A Sustainable Management-Oriented Model for Hydrodynamics and Pollutant Transport in Vegetated Seepage River Channels Using LBM-RDM

This study investigates the hydrodynamic characteristics and pollutant transport in vegetated seepage channels, with a particular focus on the impacts of seepage and vegetation density on flow velocity and pollutant dispersion. The primary innovation of this research lies in the novel integration of the Lattice Boltzmann Method (LBM) and the Random Displacement Method (RDM) to establish a numerical model for simulating vertical flow velocity and pollutant transport in such channels. To enhance simulation accuracy, the sediment bed was treated as a porous medium. The findings reveal that higher seepage rates significantly increase pollutant infiltration, and denser vegetation further amplifies this effect by enhancing turbulent diffusion and mechanical dispersion within the vegetated zone. These insights are critical for sustainable groundwater protection and the design of vegetated buffer zones in river management. Furthermore, treating the sediment layer as a porous medium yielded more accurate flow velocity predictions. These results provide new insights into the complex interactions between seepage, vegetation, and pollutant transport, and offer a valuable theoretical basis for optimizing sustainable vegetation planting schemes and management practices in vegetated seepage rivers to protect groundwater quality.

Authors

Institutions

Publication Details

Journal
Sustainability
Published
2025-11-13
DOI
https://doi.org/10.3390/su172210138
Primary Topic
Lattice Boltzmann Simulation Studies
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A Sustainable Management-Oriented Model for Hydrodynamics and Pollutant Transport in Vegetated Seepage River Channels Using LBM-RDM

Wenlong Tang, Weidong Xuan, Yu Bai
Sustainability
Lattice Boltzmann Simulation Studies
article

A Sustainable Management-Oriented Model for Hydrodynamics and Pollutant Transport in Vegetated Seepage River Channels Using LBM-RDM

Wenlong Tang, Weidong Xuan, Yu Bai
article en

Abstract

This study investigates the hydrodynamic characteristics and pollutant transport in vegetated seepage channels, with a particular focus on the impacts of seepage and vegetation density on flow velocity and pollutant dispersion. The primary innovation of this research lies in the novel integration of the Lattice Boltzmann Method (LBM) and the Random Displacement Method (RDM) to establish a numerical model for simulating vertical flow velocity and pollutant transport in such channels. To enhance simulation accuracy, the sediment bed was treated as a porous medium. The findings reveal that higher seepage rates significantly increase pollutant infiltration, and denser vegetation further amplifies this effect by enhancing turbulent diffusion and mechanical dispersion within the vegetated zone. These insights are critical for sustainable groundwater protection and the design of vegetated buffer zones in river management. Furthermore, treating the sediment layer as a porous medium yielded more accurate flow velocity predictions. These results provide new insights into the complex interactions between seepage, vegetation, and pollutant transport, and offer a valuable theoretical basis for optimizing sustainable vegetation planting schemes and management practices in vegetated seepage rivers to protect groundwater quality.

SustainabilityVol. 17(22)
Zhejiang University of Water Resource and Electric Power (CN)
Openalex Percentile: Top 65%
Lattice Boltzmann Simulation Studies
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.