Variational-Based Data Assimilation to Simulate Sediment Concentration in the Lower Yellow River, China
Publication: Journal of Hydrologic Engineering
Volume 21, Issue 5
Abstract
The heavy sediment load of the Yellow River makes it difficult to simulate sediment concentration using classic numerical models. In this paper, on the basis of the classic one-dimensional numerical model of open channel flow, a variational-based data assimilation method is introduced to improve the simulation accuracy of sediment concentration and to estimate parameters in sediment carrying capacity. In this method, a cost function is introduced first to determine the difference between the sediment concentration distributions and available field observations. A one-dimensional suspended sediment transport equation, assumed as a constraint, is integrated into the cost function. An adjoint equation of the data assimilation system is used to solve the minimum problem of the cost function. Field data observed from the Yellow River in 2013 are used to test the proposed method. When running the numerical model with the data assimilation method, errors between the calculations and the observations are analyzed. Results show that (1) the data assimilation system can improve the prediction accuracy of suspended sediment concentration; (2) the variational inverse data assimilation is an effective way to estimate the model parameters, which are poorly known in previous research; and (3) although the available observations are limited to two cross sections located in the central portion of the study reach, the variational-based data assimilation system has a positive effect on the simulated results in the portion of the model domain in which no observations are available.
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Acknowledgments
This project was supported by the National Natural Science Foundation of China (Grant Nos. 51409113 and 51479081), the National Basic Research and Development Program of China (973 Program, Grant No. 2011CB403306), and the Ministry of Water Resources’ Special Funds for Scientific Research on Public Causes (201301062).
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Published In
Journal of Hydrologic Engineering
Volume 21 • Issue 5 • May 2016
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This work is made available under the terms of the Creative Commons Attribution 4.0 International license, http://creativecommons.org/licenses/by/4.0/.
History
Received: May 11, 2015
Accepted: Nov 7, 2015
Published online: Feb 24, 2016
Published in print: May 1, 2016
Discussion open until: Jul 24, 2016
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