François Anctil
François Anctil
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Which potential evapotranspiration input for a lumped rainfall–runoff model?: Part 2—Towards a simple and efficient potential evapotranspiration model for rainfall–runoff …
L Oudin, F Hervieu, C Michel, C Perrin, V Andréassian, F Anctil, ...
Journal of hydrology 303 (1-4), 290-306, 2005
Daily reservoir inflow forecasting using artificial neural networks with stopped training approach
P Coulibaly, F Anctil, B Bobée
Journal of Hydrology 230 (3-4), 244-257, 2000
Artificial neural network modeling of water table depth fluctuations
P Coulibaly, F Anctil, R Aravena, B Bobée
Water resources research 37 (4), 885-896, 2001
Two decades of anarchy? Emerging themes and outstanding challenges for neural network river forecasting
RJ Abrahart, F Anctil, P Coulibaly, CW Dawson, NJ Mount, LM See, ...
Progress in Physical Geography 36 (4), 480-513, 2012
Downscaling precipitation and temperature with temporal neural networks
P Coulibaly, YB Dibike, F Anctil
Journal of Hydrometeorology 6 (4), 483-496, 2005
Comparing sigmoid transfer functions for neural network multistep ahead streamflow forecasting
H Yonaba, F Anctil, V Fortin
Journal of hydrologic engineering 15 (4), 275-283, 2010
Multivariate reservoir inflow forecasting using temporal neural networks
P Coulibaly, F Anctil, B Bobee
Journal of Hydrologic Engineering 6 (5), 367-376, 2001
Impact of the length of observed records on the performance of ANN and of conceptual parsimonious rainfall-runoff forecasting models
F Anctil, C Perrin, V Andréassian
Environmental Modelling & Software 19 (4), 357-368, 2004
Which potential evapotranspiration input for a lumped rainfall-runoff model?: Part 1—Can rainfall-runoff models effectively handle detailed potential evapotranspiration inputs?
L Oudin, C Michel, F Anctil
Journal of hydrology 303 (1-4), 275-289, 2005
Why should ensemble spread match the RMSE of the ensemble mean?
V Fortin, M Abaza, F Anctil, R Turcotte
Journal of Hydrometeorology 15 (4), 1708-1713, 2014
Multimodel evaluation of twenty lumped hydrological models under contrasted climate conditions
G Seiller, F Anctil, C Perrin
Hydrology and Earth System Sciences 16 (4), 1171-1189, 2012
Prévision hydrologique par réseaux de neurones artificiels: état de l'art
P Coulibaly, F Anctil, B Bobée
Canadian Journal of civil engineering 26 (3), 293-304, 1999
Assessing the capability of the SWAT model to simulate snow, snow melt and streamflow dynamics over an alpine watershed
Y Grusson, X Sun, S Gascoin, S Sauvage, S Raghavan, F Anctil, ...
Journal of Hydrology 531, 574-588, 2015
Wavelet analysis of the interannual variability in southern Québec streamflow
F Anctil, P Coulibaly
Journal of climate 17 (1), 163-173, 2004
An exploration of artificial neural network rainfall-runoff forecasting combined with wavelet decomposition
F Anctil, DG Tape
Journal of Environmental Engineering and Science 3 (S1), S121-S128, 2004
A soil moisture index as an auxiliary ANN input for stream flow forecasting
F Anctil, C Michel, C Perrin, V Andréassian
Journal of Hydrology 286 (1-4), 155-167, 2004
Neural network estimation of air temperatures from AVHRR data
JD Jang, AA Viau, F Anctil
International Journal of Remote Sensing 25 (21), 4541-4554, 2004
Air–water momentum flux observations over shoaling waves
F Anctil, MA Donelan
Journal of physical oceanography 26 (7), 1344-1353, 1996
Eddy-correlation measurements of air-sea fluxes from a discus buoy
F Anctil, MA Donelan, WM Drennan, HC Graber
Journal of Atmospheric and Oceanic technology 11 (4), 1144-1150, 1994
Can a multi-model approach improve hydrological ensemble forecasting? A study on 29 French catchments using 16 hydrological model structures
JA Velazquez, F Anctil, MH Ramos, C Perrin
Advances in Geosciences 29, 33-42, 2011
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