Articles | Volume 24, issue 11
Hydrol. Earth Syst. Sci., 24, 5519–5538, 2020
https://doi.org/10.5194/hess-24-5519-2020

Special issue: Hydrological cycle in the Mediterranean (ACP/AMT/GMD/HESS/NHESS/OS...

Hydrol. Earth Syst. Sci., 24, 5519–5538, 2020
https://doi.org/10.5194/hess-24-5519-2020

Research article 23 Nov 2020

Research article | 23 Nov 2020

On the potential of variational calibration for a fully distributed hydrological model: application on a Mediterranean catchment

Maxime Jay-Allemand et al.

Related authors

A 50-year analysis of hydrological trends and processes in a Mediterranean catchment
Nathalie Folton, Eric Martin, Patrick Arnaud, Pierre L'Hermite, and Mathieu Tolsa
Hydrol. Earth Syst. Sci., 23, 2699–2714, https://doi.org/10.5194/hess-23-2699-2019,https://doi.org/10.5194/hess-23-2699-2019, 2019
Short summary
DamaGIS: a multisource geodatabase for collection of flood-related damage data
Clotilde Saint-Martin, Pierre Javelle, and Freddy Vinet
Earth Syst. Sci. Data, 10, 1019–1029, https://doi.org/10.5194/essd-10-1019-2018,https://doi.org/10.5194/essd-10-1019-2018, 2018
Short summary
Using damage reports to assess different versions of a hydrological early warning system
D. Defrance, P. Javelle, D. Organde, S. Ecrepont, V. Andréassian, and P. Arnaud
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hessd-11-4365-2014,https://doi.org/10.5194/hessd-11-4365-2014, 2014
Revised manuscript has not been submitted

Related subject area

Subject: Hydrometeorology | Techniques and Approaches: Modelling approaches
Evaluating a land surface model at a water-limited site: implications for land surface contributions to droughts and heatwaves
Mengyuan Mu, Martin G. De Kauwe, Anna M. Ukkola, Andy J. Pitman, Teresa E. Gimeno, Belinda E. Medlyn, Dani Or, Jinyan Yang, and David S. Ellsworth
Hydrol. Earth Syst. Sci., 25, 447–471, https://doi.org/10.5194/hess-25-447-2021,https://doi.org/10.5194/hess-25-447-2021, 2021
Short summary
A two-stage blending approach for merging multiple satellite precipitation estimates and rain gauge observations: an experiment in the northeastern Tibetan Plateau
Yingzhao Ma, Xun Sun, Haonan Chen, Yang Hong, and Yinsheng Zhang
Hydrol. Earth Syst. Sci., 25, 359–374, https://doi.org/10.5194/hess-25-359-2021,https://doi.org/10.5194/hess-25-359-2021, 2021
Short summary
Identifying robust bias adjustment methods for European extreme precipitation in a multi-model pseudo-reality setting
Torben Schmith, Peter Thejll, Peter Berg, Fredrik Boberg, Ole Bøssing Christensen, Bo Christiansen, Jens Hesselbjerg Christensen, Marianne Sloth Madsen, and Christian Steger
Hydrol. Earth Syst. Sci., 25, 273–290, https://doi.org/10.5194/hess-25-273-2021,https://doi.org/10.5194/hess-25-273-2021, 2021
Short summary
Developing a hydrological monitoring and sub-seasonal to seasonal forecasting system for South and Southeast Asian river basins
Yifan Zhou, Benjamin F. Zaitchik, Sujay V. Kumar, Kristi R. Arsenault, Mir A. Matin, Faisal M. Qamer, Ryan A. Zamora, and Kiran Shakya
Hydrol. Earth Syst. Sci., 25, 41–61, https://doi.org/10.5194/hess-25-41-2021,https://doi.org/10.5194/hess-25-41-2021, 2021
Short summary
Simulation analysis of local land atmosphere coupling in rainy season over a typical underlying surface in the Tibetan Plateau
Genhou Sun, Zeyong Hu, Yaoming Ma, Zhipeng Xie, Jiemin Wang, and Song Yang
Hydrol. Earth Syst. Sci., 24, 5937–5951, https://doi.org/10.5194/hess-24-5937-2020,https://doi.org/10.5194/hess-24-5937-2020, 2020
Short summary

Cited articles

Abbaris, A., Dakhlaoui, H., Thiria, S., and Bargaoui, Z.: Variational data assimilation with the YAO platform for hydrological forecasting, P. Int. Ass. Hydrol. Sci., 364, 3–8, https://doi.org/10.5194/piahs-364-3-2014, 2014. a
Abbaspour, K. C., Yang, J., Maximov, I., Siber, R., Bogner, K., Mieleitner, J., Zobrist, J., and Srinivasan, R.: Modelling hydrology and water quality in the pre-alpine/alpine Thur watershed using SWAT, J. Hydrol., 333, 413–430, 2007. a, b
Anderson, R. M., Koren, V. I., and Reed, S. M.: Using SSURGO data to improve Sacramento Model a priori parameter estimates, J. Hydrol., 320, 103–116, https://doi.org/10.1016/j.jhydrol.2005.07.020, 2006. a
Arnaud, P., Lavabre, J., Fouchier, C., Diss, S., and Javelle, P.: Sensitivity of hydrological models to uncertainty in rainfall input, Hydrolog. Sci. J., 56, 397–410, 2011. a
Artigue, G., Johannet, A., Borrell, V., and Pistre, S.: Flash flood forecasting in poorly gauged basins using neural networks: case study of the Gardon de Mialet basin (southern France), Nat. Hazards Earth Syst. Sci., 12, 3307–3324, https://doi.org/10.5194/nhess-12-3307-2012, 2012. a
Download
Short summary
This study contributes to flash flood prediction using a hydrological model. The model describes the spatial properties of the watersheds with hundreds of unknown parameters. The Gardon d'Anduze watershed is chosen as the study benchmark. A sophisticated numerical algorithm and the downstream discharge measurements make the identification of the model parameters possible. Results provide better model predictions and relevant spatial variability of some parameters inside this watershed.