Articles | Volume 29, issue 20
https://doi.org/10.5194/hess-29-5535-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-29-5535-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
22 Oct 2025
Research article |
| 22 Oct 2025
| 22 Oct 2025
Using century-long reanalysis and a rainfall-runoff model to explore multi-decadal variability in catchment hydrology at the European scale
Pierre Brigode
CORRESPONDING AUTHOR
Univ Rennes, CNRS, Géosciences Rennes – UMR 6118, Rennes 35000, France
Ludovic Oudin
Sorbonne Université, Université PSL, EPHE, CNRS, Milieux Environnementaux, Transferts et Interactions dans les hydrosystèmes et les Sols, METIS, Case 105, 4 place Jussieu, 75005 Paris, France
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Cited articles
Arsenault, R., Brissette, F., and Martel, J.-L.: The hazards of split-sample validation in hydrological model calibration, J. Hydrol., https://doi.org/10.1016/j.jhydrol.2018.09.027, 2018.
Baulon, L., Allier, D., Massei, N., Bessiere, H., Fournier, M., and Bault, V.: Influence of low-frequency variability on groundwater level trends, J. Hydrol., 606, 127436, https://doi.org/10.1016/j.jhydrol.2022.127436, 2022.
Beck, H. E., Wood, E. F., Pan, M., Fisher, C. K., Miralles, D. G., van Dijk, A. I. J. M., McVicar, T. R., and Adler, R. F.: MSWEP V2 global 3-hourly 0.1° precipitation: methodology and quantitative assessment, B. Am. Meteorol. Soc., https://doi.org/10.1175/BAMS-D-17-0138.1, 2018.
Blanc, A., Blanchet, J., and Creutin, J.-D.: Past evolution of western Europe large-scale circulation and link to precipitation trend in the northern French Alps, Weather Clim. Dynam., 3, 231–250, https://doi.org/10.5194/wcd-3-231-2022, 2022.
Blöschl, G., Bierkens, M. F. P., Chambel, A., et al.: Twenty-three Unsolved Problems in Hydrology (UPH) – a community perspective, Hydrolog. Sci. J., https://doi.org/10.1080/02626667.2019.1620507, 2019.
Blöschl, G., Kiss, A., Viglione, A., Barriendos, M., Böhm, O., Brázdil, R., Coeur, D., Demarée, G., Llasat, M. C., Macdonald, N., Retsö, D., Roald, L., Schmocker-Fackel, P., Amorim, I., Bělínová, M., Benito, G., Bertolin, C., Camuffo, D., Cornel, D., Doktor, R., Elleder, L., Enzi, S., Garcia, J. C., Glaser, R., Hall, J., Haslinger, K., Hofstätter, M., Komma, J., Limanówka, D., Lun, D., Panin, A., Parajka, J., Petrić, H., Rodrigo, F. S., Rohr, C., Schönbein, J., Schulte, L., Silva, L. P., Toonen, W. H. J., Valent, P., Waser, J., and Wetter, O.: Current European flood-rich period exceptional compared with past 500 years, Nature, 583, 560–566, https://doi.org/10.1038/s41586-020-2478-3, 2020.
Bonnet, R., Boé, J., Dayon, G., and Martin, E.: Twentieth-Century Hydrometeorological Reconstructions to Study the Multidecadal Variations of the Water Cycle Over France, Water Resour. Res., 53, 8366–8382, https://doi.org/10.1002/2017WR020596, 2017.
Bonnet, R., Boé, J., and Habets, F.: Influence of multidecadal variability on high and low flows: the case of the Seine basin, Hydrol. Earth Syst. Sci., 24, 1611–1631, https://doi.org/10.5194/hess-24-1611-2020, 2020.
Brigode, P., Oudin, L., and Perrin, C.: Hydrological model parameter instability: A source of additional uncertainty in estimating the hydrological impacts of climate change?, J. Hydrol., 476, 410–425, https://doi.org/10.1016/j.jhydrol.2012.11.012, 2013.
Brigode, P., Paquet, E., Bernardara, P., Gailhard, J., Garavaglia, F., Ribstein, P., Bourgin, F., Perrin, C., and Andréassian, V.: Dependence of model-based extreme flood estimation on the calibration period: case study of the Kamp River (Austria), Hydrolog. Sci. J., 60, 1424–1437, https://doi.org/10.1080/02626667.2015.1006632, 2015.
Brigode, P., Brissette, F., Nicault, A., Perreault, L., Kuentz, A., Mathevet, T., and Gailhard, J.: Streamflow variability over the 1881–2011 period in northern Québec: comparison of hydrological reconstructions based on tree rings and geopotential height field reanalysis, Clim. Past, 12, 1785–1804, https://doi.org/10.5194/cp-12-1785-2016, 2016.
Brönnimann, S., Stucki, P., Franke, J., Valler, V., Brugnara, Y., Hand, R., Slivinski, L. C., Compo, G. P., Sardeshmukh, P. D., Lang, M., and Schaefli, B.: Influence of warming and atmospheric circulation changes on multidecadal European flood variability, Clim. Past, 18, 919–933, https://doi.org/10.5194/cp-18-919-2022, 2022.
Caillouet, L., Vidal, J.-P., Sauquet, E., and Graff, B.: Probabilistic precipitation and temperature downscaling of the Twentieth Century Reanalysis over France, Clim. Past, 12, 635–662, https://doi.org/10.5194/cp-12-635-2016, 2016.
Christensen, J. H. and Christensen, O. B.: A summary of the PRUDENCE model projections of changes in European climate by the end of this century, Climatic Change, 81, 7–30, https://doi.org/10.1007/s10584-006-9210-7, 2007.
Coron, L., Thirel, G., Delaigue, O., Perrin, C., and Andréassian, V.: The suite of lumped GR hydrological models in an R package, Environ. Modell. Softw., 94, 166–171, https://doi.org/10.1016/j.envsoft.2017.05.002, 2017.
Coron, L., Delaigue, O., Thirel, G., Dorchies, D., Perrin, C., and Michel, C.: airGR: Suite of GR Hydrological Models for Precipitation-Runoff Modelling. R package version 1.7.6, Recherche Data Gouv, https://doi.org/10.15454/EX11NA, 2023.
Coxon, G., Addor, N., Bloomfield, J. P., Freer, J., Fry, M., Hannaford, J., Howden, N. J. K., Lane, R., Lewis, M., Robinson, E. L., Wagener, T., and Woods, R.: CAMELS-GB: hydrometeorological time series and landscape attributes for 671 catchments in Great Britain, Earth Syst. Sci. Data, 12, 2459–2483, https://doi.org/10.5194/essd-12-2459-2020, 2020.
Cram, T. A., Compo, G. P., Yin, X., Allan, R. J., McColl, C., Vose, R. S., Whitaker, J. S., Matsui, N., Ashcroft, L., Auchmann, R., Bessemoulin, P., Brandsma, T., Brohan, P., Brunet, M., Comeaux, J., Crouthamel, R., Gleason, B. E., Groisman, P. Y., Hersbach, H., Jones, P. D., Jónsson, T., Jourdain, S., Kelly, G., Knapp, K. R., Kruger, A., Kubota, H., Lentini, G., Lorrey, A., Lott, N., Lubker, S. J., Luterbacher, J., Marshall, G. J., Maugeri, M., Mock, C. J., Mok, H. Y., Nordli, Ø., Rodwell, M. J., Ross, T. F., Schuster, D., Srnec, L., Valente, M. A., Vizi, Z., Wang, X. L., Westcott, N., Woollen, J. S., and Worley, S. J.: The International Surface Pressure Databank version 2, Geosci. Data J., 2, 31–46, https://doi.org/10.1002/gdj3.25, 2015.
David, C. H. and Frasson, R. P. D. M.: Blame the river not the rain, Nat. Geosci., 16, 282–283, https://doi.org/10.1038/s41561-023-01163-w, 2023.
Dawdy, D. R. and Bergmann, J. M.: Effect of rainfall variability on streamflow simulation, Water Resour. Res., 5, 958–966, https://doi.org/10.1029/WR005i005p00958, 1969.
Delaigue, O., Guimarães, G. M., Brigode, P., Génot, B., Perrin, C., Soubeyroux, J.-M., Janet, B., Addor, N., and Andréassian, V.: CAMELS-FR dataset: a large-sample hydroclimatic dataset for France to explore hydrological diversity and support model benchmarking, Earth Syst. Sci. Data, 17, 1461–1479, https://doi.org/10.5194/essd-17-1461-2025, 2025.
Devers, A., Vidal, J.-P., Lauvernet, C., and Vannier, O.: FYRE Climate: a high-resolution reanalysis of daily precipitation and temperature in France from 1871 to 2012, Clim. Past, 17, 1857–1879, https://doi.org/10.5194/cp-17-1857-2021, 2021.
Devers, A., Vidal, J.-P., Lauvernet, C., Vannier, O., and Caillouet, L.: 140-year daily ensemble streamflow reconstructions over 661 catchments in France, Hydrol. Earth Syst. Sci., 28, 3457–3474, https://doi.org/10.5194/hess-28-3457-2024, 2024.
Do, H. X., Gudmundsson, L., Leonard, M., and Westra, S.: The Global Streamflow Indices and Metadata Archive (GSIM) – Part 1: The production of a daily streamflow archive and metadata, Earth Syst. Sci. Data, 10, 765–785, https://doi.org/10.5194/essd-10-765-2018, 2018.
Duethmann, D., Blöschl, G., and Parajka, J.: Why does a conceptual hydrological model fail to correctly predict discharge changes in response to climate change?, Hydrol. Earth Syst. Sci., 24, 3493–3511, https://doi.org/10.5194/hess-24-3493-2020, 2020.
Fossa, M., Dieppois, B., Massei, N., Fournier, M., Laignel, B., and Vidal, J.-P.: Spatiotemporal and cross-scale interactions in hydroclimate variability: a case-study in France, Hydrol. Earth Syst. Sci., 25, 5683–5702, https://doi.org/10.5194/hess-25-5683-2021, 2021.
Fowler, K., Peel, M., Western, A., and Zhang, L.: Improved Rainfall-Runoff Calibration for Drying Climate: Choice of Objective Function, Water Resour. Res., https://doi.org/10.1029/2017WR022466, 2018.
Fowler, K., Knoben, W., Peel, M., Peterson, T., Ryu, D., Saft, M., Seo, K.-W., and Western, A.: Many Commonly Used Rainfall-Runoff Models Lack Long, Slow Dynamics: Implications for Runoff Projections, Water Resour. Res., 56, e2019WR025286, https://doi.org/10.1029/2019WR025286, 2020.
Fowler, K., Peel, M., Saft, M., Peterson, T. J., Western, A., Band, L., Petheram, C., Dharmadi, S., Tan, K. S., Zhang, L., Lane, P., Kiem, A., Marshall, L., Griebel, A., Medlyn, B. E., Ryu, D., Bonotto, G., Wasko, C., Ukkola, A., Stephens, C., Frost, A., Gardiya Weligamage, H., Saco, P., Zheng, H., Chiew, F., Daly, E., Walker, G., Vervoort, R. W., Hughes, J., Trotter, L., Neal, B., Cartwright, I., and Nathan, R.: Explaining changes in rainfall–runoff relationships during and after Australia's Millennium Drought: a community perspective, Hydrol. Earth Syst. Sci., 26, 6073–6120, https://doi.org/10.5194/hess-26-6073-2022, 2022.
Ghosh, R., Müller, W. A., Baehr, J., and Bader, J.: Impact of observed North Atlantic multidecadal variations to European summer climate: a linear baroclinic response to surface heating, Clim. Dynam., 48, 3547–3563, https://doi.org/10.1007/s00382-016-3283-4, 2017.
Giuntoli, I., Renard, B., Vidal, J.-P., and Bard, A.: Low flows in France and their relationship to large-scale climate indices, J. Hydrol., 482, 105–118, https://doi.org/10.1016/j.jhydrol.2012.12.038, 2013.
GRDC: Data Portal, https://grdc.bafg.de/data/data_portal/, last access: 26 April 2023.
Gudmundsson, L., Do, H. X., Leonard, M., and Westra, S.: The Global Streamflow Indices and Metadata Archive (GSIM) – Part 2: Quality control, time-series indices and homogeneity assessment, Earth Syst. Sci. Data, 10, 787–804, https://doi.org/10.5194/essd-10-787-2018, 2018.
Gudmundsson, L., Leonard, M., Do, H. X., Westra, S., and Seneviratne, S. I.: Observed Trends in Global Indicators of Mean and Extreme Streamflow, Geophys. Res. Lett., 46, 756–766, https://doi.org/10.1029/2018GL079725, 2019.
Gupta, H. V., Kling, H., Yilmaz, K. K., and Martinez, G. F.: Decomposition of the mean squared error and NSE performance criteria: Implications for improving hydrological modelling, J. Hydrol., 377, 80–91, https://doi.org/10.1016/j.jhydrol.2009.08.003, 2009.
Hashemi, R., Brigode, P., Garambois, P.-A., and Javelle, P.: How can we benefit from regime information to make more effective use of long short-term memory (LSTM) runoff models?, Hydrol. Earth Syst. Sci., 26, 5793–5816, https://doi.org/10.5194/hess-26-5793-2022, 2022.
Haslinger, K., Hofstätter, M., Schöner, W., and Blöschl, G.: Changing summer precipitation variability in the Alpine region: on the role of scale dependent atmospheric drivers, Clim. Dynam., 57, 1009–1021, https://doi.org/10.1007/s00382-021-05753-5, 2021.
Hersbach, H., Bell, B., Berrisford, P., Hirahara, S., Horányi, A., Muñoz-Sabater, J., Nicolas, J., Peubey, C., Radu, R., Schepers, D., Simmons, A., Soci, C., Abdalla, S., Abellan, X., Balsamo, G., Bechtold, P., Biavati, G., Bidlot, J., Bonavita, M., Chiara, G. D., Dahlgren, P., Dee, D., Diamantakis, M., Dragani, R., Flemming, J., Forbes, R., Fuentes, M., Geer, A., Haimberger, L., Healy, S., Hogan, R. J., Hólm, E., Janisková, M., Keeley, S., Laloyaux, P., Lopez, P., Lupu, C., Radnoti, G., Rosnay, P. de, Rozum, I., Vamborg, F., Villaume, S., and Thépaut, J.-N.: The ERA5 global reanalysis, Q. J. Roy. Meteor. Soc., 146, 1999–2049, https://doi.org/10.1002/qj.3803, 2020.
Höge, M., Kauzlaric, M., Siber, R., Schönenberger, U., Horton, P., Schwanbeck, J., Floriancic, M. G., Viviroli, D., Wilhelm, S., Sikorska-Senoner, A. E., Addor, N., Brunner, M., Pool, S., Zappa, M., and Fenicia, F.: CAMELS-CH: hydro-meteorological time series and landscape attributes for 331 catchments in hydrologic Switzerland, Earth Syst. Sci. Data, 15, 5755–5784, https://doi.org/10.5194/essd-15-5755-2023, 2023.
Horton, P.: Analogue methods and ERA5: Benefits and pitfalls, Int. J. Climatol., 42, 4078–4096, https://doi.org/10.1002/joc.7484, 2022.
Klingler, C., Schulz, K., and Herrnegger, M.: LamaH-CE: LArge-SaMple DAta for Hydrology and Environmental Sciences for Central Europe, Earth Syst. Sci. Data, 13, 4529–4565, https://doi.org/10.5194/essd-13-4529-2021, 2021.
Kuentz, A., Mathevet, T., Gailhard, J., and Hingray, B.: Building long-term and high spatio-temporal resolution precipitation and air temperature reanalyses by mixing local observations and global atmospheric reanalyses: the ANATEM model, Hydrol. Earth Syst. Sci., 19, 2717–2736, https://doi.org/10.5194/hess-19-2717-2015, 2015.
Lehner, B., Liermann, C. R., Revenga, C., Vörösmarty, C., Fekete, B., Crouzet, P., Döll, P., Endejan, M., Frenken, K., Magome, J., Nilsson, C., Robertson, J. C., Rödel, R., Sindorf, N., and Wisser, D.: High-resolution mapping of the world's reservoirs and dams for sustainable river-flow management, Front. Ecol. Environ., 9, 494–502, https://doi.org/10.1890/100125, 2011.
Lemaitre-Basset, T., Oudin, L., and Thirel, G.: Evapotranspiration in hydrological models under rising CO2: a jump into the unknown, Climatic Change, 172, 36, https://doi.org/10.1007/s10584-022-03384-1, 2022a.
Lemaitre-Basset, T., Oudin, L., Thirel, G., and Collet, L.: Unraveling the contribution of potential evaporation formulation to uncertainty under climate change, Hydrol. Earth Syst. Sci., 26, 2147–2159, https://doi.org/10.5194/hess-26-2147-2022, 2022b.
Lindström, G. and Bergström, S.: Runoff trends in Sweden 1807–2002, Hydrolog. Sci. J., 49, 69–83, https://doi.org/10.1623/hysj.49.1.69.54000, 2004.
Lorenzo-Lacruz, J., Morán-Tejeda, E., Vicente-Serrano, S. M., Hannaford, J., García, C., Peña-Angulo, D., and Murphy, C.: Streamflow frequency changes across western Europe and interactions with North Atlantic atmospheric circulation patterns, Global Planet. Change, 212, 103797, https://doi.org/10.1016/j.gloplacha.2022.103797, 2022.
Martel, J.-L., Arsenault, R., Lachance-Cloutier, S., Castaneda-Gonzalez, M., Turcotte, R., and Poulin, A.: Improved historical reconstruction of daily flows and annual maxima in gauged and ungauged basins, J. Hydrol., 129777, https://doi.org/10.1016/j.jhydrol.2023.129777, 2023.
Masseroni, D., Camici, S., Cislaghi, A., Vacchiano, G., Massari, C., and Brocca, L.: The 63-year changes in annual streamflow volumes across Europe with a focus on the Mediterranean basin, Hydrol. Earth Syst. Sci., 25, 5589–5601, https://doi.org/10.5194/hess-25-5589-2021, 2021.
Montanari, A.: Hydrology of the Po River: looking for changing patterns in river discharge, Hydrol. Earth Syst. Sci., 16, 3739–3747, https://doi.org/10.5194/hess-16-3739-2012, 2012.
Müller, M. F., Roche, K. R., and Dralle, D. N.: Catchment processes can amplify the effect of increasing rainfall variability, Environ. Res. Lett., 16, 084032, https://doi.org/10.1088/1748-9326/ac153e, 2021.
Nasreen, S., Součková, M., Vargas Godoy, M. R., Singh, U., Markonis, Y., Kumar, R., Rakovec, O., and Hanel, M.: A 500-year annual runoff reconstruction for 14 selected European catchments, Earth Syst. Sci. Data, 14, 4035–4056, https://doi.org/10.5194/essd-14-4035-2022, 2022.
Oudin, L., Hervieu, F., Michel, C., Perrin, C., Andréassian, V., Anctil, F., and Loumagne, C.: Which potential evapotranspiration input for a lumped rainfall–runoff model?: Part 2-Towards a simple and efficient potential evapotranspiration model for rainfall–runoff modelling, J. Hydrol., 303, 290–306, https://doi.org/10.1016/j.jhydrol.2004.08.026, 2005.
Oudin, L., Perrin, C., Mathevet, T., Andréassian, V., and Michel, C.: Impact of biased and randomly corrupted inputs on the efficiency and the parameters of watershed models, J. Hydrol., 320, 62–83, https://doi.org/10.1016/j.jhydrol.2005.07.016, 2006.
Paprotny, D., Terefenko, P., and Śledziowski, J.: HANZE v2.1: an improved database of flood impacts in Europe from 1870 to 2020, Earth Syst. Sci. Data, 16, 5145–5170, https://doi.org/10.5194/essd-16-5145-2024, 2024.
Parodi, A., Ferraris, L., Gallus, W., Maugeri, M., Molini, L., Siccardi, F., and Boni, G.: Ensemble cloud-resolving modelling of a historic back-building mesoscale convective system over Liguria: the San Fruttuoso case of 1915, Clim. Past, 13, 455–472, https://doi.org/10.5194/cp-13-455-2017, 2017.
Perrin, C., Michel, C., and Andréassian, V.: Improvement of a parsimonious model for streamflow simulation, J. Hydrol., 279, 275–289, https://doi.org/10.1016/S0022-1694(03)00225-7, 2003.
Poli, P., Hersbach, H., Dee, D. P., Berrisford, P., Simmons, A. J., Vitart, F., Laloyaux, P., Tan, D. G. H., Peubey, C., Thépaut, J.-N., Trémolet, Y., Hólm, E. V., Bonavita, M., Isaksen, L., and Fisher, M.: ERA-20C: An Atmospheric Reanalysis of the Twentieth Century, J. Climate, 29, 4083–4097, https://doi.org/10.1175/JCLI-D-15-0556.1, 2016.
Pushpalatha, R., Perrin, C., Le Moine, N., and Andréassian, V.: A review of efficiency criteria suitable for evaluating low-flow simulations, J. Hydrol., 420–421, 171–182, https://doi.org/10.1016/j.jhydrol.2011.11.055, 2012.
R Core Team: R: A Language and Environment for Statistical Computing, R Foundation for Statistical Computing, Vienna, Austria, https://www.R-project.org/ (last access: 17 October 2025), 2024.
Renard, B., McInerney, D., Westra, S., Leonard, M., Kavetski, D., Thyer, M., and Vidal, J.-P.: Floods and Heavy Precipitation at the Global Scale: 100-Year Analysis and 180-Year Reconstruction, J. Geophys. Res.-Atmos., 128, e2022JD037908, https://doi.org/10.1029/2022JD037908, 2023.
Rust, W., Bloomfield, J. P., Cuthbert, M., Corstanje, R., and Holman, I.: The importance of non-stationary multiannual periodicities in the North Atlantic Oscillation index for forecasting water resource drought, Hydrol. Earth Syst. Sci., 26, 2449–2467, https://doi.org/10.5194/hess-26-2449-2022, 2022.
Slivinski, L. C., Compo, G. P., Whitaker, J. S., Sardeshmukh, P. D., Giese, B. S., McColl, C., Allan, R., Yin, X., Vose, R., Titchner, H., Kennedy, J., Spencer, L. J., Ashcroft, L., Brönnimann, S., Brunet, M., Camuffo, D., Cornes, R., Cram, T. A., Crouthamel, R., Domínguez-Castro, F., Freeman, J. E., Gergis, J., Hawkins, E., Jones, P. D., Jourdain, S., Kaplan, A., Kubota, H., Blancq, F. L., Lee, T.-C., Lorrey, A., Luterbacher, J., Maugeri, M., Mock, C. J., Moore, G. W. K., Przybylak, R., Pudmenzky, C., Reason, C., Slonosky, V. C., Smith, C. A., Tinz, B., Trewin, B., Valente, M. A., Wang, X. L., Wilkinson, C., Wood, K., and Wyszyński, P.: Towards a more reliable historical reanalysis: Improvements for version 3 of the Twentieth Century Reanalysis system, Quarterly Journal of the Royal Meteorological Society, 145, 2876–2908, https://doi.org/10.1002/qj.3598, 2019.
Stahl, K., Hisdal, H., Hannaford, J., Tallaksen, L. M., van Lanen, H. A. J., Sauquet, E., Demuth, S., Fendekova, M., and Jódar, J.: Streamflow trends in Europe: evidence from a dataset of near-natural catchments, Hydrol. Earth Syst. Sci., 14, 2367–2382, https://doi.org/10.5194/hess-14-2367-2010, 2010.
Tarasova, L., Lun, D., Merz, R., Blöschl, G., Basso, S., Bertola, M., Miniussi, A., Rakovec, O., Samaniego, L., Thober, S., and Kumar, R.: Shifts in flood generation processes exacerbate regional flood anomalies in Europe, Commun. Earth Environ., 4, 1–12, https://doi.org/10.1038/s43247-023-00714-8, 2023.
Tarboton, D. G.: TauDEM 5.1: Guide to using the TauDEM command line functions, https://hydrology.usu.edu/taudem/taudem5/documentation.html (last access: 17 October 2025), 2013.
Teutschbein, C., Quesada Montano, B., Todorović, A., and Grabs, T.: Streamflow droughts in Sweden: Spatiotemporal patterns emerging from six decades of observations, J. Hydrol. Reg. Stud., 42, 101171, https://doi.org/10.1016/j.ejrh.2022.101171, 2022.
Thébault, C., Perrin, C., Andréassian, V., Thirel, G., Legrand, S., and Delaigue, O.: Multi-model approach in a variable spatial framework for streamflow simulation, Hydrol. Earth Syst. Sci., 28, 1539–1566, https://doi.org/10.5194/hess-28-1539-2024, 2024.
Trotter, L., Saft, M., Peel, M. C., and Fowler, K. J. A.: Symptoms of Performance Degradation During Multi-Annual Drought: A Large-Sample, Multi-Model Study, Water Resour. Res., 59, e2021WR031845, https://doi.org/10.1029/2021WR031845, 2023.
Valéry, A., Andréassian, V., and Perrin, C.: “As simple as possible but not simpler”: what is useful in a temperature-based snow-accounting routine? Part 2 – Sensitivity analysis of the Cemaneige snow accounting routine on 380 catchments, J. Hydrol., 517, 1176–1187, https://doi.org/10.1016/j.jhydrol.2014.04.058, 2014.
Wan, Y., Chen, J., Xu, C.-Y., Xie, P., Qi, W., Li, D., and Zhang, S.: Performance dependence of multi-model combination methods on hydrological model calibration strategy and ensemble size, J. Hydrol., 603, 127065, https://doi.org/10.1016/j.jhydrol.2021.127065, 2021.
Wilcoxon, F.: Individual Comparisons by Ranking Methods, Biometrics Bulletin, 1, 80–83, https://doi.org/10.2307/3001968, 1945.
Wilhelm, B., Rapuc, W., Amann, B., Anselmetti, F. S., Arnaud, F., Blanchet, J., Brauer, A., Czymzik, M., Giguet-Covex, C., Gilli, A., Glur, L., Grosjean, M., Irmler, R., Nicolle, M., Sabatier, P., Swierczynski, T., and Wirth, S. B.: Impact of warmer climate periods on flood hazard in the European Alps, Nat. Geosci., 1–6, https://doi.org/10.1038/s41561-021-00878-y, 2022.
Woodruff, S. D., Worley, S. J., Lubker, S. J., Ji, Z., Eric Freeman, J., Berry, D. I., Brohan, P., Kent, E. C., Reynolds, R. W., Smith, S. R., and Wilkinson, C.: ICOADS Release 2.5: extensions and enhancements to the surface marine meteorological archive, Int. J. Climatol., 31, 951–967, https://doi.org/10.1002/joc.2103, 2011.
Yeste, P., García-Valdecasas Ojeda, M., Gámiz-Fortis, S. R., Castro-Díez, Y., Bronstert, A., and Esteban-Parra, M. J.: A large-sample modelling approach towards integrating streamflow and evaporation data for the Spanish catchments, Hydrol. Earth Syst. Sci., 28, 5331–5352, https://doi.org/10.5194/hess-28-5331-2024, 2024.
Short summary
We analyzed how well two global climate datasets can simulate river flows across Europe over the last 150 years. Our results show good performance overall, revealing important long-term changes in water availability and extreme events, like floods, in different regions. This research helps us better understand past and future water trends, providing insights to manage resources and address the challenges posed by climate change.
We analyzed how well two global climate datasets can simulate river flows across Europe over the...
