Clogging of Infiltration Basin and Its Impact on Suspended Particles Transport in Unconfined Sand Aquifer: Insights from a Laboratory Study

Abstract

A laboratory study was undertaken to investigate the physical clogging of a sand medium by injecting suspended particles (SP), with diameters ranging from 0.03 to 63.41 μm, into an infiltration basin, which was installed in a sand tank under the condition of constant head. The hydraulic conductivity (K) of the saturated porous medium was found to have decreased by 27% because of re-arrangement over the seven days of self-filtration. A clogging layer was observed on the infiltration basin bottom, probably due to straining over the stormwater infiltration stage. Particle-size analyses also indicate that retention of bigger SP led to faster straining of smaller SP, despite the small fraction of bigger SP. The clogging layer weakened the hydraulic connection between the water level in the basin and the water table of the unconfined aquifer until nearly no water could infiltrate into the aquifer. The deposition of finer SP that entered into the aquifer are governed by the hydrodynamic forces. These finer SP caused non-uniform permeability reduction of the porous medium, with an estimated 35% of permeability reduction occurring beneath the infiltration basin. However, the reduction appears to be reversible, as the fine SP deposited on the pore surfaces of the porous medium can be released or detached by the continuous horizontal hydraulic gradient. Extended tailing of the outlet breakthrough curve (BTC) also strongly supported the detachment of SP. This study focused on the effects of particles’ polydispersity and hydrodynamic forces on the hydraulic characteristics of the porous medium.

Evaluation of the Offsets of Artificial Recharge on the Extra Run-Off Induced by Urbanization and Extreme Storms Based on an Enhanced Semi-Distributed Hydrologic Model with an Infiltration Basin Module

“…In this case, the proportion of the upstream surface runoff flowing into the infiltration basin was assumed to be a maximal value of 1. To consider the impacts of logging in the vadose zone during artificial recharge [28,29], the coefficient accounting for impacts of logging was assumed to be 0.1. The areas of infiltration basins were assumed to vary from 0.3% to 10% of the urban areas of the Rush River watershed.…”

“…Second, there are two thresholds for the outflow of impoundment [26]. Third, the effects of the vadose zone on the infiltration through impoundments are ignored [26], while clogging during artificial recharge always decreases the hydraulic conductivities [28,29]. In this case, our new infiltration basin module considered unique features of infiltration basins compared to other impoundments.…”

Physical Experiment and Modeling of the Transport and Deposition of Polydisperse Particles in Stormwater: Effects of a Depth-Dependent Initial Filter Coefficient

“…The uneven SP deposition inevitably cause uneven permeability reduction to the porous medium, as the permeability is directly related to the porosity [31]. Darcy's law with measurements of head losses at different times assessed the permeability decline of the porous medium due to SP accumulation.…”

“…Straining is also a prevalent process in stormwater filtration applications, but it is not considered in traditional filtration models [30]. Straining occurs when the pore throats is too narrow for SP to be transported, and straining is independent of hydrodynamic conditions [31]. Straining is only determined by the ratio between the diameter (d p ) of the particles and that (d g ) of porous medium grain.…”

Application of physical clogging models to Managed Aquifer Recharge: a review of modelling approaches from engineering fields

“…Studies have documented observations of physical clogging directly at MAR schemes (Escalante, 2013;Martin, 2013;Pavelic et al, 2007;Rinck-Pfeiffer et al, 2000). Soil column and field experiments have been undertaken to understand relevant mechanisms in the clogging formation (Du et al, 2018;Duryea, 1996;Fichtner et al, 2019;Mays & Martin, 2013;Pavelic et al, 2011;Sallwey et al, 2019;Zou et al, 2019). The effect of clogging has been integrated into numerical simulation through time-varying parameters calibrated from the field or experimental observations (Glass et al, 2020;Majumdar et al, 2008).…”