Abstract
The estimation of hydrometric rating curves uncertainty has constituted an active topic of research on hydrology. In this regard, the BaRatin inference framework, which estimates rating curves on the basis of prior hydraulic knowledge, has been considered a promising alternative. In building inference setups, a variety of structural error models have been combined with BaRatin. However, most of them neglect the potentially high scatter levels in the lower portion of rating curves, caused by changes in the channel bottom. For addressing this issue, in this paper we propose a Gaussian heteroscedastic structural error model, which attributes larger uncertainty for both upper and lower portions of the rating curve. The inference framework was applied to two catchments in Brazil with distinct hydraulic controls and channel bed stability conditions. Results demonstrated that, under the proposed error model, the total uncertainty intervals encompassed most measured large flows and even relatively high scatters of low discharges, which suggest the overall suitability of the proposed modeling strategy and its capacity to achieve more realistic intervals of uncertainty.
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Data Availability Statement
Some or all data, models, or code generated or used during the study are available from the corresponding author by request.
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The rating-curve Bayesian calibration code is available at R programming language.
Acknowledgments
The authors wish to thank the agencies FAPEMIG—“Fundação de Amparo à Pesquisa do Estado de Minas Gerais”, CAPES—Coordenação de Aperfeiçoamento de Pessoal de Nível Superior” and CNPq (“Conselho Nacional de Desenvolvimento Científico e Tecnológico”) for their financial support of this research. The authors also wish to acknowledge the anonymous reviewers and editors for their valuable comments and suggestions, which greatly improved the paper.
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©2020 American Society of Civil Engineers.
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Received: Apr 1, 2019
Accepted: Oct 29, 2019
Published online: Feb 26, 2020
Published in print: May 1, 2020
Discussion open until: Jul 26, 2020
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