Hydrology and Earth System Sciences
Hydrology and Earth System Sciences
HESS
Articles | Volume 23, issue 6
Articles | Volume 23, issue 6
https://doi.org/10.5194/hess-23-2735-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-23-2735-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 23, issue 6
Research article
 | 
28 Jun 2019
Research article |  | 28 Jun 2019

Analysis of the effects of biases in ensemble streamflow prediction (ESP) forecasts on electricity production in hydropower reservoir management

Richard Arsenault and Pascal Côté

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Cited articles

Anghileri, D., Voisin, N., Castelletti, A., Pianosi, F., Nijssen, B., and Lettenmaier, D. P.: Value of long-term streamflow forecasts to reservoir operations for water supply in snow-dominated river catchments, Water Resour. Res., 52, 4209–4225, 2016. 
Arsenault, R., Malo, J., Brissette, F., Minville, M., and Leconte, R.: Structural and non-structural climate change adaptation strategies for the Péribonka water resource system, Water Resour. Manag., 27, 2075–2087, https://doi.org/10.1007/s11269-013-0275-6, 2013. 
Arsenault, R., Poulin, A., Côté, P., and Brissette, F.: A comparison of stochastic optimization algorithms in hydrological model calibration, J. Hydrol. Eng., 19, 1374–1384, https://doi.org/10.1061/(ASCE)HE.1943-5584.0000938, 2014. 
Arsenault, R., Latraverse, M., and Duchesne, T.: An efficient method to correct under-dispersion in ensemble streamflow prediction for seasonal volumetric forecasting, Water Resour. Manag., 30, 4363–4380, https://doi.org/10.1007/s11269-016-1425-4, 2016. 
Boucher, M. A., Tremblay, D., Delorme, L., Perreault, L., and Anctil, F.: Hydro-economic assessment of hydrological forecasting systems, J. Hydrol., 416, 133–144, https://doi.org/10.1016/j.jhydrol.2011.11.042, 2012. 
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Hydrological forecasting allows hydropower system operators to make the most efficient use of the available water as possible. Accordingly, hydrologists have been aiming at improving the quality of these forecasts. This work looks at the impacts of improving systematic errors in a forecasting scheme on the hydropower generation using a few decision-aiding tools that are used operationally by hydropower utilities. We find that the impacts differ according to the hydropower system characteristics.
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