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Recent Progresses of Shallow Water Hydro-sediment-morphodynamic Modelling: Improvement of Computational Efficiencies and Typical Applications

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1 Ocean College, Zhejiang University, Hangzhou, 310058, China

* Corresponding Author: Peng Hu. Email: email

The International Conference on Computational & Experimental Engineering and Sciences 2023, 25(2), 1-1. https://doi.org/10.32604/icces.2023.09880

Abstract

Shallow water hydro-sediment-morphodynamic modelling plays significant role in several aspects (e.g., river and estuarine engineering). In response to climate change and intense human activities, there have been dramatic changes in river water and sediment flux conditions, and thus sediment transport intensity and bed morphological evolution differs from traditional characteristics. These necessitates fully coupled shallow water hydro-sediment-morphodynamic modelling, which however may damage the computational efficiency. Here we report some progresses in developing a computationally efficient version of fully coupled shallow water hydro-sediment-morphodynamic model and its preliminary applications in bottle-neck navigational waterways of the Yangtze river.

Cite This Article

APA Style
Hu, P. (2023). Recent progresses of shallow water hydro-sediment-morphodynamic modelling: improvement of computational efficiencies and typical applications. The International Conference on Computational & Experimental Engineering and Sciences, 25(2), 1-1. https://doi.org/10.32604/icces.2023.09880
Vancouver Style
Hu P. Recent progresses of shallow water hydro-sediment-morphodynamic modelling: improvement of computational efficiencies and typical applications. Int Conf Comput Exp Eng Sciences . 2023;25(2):1-1 https://doi.org/10.32604/icces.2023.09880
IEEE Style
P. Hu, “Recent Progresses of Shallow Water Hydro-sediment-morphodynamic Modelling: Improvement of Computational Efficiencies and Typical Applications,” Int. Conf. Comput. Exp. Eng. Sciences , vol. 25, no. 2, pp. 1-1, 2023. https://doi.org/10.32604/icces.2023.09880



cc Copyright © 2023 The Author(s). Published by Tech Science Press.
This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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