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<article language="en">
	<journal>
		<journal_title>Hydrology and Earth System Sciences</journal_title>
		<journal_url>www.hydrol-earth-syst-sci.net</journal_url>
		<issn>1027-5606</issn>
		<eissn>1607-7938</eissn>
		<volume_number>13</volume_number>
		<issue_number>11</issue_number>
		<publication_year>2009</publication_year>
	</journal>
	<doi>10.5194/hess-13-2221-2009</doi>
	<article_url>http://www.hydrol-earth-syst-sci.net/13/2221/2009/</article_url>
	<abstract_html>http://www.hydrol-earth-syst-sci.net/13/2221/2009/hess-13-2221-2009.html</abstract_html>
	<fulltext_pdf>http://www.hydrol-earth-syst-sci.net/13/2221/2009/hess-13-2221-2009.pdf</fulltext_pdf>
	<start_page>2221</start_page>
	<end_page>2231</end_page>
	<publication_date>2009-11-25</publication_date>
	<article_title content_type="html">An evaluation of the Canadian global meteorological ensemble prediction system for short-term hydrological forecasting</article_title>
	<authors>
		<author numeration="1" affiliations="1">
			<name>J. A. Velázquez</name>
			<email>juan-alberto.velazquez.l@ulaval.ca</email>
		</author>
		<author numeration="2" affiliations="1">
			<name>T. Petit</name>
		</author>
		<author numeration="3" affiliations="1">
			<name>A. Lavoie</name>
		</author>
		<author numeration="4" affiliations="1">
			<name>M.-A. Boucher</name>
		</author>
		<author numeration="5" affiliations="2">
			<name>R. Turcotte</name>
		</author>
		<author numeration="6" affiliations="3">
			<name>V. Fortin</name>
		</author>
		<author numeration="7" affiliations="1">
			<name>F. Anctil</name>
		</author>
	</authors>
	<affiliations>
		<affiliation numeration="1" content_type="html">Chaire de recherche EDS en prévisions et actions hydrologiques, Université Laval, Québec, Canada</affiliation>
		<affiliation numeration="2" content_type="html">Centre d&apos;expertise hydrique du Québec, Québec, Canada</affiliation>
		<affiliation numeration="3" content_type="html">Recherche en prévision numérique environnementale, Environnement Canada, Montréal, Canada</affiliation>
	</affiliations>
	<abstract content_type="html">Hydrological forecasting consists in the assessment of future streamflow.
Current deterministic forecasts do not give any information concerning the
uncertainty, which might be limiting in a decision-making process. Ensemble
forecasts are expected to fill this gap.
&lt;br&gt;&lt;br&gt;
In July 2007, the Meteorological Service of Canada has improved its ensemble
prediction system, which has been operational since 1998. It uses the GEM
model to generate a 20-member ensemble on a 100 km grid, at mid-latitudes.
This improved system is used for the first time for hydrological ensemble
predictions. Five watersheds in Quebec (Canada) are studied: Chaudière,
Châteauguay, Du Nord, Kénogami and Du Lièvre. An interesting
17-day rainfall event has been selected in October 2007. Forecasts are
produced in a 3 h time step for a 3-day forecast horizon. The
deterministic forecast is also available and it is compared with the
ensemble ones. In order to correct the bias of the ensemble, an updating
procedure has been applied to the output data. Results showed that ensemble
forecasts are more skilful than the deterministic ones, as measured by the
Continuous Ranked Probability Score (CRPS), especially for 72 h forecasts.
However, the hydrological ensemble forecasts are under dispersed: a
situation that improves with the increasing length of the prediction
horizons. We conjecture that this is due in part to the fact that
uncertainty in the initial conditions of the hydrological model is not taken
into account.</abstract>
	<references>
		<reference numeration="1" content_type="text"> % vor jede Referenz Atger, F.: The skill of ensemble prediction systems, Mon. Weather Rev., 127, 1941–1953, 1999. </reference>
		<reference numeration="2" content_type="text"> Bartholmes, J. and Todini, E.: Coupling meteorological and hydrological models for flood forecasting, Hydrol. Earth Syst. Sci., 9, 333–346, 2005. </reference>
		<reference numeration="3" content_type="text"> Beck, M. B.: Water quality modeling – a review of the analysis of uncertainty, Water Resour. Res., 23(8), 1393–1442, 1987. </reference>
		<reference numeration="4" content_type="text"> Boucher, M. A., Perreault, L., and Anctil, F.: Tools for the assessment of hydrological ensemble forecasts obtained by neural networks, J. Hydroinform., 11, 297–307, 2009. </reference>
		<reference numeration="5" content_type="text"> Candille, G. and Talagrand, O.: Evaluation of probabilistic prediction systems for a scalar variable, Q. J. Roy. Meteor. Soc., 131, 2131–2150, 2005 </reference>
		<reference numeration="6" content_type="text">Clark, M. and Hay, L. E.: Use of Medium-Range Numerical Weather Prediction Model Output to Produce Forecasts of Streamflow, J. Hydrometeorol., 5, 15–32, 2004. </reference>
		<reference numeration="7" content_type="text"> Cloke, H. L. and Pappenberger, F.: Ensemble flood forecasting: a review, J. Hydrol., 375, 613–626, 2009. </reference>
		<reference numeration="8" content_type="text"> Day, G. N.: Extended Streamflow Forecasting using NWSRFS, J. Water Res. Pl.-ASCE, 111(2), 157–170, 1985. </reference>
		<reference numeration="9" content_type="text"> Fortin, J. P., Moussa, R., Bocquillon, C., and Villeneuve, J. P.: HYDROTEL, un model hydrologique distribué pouvant bénéficier des données fournies par la détection et les systèmes d&apos;information géographique, Revue des sciences de l&apos;eau, 8(1), 97–124, 1995. </reference>
		<reference numeration="10" content_type="text"> Fortin, V., Favre, A. C., and Said, M.: Probabilistic forecasting from ensemble prediction systems: Improving upon the best-member method by using a different weight and dressing kernel for each member, Q. J. Roy. Meteor. Soc., B132, 1349–1369, 2006. </reference>
		<reference numeration="11" content_type="text"> Gneiting, T., Raftery, A. E., Westveld III, A. H., and Goldman, T.: Calibrated probabilistic forecasting using ensemble model output statistics and minimum CRPS estimation, Mon. Weather Rev., 133(5), 1098–1118, 2005. </reference>
		<reference numeration="12" content_type="text"> Gneiting, T. and Raftery, A. E.: Strictly proper scoring rules, prediction, and estimation, J. Am. Stat. Assoc., 102, 359–378, 2007. </reference>
		<reference numeration="13" content_type="text"> Hamill, T. M.: Interpretation of Rank Histograms for Verifying Ensemble Forecasts, Mon. Weather Rev., 129, 550–560, 2001. </reference>
		<reference numeration="14" content_type="text"> Haché, M., Larouche, B., Perreault, L., Mathier, L., and Bobée, B.: Validation des apports non contrôlés historiques, INRS-Eau, Sainte-Foy, Québec, Rapport de recherche R-423, 65~pp., 1994. </reference>
		<reference numeration="15" content_type="text"> Hers bach, H.: Decomposition of the Continuous Ranked Probability Score for Ensemble Prediction Systems, Weather Forecast., 15, 559–570, 2000. </reference>
		<reference numeration="16" content_type="text"> Houtekamer, P. L., Mitchell, H. L., Pellerin, G., Buehner, M., Charron, M., Spacek, L., and Hansen, M.: Atmospheric data assimilation with an ensemble Kalman filter: Results with real observations, Mon. Weather Rev., 133(3), 604–620, 2005. </reference>
		<reference numeration="17" content_type="text"> Jaun, S., Ahrens, B., Walser, A., Ewen, T., and Schär, C.: A probabilistic view on the August 2005 floods in the upper Rhine catchment, Nat. Hazards Earth Syst. Sci., 8, 281–291, 2008. </reference>
		<reference numeration="18" content_type="text"> Jaun, S. and Ahrens, B.: Evaluation of a probabilistic hydrometeorological forecast system, Hydrol. Earth Syst. Sci., 13, 1031–1043, 2009. </reference>
		<reference numeration="19" content_type="text"> Lauzon, N., Birikundavyi, S., Gignac, C., and Rouselle, J.: Comparaison de deux procédures d&apos;amélioration des prévisions à court terme des apports naturels d&apos;un modèle déterministe, Can. J. Civil Eng., 24, 723–735, 1997. </reference>
		<reference numeration="20" content_type="text"> Matheson, J. E. and Winkler, R. L.: Scoring rules for continuous probability distributions, Manage Sci., 22, 1087–1096, 1976. </reference>
		<reference numeration="21" content_type="text"> O&apos;Connell, P. E. and Clarke, R. T.: Adaptative hydrological forecasting: A review, Hydrolog. Sci. Bulletin, 26(2), 179–205, 1981. </reference>
		<reference numeration="22" content_type="text"> Pica, J.: Review of Extended Streamflow Prediction of the National Weather Service NWSRFS ESP, in: CE505 Conference Course, Civil Engineering, Portland State University, 1 July 1997. </reference>
		<reference numeration="23" content_type="text"> Poirier, C., Turcotte, R., and Lacombe, P.: Procédure de reconstitution d&apos;apports historiques, in: Congrès de l&apos;Association canadienne des barrages, Calgary, 3–5 October 2005. </reference>
		<reference numeration="24" content_type="text"> Raftery, A. E., Gneiting, T., Balabdaoui, F., and Polakowski, M.: Using bayesian model averaging to calibrate forecast ensembles, Mon. Weather Rev., 133, 1155–1174, 2005. </reference>
		<reference numeration="25" content_type="text"> Refsgaard, J. C.: Validation and intercomparison of different updating procedures for real-time forecasting, Nord. Hydrol., 28, 65–84, 1997. </reference>
		<reference numeration="26" content_type="text"> Renner, M., Werner, M. G. F., Rademacher, S., and Sprokkereef, E.: Verification of ensemble flow forecast for the River Rhine, J. Hydrol., 376, 463–475, 2009. </reference>
		<reference numeration="27" content_type="text"> Roulin, E. and Vannitsem, S.: Skill of medium-range hydrological ensemble predictions, J. Hydrometeorol., 6, 729–744, 2005. </reference>
		<reference numeration="28" content_type="text"> Stensrud D. J. and Yussouf, N.: Reliable probabilistic quantitative precipitation forecasts from a short-range ensemble forecasting system, Weather Forecast., 22(1), 3–17, 2007. </reference>
		<reference numeration="29" content_type="text"> Székely, G. J. and Rizzo, M. L.: A new test for multivariate normality, J. Multivariate Anal., 93(1), 58–80, 2005. </reference>
		<reference numeration="30" content_type="text"> Talagrand, O., Vautard, R., and Strauss, B.: Evaluation of the probabilistic prediction systems, in: Proceedings, ECMWF Workshop on Predictability, Shinfield Park, Reading, Berkshire, ECMWF, 1–25, 1999. </reference>
		<reference numeration="31" content_type="text"> Turcotte, R., Lacombe, P., Dimnik, C., and Villeneuve, J. P.: Prévision hydrologique distribuée pour la gestion de barrages publics du Québec, Can. J. Civil Eng., 31, 308–320, 2004. </reference>
		<reference numeration="32" content_type="text"> Weber, F., Perreault, L., Fortin, V., and Gaudet, J.: Performance measures for probabilistic hydrologic forecasts used at BC-Hydro and Hydro-Québec, in: EGU Conference, April 2006. </reference>
		<reference numeration="33" content_type="text"> Wilks, D. S.: Statistical Methods in the Atmospheric Sciences, Academic Press, San Diego, CA, 465~pp., 1995. </reference>
	</references>
</article>

