Scaling factors in HYDRUS to simulate a reduction in hydraulic conductivity during infiltration from recharge wells and infiltration basins

Abstract

Managed aquifer recharge (MAR) represents a promising technique to cope with increasing water stress worldwide. However, it can be challenging to operate MAR systems, especially concerning clogging. Clogging reduces the infiltration capacity and system efficiency of a MAR facility. Processes that cause clogging are difficult to quantify and assess, and their simulations in MAR schemes have so far been limited. The variably saturated water flow model HYDRUS-2D was therefore modified to include time-variable hydraulic conductivities to more realistically represent clogging at the infiltration interface of infiltration basins and recharge wells. An exponential function with a time-variable scaling factor was implemented into HYDRUS to vary the soil hydraulic conductivity over time during simulations. The new approach was tested, in combination with the reservoir boundary condition, by simulating two-dimensional cross-sections of two three-dimensional laboratory experiments representing recharge from infiltration basins and injection wells. With the help of the time-variable scaling factor, the increasing ponding depth in both experiments due to progressive clogging was reproduced. Hypothetical simulations with various well configurations, soils, and injection rates indicate that clogging influences the infiltration volumes and subsurface infiltration area, which should be considered during the planning of MAR systems. The approach can be used to evaluate the resulting infiltration capacity numerically and to help with the operation and design of MAR facilities. However, further research is required to fully understand and integrate the processes that lead to clogging at MAR facilities into numerical simulations.

Quantifying Dynamic Linkages Between Precipitation, Groundwater Recharge, and Runoff using Ensemble Rainfall-Runoff Analysis

“…Several key equations can be found in appendix A; more complete documentation can be found in the Hydrus-1D manual and the corresponding literature (van Genuchten, 1980;Šimůnek & van Genuchten, 1996). The model equations contain six soil hydraulic parameters that must be calibrated: residual soil water content θ r [L 3 L −3 ], saturated soil water content θ s [L 3 L −3 ], saturated hydraulic conductivity K s [LT −1 ], and the van Genuchten-Mualem parameters α [L −1 ], n, and l. The pore-connectivity parameter l was fixed at 0.5, which is the original optimal value based on 45 soil tests (Mualem, 1976) and has been commonly used as a default value (Fields et al, 2020;Glass et al, 2020;Schaap & Leij, 2000).…”

Developments and applications of the HYDRUS computer software packages since 2016

“…HYDRUS has been used to evaluate many of these technologies. The most common application has been studies of the hydrological functioning of drywells (e.g., Glass et al, 2020;Helles & Mogheir, 2023;Moreno et al, 2023;Sasidharan et al, 2018Sasidharan et al, , 2019Sasidharan et al, , 2020Sasidharan et al, , 2021 and infiltration basins (e.g., Cannavo et al, 2018;Glass et al, 2020;Lu et al 2021;Nieec et al, 2021;Qi et al, 2021). The reservoir boundary condition in HYDRUS, for which the water level in a well or infiltration basin depends on the rate of water injection or pumping along with water infiltration or exfiltration, has most often been used in these applications (e.g., Glass et al, 2020;Sasidharan et al, 2018Sasidharan et al, , 2019.…”

“…Various factors influencing infiltration from drywells and infiltration basins, such as spatial soil heterogeneity (e.g., Sasidharan et al, 2019Sasidharan et al, , 2020Sasidharan et al, , 2021 and clogging (Glass et al, 2020), have been evaluated in the above studies. Several have compared the hydrological functioning of drywells with infiltration basins (e.g., Glass et al, 2020;Sasidharan et al, 2021), the surface area required by these technologies (Sasidharan et al, 2021), or how infiltration from an infiltration basin can be enhanced substantially using drywell techniques (Helles & Mogheir, 2023;Sasidharan et al, 2021). While Sasidharan et al ( 2021) considered a single drywell in the center of a circular infiltration basin, which only requires a 2D axisymmetrical formulation, Helles and Mogheir (2023) considered a more complicated 3D transport domain with an infiltration basin containing 18 drywells.…”

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

“…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). The comprehensive numerical code CLOG of Pérez Paricio (2001) simulates the individual clogging processes, however, kinetic parameters require further calibration for application.…”