Diagnostic Evaluation of Hydrologic Models Employing Flow Duration Curve
Publication: Journal of Hydrologic Engineering
Volume 24, Issue 6
Abstract
The assessment of water availability using hydrological models is subject to modeling uncertainties. Model performance evaluation based on conventional likelihood measures on an overall time-series simulation has shortcomings. To overcome this, a model diagnostic evaluation is carried out. The main objectives of the study are to (a) demonstrate the strength of the model diagnostic assessment, (b) formulate an improved likelihood measure through a flow duration curve (FDC)–based flow portioning to enhance model performance, and (c) correlate the model simulation to basin hydroclimatic features. The objectives are achieved through the use of a conceptual rainfall-runoff model within a generalized likelihood uncertainty estimation (GLUE) framework applied on 17 basins in the Southeastern United States. The results indicate that the diagnostic assessment is crucial in model evaluation. The two-phase model assessment helped to improve model performance by 6% in terms of Nash–Sutcliffe efficiency for overall flow time series, 32% in terms of average volume efficiency, and 24% in terms of the ratio of the root-mean square error to the standard deviation of observation for the low flows.
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Acknowledgments
This research was funded by the Natural Sciences and Engineering Research Council (NSERC) of Canada through a Discovery grant to the senior authors. The first author was supported through an Ontario Graduate Scholarship.
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Journal of Hydrologic Engineering
Volume 24 • Issue 6 • June 2019
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©2019 American Society of Civil Engineers.
History
Received: Nov 29, 2017
Accepted: Nov 27, 2018
Published online: Mar 26, 2019
Published in print: Jun 1, 2019
Discussion open until: Aug 26, 2019
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