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Methodology for assessment and forecast of drought severity based on the water balance analysis

물수지 분석에 기반한 가뭄 심각도 평가 및 예측 방법

  • Jang, Ock-Jae (Department of Civil Engineering, University of Seoul) ;
  • Moon, Young-Il (Department of Civil Engineering, University of Seoul) ;
  • Moon, Hyeon-Tae (Department of Civil Engineering, University of Seoul)
  • 장옥재 (서울시립대학교 토목공학과) ;
  • 문영일 (서울시립대학교 토목공학과) ;
  • 문현태 (서울시립대학교 토목공학과)
  • Received : 2020.12.22
  • Accepted : 2021.03.01
  • Published : 2021.04.30

Abstract

Drought is a natural disaster which is hard to recognize its onset and termination and to estimate the damage from the events which occurred in the past and are expected in near future. While the drought indices or their frequencies are widely applied to explain the severity of each event in the existing studies, decision-makers and stakeholders (the public) may have trouble in understanding the results due to the unfamiliar expression with statistical values. In this study, therefore, the methodology for assessment and forecast of drought severity based on the amount of water shortage from the water balance analysis was be placed at the center of the discussion. Firstly, in order to improve the existing analysis for drought assessment adopted in the National Water Resources Plan, alternative methods have been suggested to estimate the amount of water demand in each sub-basin using the land use map, and in an aspect of water supply, reservoirs and underground water are included in the simulation of MODSIM-DSS. The relationship between drought severity from the simulated water shortage in the study area and the values of SPEIs (SPEI 6 = estimated for 6 months - winter and spring season, SPEI 3 = estimated for 3 months - summer season) has been analyzed by the Decision tree. Due to this achievement, at the end of the spring season, every year the forecast for the drought severity will be available with the quantitatively estimated water shortage, and it will be helpful to activate the drought mitigation measures before the disaster occurs.

가뭄은 발생시점과 종료시점을 명확하게 알기 어려우며, 과거에 발생한 피해도, 향후 예상되는 피해도 추산하기 어렵다는 특성을 가지는 자연재해이다. 그렇기 때문에 기존 연구에서는 가뭄지수나 가뭄의 빈도를 사용하여 매번 가뭄의 심각도를 표현하고 있으나 이는 의사결정자나 지역 주민들이 익숙하지 않은 통계적인 수치로 표현되기 때문에 이해하기 어려운 측면이 있다. 따라서 본 연구에서는 물수지 분석 결과로부터 정량적으로 산출된 물부족량을 바탕으로 가뭄 심각도를 평가하고, 예측하는 방안에 대해 중심적으로 기술하였다. 먼저 가뭄의 심각도 평가를 위해 기존 수자원장기종합계획에서 적용하는 물수지 분석 방법에서 중권역의 수요량을 산출하는 방법을 토지이용도를 적용하여 개선하였으며, 공급량 측면에서는 농업용 저수지와 지하수를 MODSIM-DSS모형에 포함하여 모의하는 것을 제시하였다. 다음으로 대상 유역에 적용하여 산출된 중권역별 물부족량과 겨울철~봄철의 6개월 동안의 SPEI, 그리고 여름철 3개월 동안의 SPEI의 상관관계를 Decision tree 방법을 적용하여 분석하였다. 이를 통해 매년 봄철이 끝날 때 가뭄 심각도를 물부족량과 함께 수치로 예측함으로써 가뭄 재해 발생 전에 대응 활동을 계획하는데 도움이 될 것으로 판단된다.

Keywords

References

  1. Choi, S.J., Kang, S.K., Lee, D.R., and Kim, J.H. (2018). "A study on water supply and demand prospects for water resources planning." Journal of the Korean Society of Hazard Mitigation, Vol. 18, No. 7, pp. 589-593. https://doi.org/10.9798/kosham.2018.18.7.589
  2. Hong, W., and Wilhite, D.A. (2004). "An operational agricultural drought risk assessment model for Nebraska, USA." Natural Hazards, Vol. 33, pp. 1-21. https://doi.org/10.1023/B:NHAZ.0000034994.44357.75
  3. Huang, W.C., and Chou, C.C. (2008). "Risk-based drought early warning system in reservoir operation." Advances in Water Resources, Vol. 31, pp. 649-660. https://doi.org/10.1016/j.advwatres.2007.12.004
  4. Kim, T.W., Park, J.Y., and Shin, J.Y. (2020). "Determining proper threshold levels for hydrological drought analysis based on independent tests." Journal of Korea Water Resource Associate, Vol. 53, No. 3, pp. 193-200.
  5. K-water (2007). K-MODSIM manual Ver 1.1. pp. 1-40.
  6. K-water (2008). A study on the basic plan for water management. Publication No. 11-B500001-000091-01, pp. 233-287.
  7. Labadie, J.W., and Larson, R. (2007). MODSIM 8.1: River basin management decision support system. User manual and documentation. pp. 19-20.
  8. Lee, D.R., and Choi, S.J. (2011). "Introduction of integrated water resources assessment planning Model-K-WEAP (Korea-water evaluation and planning system)." Water for Future, Vol. 44, No. 9, pp. 117-123.
  9. Lee, J.E., Lee, K.M., and Cha, G.W. (2012). "Idea on the improvement of water yield evaluation methodology." Water for Future, Vol. 45, No. 12, pp. 51-57.
  10. Lee, J.E., Yoon, S.M., Im, E.S., and Kang, G.C. (2020). "A study on management criteria on seepage for fill dams considering rainfall effect." Journal of the Korean Geotechnical Society, Vol. 36, No. 5, pp. 5-16. https://doi.org/10.7843/KGS.2020.36.5.5
  11. Mckee, T.B., Doesken, N.J., and John, K. (1993). "The relationship of drought frequency and duration of time scales." 8th Conference on Applied Climatology, Anaheim, CA, U.S., pp. 179-184.
  12. Ministry of Construction and Transportation (MOCT) (2006). National water resources plan (2006 ~ 2020). Publication No. 11-B50 0001-000083-13, pp. 438-440.
  13. Ministry of Environment (ME) (2019). 2019 Groundwater annual report. Publication No. 11-1480000-001551-10, pp. 223-330.
  14. Ministry of Land, Infrastructure and Transport (MOLIT) (2016). National water resources plan (2001 ~ 2020) (3rd rev.). Publication No. 11-1613000-001716-13, pp. 198-233.
  15. Mishra, A.K., and Singh, V.P. (2010). "A review of drought concepts." Journal of Hydrology, Vol. 391, pp. 202-216.
  16. National Drought Information-Analysis Center (NDIC) (2016). Response guidebook for drought disaster. p. 117.
  17. National Drought Information Portal (NDIP) (2020). Korea, accessed 14 November 2020, .
  18. National Spatial Data Infrastructure (NSDI) (2020). Korea, accessed 14 August 2020, .
  19. Oh, J.H., Kim, Y.S., Ryu, K.S., and Bae, Y.D. (2019a). "Comparison and discussion of water supply and demand forecasts considering spatial resolution in the Han-river basin." Journal of Korea Water Resource Associate, Vol. 52, No. 7, pp. 505-514.
  20. Oh, J.H., Kim, Y.S., Ryu, K.S., and Jo, Y.S. (2019b). "Comparison and discussion of MODSM and K-WEAP model considering water supply priority." Journal of Korea Water Resource Associate, Vol. 52, No. 7, pp. 463-473.
  21. Quiring, A.M., and Papakryiakou, T.N. (2003). "An evaluation of agricultural drought indices for the Canadian prairies." Agricultural and Forest Meteorology, Vol. 118, pp. 49-62. https://doi.org/10.1016/S0168-1923(03)00072-8
  22. Razmkhah, H. (2016). "Preparing stream flow drought severity duration-frequency curves using threshold level method." Arabian Journal of Geosciences, Vol. 9, No. 7, p. 513. https://doi.org/10.1007/s12517-016-2528-1
  23. Scikit-learn (2020). Decision Trees, accessed 14 November 2020, .
  24. Sim, H.J., Ryu, J.S., Ahn, J., Kim, J., and Kim, S. (2013). "Real time drought index for determining drought conditions in natural water supply system communities." Journal of the Korean Society of Hazard Mitigation, Vol. 13, No. 5, pp. 363-373.
  25. So, J.M., Oh, T.S., and Bae, D.H. (2017). "Estimation and assessment of long-term drought outlook information using the long-term forecasting data." Journal of Korea Water Resource Associate, Vol. 50, No. 10, pp. 691-701.
  26. Sung, J.H., and Chung, E.S. (2014). "Application of streamflow drought index using threshold level method." Journal of Korea Water Resource Associate, Vol. 47, No. 5, pp. 491-500. https://doi.org/10.3741/JKWRA.2014.47.5.491
  27. Vicente-Serrano, S.M., Begueria, S., and Lopez-Moreno, J.I. (2010). "A multi-scalar drought index sensitive to global warming: The standardized precipitation evapotranspiration index." Journal of Climate, Vol. 23, pp. 1696-1718.
  28. Water Resources Management Information System (WAMIS) (2020). Korea, accessed 22 October 2020, .
  29. Won, M.S., Cheon, S.H., Shin, S.I., and Lee, S.Y. (2019). "Analysis of public transport ridership during a heavy snowfall in Seoul." Journal of the Korean Society of Civil Engineerings, Vol. 39, No. 6, pp. 859-867.
  30. Yu, J.S., Yoo, J.Y., Lee, J.H., and Kim, T.W. (2016). "Estimation of drought risk through the bivariate drought frequency analysis using copula functions." Journal of Korean Water Resources Association, Vol. 49, No. 3, pp. 217-225. https://doi.org/10.3741/JKWRA.2016.49.3.217