World's Best Scientists 2026 revealed!
François Anctil

François Anctil

D-Index & Metrics

Environmental Sciences

D-Index
49
Citations
11276
World Ranking
5165
National Ranking
217

François Anctil publication distribution in Environmental Sciences in 2026

The chart shows the distribution of publications by all Research.com ranked scientists in the field of Environmental Sciences in 2026. The highlighted bar marks where François Anctil sits on this spectrum.

41–50 publications: 21 scientists 51–60 publications: 62 scientists 61–70 publications: 133 scientists 71–80 publications: 257 scientists 81–90 publications: 361 scientists 91–100 publications: 440 scientists 101–110 publications: 492 scientists 111–120 publications: 541 scientists 121–130 publications: 617 scientists 131–140 publications: 544 scientists 141–150 publications: 541 scientists 151–160 publications: 539 scientists 161–170 publications: 444 scientists 171–180 publications: 444 scientists 181–190 publications: 400 scientists 191–200 publications: 377 scientists 201–210 publications: 318 scientists 211–220 publications: 283 scientists 221–230 publications: 263 scientists 231–240 publications: 220 scientists 241–250 publications: 217 scientists 251–260 publications: 180 scientists 261–270 publications: 181 scientists 271–280 publications: 155 scientists 281–290 publications: 130 scientists 291–300 publications: 127 scientists 301–310 publications: 130 scientists 311–320 publications: 85 scientists 321–330 publications: 106 scientists 331–340 publications: 80 scientists 341–350 publications: 83 scientists 351–360 publications: 75 scientists 361–370 publications: 69 scientists 371–380 publications: 52 scientists 381–390 publications: 54 scientists 391–400 publications: 56 scientists 401–410 publications: 44 scientists 411–420 publications: 40 scientists 421–430 publications: 36 scientists 431–440 publications: 25 scientists 441–450 publications: 25 scientists 451–460 publications: 32 scientists 461–470 publications: 29 scientists 471–480 publications: 21 scientists 481–490 publications: 26 scientists 491–500 publications: 25 scientists 501–510 publications: 17 scientists 511–520 publications: 18 scientists 521–530 publications: 15 scientists 531–540 publications: 22 scientists 541–550 publications: 12 scientists 551–560 publications: 15 scientists 561–570 publications: 11 scientists 571–580 publications: 19 scientists 581–590 publications: 9 scientists 591–600 publications: 9 scientists 601–610 publications: 7 scientists 611–620 publications: 11 scientists 621–630 publications: 5 scientists 631–640 publications: 5 scientists 641–650 publications: 6 scientists 651–660 publications: 3 scientists 661–670 publications: 3 scientists 671–680 publications: 4 scientists 681–686 publications: 3 scientists 687+ publications: 100 scientists
41 publications 687+

This scientist: 249 publications — 77th percentile

77% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 687 publications or more.

François Anctil D-index placement in Environmental Sciences in 2026

The chart shows the D-index (discipline H-index) distribution of Environmental Sciences scientists ranked by Research.com in 2026. The highlighted bar marks where François Anctil sits on this spectrum.

30 D-Index: 12 scientists 31 D-Index: 26 scientists 32 D-Index: 51 scientists 33 D-Index: 88 scientists 34 D-Index: 123 scientists 35 D-Index: 163 scientists 36 D-Index: 206 scientists 37 D-Index: 267 scientists 38 D-Index: 265 scientists 39 D-Index: 275 scientists 40 D-Index: 321 scientists 41 D-Index: 343 scientists 42 D-Index: 305 scientists 43 D-Index: 336 scientists 44 D-Index: 330 scientists 45 D-Index: 348 scientists 46 D-Index: 291 scientists 47 D-Index: 275 scientists 48 D-Index: 272 scientists 49 D-Index: 273 scientists 50 D-Index: 263 scientists 51 D-Index: 232 scientists 52 D-Index: 266 scientists 53 D-Index: 217 scientists 54 D-Index: 199 scientists 55 D-Index: 177 scientists 56 D-Index: 202 scientists 57 D-Index: 204 scientists 58 D-Index: 166 scientists 59 D-Index: 177 scientists 60 D-Index: 166 scientists 61 D-Index: 152 scientists 62 D-Index: 143 scientists 63 D-Index: 150 scientists 64 D-Index: 124 scientists 65 D-Index: 119 scientists 66 D-Index: 120 scientists 67 D-Index: 118 scientists 68 D-Index: 82 scientists 69 D-Index: 98 scientists 70 D-Index: 94 scientists 71 D-Index: 105 scientists 72 D-Index: 74 scientists 73 D-Index: 84 scientists 74 D-Index: 70 scientists 75 D-Index: 67 scientists 76 D-Index: 78 scientists 77 D-Index: 60 scientists 78 D-Index: 59 scientists 79 D-Index: 52 scientists 80 D-Index: 47 scientists 81 D-Index: 38 scientists 82 D-Index: 48 scientists 83 D-Index: 42 scientists 84 D-Index: 42 scientists 85 D-Index: 43 scientists 86 D-Index: 29 scientists 87 D-Index: 37 scientists 88 D-Index: 29 scientists 89 D-Index: 30 scientists 90 D-Index: 34 scientists 91 D-Index: 20 scientists 92 D-Index: 22 scientists 93 D-Index: 17 scientists 94 D-Index: 19 scientists 95 D-Index: 24 scientists 96 D-Index: 21 scientists 97 D-Index: 20 scientists 98 D-Index: 24 scientists 99 D-Index: 17 scientists 100 D-Index: 17 scientists 101 D-Index: 21 scientists 102 D-Index: 25 scientists 103 D-Index: 18 scientists 104 D-Index: 26 scientists 105 D-Index: 19 scientists 106 D-Index: 15 scientists 107 D-Index: 10 scientists 108 D-Index: 13 scientists 109 D-Index: 15 scientists 110 D-Index: 12 scientists 111 D-Index: 8 scientists 112 D-Index: 7 scientists 113 D-Index: 9 scientists 114 D-Index: 6 scientists 115 D-Index: 12 scientists 116 D-Index: 7 scientists 117 D-Index: 8 scientists 118 D-Index: 3 scientists 119 D-Index: 5 scientists 120 D-Index: 7 scientists 121 D-Index: 2 scientists 122 D-Index: 4 scientists 123 D-Index: 8 scientists 124 D-Index: 7 scientists 125+ D-Index: 99 scientists
30 D-Index 125+

This scientist: 49 D-Index — 47th percentile

47% of scientists in this discipline score the same or lower.

The last bar groups every scientist with 125 D-Index or more.

Overview

François Anctil is affiliated with Université Laval in Canada and has a research focus primarily in Environmental Science and Earth and Planetary Sciences. Their work encompasses several subfields including Atmospheric Science, Global and Planetary Change, Water Science and Technology, Environmental Engineering, and Ecology.

The scientist's research topics cover various aspects of hydrology and watershed management, cryospheric studies and observations, climate change and permafrost, plant water relations and carbon dynamics, flood risk assessment and management, hydrology and drought analysis, and climate variability and models.

They have contributed to numerous publications in a range of journals. Frequent publication venues include:

  • Hydrology and Earth System Sciences
  • Journal of Hydrometeorology
  • Zenodo (CERN European Organization for Nuclear Research)
  • Water
  • Hydrological Processes

Recent notable papers include:

  • Using bias correction and ensemble modelling for predictive mapping and related uncertainty: A case study in digital soil mapping, 2021, Geoderma
  • Uncertainty Analysis of a 1D River Hydraulic Model with Adaptive Calibration, 2020, Water
  • Choosing between post-processing precipitation forecasts or chaining several uncertainty quantification tools in hydrological forecasting systems, 2022, Hydrology and Earth System Sciences
  • Exploring the spatiotemporal variability of the snow water equivalent in a small boreal forest catchment through observation and modelling, 2020, Hydrological Processes
  • Asynchronous Hydroclimatic Modeling for the Construction of Physically Based Streamflow Projections in a Context of Observation Scarcity, 2020, Frontiers in Earth Science

Their collaborative network includes frequent co-authors such as:

  • Daniel F. Nadeau
  • Antoine Thiboult
  • Pierre-Erik Isabelle
  • Jean-Daniel Sylvain
  • Annie-Claude Parent

Best Publications

  • Which potential evapotranspiration input for a lumped rainfall-runoff model?. Part 2: Towards a simple and efficient potential evapotranspiration model for rainfall-runoff modelling

    Ludovic Oudin;Frédéric Hervieu;Claude Michel;Charles Perrin

  • Daily reservoir inflow forecasting using artificial neural networks with stopped training approach

    P. Coulibaly;F. Anctil;B. Bobée

  • Artificial neural network modeling of water table depth fluctuations

    Paulin Coulibaly;François Anctil;Ramon Aravena;Bernard Bobée

  • Two decades of anarchy? Emerging themes and outstanding challenges for neural network river forecasting

    Robert J. Abrahart;François Anctil;Paulin Coulibaly;Christian W. Dawson

  • Why Should Ensemble Spread Match the RMSE of the Ensemble Mean

    V. Fortin;M. Abaza;F. Anctil;R. Turcotte

  • Downscaling Precipitation and Temperature with Temporal Neural Networks

    Paulin Coulibaly;Yonas B. Dibike;François Anctil

  • Comparing Sigmoid Transfer Functions for Neural Network Multistep Ahead Streamflow Forecasting

    H. Yonaba;H. Yonaba;F. Anctil;F. Anctil;V. Fortin;V. Fortin

  • Multivariate Reservoir Inflow Forecasting Using Temporal Neural Networks

    Paulin Coulibaly;François Anctil;Bernard Bobée

  • Which potential evapotranspiration input for a lumped rainfall-runoff model?. Part 1—Can rainfall-runoff models effectively handle detailed potential evapotranspiration inputs?

    Ludovic Oudin;Claude Michel;François Anctil

  • Impact of the length of observed records on the performance of ANN and of conceptual parsimonious rainfall-runoff forecasting models

    François Anctil;Charles Perrin;Vazken Andréassian

  • Assessing the capability of the SWAT model to simulate snow, snow melt and streamflow dynamics over an alpine watershed

    Youen Grusson;Youen Grusson;Xiaoling Sun;Xiaoling Sun;Simon Gascoin;Sabine Sauvage;Sabine Sauvage

  • Wavelet Analysis of the Interannual Variability in Southern Quebec Streamflow

    François Anctil;Paulin Coulibaly

  • An exploration of artificial neural network rainfall-runoff forecasting combined with wavelet decomposition

    François Anctil;Doha Guy Tape

  • A soil moisture index as an auxiliary ANN input for stream flow forecasting

    François Anctil;Claude Michel;Charles Perrin;Vazken Andréassian

  • Multimodel evaluation of twenty lumped hydrological models under contrasted climate conditions

    G. Seiller;F. Anctil;C. Perrin

  • Neural network estimation of air temperatures from AVHRR data

    J.-D. Jang;A. A. Viau;F. Anctil

  • Air Water Momentum Flux Observations over Shoaling waves

    F. Anctil;M. A. Donelan

  • Prévision hydrologique par réseaux de neurones artificiels : état de l'art

    Paulin Coulibaly;François Anctil;Bernard Bobée

  • Can a multi-model approach improve hydrological ensemble forecasting? A study on 29 French catchments using 16 hydrological model structures

    J. A. Velázquez;F. Anctil;M. H. Ramos;C. Perrin

  • Eddy-correlation measurements of air-sea fluxes from a discus buoy

    François Anctil;Mark A. Donelan;William M. Drennan;Hans C. Graber

  • Evaluation of streamflow simulation by SWAT model for two small watersheds under snowmelt and rainfall

    Étienne Lévesque;François Anctil;Ann Van Griensven;Nicolas Beauchamp

Frequent Co-Authors

Paulin Coulibaly
Paulin Coulibaly McMaster University
Peter A. Vanrolleghem
Peter A. Vanrolleghem Université Laval
Charles Perrin
Charles Perrin University of Paris-Saclay
Sabine Sauvage
Sabine Sauvage Paul Sabatier University
Vazken Andréassian
Vazken Andréassian University of Paris-Saclay
Ludovic Oudin
Ludovic Oudin Sorbonne University
Simon Gascoin
Simon Gascoin Centre d'Etudes Spatiales de la BIOsphère
Robert L. Wilby
Robert L. Wilby Loughborough University
Mark A. Donelan
Mark A. Donelan University of Miami
Thomas Kätterer
Thomas Kätterer Swedish University of Agricultural Sciences

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