Articles | Volume 11, issue 6
https://doi.org/10.5194/esurf-11-1199-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/esurf-11-1199-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Numerical modelling of the evolution of a river reach with a complex morphology to help define future sustainable restoration decisions
Rabab Yassine
CORRESPONDING AUTHOR
Institut de Mécanique des Fluides de Toulouse (IMFT), Université de Toulouse, CNRS, Toulouse, France
INP/ENIT, LGP, Université de Toulouse, Tarbes, France
Pays de Lourdes et des Vallées des Gaves, Lourdes, France
currently at: EGIS Business Unit, Major Structures, Water, Environment, Energy, Montpellier, France
Ludovic Cassan
Institut de Mécanique des Fluides de Toulouse (IMFT), Université de Toulouse, CNRS, Toulouse, France
Hélène Roux
Institut de Mécanique des Fluides de Toulouse (IMFT), Université de Toulouse, CNRS, Toulouse, France
Olivier Frysou
Pays de Lourdes et des Vallées des Gaves, Lourdes, France
François Pérès
INP/ENIT, LGP, Université de Toulouse, Tarbes, France
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Ngo Nghi Truyen Huynh, Pierre-André Garambois, Benjamin Renard, François Colleoni, Jérôme Monnier, and Hélène Roux
Hydrol. Earth Syst. Sci., 29, 3589–3613, https://doi.org/10.5194/hess-29-3589-2025, https://doi.org/10.5194/hess-29-3589-2025, 2025
Short summary
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Understanding and modeling flash-flood-prone areas remains challenging due to limited data and scale-relevant hydrological theory. While machine learning shows promise, its integration with process-based models is difficult. We present an approach incorporating machine learning into a high-resolution hydrological model to correct internal fluxes and transfer parameters between watersheds. Results show improved accuracy, advancing the development of learnable and interpretable process-based models.
Mohamed Saadi, Louis Guichard, Gabrielle Cognot, Laurent Labbouz, and Hélène Roux
EGUsphere, https://doi.org/10.5194/egusphere-2025-3393, https://doi.org/10.5194/egusphere-2025-3393, 2025
This preprint is open for discussion and under review for Hydrology and Earth System Sciences (HESS).
Short summary
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LSTM networks are excellent deep-learning tools to reproduce stream temperature observations, but their performances over the range of extreme (summer) stream temperature values have been overlooked. We close this gap by looking at strategies to improve the LSTM performances over the highest 10 % values of stream temperature observations. We found that the best strategy is to train the LSTM models at several locations with input variables that include static catchment and reach attributes.
Abubakar Haruna, Pierre-Andre Garambois, Helene Roux, Pierre Javelle, and Maxime Jay-Allemand
Hydrol. Earth Syst. Sci. Discuss., https://doi.org/10.5194/hess-2021-414, https://doi.org/10.5194/hess-2021-414, 2021
Manuscript not accepted for further review
Short summary
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We compared three hydrological models in a flash flood modelling framework. We first identified the sensitive parameters of each model, then compared their performances in terms of outlet discharge and soil moisture simulation. We found out that resulting from the differences in their complexities/process representation, performance depends on the aspect/measure used. The study then highlights and proposed some future investigations/modifications to improve the models.
Judith Eeckman, Hélène Roux, Audrey Douinot, Bertrand Bonan, and Clément Albergel
Hydrol. Earth Syst. Sci., 25, 1425–1446, https://doi.org/10.5194/hess-25-1425-2021, https://doi.org/10.5194/hess-25-1425-2021, 2021
Short summary
Short summary
The risk of flash flood is of growing importance for populations, particularly in the Mediterranean area in the context of a changing climate. The representation of soil processes in models is a key factor for flash flood simulation. The importance of the various methods for soil moisture estimation are highlighted in this work. Local measurements from the field as well as data derived from satellite imagery can be used to assess the performance of model outputs.
Cited articles
Aguirre, D., Bui, M., Giehl, S., Reisenbüchler, M., and Rutschmann, P.: Development of a hydro-morphodynamic Model for Sediment Management in the Rosenheim Reservoir, in: Proceedings of the Telemac User Conference 2019 (TUC2019), Zenodo, https://doi.org/10.5281/zenodo.3611498, 2020. a, b
Arnaud, F.: Approches géomorphologiques historique et expérimentale pour la restauration de la dynamique sédimentaire d'un tronçonfluvial aménagé: le cas du Vieux Rhin entre Kembs et Breisach (France, Allemagne), PhD thesis, Université Lumière Lyon 2, https://doi.org/10.58165/evs-2z6x55, 2012. a
Arnaud-Fassetta, G., Astrade, L., Bardou, E., Corbonnois, J., Delahaye, D., Fort, M., Gautier, E., Jacob, N., Peiry, J.-L., Piégay, H., and Penven, M.-J.: Fluvial geomorphology and flood-risk management, Géomorphologie, 15, 109–128, https://doi.org/10.4000/geomorphologie.7554 2009. a
Badoux, A., Andres, N., and Turowski, J. M.: Damage costs due to bedload transport processes in Switzerland, Nat. Hazards Earth Syst. Sci., 14, 279–294, https://doi.org/10.5194/nhess-14-279-2014, 2014. a, b
Blanpied, J.: La torrentialité dans les Pyrénées centrales: évolution depuis la fin du Petit Âge Glaciaire, spécificités et dynamiques géomorphologiques actuelles, PhD thesis, Université de Toulouse – Jean Jaurès, 2019. a
Carr, K. J., Tu, T., Ercan, A., Kavvas, M. L., and Nosacka, J.: Two-Dimensional Unsteady Flow Modeling of Flood Inundation in a Leveed Basin, in: World Environmental and Water Resources Congress 2015, 1597–1606, https://doi.org/10.1061/9780784479162.156, 2015. a
Chapuis, M.: Mobilité des sédiments fluviaux grossiers dans les systèmes fortement anthropisés: éléments pous la gestion de la basse vallée de la Durance, PhD thesis, Université Aix Marseille, 2012. a
Cordier, F., Tassi, P., Claude, N., Crosato, A., Rodrigues, S., and Pham Van Bang, D.: Numerical Study of Alternate Bars in Alluvial Channels With Nonuniform Sediment, Water Resour. Res., 55, 2976–3003, https://doi.org/10.1029/2017WR022420, 2019. a
de Saint-Venant, M.: Théorie du mouvement non permanent des eaux, avec application aux crues des rivières et à l'introduction des marées dan leur lit, Paris, frei, https://www.sudoc.abes.fr/cbs/xslt/DB=2.1//SRCH?IKT=12&TRM=14531846X (last access: 17 November 2023), 1871. a
Douinot, A., Roux, H., Garambois, P.-A., and Dartus, D.: Using a multi-hypothesis framework to improve the understanding of flow dynamics during flash floods, Hydrol. Earth Syst. Sci., 22, 5317–5340, https://doi.org/10.5194/hess-22-5317-2018, 2018. a
DREAL Midi-Pyrénées: Crues des Pyrénées des 18 et 19 Juin 2013. Retour d'expérience global, Tech. rep., DREAL, 2013. a
Einstein, H. A.: The bed-load function for sediment transportation in open channel flows, 1026, US Government Printing Office, https://doi.org/10.22004/ag.econ.156389, 1950. a
Exner, F. M.: Zur Physik der Düunen, 1920. a
Gonzales De Linares, M., Mano, V., Piton, G., and Recking, A.: Modelling of massive bedload deposition in a debris basin: cross comparison between numerical and small scale modelling, in: RiverFlow 2020, Proceedings of the 10th Conference on Fluvial Hydraulics, Delft, the Netherlands, https://hal.archives-ouvertes.fr/hal-02935173 (last access: 17 November 2023), 2020. a
Gonzales de Linares, M., Ronzani, F., Recking, A., Mano, V., and Piton, G.: Coupling Surface Grain-Size and Friction for Realistic 2D Modelling of Channel Dynamics on Massive Bedload Deposition, in: Conference: SimHydro 2021: Models for complex and global water issues – Practices and expectations, vol. 30 of Actes de la conférence SimHydro 2021, Sophia-Antipolis, France, 1–10, https://hal.archives-ouvertes.fr/hal-03363327 last access: 17 November 2023), 2021. a
Guan, M., Wright, N. G., and Andrew Sleigh, P.: Multiple effects of sediment transport and geomorphic processes within flood events: Modelling and understanding, Int. J. Sediment Res., 30, 371–381, https://doi.org/10.1016/j.ijsrc.2014.12.001, 2015. a, b
Guan, M., Carrivick, J. L., Wright, N. G., Sleigh, P. A., and Staines, K. E.: Quantifying the combined effects of multiple extreme floods on river channel geometry and on flood hazards, J. Hydrol., 538, 256–268, https://doi.org/10.1016/j.jhydrol.2016.04.004, 2016. a
Ham, D. and Church, M.: Morphodynamics of an extended bar complex, Fraser River, British Columbia, Earth Surf. Proc. Land., 37, 1074–1089, https://doi.org/10.1002/esp.3231, 2012. a
IDEALP: Etude d'hydraulique torrentielle et morphodynamique du Bastan, Tech. rep., IDEALP, 2014. a
Kang, J. and Yeo, H.: Survey and analysis of the sediment transport for river restoration: The case of the Magyeong river, Open J. Civ. Eng., 5, 399–411, https://doi.org/10.4236/ojce.2015.54040, 2015. a
Koch, F. and Flokstra, C.: Bed level computations for curved alluvial channels, in: XIXth Congress of the International Association for Hydraulics Research, New Delhi, India, 1981. a
Lefort, P.: Une formule semi-empirique pour le transport solide des rivières et des torrents, in: Colloque SHF – Transport solide et gestion des sédiments en milieux naturels et urbains, 2007. a
Lepesqueur, J., Hostache, R., Martínez-Carreras, N., Montargès-Pelletier, E., and Hissler, C.: Sediment transport modelling in riverine environments: on the importance of grain-size distribution, sediment density, and suspended sediment concentrations at the upstream boundary, Hydrol. Earth Syst. Sci., 23, 3901–3915, https://doi.org/10.5194/hess-23-3901-2019, 2019. a
Liébault, F., Peteuil, C., Jousse, C., Fragnol, B., Theule, J., Berger, F., Saez, J. L., Gotteland, A., Jaboyedoff, M., and Loye, A.: L'utilisation des plages de dépôts pour la mesure du transport solide torrentiel: applications dans le département de l'Isère, Tech. rep., Conseil général de l'Isère, https://irsteadoc.irstea.fr/cemoa/PUB00032641 (last access: 17 November 2023), 2010. a
Malavoi, J., Garnier, C. C., Landon, N., Recking, A., and Baran, P.: Eléments de connaissance pour la gestion du transport solide en rivière, ONEMA, 2011. a
Misset, C., Recking, A., Legout, C., Bakker, M., Bodereau, N., Borgniet, L., Cassel, M., Geay, T., Gimbert, F., Navratil, O., Piegay, H., Valsangkar, N., Cazilhac, M., Poirel, A., and Zanker, S.: Combining multi-physical measurements to quantify bedload transport and morphodynamics interactions in an Alpine braiding river reach, Geomorphology, 351, 106877, https://doi.org/10.1016/j.geomorph.2019.106877, 2020. a
open TELEMAC-MASCARET: Downloading the TELEMAC system, https://www.opentelemac.org/index.php/download (last access: 17 November 2023), 2023. a
Orseau, S., Huybrechts, N., Tassi, P., Pham Van Bang, D., and Klein, F.: Two-dimensional modeling of fine sediment transport with mixed sediment and consolidation: Application to the Gironde Estuary, France, Int. J. Sediment Res., 36, 736–746, https://doi.org/10.1016/j.ijsrc.2019.12.005, 2021. a
Ramirez, J. A., Zischg, A. P., Schürmann, S., Zimmermann, M., Weingartner, R., Coulthard, T., and Keiler, M.: Modeling the geomorphic response to early river engineering works using CAESAR-Lisflood, Anthropocene, 32, 100266, https://doi.org/10.1016/j.ancene.2020.100266, 2020. a
Recking, A.: A comparison between flume and field bed load transport data and consequences for surface-based bed load transport prediction, Water Resour. Res., 46, W03518, https://doi.org/10.1029/2009WR008007, 2010. a
Recking, A.: An analysis of nonlinearity effects on bedload transport prediction, J.Geophys. Res., 118, 1264–1281, https://doi.org/10.1002/jgrf.20090, 2013b. a, b
Recking, A., Leduc, P., Liébault, F., and Church, M.: A field investigation of the influence of sediment supply on step-pool morphology and stability, Geomorphology, 139–140, 53–66, https://doi.org/10.1016/j.geomorph.2011.09.024, 2012. a, b
Recking, A., Piton, G., Vazquez-Tarrio, D., and Parker, G.: Quantifying the Morphological Print of Bedload Transport, Earth Surf. Proc. Land., 41, 809–822, https://doi.org/10.1002/esp.3869, 2016. a, b, c, d
Reid, S. C., Lane, S. N., Berney, J. M., and Holden, J.: The timing and magnitude of coarse sediment transport events within an upland, temperate gravel-bed river, Geomorphology, 83, 152–182, https://doi.org/10.1016/j.geomorph.2006.06.030, 2007. a, b
Reisenbüchler, M., Bui, M. D., Skublics, D., and Rutschmann, P.: Enhancement of a numerical model system for reliably predicting morphological development in the Saalach River, Int. J. River Basin Manage., 18, 335–347, https://doi.org/10.1080/15715124.2019.1628034, 2019a. a, b
Reisenbüchler, M., Bui, M. D., Skublics, D., and Rutschmann, P.: An integrated approach for investigating the correlation between floods and river morphology: A case study of the Saalach River, Germany, Sci. Total Environ., 647, 814–826, https://doi.org/10.1016/j.scitotenv.2018.08.018, 2019b. a
Reisenbüchler, M., Bui, M. D., Skublics, D., and Rutschmann, P.: Enhancement of a numerical model system for reliably predicting morphological development in the Saalach River, Int. J. River Basin Manage., 18, 335–347, https://doi.org/10.1080/15715124.2019.1628034, 2020. a
Rickenmann, D. and Recking, A.: Evaluation of flow resistance in gravel-bed rivers through a large filed data set, Water Resour. Res., 47, W07538, https://doi.org/10.1029/2010WR009793, 2011. a, b, c
Rickenmann, D., Badoux, A., and Hunzinger, L.: Significance of sediment transport processes during piedmont floods: the 2005 flood events in Switzerland, Earth Surf. Proc. Land., 41, 224–230, https://doi.org/10.1002/esp.3835, 2016. a, b
Riesterer, J., Wenka, T., Brudy-Zippelius, T., and Nestmann, F.: Bed load transport modeling of a secondary flow influenced curved channel with 2D and 3D numerical models, J. Appl. Water Eng. Res., 4, 54–66, https://doi.org/10.1080/23249676.2016.1163649, 2016. a
Rifai, I., Le Bouteiller, C., and Recking, A.: Numerical study of braiding channels formation, in: Telemac Mascaret User Club Conference, Grenoble, France, 159–167, https://hal.inrae.fr/hal-02606139 (last access: 17 November 2023), 2014. a
Rinaldi, M. and Darby, S. E.: 9 Modelling river-bank-erosion processes and mass failure mechanisms: progress towards fully coupled simulations, in: Gravel-Bed Rivers VI: From Process Understanding to River Restoration, vol. 11 of Developments in Earth Surface Processes, edited by: Habersack, H., Piégay, H., and Rinaldi, M., Elsevier, 213–239, https://doi.org/10.1016/S0928-2025(07)11126-3, 2007. a, b
Roux, H., Labat, D., Garambois, P.-A., Maubourguet, M.-M., Chorda, J., and Dartus, D.: A physically-based parsimonious hydrological model for flash floods in Mediterranean catchments, Nat. Hazards Earth Syst. Sci., 11, 2567–2582, https://doi.org/10.5194/nhess-11-2567-2011, 2011. a
Roux, H., Amengual, A., Romero, R., Bladé, E., and Sanz-Ramos, M.: Evaluation of two hydrometeorological ensemble strategies for flash-flood forecasting over a catchment of the eastern Pyrenees, Nat. Hazards Earth Syst. Sci., 20, 425–450, https://doi.org/10.5194/nhess-20-425-2020, 2020. a
Soulsby, R.: Dynamics of Marine Sands: A Manual for Practical Applications, Thomas Telford, London, http://site.ebrary.com/id/10868638 (last access: 17 November 2023), 1997. a
Strickler, A.: Beiträge zur Frage der Geschwindigkeitsformel und der Rauhigkeitszahlen für Ströme, Kanäle und geschlossene Leitungen: mit … Tab., Im Selbstverlag, 1923. a
SUEZ Consulting: Étude hydraulique et AMC pour évaluer l'intérêt de considérer la Voie Verte des Gaves comme un ouvrage de protection contre les crues. Phase 2: Diagnostic – étude hydrologique, Tech. rep., PLVG, 2019. a
Sutherland, J., Peet, A., and Soulsby, R.: Evaluating the performance of morphological models, Coast. Eng., 51, 917–939, https://doi.org/10.1016/j.coastaleng.2004.07.015, 2004. a
Tal, M. and Paola, C.: Effects of vegetation on channel morphodynamics: results and insights from laboratory experiments, Earth Surf. Proc. Land., 35, 1014–1028. https://doi.org/10.1002/esp.1908, 2010. a
Tu, T., Carr, K. J., Ercan, A., Trinh, T., Kavvas, M. L., and Nosacka, J.: Assessment of the effects of multiple extreme floods on flow and transport processes under competing flood protection and environmental management strategies, Sci. Total Environ., 607–608, 613–622, https://doi.org/10.1016/j.scitotenv.2017.06.271, 2017. a
van Rijn, L. C.: Sediment Transport, Part I: Bed Load Transport, J. Hydraul. Eng., 110, 1431–1456, https://doi.org/10.1061/(asce)0733-9429(1984)110:10(1431), 1984a. a
van Rijn, L. C.: Sediment Transport, Part II: Suspended Load Transport, J. Hydraul. Eng., 110, 1613–1641, https://doi.org/10.1061/(ASCE)0733-9429(1984)110:11(1613), 1984b. a
Wilcock, P. R. and Crowe, J. C.: Surface-based transport model for mixed-size sediment, J. Hydraul. Eng., 129, 120–128, 2003. a
Williams, R. D., Brasington, J., Hicks, M., Measures, R., Rennie, C. D., and Vericat, D.: Hydraulic validation of two-dimensional simulations of braided river flow with spatially continuous aDcp data, Water Resour. Res., 49, 5183–5205, https://doi.org/10.1002/wrcr.20391, 2013. a
Williams, R. D., Brasington, J., and Hicks, D. M.: Numerical Modelling of Braided River Morphodynamics: Review and Future Challenges, Geogr. Compass, 10, 102–127, https://doi.org/10.1111/gec3.12260, 2016a. a, b, c
Williams, R. D., Measures, R., Hicks, D. M., and Brasington, J.: Assessment of a numerical model to reproduce event-scale erosion and deposition distributions in a braided river, Water Resour. Res., 52, 6621–6642, https://doi.org/10.1002/2015WR018491, 2016b. a
Wohl, E., Bledsoe, B. P., Jacobson, R. B., Poff, N. L., Rathburn, S. L., Walters, D. M., and Wilcox, A. C.: The Natural Sediment Regime in Rivers: Broadening the Foundation for Ecosystem Management, BioScience, 65, 358–371, https://doi.org/10.1093/biosci/biv002, 2015. a
Wolman, M. G.: A method of sampling coarse river-bed material, Eos Trans. AGU, 35, 951–956, https://doi.org/10.1029/TR035i006p00951, 1954. a
Short summary
Predicting river morphology evolution is very complicated, especially for mountain rivers with complex morphologies such as the Lac des Gaves reach in France. A 2D hydromorphological model was developed to reproduce the channel's evolution and provide reliable volumetric predictions while revealing the challenge of choosing adapted sediment transport and friction laws. Our model can provide decision-makers with reliable predictions to design suitable restoration measures for this reach.
Predicting river morphology evolution is very complicated, especially for mountain rivers with...