Sediment properties in the fluvial and estuarine environments of the Mekong River

Journal Article (2018)
Author(s)

Hoang-Anh Le (Université Catholique de Louvain, Ho Chi Minh City University of Technology (HCMUT))

Nicolas Gratiot (Institut de Recherche pour le Développement, Ho Chi Minh City University of Technology (HCMUT))

William Santini (Institut de Recherche pour le Développement)

Olivier Ribolzi (Université Paul Sabatier)

Sandra Soares-Frazão (Université Catholique de Louvain)

Eric Deleersnijder (TU Delft - Mathematical Physics, Université Catholique de Louvain)

Research Group
Mathematical Physics
DOI related publication
https://doi.org/10.1051/e3sconf/20184005063 Final published version
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Publication Year
2018
Language
English
Research Group
Mathematical Physics
Volume number
40
Article number
05063
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307
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Abstract

The Mekong river, located in Southeast Asia, is one of the largest rivers in the world. It is facing serious problems related to sediment transport, e.g. the reduction of sediment volume supply to the delta and estuary. This study focuses on the physical properties of suspended particles in the upstream fluvial section (Luang Prabang, Laos) and in the region of tidal influence (Song Hau estuary, Vietnam). These sites are respectively the upper and lower limits of the Lower Mekong River (LMR), which are experiencing contrasted transport modes. The main objective of this study is to quantify the proportion of inert sand and of cohesive particles in the water through comprehensive measurements of particle size, settling velocity and flocculation in the water column. Two field campaigns were undertaken in the summer monsoon season. The results point out the predominance of flocculi, with sizes of 18 ± 5 μm in the fluvial environment and 15 ± 5 μm in the estuary and the similarities in patterns, mixture of sand (12 ± 5 %) and mud (88 ± 5 %). They also provide a statistically representative set of suspended particle populations in the upstream and downstream regions that could be used for improving numerical models.