Hydrologic Memory Patterns Assessment over a Drought-Prone Canadian Prairies Catchment
Publication: Journal of Hydrologic Engineering
Volume 20, Issue 7
Abstract
Understanding the persistence in land surface processes, such as that in the deep subsurface moisture storage, has great implications for seasonal weather prediction over a drainage basin. The Canadian Prairies is a region of intense and recurrent drought outbreaks with myriad negative impacts on the regional ecosystem as well as on all sectors of the Prairies’ economy due to high mitigation costs associated with these frequent outbreaks. Given that there are neither physical observations of soil moisture at depths of hydrological importance nor measurements of the total water storage over drought-prone Canadian Prairies subcatchments, this places constraints on studies that focus on the assessments of the interrelationship between the land surface and atmospheric processes. This study focuses on the estimation of the memory in the simulated deep soil moisture and total water storages over the Saskatchewan River Basin (SRB) in the Canadian Prairies using a physically based land surface model. The variable infiltration capacity (VIC) hydrological model was developed and deployed in simulating the deep soil moisture in conjunction with the total water storage over this large catchment. In developing a suitable hydrological model for the SRB, parameters estimated from the calibrated and validated hydrological model for the adjacent Upper Assiniboine River Basin (UARB) were transferred. Subsequently, the memory in the anomalies associated with the meteorological variables, simulated deep moisture and total water storage components in conjunction with the computed terrestrial storage deficit indices (TSDIs) estimated from the gravity recovery and climate experiment (GRACE) remote-sensing satellite system and the VIC model were assessed. Given the degree of agreement in the estimated memory associated with the hydrologic model-based terrestrial storage deficit indices with those estimated for the simulated deep moisture storage anomalies over this catchment, this study concludes that the latter could also be used in characterizing the severity of frequent Canadian Prairies droughts.
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Acknowledgments
The authors sincerely appreciate the Atlantic Computational Excellence Network (ACEnet). Computational facilities are provided by ACEnet, the regional high performance computing consortium for universities in Atlantic Canada. ACEnet is funded by the Canada Foundation for Innovation (CFI), the Atlantic Canada Opportunities Agency (ACOA), and the provinces of Newfoundland and Labrador, Nova Scotia, and New Brunswick. The authors are also grateful to Dr. Stefan Kern at the Integrated Climate Data Center (ICDC), University of Hamburg in Germany for the provision of the monthly means of the land surface temperature from the MODIS satellite system used in this study. Finally, the authors grateful acknowledge the financial support from Dillon Consulting Limited.
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Journal of Hydrologic Engineering
Volume 20 • Issue 7 • July 2015
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© 2014 American Society of Civil Engineers.
History
Received: Jun 29, 2013
Accepted: Sep 24, 2014
Published online: Nov 7, 2014
Discussion open until: Apr 7, 2015
Published in print: Jul 1, 2015
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