| Issue |
E3S Web Conf.
Volume 708, 2026
7th International Conference on Smart Applications and Water Information Systems: “Intelligent Systems, Geospatial Technologies and Modeling for the Sustainable Management of Water Resources” (SAWIS 2025)
|
|
|---|---|---|
| Article Number | 02008 | |
| Number of page(s) | 11 | |
| Section | Water Quality, Treatment, and Environmental Processes | |
| DOI | https://doi.org/10.1051/e3sconf/202670802008 | |
| Published online | 30 April 2026 | |
Quantitative Assessment of Clogging in Porous Media Using a Coupled Bouwer Model-Column Experiment Approach
1 Hydroinformatics Team, Faculty of Sciences, Ibn Tofail University, Maamora Campus, P.O. Box 133, 1400 Kenitra, Morocco.
2 International Water Research Institute (IWRI), Mohammed VI Polytechnic University, Ben Guerir, 43150, Morocco.
Abstract
Clogging in porous media significantly affects the performance of stormwater infiltration systems. This study applies the Bouwer model to quantify the hydraulic resistance (Rh) of clogged layers during column tests conducted under various experimental conditions. Three successive injections (particle-free water and particle-laden water containing local Hamri soil) were performed on sand, along with a single particle-free water injection on Hamri soil, to evaluate clogging dynamics. The least-squares method was used to optimize Rh, revealing a 600-fold increase in the hydraulic resistance of sand after two particle-laden water injections, indicating severe clogging. Hamri soil exhibited twice the susceptibility to clogging compared to sand due to its finer texture. These findings validate Rh as a robust indicator for assessing clogging, offering insights for optimizing filter materials in the design of infiltration basins. The study highlights the importance of soil texture and water quality in clogging susceptibility and proposes a framework for predictive modeling in stormwater management.
© The Authors, published by EDP Sciences, 2026
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.

