DOI QR코드

DOI QR Code

Development of a decision scaling framework for drought vulnerability assessment of dam operation under climate change

Decision Scaling 기반 댐 운영 기후변화 가뭄 취약성 평가

  • Kim, Jiheun (Institute of Urban Science, University of Seoul) ;
  • Seo, Seung Beom (International School of Urban Sciences, University of Seoul) ;
  • Cho, Jaepil (Integrated Watershed Management Institute)
  • 김지흔 (서울시립대학교 도시과학연구원 국제도시 및 인프라연구센터) ;
  • 서승범 (서울시립대학교 국제도시과학대학원) ;
  • 조재필 (유역통합관리연구원)
  • Received : 2023.02.09
  • Accepted : 2023.03.27
  • Published : 2023.04.30

Abstract

Water supply is continuously suffering from frequent droughts under climate change, and such extreme events are expected to become more frequent due to climate change. In this study, the decision scaling method was introduced to evaluate the drought vulnerability under future climate change in a wider range. As a result, the water supply reliability of the Boryeong Dam ranged from 95.80% to 98.13% to the condition of the aqueduct which was constructed at the Boryeong Dam. Furthermore, the Boryeong Dam was discovered to be vulnerable under climate change scenarios. Hence, genetic algorithm-based hedging rules were developed to evaluate the reduction effect of drought vulnerability. Moreover, three demand scenarios (high, standard, and low demand) were also considered to reflect the future socio-economic change in the Boryeong Dam. By analyzing quantitative reliability and the probability of extreme drought occurrence under 5% of the water storage rate, all hedging rules demonstrated that they were superior in preparing for extreme drought under low-demand scenarios.

최근 지속적인 가뭄으로 물 공급에 큰 어려움을 겪고 있으며, 이러한 극한 사상의 발생은 기후변화에 따라 더욱 빈번해질 것으로 전망된다. 본 연구는 기후변화에 따른 댐 운영 가뭄 취약성을 평가하고자, 보다 넓은 범위에서 미래 기후변화의 변동성을 반영할 수 있는 decision scaling 기법을 제안하였다. 충청남도 보령댐을 시범유역으로 선정하고 양적 신뢰도를 이용하여 평가한 결과, 보령댐의 가뭄 취약도는 도수로 반영 여부에 따라 95.80% 에서 98.13%까지 변동하였고, 기후변화에 매우 취약한 것으로 나타났다. 더불어 유전 알고리즘 기반 최적의 헤징룰을 산정하여 가뭄 취약성의 저감 효과를 분석하였고, 다양한 사회·경제적 변화에 대응하기 위해 세 가지 수요 시나리오(고수요, 저수요, 기준수요) 하에서 평가를 진행하였다. 양적 신뢰도와 극한가뭄 발생 빈도를 평가 기준으로 분석한 결과, 두 헤징룰은 K-water의 용수공급 조정기준 대비 저수요 시나리오에서 공급 안정도를 개선시킴으로써 극한가뭄에 적절히 대처할 수 있는 방법으로 사용될 수 있을 것이다.

Keywords

Acknowledgement

본 결과물은 환경부의 재원으로 한국환경산업기술원의 가뭄 대응 물관리 혁신기술개발사업(과제번호: 2022003610001) 의 지원을 받아 수행되었습니다. 이에 감사드립니다.

References

  1. Alahdin, S., Ghafouri, H.R., and Haghighi, A. (2019). "Multi-reservoir system operation in drought periods with balancing multiple groups of objectives." KSCE Journal of Civil Engineering, Vol. 23, No. 2, pp. 914-922. https://doi.org/10.1007/s12205-018-0109-4
  2. Broderick, C., Murphy, C., Wilby, R.L., Matthews, T., Prudhomme, C., and Adamson, M. (2019). "Using a scenario neutral framework to avoid potential maladaptation to future flood risk." Water Resources Research, Vol. 55, No. 2, pp. 1079-1104. https://doi.org/10.1029/2018WR023623
  3. Brown, C., Ghile, Y., Laverty, M., and Li, K. (2012). "Decision scaling: Linking bottom up vulnerability analysis with climate projections in the water sector." Water Resources Research, Vol. 48, No. 9, W09537. doi: 10.1029/2011WR011212.
  4. Brown, C., Werick, W., Leger, W., and Fay, D. (2011). "A Decision Analytic approach to managing climate risks: Application to the upper great lakes." Journal of the American Water Resources Association, Vol. 47, No. 3, pp. 524-534. https://doi.org/10.1111/j.1752-1688.2011.00552.x
  5. ChungNam Institute (2016). Boryeong Dam water supply capacity assessment and drought response plan research, 2016-33. pp. 68-69.
  6. Culley, S., Bennett, B., Westra, S., and Maier, H.R. (2019). "Generating realistic perturbed hydrometeorological time series to inform scenario-neutral climate impact assessments." Journal of Hydrology, Vol. 576, pp. 111-122. https://doi.org/10.1016/j.jhydrol.2019.06.005
  7. Gomes, L.S., Maia, A.G., and de Medeiros, J.D.F. (2021). "Fuzzified hedging rules for a reservoir in the Brazilian semiarid region." Environmental Challenges, Vol. 4, 100125.
  8. Hashimoto, T., Stedinger, J.R., and Loucks, D.P. (1982). "Reliability, resiliency, and vulnerability criteria for water resource system performance evaluation." Water Resources Research, Vol. 18, No. 1, pp. 14-20. https://doi.org/10.1029/WR018i001p00014
  9. Hirpa, F.A., Dyer, E., Hope, R., Olago, D.O., and Dadson, S.J. (2018). "Finding sustainable water futures in data-sparse regions under climate change: Insights from the Turkwel River basin, Kenya." Journal of Hydrology: Regional Studies, Vol. 19, pp. 124-135. https://doi.org/10.1016/j.ejrh.2018.08.005
  10. Keller, L., Rossler, O., Martius, O., and Weingartner, R. (2019). "Comparison of scenario neutral approaches for estimation of climate change impacts on flood characteristics." Hydrological Processes, Vol. 33, No. 4, pp. 535-550. https://doi.org/10.1002/hyp.13341
  11. Kim, D., Chun, J.A., and Choi, S.J. (2019). "Incorporating the logistic regression into a decision-centric assessment of climate change impacts on a complex river system." Hydrology and Earth System Sciences, Vol. 23, No. 2, pp. 1145-1162. https://doi.org/10.5194/hess-23-1145-2019
  12. Kim, D., Kim, E., Lee, S.C., Kim, E., and Shin, J. (2022a). "A decisioncentric impact assessment of operational performance of the Yongdam Dam, South Korea." Journal of Korea Water Resources Association, Vol. 55, No. 3, pp. 205-215.
  13. Kim, J., Jung, K., and Hur, J. (2022b). Long-term economic growth: Projection and implications. Korea Development Institute, pp. 6-8.
  14. Lee, D.R., Choe, S.J., and Baek, S.H. (2015). "Water supply capacity evaluation technology for water resource facilities based on climate change development." Water for Future, Vol. 48, No. 5, pp. 17-22.
  15. Lee, J.H., Park, S.Y., Kim, M.G., and Chung, I.M. (2021). "Hydrological drought analysis and monitoring using multiple drought indices: The case of Mulrocheon watershed." Journal of Civil and Environmental Engineering, Vol. 41, No. 5, pp. 477-484.
  16. Lim, G., Noh, S., Son, M., and Jung, K. (2021). "Boryeong Dam emergency water diversion facility: Ensuring operational flexibility and resilient response to climate change." Journal of Society of the Korean Society of Hazard and Mitigation. Vol. 21, No. 3, pp. 11-12. https://doi.org/10.9798/KOSHAM.2021.21.3.11
  17. Ministry of Environment (ME) (2020). Korean climate change assessment report 2020. Report 11-1480000-001690-01, pp. 30-68.
  18. Ministry of Land, Transport and Maritime Affairs (MLTM) (2011). Water vision (2011-2020). Report 11-1611000-002114-13.
  19. Nazemi, A., Wheater, H.S., Chun, K.P., and Elshorbagy, A. (2013). "A stochastic reconstruction framework for analysis of water resource system vulnerability to climate induced changes in river flow regime." Water Resources Research, Vol. 49, No. 1, pp. 291-305. https://doi.org/10.1029/2012WR012755
  20. Perrin, C., Michel, C., and Andreassian, V. (2003). "Improvement of a parsimonious model for streamflow simulation." Journal of Hydrology, Vol. 279, No. 1-4, pp. 275-289. https://doi.org/10.1016/S0022-1694(03)00225-7
  21. Scrucca, L. (2013). "GA: A package for genetic algorithms in R." Journal of Statistical Software, Vol. 53, pp. 1-37. https://doi.org/10.18637/jss.v053.i04
  22. Seo, S.B., Kim, Y.O., and Kang, S.U. (2019a). "Time-varying discrete hedging rules for drought contingency plan considering longrange dependency in streamflow." Water Resources Management, Vol. 33, No. 8, pp. 2791-2807. https://doi.org/10.1007/s11269-019-02244-5
  23. Seo, S.B., Kim, Y.O., Kim, Y., and Eum, H.I. (2019b). "Selecting climate change scenarios for regional hydrologic impact studies based on climate extremes indices." Climate Dynamics, Vol. 52, pp. 1595-1611. https://doi.org/10.1007/s00382-018-4210-7
  24. Singh, R., Wagener, T., Crane, R., Mann, M.E., and Ning, L. (2014). "A vulnerability driven approach to identify adverse climate and land use change combinations for critical hydrologic indicator thresholds: Application to a watershed in Pennsylvania, USA." Water Resources Research, Vol. 50, No. 4, pp. 3409-3427. https://doi.org/10.1002/2013WR014988
  25. Stainforth, D.A., Downing, T.E., Washington, R., Lopez, A., and New, M. (2007). "Issues in the interpretation of climate model ensembles to inform decisions." Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, Vol. 365, No. 1857, pp. 2163-2177. https://doi.org/10.1098/rsta.2007.2073
  26. Steinschneider, S., McCrary, R., Wi, S., Mulligan, K., Mearns, L.O., and Brown, C. (2015). "Expanded decision-scaling framework to select robust long-term water-system plans under hydroclimatic uncertainties." Journal of Water Resources Planning and Management, Vol. 141, No. 11, 04015023.
  27. Sung, J., Kang, B., Kim, B., and Noh, S. (2022). "Development and application of integrated indicators for assessing the water resources performance of multi-purpose and water supply dams." Journal of Korea Water Resources Association, Vol. 55, No. 9, pp. 687-700. https://doi.org/10.3741/JKWRA.2022.55.9.687
  28. Turner, S.W., Marlow, D., Ekstrom, M., Rhodes, B.G., Kularathna, U., and Jeffrey, P.J. (2014). "Linking climate projections to performance: A yield based decision scaling assessment of a large urban water resources system." Water Resources Research, Vol. 50, No. 4, pp. 3553-3567. https://doi.org/10.1002/2013WR015156
  29. Whateley, S., Steinschneider, S., and Brown, C. (2014). "A climate change range based method for estimating robustness for water resources supply." Water Resources Research, Vol. 50, No. 11, pp. 8944-8961. https://doi.org/10.1002/2014WR015956
  30. Yoon, H.N., Seo, S.B., and Kim, Y-O. (2018). "Development of Robust-SDP for improving dam operation to cope with non-stationarity of climate change." Journal of Korea Water Resources Association, Vol. 51, No. S-1, pp. 1135-1148.