Articles | Volume 373
https://doi.org/10.5194/piahs-373-87-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/piahs-373-87-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Spatial variability of the parameters of a semi-distributed hydrological model
Alban de Lavenne
CORRESPONDING AUTHOR
Irstea, Hydrosystems and Bioprocesses Research Unit (HBAN),
1, rue Pierre-Gilles de Gennes, CS 10030, 92761 Antony Cedex, France
Guillaume Thirel
Irstea, Hydrosystems and Bioprocesses Research Unit (HBAN),
1, rue Pierre-Gilles de Gennes, CS 10030, 92761 Antony Cedex, France
Vazken Andréassian
Irstea, Hydrosystems and Bioprocesses Research Unit (HBAN),
1, rue Pierre-Gilles de Gennes, CS 10030, 92761 Antony Cedex, France
Charles Perrin
Irstea, Hydrosystems and Bioprocesses Research Unit (HBAN),
1, rue Pierre-Gilles de Gennes, CS 10030, 92761 Antony Cedex, France
Maria-Helena Ramos
Irstea, Hydrosystems and Bioprocesses Research Unit (HBAN),
1, rue Pierre-Gilles de Gennes, CS 10030, 92761 Antony Cedex, France
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Cited
21 citations as recorded by crossref.
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- Extra constraint on actual evaporation in a semi-distributed conceptual model to improve model physical realism S. Hsu et al. 10.1080/02626667.2025.2468846
- Mechanical Response of Shallow Crust to Groundwater Storage Variations: Inferences From Deformation and Seismic Observations in the Eastern Southern Alps, Italy F. Pintori et al. 10.1029/2020JB020586
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- Performance assessment of methods to estimate initial hydrologic conditions for event-based rainfall-runoff modelling V. Manikanta & N. Umamahesh 10.2166/wcc.2023.043
- A Regularization Approach to Improve the Sequential Calibration of a Semidistributed Hydrological Model A. de Lavenne et al. 10.1029/2018WR024266
- Improving reservoir inflow prediction via rolling window and deep learning-based multi-model approach: case study from Ermenek Dam, Turkey H. Feizi et al. 10.1007/s00477-022-02185-3
- Performance evaluation of various hydrological models with respect to hydrological responses under climate change scenario: a review Y. Bihon et al. 10.1080/23311916.2024.2360007
- Impact on discharge modelling using different spatial and temporal resolution scenarios in South of Chile I. Fustos et al. 10.1016/j.jsames.2022.103727
- On constraining a lumped hydrological model with both piezometry and streamflow: results of a large sample evaluation A. Pelletier & V. Andréassian 10.5194/hess-26-2733-2022
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- Quels futurs possibles pour les débits des affluents français du Rhin (Moselle, Sarre, Ill) ? G. Thirel et al. 10.1051/lhb/2019039
- Calibration of hydrological models for ecologically relevant streamflow predictions: a trade-off between fitting well to data and estimating consistent parameter sets? T. Hallouin et al. 10.5194/hess-24-1031-2020
- Valuing scarce observation of rainfall variability with flexible semi-distributed hydrological modelling – Mountainous Mediterranean context J. Aouissi et al. 10.1016/j.scitotenv.2018.06.086
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Latest update: 06 Nov 2025
Short summary
Developing modelling tools that help to understand the spatial distribution of water resources is a key issue for better management. Ideally, hydrological models which discretise catchment space into sub-catchments should offer better streamflow simulations than lumped models, along with spatially-relevant water resources management solutions. However we demonstrate that those model raise other issues related to the calibration strategy and to the identifiability of the parameters.
Developing modelling tools that help to understand the spatial distribution of water resources...