Chen, R., Shao, S. and Liu, X. (2015) Water–sediment flow modeling for field case studies in Southwest China. Natural Hazards. ISSN 0921-030X
Abstract
This paper presents a highly robust numerical model to simulate water–sediment mixture flows in practical field studies. The model is composed of an integrated algorithm combining the finite element characteristic splitting method and finite volume Godunov scheme. The former maintains the generality and stability of the numerical algorithm, while the latter ensures the conservation and accuracy of the model. The proposed model is first tested by three benchmark flow problems including flood flow in a pool, dam break over a mobile bed, and morphological process of a dam removal. Then, the model is applied to two practical field case studies to demonstrate its potential engineering values. The first case study is related to the damage of the Polo Hydropower Plant by a sediment flooding event. The second one is the investigation of a well-known 2013 dam-break flooding that happened in the Tangjiashan Mountain. It is shown that the simulated water and sediment flows are in good agreement with the documented laboratory and field data, and the numerical model is capable of providing useful information on the flow predictions, thus making further engineering measures to mitigate these disasters.
Metadata
Item Type: | Article |
---|---|
Authors/Creators: |
|
Copyright, Publisher and Additional Information: | © Springer Science+Business Media Dordrecht 2015. This is an author produced version of a paper subsequently published in Natural Hazards. Uploaded in accordance with the publisher's self-archiving policy. |
Dates: |
|
Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Civil and Structural Engineering (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 02 Jun 2015 15:29 |
Last Modified: | 30 Apr 2016 15:47 |
Published Version: | http://dx.doi.org/10.1007/s11069-015-1765-z |
Status: | Published |
Publisher: | Springer |
Refereed: | Yes |
Identification Number: | 10.1007/s11069-015-1765-z |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:86324 |