Articles | Volume 15, issue 7
https://doi.org/10.5194/gmd-15-2917-2022
https://doi.org/10.5194/gmd-15-2917-2022
Development and technical paper
 | 
07 Apr 2022
Development and technical paper |  | 07 Apr 2022

Modeling of streamflow in a 30 km long reach spanning 5 years using OpenFOAM 5.x

Yunxiang Chen, Jie Bao, Yilin Fang, William A. Perkins, Huiying Ren, Xuehang Song, Zhuoran Duan, Zhangshuan Hou, Xiaoliang He, and Timothy D. Scheibe

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Cited articles

Alfieri, L., Lorini, V., Hirpa, F. A., Harrigan, S., Zsoter, E., Prudhomme, C., and Salamon, P.: A global streamflow reanalysis for 1980–2018, J. Hydrol. X, 6, 100049, https://doi.org/10.1016/j.hydroa.2019.100049, 2020. a
Bao, J., Zhou, T., Huang, M., Hou, Z., Perkins, W., Harding, S., Titzler, S., Hammond, G., Ren, H., Thorne, P., Suffield, S., Murray, C., and Zachara, J.: Modulating factors of hydrologic exchanges in a large‐scale river reach: Insights from three‐dimensional computational fluid dynamics simulations, Hydrol. Process., 32, 3446–3463, https://doi.org/10.1002/hyp.13266, 2018. a, b
Bao, J., Chen, Y., Fang, Y., Song, X., Perkins, W., Duan, Z., Shuai, P., Ren, H., Hou, Z., Richmond, M., He, X., and Scheibe, T.: Modeling framework for evaluating the impacts of hydrodynamic pressure on hydrologic exchange fluxes and residence time for a large-scale river section over a long-term period, Environ. Modell. Softw., 148, 105277, https://doi.org/10.1016/j.envsoft.2021.105277, 2022. a, b
Bates, P. D., Anderson, M. G., and Hervouet, J. M.: Initial comparison of two two-dimensional finite element codes for river flood simulation, P. I. Civil Eng.-Water, 112, 238–248, https://doi.org/10.1680/iwtme.1995.27886, 1995. a
Bates, P. D., Lane, S. N., and Ferguson, R. I.: Computational fluid dynamics: applications in environmental hydraulics, edited by: Bates, P. D., Lane, S. N., and Ferguson, R. I., John Wiley & Sons, Ltd, Chichester, UK, https://doi.org/10.1002/0470015195, 2005. a
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Short summary
Climate change affects river discharge variations that alter streamflow. By integrating multi-type survey data with a computational fluid dynamics tool, OpenFOAM, we show a workflow that enables accurate and efficient streamflow modeling at 30 km and 5-year scales. The model accuracy for water stage and depth average velocity is −16–9 cm and 0.71–0.83 in terms of mean error and correlation coefficients. This accuracy indicates the model's reliability for evaluating climate impact on rivers.
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