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Natural Hazards and Earth System Sciences An interactive open-access journal of the European Geosciences Union
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https://doi.org/10.5194/nhess-2017-163
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/nhess-2017-163
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.

  19 Jun 2017

19 Jun 2017

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This discussion paper is a preprint. It has been under review for the journal Natural Hazards and Earth System Sciences (NHESS). The manuscript was not accepted for further review after discussion.

The Probabilistic Drought Forecast Based on the Ensemble Technique Using the Korean Surface Water Supply Index

Suk Hwan Jang1, Jae-Kyoung Lee2, Ji Hwan Oh3, Jun Won Jo4, and Younghyun Cho5 Suk Hwan Jang et al.
  • 1Professor, Department of Civil Engineering, Daejin Universit y, Pocheon-si, Gyeonggi-do, Korea
  • 2Assistant Professor, Innovation Center for Engineering Education, Daejin University, Pocheon-si, Gyeonggi-do, Korea
  • 3Ph.D Candidate, Department of Civil Engineering, Daejin Universit y, Pocheon-si, Gyeonggi-do, Korea
  • 4Master course, Department of Civil Engineering, Daejin Universit y, Pocheon-si, Gyeonggi-do, Korea
  • 5Principal Researcher, Hydrometeorological Cooperation Center, Gwacheon-si, Gyeonggi-do, Korea

Abstract. This study proposes the new hydrological drought index, Korean Surface Water Supply Index (KSWSI), which overcomes some of the limitations in the calculation of previous SWSI applied in Korea and conducts the probabilistic drought forecasts using KSWSI. In this study, all hydrometeorological variables in the Geum River basin were investigated and appropriate variables were selected as KSWSI components for each sub-basin. And whereby only the normal distributions are applied to all drought components, probability distributions suitable for each KSWSI component were estimated. As a result of verifying KSWSIs, the accuracy of KSWSIs showed better drought phenomenon in drought events. The monthly probabilistic drought forecasts were also calculated based on ensemble technique using KSWSI. In 2006 and 2014 drought events, the accuracy of the drought forecasts using KSWSIs were higher than those using previous SWSI, demonstrating that KSWSI is able to enhance the accuracy of drought forecasts. The influence of expanding hydrometeorological components and selecting appropriate probability distributions for each KSWSI component were analyzed. It is confirmed that the accuracy of KSWSIs may be affected by the choice of hydrometerological components, the station data obtained, the length of used data for each station, and the probability distributions selected. Furthermore, the uncertainty quantification of the KSWSI calculation procedure was also carried out using the Maximum Entropy (ME) theory. The large MEs and standard deviations of KSWSIs in the flood season cause uncertainties, implying that the selection of the appropriate probability distributions for selected drought components in the flood season is very important.

Suk Hwan Jang et al.

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Suk Hwan Jang et al.

Suk Hwan Jang et al.

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Short summary
In this paper, we focus on the new hydrological drought index, Korean Surface Water Supply Index (KSWSI), which overcomes some of the limitations in the calculation of previous SWSI applied in Korea and conducts the probabilistic drought forecasts using KSWSI. The paper should be of interest to readers in the areas of the drought index and drought forecasts.
In this paper, we focus on the new hydrological drought index, Korean Surface Water Supply Index...
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