Articles | Volume 18, issue 2
https://doi.org/10.5194/hess-18-575-2014
https://doi.org/10.5194/hess-18-575-2014
Research article
 | 
17 Feb 2014
Research article |  | 17 Feb 2014

When does higher spatial resolution rainfall information improve streamflow simulation? An evaluation using 3620 flood events

F. Lobligeois, V. Andréassian, C. Perrin, P. Tabary, and C. Loumagne

Related authors

The influence of conceptual model structure on model performance: a comparative study for 237 French catchments
W. R. van Esse, C. Perrin, M. J. Booij, D. C. M. Augustijn, F. Fenicia, D. Kavetski, and F. Lobligeois
Hydrol. Earth Syst. Sci., 17, 4227–4239, https://doi.org/10.5194/hess-17-4227-2013,https://doi.org/10.5194/hess-17-4227-2013, 2013

Related subject area

Subject: Global hydrology | Techniques and Approaches: Modelling approaches
Technical note: Comparing three different methods for allocating river points to coarse-resolution hydrological modelling grid cells
Juliette Godet, Eric Gaume, Pierre Javelle, Pierre Nicolle, and Olivier Payrastre
Hydrol. Earth Syst. Sci., 28, 1403–1413, https://doi.org/10.5194/hess-28-1403-2024,https://doi.org/10.5194/hess-28-1403-2024, 2024
Short summary
Representing farmer irrigated crop area adaptation in a large-scale hydrological model
Jim Yoon, Nathalie Voisin, Christian Klassert, Travis Thurber, and Wenwei Xu
Hydrol. Earth Syst. Sci., 28, 899–916, https://doi.org/10.5194/hess-28-899-2024,https://doi.org/10.5194/hess-28-899-2024, 2024
Short summary
Combined impacts of climate and land-use change on future water resources in Africa
Celray James Chawanda, Albert Nkwasa, Wim Thiery, and Ann van Griensven
Hydrol. Earth Syst. Sci., 28, 117–138, https://doi.org/10.5194/hess-28-117-2024,https://doi.org/10.5194/hess-28-117-2024, 2024
Short summary
Deep learning for quality control of surface physiographic fields using satellite Earth observations
Tom Kimpson, Margarita Choulga, Matthew Chantry, Gianpaolo Balsamo, Souhail Boussetta, Peter Dueben, and Tim Palmer
Hydrol. Earth Syst. Sci., 27, 4661–4685, https://doi.org/10.5194/hess-27-4661-2023,https://doi.org/10.5194/hess-27-4661-2023, 2023
Short summary
Global dryland aridity changes indicated by atmospheric, hydrological, and vegetation observations at meteorological stations
Haiyang Shi, Geping Luo, Olaf Hellwich, Xiufeng He, Alishir Kurban, Philippe De Maeyer, and Tim Van de Voorde
Hydrol. Earth Syst. Sci., 27, 4551–4562, https://doi.org/10.5194/hess-27-4551-2023,https://doi.org/10.5194/hess-27-4551-2023, 2023
Short summary

Cited articles

Ajami, N. K., Gupta, H. V, Wagener, T., and Sorooshian, S.: Calibration of a semi-distributed hydrologic model for streamflow estimation along a river system, J. Hydrol., 298, 112–135, https://doi.org/10.1016/j.jhydrol.2004.03.033, 2004.
Andréassian, V., Perrin, C., Michel, C., Usartsanchez, I., and Lavabre, J.: Impact of imperfect rainfall knowledge on the efficiency and the parameters of watershed models, J. Hydrol., 250, 206–223, https://doi.org/10.1016/S0022-1694(01)00437-1, 2001.
Andréassian, V., Oddos, A., Michel, C., Anctil, F., Perrin, C., and Loumagne, C.: Impact of spatial aggregation of inputs and parameters on the efficiency of rainfall–runoff models: A theoretical study using chimera watersheds, Water Resour. Res., 40, 1–9, https://doi.org/10.1029/2003WR002854, 2004.
Andréassian, V., Perrin, C., Berthet, L., Le Moine, N., Lerat, J., Loumagne, C., Oudin, L., Mathevet, T., Ramos, M.-H., and Valéry, A.: HESS Opinions "Crash tests for a standardized evaluation of hydrological models", Hydrol. Earth Syst. Sci., 13, 1757–1764, https://doi.org/10.5194/hess-13-1757-2009, 2009.
Apip, Sayama, T., Tachikawa, Y., and Takara, K.: Spatial lumping of a distributed rainfall-sediment-runoff model and its effective lumping scale, Hydrol. Process., 26, 855–871, https://doi.org/10.1002/hyp.8300, 2012.
Download