Toward Discharge Estimation for Water Resources Management with a Semidistributed Model and Local Ensemble Kalman Filter Data Assimilation
Publication: Journal of Hydrologic Engineering
Volume 26, Issue 2
Abstract
Estimating discharges is a major challenge in water resources management, and techniques such as data assimilation (DA) can be used to improve these estimates. This study assessed application of the local ensemble Kalman filter (LEnKF) DA scheme within a large-scale hydrological-hydrodynamic model to improve discharge estimates. Different scenarios with assimilation and validation gauges were performed to obtain an optimal setup of localization, ensemble size, assimilation parameters, and observation type (discharge or logarithm of discharge). These parameters were used to analyze the estimated discharge series and reference discharge values for maximum, minimum, and average flows. Results showed that joint perturbation of precipitation and groundwater reservoir volume leads to the most sensitive model responses. Furthermore, using the adequate setup of LEnKF parameters and assimilating the logarithm of discharge, better estimates of reference discharge values were obtained with the DA scheme when compared to a simple regionalization method, leading to reduction of errors of more than double in many cases.
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Data Availability Statement
The historical hydrologic and meteorological data are available from the Brazilian National Water Agency and the Brazilian National Institute of Meteorology. The model-simulated data and code are available from the corresponding author upon reasonable request.
Acknowledgments
The first author is grateful for a grant from the Brazilian agency CAPES (Grant No. PROEX–0487); the second author, for a grant from the CNPq Agency (Grant No. 141161/2017-5). This study was carried out as part of the SWOT-MOD project (https://swot.jpl.nasa.gov/st_projects.htm). The authors are grateful to the contributions of Vinícius Siqueira (M.Sc.) for data supply, and Professor Walter Collischonn for ideas and constructive comments. Thank go as well to Dr. Gaia Piazzi for contributions and to three anonymous reviewers for their comments and suggestions, which helped significantly in improving this article.
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Journal of Hydrologic Engineering
Volume 26 • Issue 2 • February 2021
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© 2020 American Society of Civil Engineers.
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Received: Mar 27, 2020
Accepted: Aug 20, 2020
Published online: Nov 24, 2020
Published in print: Feb 1, 2021
Discussion open until: Apr 24, 2021
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