Approaches reproducing suspended sediment transport through vegetation

Jiaqi Liu*, Francesco Bregoli, Alessandra Crosato, Giulio Calvani

*Corresponding author for this work

Research output: Contribution to conferenceAbstractScientific

46 Downloads (Pure)

Abstract

Working as natural filter, well-designed vegetation schemes have been widely applied to improve the quality of water (Aiona, 2013; Stefanakis, 2015). Proper design, however, requires appropriate physics-based modelling of their filtering capacity. Several theoretical models predicting sediment transport in vegetated flow have been proposed: Baptist (2005); Yang and Nepf (2018); Wu et. al. (2021); Tseng and Tinoco (2021); Yagci and Strom (2022); Wang et. al. (2023). Some of them have been implemented in numerical tools (e.g. Caponi et al., 2022; Li et al., 2022) and in particular in Delft 3D (Deltares, 2014). However, they have been mostly designed and verified based on bedload processes, and their performance for suspended load should be further investigated.
This work compares different approaches on their ability to reproduce the effects of vegetation on suspended solids concentration in two-dimensional models built in Delft3D. The work focuses on emerging vegetation, represented as rigid cylinders, and sediment deposition. Comparisons are based on the ability to reproduce flume experiments available in the literature by analysing both flow field and sediment deposition results.
Original languageEnglish
Number of pages2
Publication statusPublished - 2024
EventNCR DAYS 2024: Tomorrow’s Rivers - Gaia, Wageningen University & Research campus, Wageningen, Netherlands
Duration: 28 Feb 202429 Feb 2024
https://ncr-web.org/events/ncr-days-2024/

Conference

ConferenceNCR DAYS 2024
Country/TerritoryNetherlands
CityWageningen
Period28/02/2429/02/24
Internet address

Keywords

  • suspended sediment transport
  • Delft 3D

Fingerprint

Dive into the research topics of 'Approaches reproducing suspended sediment transport through vegetation'. Together they form a unique fingerprint.

Cite this