Articles | Volume 13, issue 11
https://doi.org/10.5194/hess-13-2221-2009
© Author(s) 2009. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/hess-13-2221-2009
© Author(s) 2009. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
25 Nov 2009
An evaluation of the Canadian global meteorological ensemble prediction system for short-term hydrological forecasting
J. A. Velázquez
Chaire de recherche EDS en prévisions et actions hydrologiques, Université Laval, Québec, Canada
T. Petit
Chaire de recherche EDS en prévisions et actions hydrologiques, Université Laval, Québec, Canada
A. Lavoie
Chaire de recherche EDS en prévisions et actions hydrologiques, Université Laval, Québec, Canada
M.-A. Boucher
Chaire de recherche EDS en prévisions et actions hydrologiques, Université Laval, Québec, Canada
R. Turcotte
Centre d'expertise hydrique du Québec, Québec, Canada
V. Fortin
Recherche en prévision numérique environnementale, Environnement Canada, Montréal, Canada
F. Anctil
Chaire de recherche EDS en prévisions et actions hydrologiques, Université Laval, Québec, Canada
Related subject area
Subject: Engineering Hydrology | Techniques and Approaches: Modelling approaches
Soil moisture modeling with ERA5-Land retrievals, topographic indices, and in situ measurements and its use for predicting ruts
A systematic review of climate change science relevant to Australian design flood estimation
Technical Note: Resolution enhancement of flood inundation grids
Floods and droughts: a multivariate perspective
Technical note: Statistical generation of climate-perturbed flow duration curves
Deep learning methods for flood mapping: a review of existing applications and future research directions
Extreme floods in Europe: going beyond observations using reforecast ensemble pooling
Hydroinformatics education – the Water Informatics in Science and Engineering (WISE) Centre for Doctoral Training
Wetropolis extreme rainfall and flood demonstrator: from mathematical design to outreach
Technical note: The beneficial role of a natural permeable layer in slope stabilization by drainage trenches
Assessing the impacts of reservoirs on downstream flood frequency by coupling the effect of scheduling-related multivariate rainfall with an indicator of reservoir effects
Observation operators for assimilation of satellite observations in fluvial inundation forecasting
Contribution of potential evaporation forecasts to 10-day streamflow forecast skill for the Rhine River
Inundation mapping based on reach-scale effective geometry
Effects of variability in probable maximum precipitation patterns on flood losses
The challenge of forecasting impacts of flash floods: test of a simplified hydraulic approach and validation based on insurance claim data
A comparison of the discrete cosine and wavelet transforms for hydrologic model input data reduction
Hydrological modeling of the Peruvian–Ecuadorian Amazon Basin using GPM-IMERG satellite-based precipitation dataset
Technical note: Design flood under hydrological uncertainty
Topography- and nightlight-based national flood risk assessment in Canada
Regime shifts in annual maximum rainfall across Australia – implications for intensity–frequency–duration (IFD) relationships
Performance evaluation of groundwater model hydrostratigraphy from airborne electromagnetic data and lithological borehole logs
A continuous rainfall model based on vine copulas
Estimates of global dew collection potential on artificial surfaces
Climate changes of hydrometeorological and hydrological extremes in the Paute basin, Ecuadorean Andes
An assessment of the ability of Bartlett–Lewis type of rainfall models to reproduce drought statistics
Modeling root reinforcement using a root-failure Weibull survival function
Socio-hydrology: conceptualising human-flood interactions
Application of a model-based rainfall-runoff database as efficient tool for flood risk management
Estimating actual, potential, reference crop and pan evaporation using standard meteorological data: a pragmatic synthesis
HydroViz: design and evaluation of a Web-based tool for improving hydrology education
Web 2.0 collaboration tool to support student research in hydrology – an opinion
SCS-CN parameter determination using rainfall-runoff data in heterogeneous watersheds – the two-CN system approach
Discharge estimation combining flow routing and occasional measurements of velocity
Experimental investigation of the predictive capabilities of data driven modeling techniques in hydrology - Part 2: Application
Comment on "A praxis-oriented perspective of streamflow inference from stage observations – the method of Dottori et al. (2009) and the alternative of the Jones Formula, with the kinematic wave celerity computed on the looped rating curve" by Koussis (2009)
Marian Schönauer, Anneli M. Ågren, Klaus Katzensteiner, Florian Hartsch, Paul Arp, Simon Drollinger, and Dirk Jaeger
Hydrol. Earth Syst. Sci., 28, 2617–2633, https://doi.org/10.5194/hess-28-2617-2024, https://doi.org/10.5194/hess-28-2617-2024, 2024
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This work employs innovative spatiotemporal modeling to predict soil moisture, with implications for sustainable forest management. By correlating predicted soil moisture with rut depth, it addresses a critical concern of soil damage and ecological impact – and its prevention through adequate planning of forest operations.
Conrad Wasko, Seth Westra, Rory Nathan, Acacia Pepler, Timothy H. Raupach, Andrew Dowdy, Fiona Johnson, Michelle Ho, Kathleen L. McInnes, Doerte Jakob, Jason Evans, Gabriele Villarini, and Hayley J. Fowler
Hydrol. Earth Syst. Sci., 28, 1251–1285, https://doi.org/10.5194/hess-28-1251-2024, https://doi.org/10.5194/hess-28-1251-2024, 2024
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In response to flood risk, design flood estimation is a cornerstone of infrastructure design and emergency response planning, but design flood estimation guidance under climate change is still in its infancy. We perform the first published systematic review of the impact of climate change on design flood estimation and conduct a meta-analysis to provide quantitative estimates of possible future changes in extreme rainfall.
Seth Bryant, Guy Schumann, Heiko Apel, Heidi Kreibich, and Bruno Merz
Hydrol. Earth Syst. Sci., 28, 575–588, https://doi.org/10.5194/hess-28-575-2024, https://doi.org/10.5194/hess-28-575-2024, 2024
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A new algorithm has been developed to quickly produce high-resolution flood maps. It is faster and more accurate than current methods and is available as open-source scripts. This can help communities better prepare for and mitigate flood damages without expensive modelling.
Manuela Irene Brunner
Hydrol. Earth Syst. Sci., 27, 2479–2497, https://doi.org/10.5194/hess-27-2479-2023, https://doi.org/10.5194/hess-27-2479-2023, 2023
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I discuss different types of multivariate hydrological extremes and their dependencies, including regional extremes affecting multiple locations, such as spatially connected flood events; consecutive extremes occurring in close temporal succession, such as successive droughts; extremes characterized by multiple characteristics, such as floods with jointly high peak discharge and flood volume; and transitions between different types of extremes, such as drought-to-flood transitions.
Veysel Yildiz, Robert Milton, Solomon Brown, and Charles Rougé
Hydrol. Earth Syst. Sci., 27, 2499–2507, https://doi.org/10.5194/hess-27-2499-2023, https://doi.org/10.5194/hess-27-2499-2023, 2023
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The proposed approach is based on the parameterisation of flow duration curves (FDCs) to generate hypothetical streamflow futures. (1) We sample a broad range of future climates with modified values of three key streamflow statistics. (2) We generate an FDC for each hydro-climate future. (3) The resulting ensemble is ready to support robustness assessments in a changing climate. Our approach seamlessly represents a large range of futures with increased frequencies of both high and low flows.
Roberto Bentivoglio, Elvin Isufi, Sebastian Nicolaas Jonkman, and Riccardo Taormina
Hydrol. Earth Syst. Sci., 26, 4345–4378, https://doi.org/10.5194/hess-26-4345-2022, https://doi.org/10.5194/hess-26-4345-2022, 2022
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Deep learning methods have been increasingly used in flood management to improve traditional techniques. While promising results have been obtained, our review shows significant challenges in building deep learning models that can (i) generalize across multiple scenarios, (ii) account for complex interactions, and (iii) perform probabilistic predictions. We argue that these shortcomings could be addressed by transferring recent fundamental advancements in deep learning to flood mapping.
Manuela I. Brunner and Louise J. Slater
Hydrol. Earth Syst. Sci., 26, 469–482, https://doi.org/10.5194/hess-26-469-2022, https://doi.org/10.5194/hess-26-469-2022, 2022
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Assessing the rarity and magnitude of very extreme flood events occurring less than twice a century is challenging due to the lack of observations of such rare events. Here we develop a new approach, pooling reforecast ensemble members from the European Flood Awareness System to increase the sample size available to estimate the frequency of extreme flood events. We demonstrate that such ensemble pooling produces more robust estimates than observation-based estimates.
Thorsten Wagener, Dragan Savic, David Butler, Reza Ahmadian, Tom Arnot, Jonathan Dawes, Slobodan Djordjevic, Roger Falconer, Raziyeh Farmani, Debbie Ford, Jan Hofman, Zoran Kapelan, Shunqi Pan, and Ross Woods
Hydrol. Earth Syst. Sci., 25, 2721–2738, https://doi.org/10.5194/hess-25-2721-2021, https://doi.org/10.5194/hess-25-2721-2021, 2021
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How can we effectively train PhD candidates both (i) across different knowledge domains in water science and engineering and (ii) in computer science? To address this issue, the Water Informatics in Science and Engineering Centre for Doctoral Training (WISE CDT) offers a postgraduate programme that fosters enhanced levels of innovation and collaboration by training a cohort of engineers and scientists at the boundary of water informatics, science and engineering.
Onno Bokhove, Tiffany Hicks, Wout Zweers, and Thomas Kent
Hydrol. Earth Syst. Sci., 24, 2483–2503, https://doi.org/10.5194/hess-24-2483-2020, https://doi.org/10.5194/hess-24-2483-2020, 2020
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Wetropolis is a
table-topdemonstration model with extreme rainfall and flooding, including random rainfall, river flow, flood plains, an upland reservoir, a porous moor, and a city which can flood. It lets the viewer experience extreme rainfall and flood events in a physical model on reduced spatial and temporal scales with an event return period of 6.06 min rather than, say, 200 years. We disseminate its mathematical design and how it has been shown most prominently to over 500 flood victims.
Gianfranco Urciuoli, Luca Comegna, Marianna Pirone, and Luciano Picarelli
Hydrol. Earth Syst. Sci., 24, 1669–1676, https://doi.org/10.5194/hess-24-1669-2020, https://doi.org/10.5194/hess-24-1669-2020, 2020
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The aim of this paper is to demonstrate, through a numerical approach, that the presence of soil layers of higher permeability, a not unlikely condition in some deep landslides in clay, may be exploited to improve the efficiency of systems of drainage trenches for slope stabilization. The problem has been examined for the case that a unique pervious layer, parallel to the ground surface, is present at an elevation higher than the bottom of the trenches.
Bin Xiong, Lihua Xiong, Jun Xia, Chong-Yu Xu, Cong Jiang, and Tao Du
Hydrol. Earth Syst. Sci., 23, 4453–4470, https://doi.org/10.5194/hess-23-4453-2019, https://doi.org/10.5194/hess-23-4453-2019, 2019
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We develop a new indicator of reservoir effects, called the rainfall–reservoir composite index (RRCI). RRCI, coupled with the effects of static reservoir capacity and scheduling-related multivariate rainfall, has a better performance than the previous indicator in terms of explaining the variation in the downstream floods affected by reservoir operation. A covariate-based flood frequency analysis using RRCI can provide more reliable downstream flood risk estimation.
Elizabeth S. Cooper, Sarah L. Dance, Javier García-Pintado, Nancy K. Nichols, and Polly J. Smith
Hydrol. Earth Syst. Sci., 23, 2541–2559, https://doi.org/10.5194/hess-23-2541-2019, https://doi.org/10.5194/hess-23-2541-2019, 2019
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Flooding from rivers is a huge and costly problem worldwide. Computer simulations can help to warn people if and when they are likely to be affected by river floodwater, but such predictions are not always accurate or reliable. Information about flood extent from satellites can help to keep these forecasts on track. Here we investigate different ways of using information from satellite images and look at the effect on computer predictions. This will help to develop flood warning systems.
Bart van Osnabrugge, Remko Uijlenhoet, and Albrecht Weerts
Hydrol. Earth Syst. Sci., 23, 1453–1467, https://doi.org/10.5194/hess-23-1453-2019, https://doi.org/10.5194/hess-23-1453-2019, 2019
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A correct estimate of the amount of future precipitation is the most important factor in making a good streamflow forecast, but evaporation is also an important component that determines the discharge of a river. However, in this study for the Rhine River we found that evaporation forecasts only give an almost negligible improvement compared to methods that use statistical information on climatology for a 10-day streamflow forecast. This is important to guide research on low flow forecasts.
Cédric Rebolho, Vazken Andréassian, and Nicolas Le Moine
Hydrol. Earth Syst. Sci., 22, 5967–5985, https://doi.org/10.5194/hess-22-5967-2018, https://doi.org/10.5194/hess-22-5967-2018, 2018
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Inundation models are useful for hazard management and prevention. They are traditionally based on hydraulic partial differential equations (with satisfying results but large data and computational requirements). This study presents a simplified approach combining reach-scale geometric properties with steady uniform flow equations. The model shows promising results overall, although difficulties persist in the most complex urbanised reaches.
Andreas Paul Zischg, Guido Felder, Rolf Weingartner, Niall Quinn, Gemma Coxon, Jeffrey Neal, Jim Freer, and Paul Bates
Hydrol. Earth Syst. Sci., 22, 2759–2773, https://doi.org/10.5194/hess-22-2759-2018, https://doi.org/10.5194/hess-22-2759-2018, 2018
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We developed a model experiment and distributed different rainfall patterns over a mountain river basin. For each rainfall scenario, we computed the flood losses with a model chain. The experiment shows that flood losses vary considerably within the river basin and depend on the timing of the flood peaks from the basin's sub-catchments. Basin-specific characteristics such as the location of the main settlements within the floodplains play an additional important role in determining flood losses.
Guillaume Le Bihan, Olivier Payrastre, Eric Gaume, David Moncoulon, and Frédéric Pons
Hydrol. Earth Syst. Sci., 21, 5911–5928, https://doi.org/10.5194/hess-21-5911-2017, https://doi.org/10.5194/hess-21-5911-2017, 2017
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This paper illustrates how an integrated flash flood monitoring (or forecasting) system may be designed to directly provide information on possibly flooded areas and associated impacts on a very detailed river network and over large territories. The approach is extensively tested in the regions of Alès and Draguignan, located in south-eastern France. Validation results are presented in terms of accuracy of the estimated flood extents and related impacts (based on insurance claim data).
Ashley Wright, Jeffrey P. Walker, David E. Robertson, and Valentijn R. N. Pauwels
Hydrol. Earth Syst. Sci., 21, 3827–3838, https://doi.org/10.5194/hess-21-3827-2017, https://doi.org/10.5194/hess-21-3827-2017, 2017
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The accurate reduction of hydrologic model input data is an impediment towards understanding input uncertainty and model structural errors. This paper compares the ability of two transforms to reduce rainfall input data. The resultant transforms are compressed to varying extents and reconstructed before being evaluated with standard simulation performance summary metrics and descriptive statistics. It is concluded the discrete wavelet transform is most capable of preserving rainfall time series.
Ricardo Zubieta, Augusto Getirana, Jhan Carlo Espinoza, Waldo Lavado-Casimiro, and Luis Aragon
Hydrol. Earth Syst. Sci., 21, 3543–3555, https://doi.org/10.5194/hess-21-3543-2017, https://doi.org/10.5194/hess-21-3543-2017, 2017
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This paper indicates that precipitation data derived from GPM-IMERG correspond more closely to TMPA V7 than TMPA RT datasets, but both GPM-IMERG and TMPA V7 precipitation data tend to overestimate, in comparison to observed rainfall (by 11.1 % and 15.7 %, respectively). Statistical analysis indicates that GPM-IMERG is as useful as TMPA V7 or TMPA RT datasets for estimating observed streamflows in Andean–Amazonian regions (Ucayali Basin, southern regions of the Amazon Basin of Peru and Ecuador).
Anna Botto, Daniele Ganora, Pierluigi Claps, and Francesco Laio
Hydrol. Earth Syst. Sci., 21, 3353–3358, https://doi.org/10.5194/hess-21-3353-2017, https://doi.org/10.5194/hess-21-3353-2017, 2017
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The paper provides an easy-to-use implementation of the UNCODE framework, which allows one to estimate the design flood value by directly accounting for sample uncertainty. Other than a design tool, this methodology is also a practical way to quantify the value of data in the design process.
Amin Elshorbagy, Raja Bharath, Anchit Lakhanpal, Serena Ceola, Alberto Montanari, and Karl-Erich Lindenschmidt
Hydrol. Earth Syst. Sci., 21, 2219–2232, https://doi.org/10.5194/hess-21-2219-2017, https://doi.org/10.5194/hess-21-2219-2017, 2017
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Flood mapping is one of Canada's major national interests. This work presents a simple and effective method for large-scale flood hazard and risk mapping, applied in this study to Canada. Readily available data, such as remote sensing night-light data, topography, and stream network were used to create the maps.
D. C. Verdon-Kidd and A. S. Kiem
Hydrol. Earth Syst. Sci., 19, 4735–4746, https://doi.org/10.5194/hess-19-4735-2015, https://doi.org/10.5194/hess-19-4735-2015, 2015
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Rainfall intensity-frequency-duration (IFD) relationships are required for the design and planning of water supply and management systems around the world. Currently IFD information is based on the "stationary climate assumption". However, this paper provides evidence of regime shifts in annual maxima rainfall time series using 96 daily rainfall stations and 66 sub-daily rainfall stations across Australia. Importantly, current IFD relationships may under- or overestimate the design rainfall.
P. A. Marker, N. Foged, X. He, A. V. Christiansen, J. C. Refsgaard, E. Auken, and P. Bauer-Gottwein
Hydrol. Earth Syst. Sci., 19, 3875–3890, https://doi.org/10.5194/hess-19-3875-2015, https://doi.org/10.5194/hess-19-3875-2015, 2015
H. Vernieuwe, S. Vandenberghe, B. De Baets, and N. E. C. Verhoest
Hydrol. Earth Syst. Sci., 19, 2685–2699, https://doi.org/10.5194/hess-19-2685-2015, https://doi.org/10.5194/hess-19-2685-2015, 2015
H. Vuollekoski, M. Vogt, V. A. Sinclair, J. Duplissy, H. Järvinen, E.-M. Kyrö, R. Makkonen, T. Petäjä, N. L. Prisle, P. Räisänen, M. Sipilä, J. Ylhäisi, and M. Kulmala
Hydrol. Earth Syst. Sci., 19, 601–613, https://doi.org/10.5194/hess-19-601-2015, https://doi.org/10.5194/hess-19-601-2015, 2015
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The global potential for collecting usable water from dew on an
artificial collector sheet was investigated by utilising 34 years of
meteorological reanalysis data as input to a dew formation model. Continental dew formation was found to be frequent and common, but daily yields were
mostly below 0.1mm.
D. E. Mora, L. Campozano, F. Cisneros, G. Wyseure, and P. Willems
Hydrol. Earth Syst. Sci., 18, 631–648, https://doi.org/10.5194/hess-18-631-2014, https://doi.org/10.5194/hess-18-631-2014, 2014
M. T. Pham, W. J. Vanhaute, S. Vandenberghe, B. De Baets, and N. E. C. Verhoest
Hydrol. Earth Syst. Sci., 17, 5167–5183, https://doi.org/10.5194/hess-17-5167-2013, https://doi.org/10.5194/hess-17-5167-2013, 2013
M. Schwarz, F. Giadrossich, and D. Cohen
Hydrol. Earth Syst. Sci., 17, 4367–4377, https://doi.org/10.5194/hess-17-4367-2013, https://doi.org/10.5194/hess-17-4367-2013, 2013
G. Di Baldassarre, A. Viglione, G. Carr, L. Kuil, J. L. Salinas, and G. Blöschl
Hydrol. Earth Syst. Sci., 17, 3295–3303, https://doi.org/10.5194/hess-17-3295-2013, https://doi.org/10.5194/hess-17-3295-2013, 2013
L. Brocca, S. Liersch, F. Melone, T. Moramarco, and M. Volk
Hydrol. Earth Syst. Sci., 17, 3159–3169, https://doi.org/10.5194/hess-17-3159-2013, https://doi.org/10.5194/hess-17-3159-2013, 2013
T. A. McMahon, M. C. Peel, L. Lowe, R. Srikanthan, and T. R. McVicar
Hydrol. Earth Syst. Sci., 17, 1331–1363, https://doi.org/10.5194/hess-17-1331-2013, https://doi.org/10.5194/hess-17-1331-2013, 2013
E. Habib, Y. Ma, D. Williams, H. O. Sharif, and F. Hossain
Hydrol. Earth Syst. Sci., 16, 3767–3781, https://doi.org/10.5194/hess-16-3767-2012, https://doi.org/10.5194/hess-16-3767-2012, 2012
A. Pathirana, B. Gersonius, and M. Radhakrishnan
Hydrol. Earth Syst. Sci., 16, 2499–2509, https://doi.org/10.5194/hess-16-2499-2012, https://doi.org/10.5194/hess-16-2499-2012, 2012
K. X. Soulis and J. D. Valiantzas
Hydrol. Earth Syst. Sci., 16, 1001–1015, https://doi.org/10.5194/hess-16-1001-2012, https://doi.org/10.5194/hess-16-1001-2012, 2012
G. Corato, T. Moramarco, and T. Tucciarelli
Hydrol. Earth Syst. Sci., 15, 2979–2994, https://doi.org/10.5194/hess-15-2979-2011, https://doi.org/10.5194/hess-15-2979-2011, 2011
A. Elshorbagy, G. Corzo, S. Srinivasulu, and D. P. Solomatine
Hydrol. Earth Syst. Sci., 14, 1943–1961, https://doi.org/10.5194/hess-14-1943-2010, https://doi.org/10.5194/hess-14-1943-2010, 2010
A. D. Koussis
Hydrol. Earth Syst. Sci., 14, 1093–1097, https://doi.org/10.5194/hess-14-1093-2010, https://doi.org/10.5194/hess-14-1093-2010, 2010
Cited articles
Atger, F.: The skill of ensemble prediction systems, Mon. Weather Rev., 127, 1941–1953, 1999.
Bartholmes, J. and Todini, E.: Coupling meteorological and hydrological models for flood forecasting, Hydrol. Earth Syst. Sci., 9, 333–346, 2005.
Beck, M. B.: Water quality modeling – a review of the analysis of uncertainty, Water Resour. Res., 23(8), 1393–1442, 1987.
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.
Candille, G. and Talagrand, O.: Evaluation of probabilistic prediction systems for a scalar variable, Q. J. Roy. Meteor. Soc., 131, 2131–2150, 2005
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.
Cloke, H. L. and Pappenberger, F.: Ensemble flood forecasting: a review, J. Hydrol., 375, 613–626, 2009.
Day, G. N.: Extended Streamflow Forecasting using NWSRFS, J. Water Res. Pl.-ASCE, 111(2), 157–170, 1985.
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'information géographique, Revue des sciences de l'eau, 8(1), 97–124, 1995.
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.
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.
Gneiting, T. and Raftery, A. E.: Strictly proper scoring rules, prediction, and estimation, J. Am. Stat. Assoc., 102, 359–378, 2007.
Hamill, T. M.: Interpretation of Rank Histograms for Verifying Ensemble Forecasts, Mon. Weather Rev., 129, 550–560, 2001.
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.
Herbach, H.: Decomposition of the Continuous Ranked Probability Score for Ensemble Prediction Systems, Weather Forecast., 15, 559–570, 2000.
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.
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.
Jaun, S. and Ahrens, B.: Evaluation of a probabilistic hydrometeorological forecast system, Hydrol. Earth Syst. Sci., 13, 1031–1043, 2009.
Lauzon, N., Birikundavyi, S., Gignac, C., and Rouselle, J.: Comparaison de deux procédures d'amélioration des prévisions à court terme des apports naturels d'un modèle déterministe, Can. J. Civil Eng., 24, 723–735, 1997.
Matheson, J. E. and Winkler, R. L.: Scoring rules for continuous probability distributions, Manage Sci., 22, 1087–1096, 1976.
O'Connell, P. E. and Clarke, R. T.: Adaptative hydrological forecasting: A review, Hydrolog. Sci. Bulletin, 26(2), 179–205, 1981.
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.
Poirier, C., Turcotte, R., and Lacombe, P.: Procédure de reconstitution d'apports historiques, in: Congrès de l'Association canadienne des barrages, Calgary, 3–5 October 2005.
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.
Refsgaard, J. C.: Validation and intercomparison of different updating procedures for real-time forecasting, Nord. Hydrol., 28, 65–84, 1997.
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.
Roulin, E. and Vannitsem, S.: Skill of medium-range hydrological ensemble predictions, J. Hydrometeorol., 6, 729–744, 2005.
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.
Székely, G. J. and Rizzo, M. L.: A new test for multivariate normality, J. Multivariate Anal., 93(1), 58–80, 2005.
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.
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.
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.
Wilks, D. S.: Statistical Methods in the Atmospheric Sciences, Academic Press, San Diego, CA, 465 pp., 1995.
