Bayesian Uncertainty Analysis of the Distributed Hydrological Model HYDROTEL
Publication: Journal of Hydrologic Engineering
Volume 17, Issue 9
Abstract
In this study, a Bayesian, inference-based, Markov chain Monte Carlo (MCMC) method coupled with an autoregressive moving average (ARMA) error model framework was used to assess the uncertainty of the process-based, continuous, distributed hydrological model HYDROTEL when simulating daily streamflows. The uncertainty analysis was performed, as a case study, in two distinct watersheds (Montmorency, Quebec, Canada, and Sassandra, Ivory Coast, West Africa). The MCMC uncertainty analysis showed to be effective, primarily with respect to the fulfillment of the statistical assumptions of the error model. The results of the uncertainty analyses demonstrated that almost 95% of the observed daily outlet flows were bracketed by the 95% prediction uncertainty bands. This indicates that the parameter uncertainty associated with the ARMA error model could reach the prediction uncertainty. It was possible to mimic the prediction uncertainty using only the most sensitive model parameters for the Montmorency and Sassandra watersheds. The uncertainty framework, as presented herein, may be applied to any distributed, continuous, hydrological model such as HYDROTEL. Given sufficient computational resources, such framework could become quite useful in providing uncertainty bands within the scope of predicting inflows to reservoirs for subsequent planning and management purposes.
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Acknowledgments
The authors would like to thank the reviewers and the editors for the attention and time they took to review the manuscript. Their comments and questions were very useful in improving the initial version of the paper. The authors would like to acknowledge the contributions of Jin Yang of Singapore-MIT Alliance for Research & Technology (SMART); Alain Mailhot, Alain Royer and Stéphane Savary of INRS-ETE; and Richard Turcotte of the Centre d’Expertise Hydrique du Québec. Financial support was provided by Hydro-Québec, Ouranos, NSERC (Natural Sciences and Engineering Research Council of Canada), and Agriculture and Agrifood Canada.
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Published In
Journal of Hydrologic Engineering
Volume 17 • Issue 9 • September 2012
Pages: 1021 - 1032
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© 2012 American Society of Civil Engineers.
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Received: Sep 5, 2010
Accepted: Dec 5, 2011
Published online: Dec 7, 2011
Published in print: Sep 1, 2012
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