{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,11,7]],"date-time":"2026-11-07T20:30:07Z","timestamp":1794083407107,"version":"4.8.0"},"reference-count":64,"publisher":"Copernicus GmbH","issue":"5","license":[{"start":{"date-parts":[[2020,5,14]],"date-time":"2020-05-14T00:00:00Z","timestamp":1589414400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Hydrol. Earth Syst. Sci."],"abstract":"<jats:p>The European Centre for Medium-Range Weather Forecasts\n(ECMWF) recently released its most advanced reanalysis product, the ERA5\ndataset. It was designed and generated with methods giving it multiple\nadvantages over the previous release, the ERA-Interim reanalysis product.\nNotably, it has a finer spatial resolution, is archived at the hourly time\nstep, uses a more advanced assimilation system and includes more sources of\ndata. This paper aims to evaluate the ERA5 reanalysis as a potential\nreference dataset for hydrological modelling by considering the ERA5\nprecipitation and temperatures as proxies for observations in the\nhydrological modelling process, using two lumped hydrological models over\n3138 North American catchments. This study shows that ERA5-based\nhydrological modelling performance is equivalent to using observations over\nmost of North America, with the exception of the eastern half of the US,\nwhere observations lead to consistently better performance. ERA5 temperature\nand precipitation biases are consistently reduced compared to ERA-Interim\nand systematically more accurate for hydrological modelling. Differences\nbetween ERA5, ERA-Interim and observation datasets are mostly linked to\nprecipitation, as temperature only marginally influences the hydrological\nsimulation outcomes.<\/jats:p>","DOI":"10.5194\/hess-24-2527-2020","type":"journal-article","created":{"date-parts":[[2020,5,14]],"date-time":"2020-05-14T08:32:15Z","timestamp":1589445135000},"page":"2527-2544","source":"Crossref","is-referenced-by-count":600,"title":["Evaluation of the ERA5 reanalysis as a potential reference dataset for hydrological modelling over North America"],"prefix":"10.5194","volume":"24","author":[{"given":"Mostafa","family":"Tarek","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"},{"role":"corresponding-author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9754-3014","authenticated-orcid":false,"given":"Fran\u00e7ois P.","family":"Brissette","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2834-2750","authenticated-orcid":false,"given":"Richard","family":"Arsenault","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"3145","published-online":{"date-parts":[[2020,5,14]]},"reference":[{"key":"ref1","doi-asserted-by":"publisher","unstructured":"Albergel, C., Dutra, E., Munier, S., Calvet, J.-C., Munoz-Sabater, J., de Rosnay, P., and Balsamo, G.: ERA-5 and ERA-Interim driven ISBA land surface model simulations: which one performs better?, Hydrol. Earth Syst. Sci., 22, 3515\u20133532, 10.5194\/hess-22-3515-2018, 2018.","DOI":"10.5194\/hess-22-3515-2018"},{"key":"ref2","doi-asserted-by":"crossref","unstructured":"Arsenault, R., Poulin, A., C\u00f4t\u00e9, P., and Brissette, F.: Comparison of stochastic optimization algorithms in hydrological model calibration,\u00a0J. Hydrol. Eng.,\u00a019, 1374\u20131384, 2013.","DOI":"10.1061\/(ASCE)HE.1943-5584.0000938"},{"key":"ref3","doi-asserted-by":"publisher","unstructured":"Arsenault, R., Gatien, P., Renaud, B., Brissette, F., and Martel, J. L.: A comparative analysis of 9 multi-model averaging approaches in hydrological continuous streamflow simulation, J. Hydrol., 529, 754\u2013767, 10.1016\/j.jhydrol.2015.09.001, 2015.","DOI":"10.1016\/j.jhydrol.2015.09.001"},{"key":"ref4","doi-asserted-by":"publisher","unstructured":"Arsenault, R., Bazile, R., Ouellet Dallaire, C., and Brissette, F.: CANOPEX: A Canadian hydrometeorological watershed database,\u00a0Hydrol. 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Soc., 100, 473\u2013500, 2019b.","DOI":"10.1175\/BAMS-D-17-0138.1"},{"key":"ref10","doi-asserted-by":"publisher","unstructured":"Bengtsson, L., Hagemann, S., and Hodges, K. I.: Can climate trends be calculated from reanalysis data?, J. Geophys. Res.-Atmos.,\u00a0109, D11111, 10.1029\/2004JD004536, 2004.","DOI":"10.1029\/2004JD004536"},{"key":"ref11","doi-asserted-by":"crossref","unstructured":"Burn, D. H., Hannaford, J., Hodgkins, G. A., Whitfield, P. H., Thorne, R., and Marsh, T.: Reference hydrologic networks II. Using reference hydrologic networks to assess climate-driven changes in streamflow, Hydrol. Sci. J., 57, 1580\u20131593, 2012.","DOI":"10.1080\/02626667.2012.728705"},{"key":"ref12","doi-asserted-by":"crossref","unstructured":"Chaudhuri, A. H., Ponte, R. M., Forget, G., and Heimbach, P.: A comparison of atmospheric reanalysis surface products over the ocean and implications for uncertainties in air\u2013sea boundary forcing, J. Climate, 26, 153\u2013170, 2013.","DOI":"10.1175\/JCLI-D-12-00090.1"},{"key":"ref13","doi-asserted-by":"crossref","unstructured":"Chen, J., Brissette, F. P., and Chen, H.: Using reanalysis-driven regional climate model outputs for hydrology modelling, Hydrol. Process., 32, 3019\u20133031, 2018.","DOI":"10.1002\/hyp.13251"},{"key":"ref14","doi-asserted-by":"crossref","unstructured":"Citterio, M., van As, D., Ahlstr\u00f8m, A. P., Andersen, M. L., Andersen, S. B., Box, J. E., Charalampidis, C., Colgan, W. T., Fausto, R. S., Nielsen, S., and Veicherts, M.: Automatic weather stations for basic and applied glaciological research, Geological Survey of Denmark and Greenland Bulletin, 33, 69\u201372, 2015.","DOI":"10.34194\/geusb.v33.4512"},{"key":"ref15","doi-asserted-by":"publisher","unstructured":"Dee, D. P., Uppala, S. M., Simmons, A. J., Berrisford, P., Poli, P., Kobayashi, S., Andrae, U., Balmaseda, M. A., Balsamo, G., Bauer, D. P., and Bechtold, P.: The ERA-Interim reanalysis: Configuration and performance of the data assimilation system,\u00a0Q. J. Roy. Meteorol. Soc.,\u00a0137, 553\u2013597, 10.1002\/qj.828, 2011 (data available at: https:\/\/apps.ecmwf.int\/datasets\/data\/interim-full-daily\/, last access: August 2019).","DOI":"10.1002\/qj.828"},{"key":"ref16","doi-asserted-by":"publisher","unstructured":"Di Baldassarre, G. and Montanari, A.: Uncertainty in river discharge observations: a quantitative analysis, Hydrol. Earth Syst. Sci., 13, 913\u2013921, 10.5194\/hess-13-913-2009, 2009.","DOI":"10.5194\/hess-13-913-2009"},{"key":"ref17","doi-asserted-by":"crossref","unstructured":"Di Giuseppe, F., Pappenberger, F., Wetterhall, F., Krzeminski, B., Camia, A., Libert\u00e1, G., and San Miguel, J.: The potential predictability of fire danger provided by numerical weather prediction, J. Appl. Meteorol. Climatol., 55, 2469\u20132491, 2016.","DOI":"10.1175\/JAMC-D-15-0297.1"},{"key":"ref18","doi-asserted-by":"publisher","unstructured":"Emerton, R., Cloke, H. L., Stephens, E. M., Zsoter, E., Woolnough, S. J., and Pappenberger, F.: Complex picture for likelihood of ENSO-driven flood hazard, Nature Commun., 8, 14796, 10.1038\/ncomms14796, 2017.","DOI":"10.1038\/ncomms14796"},{"key":"ref19","doi-asserted-by":"crossref","unstructured":"Essou, G. R., Arsenault, R., and Brissette, F. P.: Comparison of climate datasets for lumped hydrological modeling over the continental United States, J. Hydrol., 537, 334\u2013345, 2016a.","DOI":"10.1016\/j.jhydrol.2016.03.063"},{"key":"ref20","doi-asserted-by":"crossref","unstructured":"Essou, G. R., Sabarly, F., Lucas-Picher, P., Brissette, F., and Poulin, A.: Can precipitation and temperature from meteorological reanalyses be used for hydrological modeling?, J. Hydrometeorol., 17, 1929\u20131950, 2016b.","DOI":"10.1175\/JHM-D-15-0138.1"},{"key":"ref21","doi-asserted-by":"crossref","unstructured":"Essou, G. R., Brissette, F., and Lucas-Picher, P.: The use of reanalyses and gridded observations as weather input data for a hydrological model: Comparison of performances of simulated river flows based on the density of weather stations, J. Hydrometeorol., 18, 497\u2013513, 2017.","DOI":"10.1175\/JHM-D-16-0088.1"},{"key":"ref22","doi-asserted-by":"crossref","unstructured":"Fortin, V., Roy, G., Donaldson, N., and Mahidjiba, A.: Assimilation of radar quantitative precipitation estimations in the Canadian Precipitation Analysis (CaPA), J. Hydrol., 531, 296\u2013307, 2015.","DOI":"10.1016\/j.jhydrol.2015.08.003"},{"key":"ref23","unstructured":"GISS: https:\/\/data.giss.nasa.gov\/gistemp\/stdata\/ (last access: June 2019), 2019.","type":"web-resource"},{"key":"ref24","doi-asserted-by":"crossref","unstructured":"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\u201391, 2009.","DOI":"10.1016\/j.jhydrol.2009.08.003"},{"key":"ref25","doi-asserted-by":"crossref","unstructured":"Hansen, N., M\u00fcller, S. D., and Koumoutsakos, P.: Reducing the time complexity of the derandomized evolution strategy with covariance matrix adaptation (CMA-ES), Evolutionary Computation, 11, 1\u201318, 2003.","DOI":"10.1162\/106365603321828970"},{"key":"ref26","unstructured":"Hersbach, H. and Dee, D.: ERA5 reanalysis is in production, ECMWF Newsletter 147, ECMWF, Reading, UK, available at: https:\/\/www.ecmwf.int\/en\/newsletter\/147\/news\/era5-reanalysis-production (last access: May 2020), 2016 (data available at: https:\/\/cds.climate.copernicus.eu\/cdsapp#!\/dataset\/reanalysis-era5-single-levels?tab=form, last access: May 2020).","type":"web-resource"},{"key":"ref27","doi-asserted-by":"publisher","unstructured":"Hoffmann, L., G\u00fcnther, G., Li, D., Stein, O., Wu, X., Griessbach, S., Heng, Y., Konopka, P., M\u00fcller, R., Vogel, B., and Wright, J. S.: From ERA-Interim to ERA5: the considerable impact of ECMWF's next-generation reanalysis on Lagrangian transport simulations, Atmos. Chem. Phys., 19, 3097\u20133124, 10.5194\/acp-19-3097-2019, 2019.","DOI":"10.5194\/acp-19-3097-2019"},{"key":"ref28","unstructured":"Huet, M.: Comparaison de m\u00e9thodes d'estimation de la recharge des aquif\u00e8res: exemple de la r\u00e9gion Charlevoix-Haute-C\u00f4te-Nord (Doctoral dissertation, Universit\u00e9 du Qu\u00e9bec \u00e0 Chicoutimi), 2015."},{"key":"ref29","doi-asserted-by":"crossref","unstructured":"Hutchinson, M. F., McKenney, D. W., Lawrence, K., Pedlar, J. H., Hopkinson, R. F., Milewska, E., and Papadopol, P.: Development and testing of Canada-wide interpolated spatial models of daily minimum\u2013maximum temperature and precipitation for 1961\u20132003,\u00a0J. Appl. Meteorol. Climatol.,\u00a048, 725\u2013741, 2009.","DOI":"10.1175\/2008JAMC1979.1"},{"key":"ref30","unstructured":"Janis, M. J., Hubbard, K. G., and Redmond, K. T.: Determining the Optimal Number of Stations for the United States Climate Reference Network, Final Report, Southeast Regional Climate Center Research Paper Series April 2002, 21 pp., 2002."},{"key":"ref31","doi-asserted-by":"crossref","unstructured":"Kling, H., Fuchs, M., and Paulin, M.: Runoff conditions in the upper Danube basin under an ensemble of climate change scenarios, J. Hydrol., 424, 264\u2013277, 2012.","DOI":"10.1016\/j.jhydrol.2012.01.011"},{"key":"ref32","doi-asserted-by":"crossref","unstructured":"Lespinas, F., Fortin, V., Roy, G., Rasmussen, P., and Stadnyk, T.: Performance evaluation of the Canadian precipitation analysis (CaPA), J. Hydrometeorol., 16, 2045\u20132064, 2015.","DOI":"10.1175\/JHM-D-14-0191.1"},{"key":"ref33","doi-asserted-by":"crossref","unstructured":"Lettenmaier, D. P., Alsdorf, D., Dozier, J., Huffman, G. J., Pan, M., and Wood, E. F.: Inroads of remote sensing into hydrologic science during the WRR era, Water Resour. Res., 51, 7309\u20137342, 2015.","DOI":"10.1002\/2015WR017616"},{"key":"ref34","doi-asserted-by":"crossref","unstructured":"Lindsay, R., Wensnahan, M., Schweiger, A., and Zhang, J.: Evaluation of seven different atmospheric reanalysis products in the Arctic, J. Climate, 27, 2588\u20132606, 2014.","DOI":"10.1175\/JCLI-D-13-00014.1"},{"key":"ref35","unstructured":"Lins, H. F.: Challenges to hydrological observations, Bulletin of the World Meterological Organization, v.57(1), 55\u201358, 2008."},{"key":"ref36","doi-asserted-by":"crossref","unstructured":"Luo, C., Wang, Z., Sauer, T. J., Helmers, M. J., Horton, R.: Portable canopy chamber measurements of evapotranspiration in corn, soybean, and reconstructed prairie, Agr. Water Manag., 198, 1\u20139, 2018.","DOI":"10.1016\/j.agwat.2017.11.024"},{"key":"ref37","unstructured":"Martel, J. L., Demeester, K., Brissette, F., Poulin, A., and Arsenault, R.: HMETS-A simple and efficient hydrology model for teaching hydrological modelling, flow forecasting and climate change impacts,\u00a0Int. J. Eng. Educat.,\u00a033, 1307\u20131316, https:\/\/dialnet.unirioja.es\/servlet\/articulo?codigo=6897050, 2017 (data available at: https:\/\/www.mathworks.com\/matlabcentral\/fileexchange\/48069-hmets-hydrological-model, last access: October 2016).","type":"web-resource"},{"key":"ref38","doi-asserted-by":"publisher","unstructured":"Maurer, E. P., Wood, A. W., Adam, J. C., Lettenmaier, D. P., and Nijssen, B.: A long-term hydrologically based dataset of land surface fluxes and states for the conterminous United States,\u00a0J. Climate,\u00a015, 3237\u20133251, 10.1175\/1520-0442(2002)0152.0.CO;2, 2002 (data available at: http:\/\/hydro.engr.scu.edu\/files\/gridded_obs\/daily\/ncfiles_2010, last access: December 2010).","DOI":"10.1175\/1520-0442(2002)0152.0.CO;2"},{"key":"ref39","doi-asserted-by":"publisher","unstructured":"McCabe, M. F., Rodell, M., Alsdorf, D. E., Miralles, D. G., Uijlenhoet, R., Wagner, W., Lucieer, A., Houborg, R., Verhoest, N. E. C., Franz, T. E., Shi, J., Gao, H., and Wood, E. F.: The future of Earth observation in hydrology, Hydrol. Earth Syst. Sci., 21, 3879\u20133914, 10.5194\/hess-21-3879-2017, 2017.","DOI":"10.5194\/hess-21-3879-2017"},{"key":"ref40","doi-asserted-by":"crossref","unstructured":"Menne, M. J., Williams, C. N., Gleason, B. E., Rennie, J. J., and Lawrimore, J. H.: The Global Historical Climatology Network Monthly Temperature Dataset, Version 4,\u00a0J. Climate,\u00a031, 9835\u20139854, 2018.","DOI":"10.1175\/JCLI-D-18-0094.1"},{"key":"ref41","doi-asserted-by":"crossref","unstructured":"Newman, A. J., Clark, M. P., Craig, J., Nijssen, B., Wood, A., Gutmann, E., Mizukami, N., Brekke, L., and Arnold, J. R.: Gridded ensemble precipitation and temperature estimates for the contiguous United States, J. Hydrometeorol., 16, 2481\u20132500, 2015.","DOI":"10.1175\/JHM-D-15-0026.1"},{"key":"ref42","doi-asserted-by":"crossref","unstructured":"Olauson, J.: ERA5: The new champion of wind power modelling?,\u00a0Renew. Energ.,\u00a0126, 322\u2013331, 2018.","DOI":"10.1016\/j.renene.2018.03.056"},{"key":"ref43","doi-asserted-by":"crossref","unstructured":"Oudin, L., Hervieu, F., Michel, C., Perrin, C., Andr\u00e9assian, V., Anctil, F., and Loumagne, C.: Which potential evapotranspiration input for a lumped rainfall\u2013runoff model?, Part 2 \u2013 Towards a simple and efficient potential evapotranspiration model for rainfall\u2013runoff modelling,\u00a0J. Hydrol.,\u00a0303, 290\u2013306, 2005.","DOI":"10.1016\/j.jhydrol.2004.08.026"},{"key":"ref44","doi-asserted-by":"crossref","unstructured":"Parker, W. S.: Reanalyses and observations: What's the difference?,\u00a0B. Am. Meteorol. Soc.,\u00a097, 1565\u20131572, 2016.","DOI":"10.1175\/BAMS-D-14-00226.1"},{"key":"ref45","doi-asserted-by":"publisher","unstructured":"Peel, M. C., Finlayson, B. L., and McMahon, T. A.: Updated world map of the K\u00f6ppen-Geiger climate classification, Hydrol. Earth Syst. Sci., 11, 1633\u20131644, 10.5194\/hess-11-1633-2007, 2007.","DOI":"10.5194\/hess-11-1633-2007"},{"key":"ref46","doi-asserted-by":"publisher","unstructured":"Perrin, C., Michel, C., and Andr\u00e9assian, V.: Improvement of a parsimonious model for streamflow simulation,\u00a0J. Hydrol.,\u00a0279, 275\u2013289, 10.1016\/S0022-1694(03)00225-7, 2003 (data available at: https:\/\/www.mathworks.com\/matlabcentral\/fileexchange\/61720-gr4j-rainfall-runoff-model-deterministic-and-stochastic-methods-with-matlab, last access: June 2018).","DOI":"10.1016\/S0022-1694(03)00225-7"},{"key":"ref47","doi-asserted-by":"crossref","unstructured":"Raimonet, M., Oudin, L., Thieu, V., Silvestre, M., Vautard, R., Rabouille, C., and Le Moigne, P.: Evaluation of gridded meteorological datasets for hydrological modelling, J. Hydrometeorol., 18, 3027\u20133041, 2017.","DOI":"10.1175\/JHM-D-17-0018.1"},{"key":"ref48","doi-asserted-by":"publisher","unstructured":"Raimonet, M., Thieu, V., Silvestre, M., Oudin, L., Rabouille, C., Vautard, R., and Garnier, J.: Landward perspective of coastal eutrophication potential under future climate change: The Seine River case (France), Front. Mar. Sci., 5, 136, 10.3389\/fmars.2018.00136, 2018.","DOI":"10.3389\/fmars.2018.00136"},{"key":"ref49","doi-asserted-by":"crossref","unstructured":"Raymond, C., Singh, D., and Horton, R. M.: Spatiotemporal patterns and synoptics of extreme wet bulb temperature in the contiguous United States, J. Geophys. Res.-Atmos., 122, 13\u2013108, 2017.","DOI":"10.1002\/2017JD027140"},{"key":"ref50","doi-asserted-by":"crossref","unstructured":"Riboust, P., Thirel, G., Le Moine, N., and Ribstein, P.: Revisiting a simple degree-day model for integrating satellite data: implementation of SWE-SCA hysteresis, J. Hydrol. Hydromech., 67, 70\u201381, 2019.","DOI":"10.2478\/johh-2018-0004"},{"key":"ref51","doi-asserted-by":"crossref","unstructured":"Ruffault, J., Moron, V., Trigo, R. M., and Curt, T.: Daily synoptic conditions associated with large fire occurrence in Mediterranean France: evidence for a wind-driven fire regime, Int. J. Climatol., 37, 524\u2013533, 2017.","DOI":"10.1002\/joc.4680"},{"key":"ref52","doi-asserted-by":"publisher","unstructured":"Siegert, M. J., Ross, N., and Le Brocq, A. M.: Recent advances in understanding Antarctic subglacial lakes and hydrology. Philosophical Transactions of the Royal Society A: Mathematical, Phys. Eng. Sci., 374, 20140306, 10.1098\/rsta.2014.0306, 2016.","DOI":"10.1098\/rsta.2014.0306"},{"key":"ref53","doi-asserted-by":"crossref","unstructured":"Singh, D., Swain, D. L., Mankin, J. S., Horton, D. E., Thomas, L. N., Rajaratnam, B., and Diffenbaugh, N. S.: Recent amplification of the North American winter temperature dipole, J. Geophys. Res.-Atmos., 121, 9911\u20139928, 2016.","DOI":"10.1002\/2016JD025116"},{"key":"ref54","doi-asserted-by":"crossref","unstructured":"Singh, V. P. and Woolhiser, D. A.: Mathematical modeling of watershed hydrology, J. Hydrol. Eng., 7, 270\u2013292, 2002.","DOI":"10.1061\/(ASCE)1084-0699(2002)7:4(270)"},{"key":"ref55","doi-asserted-by":"crossref","unstructured":"Stearns, C. R. and Wendler, G.: Research results from Antarctic automatic weather stations, Rev. Geophys., 26, 45\u201361, 1988.","DOI":"10.1029\/RG026i001p00045"},{"key":"ref56","doi-asserted-by":"crossref","unstructured":"Sun, Q., Miao, C., Duan, Q., Ashouri, H., Sorooshian, S., and Hsu, K. L.: A review of global precipitation data sets: data sources, estimation, and intercomparisons, Rev. Geophys., 56, 79\u2013107, 2018.","DOI":"10.1002\/2017RG000574"},{"key":"ref57","doi-asserted-by":"crossref","unstructured":"Urraca, R., Huld, T., Gracia-Amillo, A., Martinez-de-Pison, F. J., Kaspar, F., and Sanz-Garcia, A.: Evaluation of global horizontal irradiance estimates from ERA5 and COSMO-REA6 reanalyses using ground and satellite-based data,\u00a0Solar Energy,\u00a0164, 339\u2013354, 2018.","DOI":"10.1016\/j.solener.2018.02.059"},{"key":"ref58","doi-asserted-by":"publisher","unstructured":"U.S. Geological Survey: National Water Information System, USGS Water Data for the Nation, 10.5066\/F7P55KJN, 2019.","DOI":"10.5066\/F7P55KJN"},{"key":"ref59","doi-asserted-by":"publisher","unstructured":"Val\u00e9ry, A., Andr\u00e9assian, V., and Perrin, C.: `As simple as possible but not simpler': What is useful in a temperature-based snow-accounting routine? Part 2 \u2013 Sensitivity analysis of the Cemaneige snow accounting routine on 380 catchments, J. Hydrol., 517, 1176\u20131187, 10.1016\/j.jhydrol.2014.04.058, 2014 (data available at: https:\/\/www.mathworks.com\/matlabcentral\/ fileexchange\/61720-gr4j-rainfall-runoff-model-deterministic-and-stochastic-methods-with-matlab, last access: February 2020).","DOI":"10.1016\/j.jhydrol.2014.04.058"},{"key":"ref60","doi-asserted-by":"publisher","unstructured":"Wang, H.-M., Chen, J., Xu, C.-Y., Chen, H., Guo, S., Xie, P., and Li, X.: Does the weighting of climate simulations result in a better quantification of hydrological impacts?, Hydrol. Earth Syst. Sci., 23, 4033\u20134050, 10.5194\/hess-23-4033-2019, 2019.","DOI":"10.5194\/hess-23-4033-2019"},{"key":"ref61","doi-asserted-by":"crossref","unstructured":"Whitfield, P. H., Burn, D. H., Hannaford, J., Higgins, H., Hodgkins, G. A., Marsh, T., and Looser, U.: Reference hydrologic networks I, The status and potential future directions of national reference hydrologic networks for detecting trends, Hydrol. Sci. J., 57, 1562\u20131579, 2012.","DOI":"10.1080\/02626667.2012.728706"},{"key":"ref62","unstructured":"Wood, E. F.: Hydrologic measurements and observations: An assessment of needs, in: National Research Council, Hydrologic Sciences: Taking stock and looking ahead, National Academies Press, chap. 3, 67\u201385, 1998."},{"key":"ref63","unstructured":"Youssef, H., Simon, G., Younes, F., Ghani, C., and Vincent, S.: Rainfall-Runoff modeling in a semi-arid catchment with presence of snow. The Rheraya wadi case study (Marrakech, Morocco), In EGU General Assembly Conference Abstracts, Vol. 20, p.\u00a05214, 2018."},{"key":"ref64","doi-asserted-by":"crossref","unstructured":"Zhang, Y., Zheng, H., Chiew, F. H., Arancibia, J. P., and Zhou, X.: Evaluating regional and global hydrological models against streamflow and evapotranspiration measurements, J. 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