method of subjectively assigning indicator weights is still subjective and difficult to be promoted and applied. So a new model for assessing watershed risk is constructed in this study. Based on the game cross-efficiency data envelopment analysis method and the combination of simulations of climate scenarios, the model can determine the input factors of the assessment and the influencing level of the input factors by using the Principal Component Analysis and Tobit model. The model comprehensively evaluates the flood risk level in the watershed with the results of the simulation of hazard in different climate scenarios, hazard exposure and social vulnerability as input factors, and the degree of disaster loss as the output factor. Results: (1) the hazard, exposure, and social vulnerability are spatially mismatched; (2) the overall risk in the watershed presents such a pattern: upstream (0.751) > downstream (0.418) > midstream (0.362); (3) the long-term flood hazard may be reduced under the influence of climate change. The research is helpful to formulate long-term flood mitigation strategies in the future.

Suggested Citation

  • Qingmu Su, 2020. "Long-term flood risk assessment of watersheds under climate change based on the game cross-efficiency DEA," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 104(3), pages 2213-2237, December.
    • Handle: RePEc:spr:nathaz:v:104:y:2020:i:3:d:10.1007_s11069-020-04269-1
    DOI: 10.1007/s11069-020-04269-1
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    References listed on IDEAS

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    1. Kiani Mavi, Reza & Saen, Reza Farzipoor & Goh, Mark, 2019. "Joint analysis of eco-efficiency and eco-innovation with common weights in two-stage network DEA: A big data approach," Technological Forecasting and Social Change, Elsevier, vol. 144(C), pages 553-562.
    2. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
    3. Elias Bekele & H. Knapp, 2010. "Watershed Modeling to Assessing Impacts of Potential Climate Change on Water Supply Availability," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 24(13), pages 3299-3320, October.
    4. Enliang Guo & Jiquan Zhang & Xuehui Ren & Qi Zhang & Zhongyi Sun, 2014. "Integrated risk assessment of flood disaster based on improved set pair analysis and the variable fuzzy set theory in central Liaoning Province, China," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 74(2), pages 947-965, November.
    5. Richard J. Sexton, 1986. "The Formation of Cooperatives: A Game-Theoretic Approach with Implications for Cooperative Finance, Decision Making, and Stability," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 68(2), pages 214-225.
    6. Chen, Yao & Cook, Wade D. & Li, Ning & Zhu, Joe, 2009. "Additive efficiency decomposition in two-stage DEA," European Journal of Operational Research, Elsevier, vol. 196(3), pages 1170-1176, August.
    7. Subhankar Chakraborty & Sutapa Mukhopadhyay, 2019. "Assessing flood risk using analytical hierarchy process (AHP) and geographical information system (GIS): application in Coochbehar district of West Bengal, India," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 99(1), pages 247-274, October.
    8. Susan L. Cutter & Bryan J. Boruff & W. Lynn Shirley, 2003. "Social Vulnerability to Environmental Hazards," Social Science Quarterly, Southwestern Social Science Association, vol. 84(2), pages 242-261, June.
    9. R. D. Banker & A. Charnes & W. W. Cooper, 1984. "Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis," Management Science, INFORMS, vol. 30(9), pages 1078-1092, September.
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    Cited by:

    1. Fabien Candau & Charles Regnacq & Julie Schlick, 2022. "Climate Change, Comparative Advantage and the Water Capability to Produce Agricultural Goods," Working Papers hal-03671521, HAL.
    2. Candau, Fabien & Regnacq, Charles & Schlick, Julie, 2022. "Climate change, comparative advantage and the water capability to produce agricultural goods," World Development, Elsevier, vol. 158(C).
    3. Chao Zhang & Changming Ji & Yi Wang & Qian Xiao, 2022. "Flood hydrograph coincidence analysis of the upper Yangtze River and Dongting Lake, China," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 110(2), pages 1339-1360, January.
    4. Qingmu Su & Kaida Chen & Lingyun Liao, 2021. "The Impact of Land Use Change on Disaster Risk from the Perspective of Efficiency," Sustainability, MDPI, vol. 13(6), pages 1-14, March.
    5. Qingmu Su & Hsueh-Sheng Chang & Xiang Chen & Jingjing Xiao, 2022. "Metacoupling of Water Transfer: The Interaction of Ecological Environment in the Middle Route of China’s South-North Project," IJERPH, MDPI, vol. 19(17), pages 1-22, August.
    6. Qingmu Su & Hsueh-Sheng Chang & Shin-En Pai, 2022. "A Comparative Study of the Resilience of Urban and Rural Areas under Climate Change," IJERPH, MDPI, vol. 19(15), pages 1-14, July.

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