Investigating the Role of Hydrological Model Parameter Uncertainties in Future Streamflow Projections
Publication: Journal of Hydrologic Engineering
Volume 25, Issue 10
Abstract
Calibrated hydrological models forced with the climate data from various climate models have been widely employed for future streamflow projection. But a major cause of concern in such an analysis has been the suite of uncertainties inherent in the modeling chain that begins from the climate models and ends with the hydrological models. The uncertainties contributed by the hydrological models have generally been given a lesser focus. In the present research, the contribution of the hydrological model parameter uncertainty has been investigated. The multiobjective evolutionary algorithm (MOEA) is employed for calibrating the hydrological model, the Soil and Water Assessment Tool (SWAT), developed for the Magpie River, located in Northern Ontario. The calibrated model was then forced with the data from an ensemble of six regional climate models for projecting the scenario streamflow and evaluating associated uncertainties. A significant variation in seasonal water availability is projected for the two scenario periods studied. The contribution of the hydrological model parameter uncertainty in the streamflow projection is found to be significant, lying in the range of 16%–83%, depending on the month.
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Data Availability Statement
The following data, models, or code generated or used during the study are available from the corresponding author by request: climate data (observed and gridded); the SWAT model for Magpie River; and the R code for climate model data processing. The R code for the SWAT model calibration and optimization are proprietary or confidential in nature and may only be provided with restrictions. The climate model data used during the study has been extracted from the NA-CORDEX dataset (Mearns 2017).
Acknowledgments
The present research is funded by the Natural Sciences and Engineering Research Council (NSERC) of Canada through the Discovery Grant program to the senior author. The first author’s research is also supported through the Ontario Graduate Scholarship and a University of Windsor scholarship. We acknowledge the World Climate Research Programme’s Working Group on Regional Climate, and the Working Group on Coupled Modelling, formerly the coordinating body of CORDEX and the responsible panel for CMIP5. We also thank the climate modeling groups (listed in Table 1) for producing and making available their model output for the present research on impact assessment. The authors would like to thank Dr. David Hadka and Dr. Patrick M. Reed for providing the executable code of Borg used in this research for the SWAT model calibration. The authors also extend their sincere thanks to the project authorities at Brookfield Renewable for sharing the streamflow data required for the hydrologic model development and holding discussions at various stages of this work.
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Information & Authors
Information
Published In
Journal of Hydrologic Engineering
Volume 25 • Issue 10 • October 2020
Copyright
© 2020 American Society of Civil Engineers.
History
Received: Feb 28, 2019
Accepted: May 11, 2020
Published online: Jul 28, 2020
Published in print: Oct 1, 2020
Discussion open until: Dec 28, 2020
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