Articles | Volume 20, issue 9
https://doi.org/10.5194/hess-20-3601-2016
https://doi.org/10.5194/hess-20-3601-2016
Research article
 | 
06 Sep 2016
Research article |  | 06 Sep 2016

Bias correcting precipitation forecasts to improve the skill of seasonal streamflow forecasts

Louise Crochemore, Maria-Helena Ramos, and Florian Pappenberger

Related authors

INSPIRE Game: Integration of vulnerability in impact-based forecasting of urban floods
Akshay Singhal, Louise Crochemore, Isabelle Ruin, and Sanjeev Jha
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2024-116,https://doi.org/10.5194/hess-2024-116, 2024
Preprint under review for HESS
Short summary
Simulated hydrological effects of grooming and snowmaking in a ski resort on the local water balance
Samuel Morin, Hugues François, Marion Réveillet, Eric Sauquet, Louise Crochemore, Flora Branger, Étienne Leblois, and Marie Dumont
Hydrol. Earth Syst. Sci., 27, 4257–4277, https://doi.org/10.5194/hess-27-4257-2023,https://doi.org/10.5194/hess-27-4257-2023, 2023
Short summary
Quantifying multi-year hydrological memory with Catchment Forgetting Curves
Alban de Lavenne, Vazken Andréassian, Louise Crochemore, Göran Lindström, and Berit Arheimer
Hydrol. Earth Syst. Sci., 26, 2715–2732, https://doi.org/10.5194/hess-26-2715-2022,https://doi.org/10.5194/hess-26-2715-2022, 2022
Short summary
Benchmarking an operational hydrological model for providing seasonal forecasts in Sweden
Marc Girons Lopez, Louise Crochemore, and Ilias G. Pechlivanidis
Hydrol. Earth Syst. Sci., 25, 1189–1209, https://doi.org/10.5194/hess-25-1189-2021,https://doi.org/10.5194/hess-25-1189-2021, 2021
Short summary
From skill to value: isolating the influence of end user behavior on seasonal forecast assessment
Matteo Giuliani, Louise Crochemore, Ilias Pechlivanidis, and Andrea Castelletti
Hydrol. Earth Syst. Sci., 24, 5891–5902, https://doi.org/10.5194/hess-24-5891-2020,https://doi.org/10.5194/hess-24-5891-2020, 2020
Short summary

Related subject area

Subject: Hydrometeorology | Techniques and Approaches: Mathematical applications
Using statistical models to depict the response of multi-timescale drought to forest cover change across climate zones
Yan Li, Bo Huang, and Henning W. Rust
Hydrol. Earth Syst. Sci., 28, 321–339, https://doi.org/10.5194/hess-28-321-2024,https://doi.org/10.5194/hess-28-321-2024, 2024
Short summary
Past, present and future rainfall erosivity in central Europe based on convection-permitting climate simulations
Magdalena Uber, Michael Haller, Christoph Brendel, Gudrun Hillebrand, and Thomas Hoffmann
Hydrol. Earth Syst. Sci., 28, 87–102, https://doi.org/10.5194/hess-28-87-2024,https://doi.org/10.5194/hess-28-87-2024, 2024
Short summary
The most extreme rainfall erosivity event ever recorded in China up to 2022: the 7.20 storm in Henan Province
Yuanyuan Xiao, Shuiqing Yin, Bofu Yu, Conghui Fan, Wenting Wang, and Yun Xie
Hydrol. Earth Syst. Sci., 27, 4563–4577, https://doi.org/10.5194/hess-27-4563-2023,https://doi.org/10.5194/hess-27-4563-2023, 2023
Short summary
The role of atmospheric rivers in the distribution of heavy precipitation events over North America
Sara M. Vallejo-Bernal, Frederik Wolf, Niklas Boers, Dominik Traxl, Norbert Marwan, and Jürgen Kurths
Hydrol. Earth Syst. Sci., 27, 2645–2660, https://doi.org/10.5194/hess-27-2645-2023,https://doi.org/10.5194/hess-27-2645-2023, 2023
Short summary
Study on a mother wavelet optimization framework based on change-point detection of hydrological time series
Jiqing Li, Jing Huang, Lei Zheng, and Wei Zheng
Hydrol. Earth Syst. Sci., 27, 2325–2339, https://doi.org/10.5194/hess-27-2325-2023,https://doi.org/10.5194/hess-27-2325-2023, 2023
Short summary

Cited articles

Arlot, S. and Celisse, A.: A survey of cross-validation procedures for model selection, Statist. Surv., 4, 40–79, https://doi.org/10.1214/09-SS054, 2010.
Christensen, J. H., Boberg, F., Christensen, O. B., and Lucas-Picher, P.: On the need for bias correction of regional climate change projections of temperature and precipitation, Geophys. Res. Lett., 35, L20709, https://doi.org/10.1029/2008GL035694, 2008.
Crochemore, L., Ramos, M.-H., Pappenberger, F., van Andel, S. J., and Wood, A. W.: An Experiment on Risk-Based Decision-Making in Water Management Using Monthly Probabilistic Forecasts, B. Am. Meteorol. Soc., 97, 541–551, https://doi.org/10.1175/BAMS-D-14-00270.1, 2016.
Day, G.: Extended Streamflow Forecasting Using NWSRFS, J. Water Res. Pl.-ASCE, 111, 157–170, 1985.
Demirel, M. C., Booij, M. J., and Hoekstra, A. Y.: The skill of seasonal ensemble low-flow forecasts in the Moselle River for three different hydrological models, Hydrol. Earth Syst. Sci., 19, 275–291, https://doi.org/10.5194/hess-19-275-2015, 2015.
Download
Short summary
This study investigates the way bias correcting precipitation forecasts can improve the skill of streamflow forecasts at extended lead times. Eight variants of bias correction approaches based on the linear scaling and the distribution mapping methods are applied to the precipitation forecasts prior to generating the streamflow forecasts. One of the main results of the study is that distribution mapping of daily values is successful in improving forecast reliability.