| Issue |
E3S Web Conf.
Volume 659, 2025
The 7th International Conference on Green Environmental Engineering and Technology (IConGEET2025)
|
|
|---|---|---|
| Article Number | 03009 | |
| Number of page(s) | 11 | |
| Section | Environmental Sustainability and Development | |
| DOI | https://doi.org/10.1051/e3sconf/202565903009 | |
| Published online | 20 November 2025 | |
Modeling of Sediment Transport Capacity by Overland Flow Using Multifactorial Analysis: Flume Experiment
Department of Civil Engineering, Faculty of Engineering, Universiti Pertahanan Nasional Malaysia, Malaysia
* Corresponding author: zuliziana@upnm.edu.my
Sediment transport capacity (STC) is critical in predicting soil erosion under overland flow, especially on sloped and vegetated terrains. This study aims to assess the influence of hydraulic parameters (flow velocity, depth, shear stress, unit stream power) and root mass density on STC and to develop an empirical model through controlled flume experiments. Experiments were conducted under bare and vegetated surface conditions with varying slopes. STC was calculated from sediment mass collected at the flume outlet. Flow properties were derived using standard hydraulic equations, while root mass density was obtained from soil volume and dried root mass. Multiple linear regression was used to analyze variable contributions to STC. Unit stream power showed the strongest positive influence on STC (β = 0.689), while root mass density had a negative effect (β = –0.235), suggesting a stabilizing role. However, none of the predictors were statistically significant (p > 0.05). Visual trends indicated lower sediment transport in vegetated conditions, especially at higher velocities and slopes. The findings support integrating both hydraulic energy and vegetation factors into erosion prediction models and offer a base for improving land management in erosion-prone areas.
© The Authors, published by EDP Sciences, 2025
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.

