Yonas B. Dibike

Yonas B. Dibike
Research Scientist

BSc (AWTI), MSc (IHE), PhD ((TU-Delft)



PhD - Technical University of Delft (TU-Delft), The Netherlands (2002) 
MSc - International Institute for Hydraulic and Environmental Engineering (IHE), Delft, The Netherlands (1997) 
BSc - Arbaminch Water Technology Institute (AWTI), Arbaminch, Ethiopia (1992)


  • Hydro-climate analysis and climate change impact studies
  • Statistical downscaling of global climate model outputs
  • Hydraulics, hydrologic and water resources modeling
  • Artificial neural networks for hydrologic modeling


  • Adjunct Associate Professor, Department of Geography, University of Victoria

Ongoing research activities

  • Hydro-climate analysis including downscaling of global climate model outputs
  • Impacts of climate variability and change on hydrology and water resources
  • Simulation of lake ice regimes in a changing climate
  • American Geophysical Union (AGU) - Member
  • Canadian Water Resources Association - Member
  • Canadian Geophysical Union (CGU) - Member
  • International Association of Hydrological Sciences (IAHS) - Member
  • Professional Engineers Ontario (PEO) - Registered
  • The Natural Science and Engineering Research Council Industrial Research Fellowship
  • Netherlands Research Studentship Program Post Graduate Scholarship
  • Netherlands Fellowship Program Graduate Scholarship
  • Irish Bilateral Aid Fellowship Program Graduate Scholarship
  • Lique, C., M. Holland, Y. Dibike, D. Lawrence, and J. Screen. 2015. Modeling the Arctic Freshwater System and its integration in the global system: Lessons learned and future challenges, in Arctic Freshwater Synthesis, Special Issues of JGR (DOI: 10.1002/2015JG003120)
  • Eum, H-I, Dibike, Y., Prowse, T. 2014. Uncertainty in Modelling the Hydrologic Responses of a Large Watershed:  A case of the Athabasca River Basin in Canada. CGU-HS special issue in Hydrologic Processes. 28(14):4272-4293, DOI: 10.1002/hyp.10230
  • Eum, H-I, Dibike, Y., Prowse, T., Bonsal, B. 2014. Intercomparison of high-resolution gridded climate data sets and their implication on hydrological model simulation over the Athabasca Watershed in Canada. CGU-HS special issue in Hydrologic Processes. 28(14):4250-4271, DOI: 10.1002/hyp.10236
  • Dibike, Y., T. Prowse, R. Shrestha and R. Ahmed. 2012. Observed Trends and Future Projections of Precipitation and Air Temperature in the Lake Winnipeg Watershed. Journal of Great Lakes Research, Special Issue: Lake Winnipeg - The Forgotten Great Lake. 38:72-82.
  • Shrestha, R.R., Y.B. Dibike and T.D. Prowse. 2012. Modelling of climate-induced hydrologic changes in the Lake Winnipeg Watershed.Journal of Great Lakes Research, Special Issue: Lake Winnipeg, The Forgotten Great Lake. 38:83-94
  • Shrestha, R.R., Y.B. Dibike and T.D. Prowse. 2012. Modelling climate change impacts on hydrology and nutrient loading in the upper Assiniboine Catchment. Journal of the American Water Resources Association. 48(1):74-89
  • Dibike, Y.B., Prowse, T., Bonsal, B., de Rham, L. and Saloranta, T. (2011) Simulation of North American Lake-ice Cover Characteristics under Contemporary and Future Climate Conditions, International Journal of Climatology, doi:10.1002/joc.2300
  • Dibike, Y.B., Prowse, T., Saloranta, T. and Ahmed R. (2011) Response of Northern Hemisphere Lake-Ice Cover and Lake-Water Thermal Structure Patterns to a Changing Climate, Hydrological Processes, doi:10.1002/hyp.8068
  • Dibike, Y.B., Prowse, T., Shrestha R. and Ahmed, R. (2011). Observed Trends and Future Projections of Precipitation and Temperatures in the Lake Winnipeg Watershed, Journal of Great Lakes Research, special issue on Lake Winnipeg – the Forgotten Great Lake, doi:10.1016/j.jglr.2011.04.005.
  • Shrestha R, Dibike, Y.B., and Prowse, T. (2011). Modeling of climate-induced hydrologic changes in Lake Winnipeg Watersheds, Journal of Great Lakes Research, special issue on Lake Winnipeg – the Forgotten Great Lake, doi:10.1016/j.jglr.2011.02.004
  • Shrestha R, Dibike, Y.B., and Prowse, T. (2011). Modelling Climate Change Impacts on Hydrology and Nutrient Loading in the Upper Assiniboine Catchments, Journal of the American Water Resources Association (JAWRA) 48(1):74-89. DOI: 10.1111/j.1752-1688.2011.00592.x
  • Sharma, M., Coulibaly, P., Dibike, Y. B. (2010). Assessing the need for downscaling RCM data for hydrologic impact study. ASCE Journal of Hydrologic Engineering,doi:10.1061/(ASCE)HE.1943-5584.0000349
  • Prowse, T., R. Shrestha, B. Bonsal, and Y. Dibike (2010), Changing spring air-temperature gradients along large northern rivers: Implications for severity of river-ice floods, Geophys. Res. Lett., 37(L19706), 6 PP.,doi:10.1029/2010GL044878.
  • Prowse, T.D., de Rham, L., Dibike, Y., 2008. Predicting Lake and River Ice: Modelling of Historic and Future Conditions. Ice and Climate News, 10: 8-9.
  • Dibike Y. B. and Coulibaly P., 2008. TDNN with logical values for hydrologic modeling in a cold and snowy climate, Journal of Hydroinformatics, Vol 10, No 4, pp 289–300.
  • Quilbé R., A.N. Rousseau, J.-S. Moquet, N.B. Trinh, Y. Dibike, P. Gachon, D. Chaumont (2008) : Assessing the effect of climate change on river flow using general circulation models and hydrological modelling – Application to the Chaudière River (Québec, Canada). Canadian Water Resource Journal, 33 (1): 73-93.
  • Dibike, Y.B., Gachon, P., St-Hilaire, A., Ouarda, T.B.M.J., Nguyen, V.T.-V., 2008. Uncertainty analysis of statistically downscaled temperature and precipitation regimes in Northern Canada. Theoretical and Applied Climatology, 91(1-4): 149-170.
  • Dibike Y. B. and Coulibaly P. (2007) Validation of Hydrologic Models for Climate Scenario Simulation:  The Case of Saguenay Watershed in Québec, Hydrological Processes, 21(23): pp. 3123-3135.
  • Gachon P. and Dibike Y. B. (2007) Temperature change signals in northern Canada: Convergence of statistical downscaling results using two driving GCMs, International Journal of Climatology, 27(12): pp. 1623-1641.
  • Dibike Y. B. and Coulibaly P., 2006.  Temporal Neural Networks for Downscaling Climate Variability and Extremes, Neural Networks (Especial issue on Earth Sciences and Environmental Applications of Computational Intelligence), Vol. 19, No. 2, pp. 135-144.
  • Khan M.S., Coulibaly P. and Dibike Y., 2006. Uncertainty Analysis of Statistical Downscaling Methods, Journal of Hydrology, 319(1-4):357-382
  • Khan M.S., Coulibaly P. and Dibike Y., 2006. Uncertainty analysis of statistical downscaling methods using Canadian Global Climate Model predictors, Hydrological Processes, 20(14): pp. 3085-3104.
  • Dibike Y. B. and Coulibaly P., 2005. Hydrologic Impact of Climate Change in the Saguenay Watershed: Comparison of Downscaling Methods and Hydrologic Models, Journal of Hydrology, 307(1-4):145-163 
  • Coulibaly P., Dibike, Y. B. and Anctil, F., 2005. Downscaling Precipitation and Temperature with Temporal Neural Networks.  Journal of Hydrometeorology, Vol. 6, No. 4, pp 483–496.
  • Lobbrecht A.H., Dibike Y.B., and Solomatine, D.P., 2005. Artificial Neural Networks and Fuzzy Logic Systems for Model Based Control: Application to the Water System of Overwaard, ASCE Journal of water resources planning and management, Vol. 131, No. 2, pp. 135- 145.
  • Dibike, Y.B., 2002, Developing generic hydrodynamic models using artificial neural networks, Journal of Hydraulic Research, Vol.40, No.2 pp. 183-190.
  • Dibike Y.B., Velickov S., Solomatine D. and Abbott M.B., 2001, Model Induction with Support Vector Machines: Introduction and Applications,  ASCE Journal of Computing in Civil Engineering, Vol. 15, No. 3, pp. 208- 216.
  • Dibike Y.B. and Solomatine D., 2001, River Flow Forecasting Using Artificial Neural Networks, Journal of Physics and Chemistry of the Earth, Part B: Hydrology, Oceans and Atmosphere, Vol. 26, No.1, pp. 1-8
  • Solomatine D., Dibike Y.B. and Kukuric, N. 2000. Automatic calibration of groundwater models using global optimization techniques, In the Journal of Hydrological Sciences, Vol. 44, No. 6, pp. 879-893.
  • Dibike Y.B. and Abbott, M.B. 1999. Application of artificial neural networks to the simulation of a two dimensional flow, Journal of Hydraulic Research, Vol. 37, No. 4, pp. 435-446.
  • Dibike, Y.B., Minns, A.W. and Abbott, M.B. 1999. Application of artificial neural networks to the generation of wave equations from hydraulic data, Journal of Hydraulic Research, Vol.37, No.1 pp. 81-97.
  • Dibike, Y.B. Solomatine, D. and Abbott, M.B. 1999. On the encapsulation of numerical-hydraulic models in artificial neural network, Journal of Hydraulic Research, Vol.37, No.2 pp. 147-161.
  • Coulibaly P. and Dibike, Y. B., 2004. Downscaling of Global Climate Model Outputs for Flood Frequency Analysis in the Saguenay River System, Project report to the Science Sub-Component of Climate Change Action Fund, Environment Canada.
  • Lobbrecht A.H., Dibike Y.B., and Solomatine, D.P., 2002. Use of Artificial Neural Networks and Fuzzy Logic for Integrated Water Management, Project report to Stichting Toege- past Onderzoek Waterbeheer (STOWA), The Netherlands.
  • Dibike, Y.B., Prowse, T., Saloranta, T. and Ahmed, R., 2010. Evolution of Northern Hemisphere Lake-Ice Characteristics and Thermal Structures in a Changing Climate, 20th IAHR International Symposium on Ice, June 14 to 18, 2010, Lahti, Finland
  • Shrestha R., Dibike Y.B. and Prowse, T., 2010. Modelling Climate Impacts on Hydrologic Processes in the Lake Winnipeg Watershed, 2010 International Congress on Environmental Modelling and Software, Modelling for Environment’s Sake, Fifth Biennial Meeting, Ottawa, Canada
  • Shrestha R., Dibike, Y.B. and Prowse, T., 2009. Application of SWAT in hydrologic and Nutrient Transport Modeling of the Lake Winnipeg Watershed. Proceedings of the International SWAT Conference, August 5-7, 2009, Univ. of Colorado at Boulder, Colorado. USA.
  • Dibike Y. B, Shi, X. and Coulibaly P. 2006. Assessing climate change impact on design standards of hydraulic structures, Proceedings of the 7th International Conference on Hydroinformatics, 4th – 8th September, 2006, Nice, France.
  • Dibike Y. B. and Coulibaly P., 2005. Temporal Neural Networks for Downscaling Climate Variability and Extremes, Proceedings of the 2005 International Joint Conference on Neural Networks, July 31-August 4, 2005, Montreal, Canada
  • Dibike Y. B. and Coulibaly P., 2004. Downscaling Global Climate Model Outputs to Study the Hydrologic Impact of Climate Change, Proceedings of the 6th International Conference on Hydroinformatics, 21st– 24th June, 2004, Singapore
  • Dibike Y. B. and Coulibaly P., 2004. Hydrologic Impact of Climate Change in the Saguenay Watershed, proceedings of the 57th Canadian Water Resources Association Annual Congress, June 16 – 18, 2004, Montreal, Canada.
  • Dibike Y.B., Lobbrecht A.H., Solomatine, D.P., 2002.  Neural Network and Fuzzy Logic Technologies for Control of the Water System of Overwaard in the Netherlands, Proceedings of the 5th International Conference on Hydroinformatics, 1st– 5th July, 2002, Cardiff, UK,. Vol. 1, pp. 715-721,
  • Dibike Y.B. 2000, Machine learning paradigms for rainfall runoff modelling, Proceedings of the 4th International Conference on Hydroinformatics, 23rd – 27th July, 2000, Iowa, USA.
  • Hassan, K. I. and Dibike Y. B., 2000, Two-dimensional morphological modelling at the confluence of the Ganges and the Jamuna rivers for dredging and navigation, Proceedings of the Hydroinformatics-2000 conference, Iowa, U SA.
  • Xue, Y. and Dibike, Y.B., 2001, Flood forecasting mode for Huai River in China using time delay neural network, Proceedings of the XXIX IAHR congress, Beijing, China, Theme C, pp.59-66.
  • Maskey, S., Dibike, Y. B. Jonoski, A. and Solomatine, D. 2000, Groundwater model approximation with artificial neural network for selecting optimal pumping strategy for plume removal, Workshop proceedings In Artificial Intelligence Methods in Civil Engineering Applications, pp. 67-80.