Articles | Volume 28, issue 13
https://doi.org/10.5194/hess-28-2809-2024
https://doi.org/10.5194/hess-28-2809-2024
Research article
 | 
03 Jul 2024
Research article |  | 03 Jul 2024

Quantifying and reducing flood forecast uncertainty by the CHUP-BMA method

Zhen Cui, Shenglian Guo, Hua Chen, Dedi Liu, Yanlai Zhou, and Chong-Yu Xu

Related authors

Reconstruction of reservoir water level-storage relationship based on capacity loss induced by sediment accumulation and its impact on flood control operation
Qiumei Ma, Chengyu Xie, Zheng Duan, Yanke Zhang, Lihua Xiong, and Chong-Yu Xu
EGUsphere, https://doi.org/10.5194/egusphere-2025-679,https://doi.org/10.5194/egusphere-2025-679, 2025
This preprint is open for discussion and under review for Hydrology and Earth System Sciences (HESS).
Short summary
Exploring the potential processes controlling changes in precipitation–runoff relationships in non-stationary environments
Tian Lan, Tongfang Li, Hongbo Zhang, Jiefeng Wu, Yongqin David Chen, and Chong-Yu Xu
Hydrol. Earth Syst. Sci., 29, 903–924, https://doi.org/10.5194/hess-29-903-2025,https://doi.org/10.5194/hess-29-903-2025, 2025
Short summary
An explainable deep learning model based on hydrological principles for flood simulation and forecasting
Xin Xiang, Shenglian Guo, Chenglong Li, and Yun Wang
EGUsphere, https://doi.org/10.5194/egusphere-2025-279,https://doi.org/10.5194/egusphere-2025-279, 2025
Short summary
A Novel Framework for Calibration and Evaluation of Hydrological Models in Dynamic Catchments
Tian Lan, Xiao Wang, Hongbo Zhang, Xinghui Gong, Xue Xie, Yongqin David Chen, and Chong-Yu Xu
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-384,https://doi.org/10.5194/hess-2024-384, 2025
Preprint under review for HESS
Short summary
Impacts of Inter-basin Water Diversion Projects on the Feedback Loops of Water Supply-Hydropower Generation-Environment Conservation Nexus
Jiaoyang Wang, Dedi Liu, Shenglian Guo, Lihua Xiong, Pan Liu, Hua Chen, Jie Chen, Jiabo Yin, and Yuling Zhang
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-399,https://doi.org/10.5194/hess-2024-399, 2025
Revised manuscript under review for HESS
Short summary

Related subject area

Subject: Catchment hydrology | Techniques and Approaches: Modelling approaches
Long short-term memory networks for enhancing real-time flood forecasts: a case study for an underperforming hydrologic model
Sebastian Gegenleithner, Manuel Pirker, Clemens Dorfmann, Roman Kern, and Josef Schneider
Hydrol. Earth Syst. Sci., 29, 1939–1962, https://doi.org/10.5194/hess-29-1939-2025,https://doi.org/10.5194/hess-29-1939-2025, 2025
Short summary
Assessing the value of high-resolution rainfall and streamflow data for hydrological modeling: an analysis based on 63 catchments in southeast China
Mahmut Tudaji, Yi Nan, and Fuqiang Tian
Hydrol. Earth Syst. Sci., 29, 1919–1937, https://doi.org/10.5194/hess-29-1919-2025,https://doi.org/10.5194/hess-29-1919-2025, 2025
Short summary
Catchments do not strictly follow Budyko curves over multiple decades, but deviations are minor and predictable
Muhammad Ibrahim, Miriam Coenders-Gerrits, Ruud van der Ent, and Markus Hrachowitz
Hydrol. Earth Syst. Sci., 29, 1703–1723, https://doi.org/10.5194/hess-29-1703-2025,https://doi.org/10.5194/hess-29-1703-2025, 2025
Short summary
Scale dependency in modeling nivo-glacial hydrological systems: the case of the Arolla basin, Switzerland
Anne-Laure Argentin, Pascal Horton, Bettina Schaefli, Jamal Shokory, Felix Pitscheider, Leona Repnik, Mattia Gianini, Simone Bizzi, Stuart N. Lane, and Francesco Comiti
Hydrol. Earth Syst. Sci., 29, 1725–1748, https://doi.org/10.5194/hess-29-1725-2025,https://doi.org/10.5194/hess-29-1725-2025, 2025
Short summary
Extended-range forecasting of stream water temperature with deep-learning models
Ryan S. Padrón, Massimiliano Zappa, Luzi Bernhard, and Konrad Bogner
Hydrol. Earth Syst. Sci., 29, 1685–1702, https://doi.org/10.5194/hess-29-1685-2025,https://doi.org/10.5194/hess-29-1685-2025, 2025
Short summary

Cited articles

Baran, S., Hemri, S., and El Ayari, M.: Statistical post-processing of water level forecasts using Bayesian model averaging with doubly-truncated normal components, Water Resour. Res., 55, 3997–4013, https://doi.org/10.1029/2018WR024028, 2019. 
Biondi, D. and Todini, E.: Comparing hydrological postprocessors including ensemble predictions into full predictive probability distribution of streamflow, Water Resour. Res., 54, 9860–9882, https://doi.org/10.1029/2017WR022432, 2018. 
Chen, L. and Guo, S.: Copulas and its application in hydrology and water resources, Springer Water, Springer Singapore, https://doi.org/10.1007/978-981-13-0574-0, 2019. 
Cho, K. and Kim, Y.: Improving streamflow prediction in the WRF-Hydro model with LSTM networks, J. Hydrol., 605, 127297, https://doi.org/10.1016/j.jhydrol.2021.127297, 2022. 
Cloke, H. L. and Pappenberger, F.: Ensemble flood forecasting: A review, J. Hydrol., 375, 613–626, https://doi.org/10.1016/j.jhydrol.2009.06.005, 2009. 
Download
Short summary
Ensemble forecasting facilitates reliable flood forecasting and warning. This study couples the copula-based hydrologic uncertainty processor (CHUP) with Bayesian model averaging (BMA) and proposes the novel CHUP-BMA method of reducing inflow forecasting uncertainty of the Three Gorges Reservoir. The CHUP-BMA avoids the normal distribution assumption in the HUP-BMA and considers the constraint of initial conditions, which can improve the deterministic and probabilistic forecast performance.
Share