Articles | Volume 30, issue 1
https://doi.org/10.5194/hess-30-227-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-30-227-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Insights into uncertainties in future drought analysis using hydrological simulation model
Jin Hyuck Kim
Department of Civil Engineering, Chungnam National University, 99 Daehak-ro, Yuseong-gu, Daejeon 34134, South Korea
Faculty of Civil Engineering, Seoul National University of Science and Technology, 232 Gongneung-ro, Nowon-gu, Seoul 01811, South Korea
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Young Hoon Song and Eun-Sung Chung
Geosci. Model Dev., 18, 8017–8045, https://doi.org/10.5194/gmd-18-8017-2025, https://doi.org/10.5194/gmd-18-8017-2025, 2025
Short summary
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This study assessed three methods for correcting daily precipitation data: Quantile Delta Mapping, Empirical Quantile Mapping (EQM), and Detrended Quantile Mapping (DQM) using 11 GCMs. EQM performed best overall, offering reliable corrections and lower uncertainty. The best bias correction method for each grid is selected differently depending on the weighting case. The best bias correction method can vary depending on factors such as climate and terrain.
Young Hoon Song, Eun-Sung Chung, and Shamsuddin Shahid
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2022-107, https://doi.org/10.5194/hess-2022-107, 2022
Manuscript not accepted for further review
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This study proposed two new concepts for the previous Double Gamma Quantile Mapping (DGQM), such as the inclusion of flexible dividing point between two individual gamma functions and the use of more probability distributions. As a result, F-DDQM method performed the better bias correction for the GCMs very clearly. This new F-DDQM method can be also applied to the various fields such as the use of satellite climate data, reanalysis climate data and spatial downscaling or interpolation.
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Short summary
Hydrological simulation requires parameter calibration. This study quantifies uncertainties in future runoff and drought using the Soil and Water Assessment Tool, twenty general circulation models, and shared socioeconomic pathway scenarios. Results show calibration conditions significantly impact low-flow projections. While climate models dominate uncertainty, calibration choices contribute notably, highlighting the need for robust strategies in water resource planning.
Hydrological simulation requires parameter calibration. This study quantifies uncertainties in...