Journal of Hydrology 594 (2021) 125720

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Journal of Hydrology
journal homepage: www.elsevier.com/locate/jhydrol

Research papers

Comparison of recharge from drywells and infiltration basins: A
modeling study
Salini Sasidharan a, b, *, Scott A. Bradford b, Jiří Šimůnek a, Stephen R. Kraemer caDepartment of Environmental Sciences, University of California Riverside, Riverside, CA 92521, USA
United States Department of Agriculture, Agricultural Research Service, U. S. Salinity Laboratory, Riverside, CA 92507, USAcU.S. Environmental Protection Agency, Office of Research and Development, San Francisco, CA 94105, USAb

A R T I C L E I N F O

A B S T R A C T

This manuscript was handled by Corrado Cor­
radini, Editor-in-Chief, with the assistance ofWilliam Payton Gardner, Associate Editor

Drywells (DWs) and infiltration basins (IBs) are widely used as managed aquifer recharge (MAR) devices tocapture stormwater runoff and recharge groundwater. However, no published research has compared the per­formance of these two engineered systems under shared conditions. Numerical experiments were conducted on
an idealized 2D-axisymmetric domain using the HYDRUS (2D/3D) software to systematically study the perfor­
mance of a circular IB design (diameter and area) and partially penetrating DW (38 m length with water table >60 m). The effects of subsurface heterogeneity on infiltration, recharge, and storage from the DW and IB underconstant head conditions were investigated. The mean cumulative infiltration (μI) and recharge (μR) volumes
increased, and the arrival time of recharge decreased with the IB area. Values of μI were higher for a 70 m
diameter IB than an DW, whereas the value of μR was higher for a DW after 1-year of a constant head simulation
under selected subsurface heterogeneity conditions. A comparison between mean μI, μR, and mean vadose zone
storage (μS) values for all DW and IB stochastic simulations (70 for each MAR scenario) under steady-state
conditions demonstrated that five DWs can replace a 70 m diameter IB to achieve significantly higher infiltra­tion and recharge over 20 years of operation. Additional numerical experiments were conducted to study the
influence of a shallow clay layer by considering an IB, DW, and a DW integrated into an IB. The presence of sucha low permeable layer delayed groundwater recharge from an IB. In contrast, a DW can penetrate tight clay
layers and release water below them and facilitate rapid infiltration and recharge. The potential benefits of a DW
compared to an IB include a smaller footprint, the potential for pre-treatments to remove contaminants, lessevaporation, less mobilization of in-situ contaminants, and potentially lower maintenance costs. Besides, thisstudy demonstrates that combining both IB and DW helps to get the best out of both MAR techniques.

Keywords:
Managed aquifer recharge (MAR)Drywell
Infiltration Basin, Infiltration
Recharge
HYDRUS (2D/3D)

1. Introduction
Climate models, combined with water budgets and socioeconomic
information, suggest that a large proportion of the world’s population isexperiencing water stress (Vorosmarty et al., 2000). In recent decades,
groundwater has been used as a freshwater resource when surface wateris scarce (Famiglietti, 2014; Zektser and Lorne, 2004). However,intensive groundwater withdrawals have contributed to the depletion of
streams (Fleckenstein et al., 2004), land subsidence, irreversible
reduction of storage area (Faunt et al., 2016; Niswonger et al., 2017),
drying up of pumping wells, increased cost of pumping from deep
aquifers (Nelson et al., 2016), exacerbated seawater intrusion in coastal
basins (Harter, 2015; Niswonger et al., 2017), disconnected stream-

aquifer systems (Dogrul et al., 2016), and compromised groundwater
quality (Feng et al., 2013; Ghasemizade et al., 2019; Niswonger et al.,2017).
Stormwater has been increasingly integrated into sustainable urban
water management plans and developments (Chang et al., 2018).
Managed aquifer recharge (MAR) uses various cross-cutting technolo­
gies for the intentional diversion, transport, storage, infiltration, andrecharge of excess surface water (Sprenger et al., 2017). For example,
MAR can be accomplished using infiltration basins (IB) (Teatini et al.,2015), aquifer storage and recovery (Dillon et al., 1999), aquifer stor­age, transfer, and recovery (Pavelic et al., 2005), flooding land (FloodMAR) (Scherberg et al., 2014), flooding agricultural land (Ag-MAR)(Niswonger et al., 2017), and vadose zone recharge devices such as* Corresponding author at: USDA, ARS, Salinity Laboratory, Riverside, CA 92507, USA.
E-mail address: salinis@ucr.edu (S. Sasidharan).
https://doi.org/10.1016/j.jhydrol.2020.125720
Received 1 September 2020; Received in revised form 22 October 2020; Accepted 28 October 2020
Available online 4 November 20200022-1694/© 2020 Elsevier B.V. All rights reserved.

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Journal of Hydrology 594 (2021) 125720

stormwater disposal wells (McClanahan, 2006), vadose zone trenches(Heilweil et al., 2015), infiltration wells, pits, recharge shafts, or dry­wells (DW) (Bouwer, 2002; Liang et al., 2018; Sasidharan et al., 2018,2019, 2020). MAR has been expanding in popularity and intensity to
improve groundwater resources (Dillon et al., 2010; Ghasemizade et al.,2019).
The development of urban areas increases the impermeable surface
area and the amount of runoff. Stormwater runoff threatens urban in­
frastructures (bridges, roads, and buildings) and wastewater treatment
facilities, while contaminants associated with impervious surfaces(including fossil fuels, nutrients, and heavy metals) can impair surface
water and groundwater quality (Welker et al., 2006). The elevatedvolume of surface runoff, therefore, has an adverse impact not only on
the ecology and health of local rivers and streams but also has envi­
ronmental effects miles downstream due to flooding, erosion, sediments,
and contaminants (Braga et al., 2007). To tackle this problem, engineers
are investing time, money, and research to develop Best Management
Practices (BMPs) (Welker et al., 2006). Infiltration structures, such as
infiltration basins and trenches, coupled with retention compartments,
are widely used for urban stormwater management across the world(Dechesne et al., 2004, 2005).
Infiltration basins contribute valuable technical and environmental
benefits by capturing stormwater runoff and letting it infiltrate into theunderlying soil (Ferguson, 1994). They are an especially attractive andfeasible option when the surface soil has adequate permeability, and thesite has a shallow water table (Akan, 2002). Often, IBs drain runoff frommixed watersheds that have residential, commercial, and industrial
zones, major roads, and reclaimed water (Dechesne et al., 2004; Drewes
and Fox, 1999). The use of IBs enhances groundwater recharge, reduces
the peak flow and volume of water in downstream networks, limits
pollution discharges to surface waters, and decreases stormwater flows
in sewer systems (Dechesne et al., 2004, 2005). Infiltration basins arealso attractive to the public because they can improve urban landscapes
when designed as parks or playgrounds. They have a lower cost thanburied systems and act as drainage outlets from highways and parking
lots (Dechesne et al., 2004, 2005).
Although there are many potential benefits associated with the use of
IBs for stormwater capture, their more extensive application has certain
limitations. For example, even though IBs are used as a stormwater
management system in the urban area, it may not significantly decrease
the total volume of runoff all the time (Traver and Chadderton, 1983).
Therefore, they may not control potential flash flooding, erosion, andpollutants (Dechesne et al., 2005). Even though the topsoil layer of IBs
can act as a barrier for pollutants (Mikkelsen et al., 1994; Nightingale,1987), contamination of the underlying soil and groundwater still re­mains an issue (Barraud et al., 2002; Dechesne et al., 2004). In addition,
clogging of IB surfaces (Barraud et al., 1999; Gonzalez-Merchan et al.,2012; Hutchinson et al., 2017) may occur through a combination of
mechanical, biological, and chemical processes that depend on thesediment load and organic composition of the inflow water (GonzalezMerchan et al., 2012). Clogging reduces the infiltration capacity of IBs,
and causes frequent ponding or overflows, reduces the treatment ca­
pacity, and decreases groundwater recharge (Dechesne et al., 2005;
Gonzalez-Merchan et al., 2012). The annual cost associated with IBs
maintenance, such as scrapping of clogged surfaces and pre-treatment ofsource water, can be expensive (Erickson et al., 2010). IBs can be
operated for 20–30 years. However, the long-term performance of IBs isneither well understood nor controlled during operation (Dechesne
et al., 2005). Knowledge about the long-term environmental impacts of
IBs is limited since there is no information on how to restore function­ality if adequate infiltration capacity is lost (Welker et al., 2006). Also,
there is a quantifiable decrease in the available area to operate IBs withincreasing urbanization (Braga et al., 2007). There is, therefore, a crit­
ical need for alternative MAR practices that can resolve challenges
associated with IBs in growing urban environments.
In the past decade, DWs have gained a lot of attention in the UnitedStates and across the world. DWs capture stormwater and infiltrate it in
the vadose zone up to 10–40 m below the soil surface and at least 1–3 mabove the water table (LACDPW, 2014; Sasidharan et al., 2018, 2019,2020). DWs are often used as a Low Impact Development BMP engi­
neering system to capture seasonal stormwater to maintain the urban
green infrastructure. This study investigates the use of DWs for MAR asan alternative and/or in combination with IBs. DWs can be implemented
as a MAR technique in semi-arid and arid regions where the ground­water table is deep (e.g., 60–300 m or more), when high permeable soils
and/or sufficiently large land areas for surface infiltration systems are
not available, or when the installation of deep boreholes in saturated
zones are expensive (Bouwer, 2002; Liang et al., 2018). There areseveral additional advantages of using DWs over IBs. For example, DWs
have minimal water loss by evaporation, a small installation area, alarge ponding depth (hydraulic driving head), a shorter recharge time,and an opportunity for pre-treatment of sediments and contaminants insource water (Edwards et al., 2016; Sasidharan et al., 2018, 2019, 2020).
A few major cities in California, Arizona, and Washington achieve nearly
70–100 percent of their groundwater recharge through DW infiltration,and many other cities are planning to build DWs (Cadmus, 1999; EPA,
1999; Graf, 2010; Marsh et al., 1995; Snyder et al., 1994). DWs are,therefore, an attractive option for MAR in areas where an IB is not ideal
or can be used as an integrated infrastructure to enhance the recharge ofexisting IBs.
Several investigations have determined infiltration rates from infil­
tration basins (Bouwer, 2002; Bouwer and Rice, 1989; Masetti et al.,2016). In addition, several researchers have compared the performanceof an IB with other MAR techniques. For example, lab-scale experiments
coupled with numerical modeling have demonstrated that clogging islikely to influence the infiltration capacity of certain MAR systems (e.g.,
infiltration basins) more than others (e.g., recharge wells) (Glass et al.,2020). A small-diameter (2.5–5 cm diameter and 10–12 m depth) well
was reported to improve the infiltration in comparison to a spreadingbasin (Händel et al., 2016a, 2014, 2016b). However, these studies used asmall well that was not comparable to the drywell size of this investi­
gation (1.2 m diameter and 38 m depth). Jokela and Kallio (2015)
compared the performance of deep injection wells (40 cm diameter and
32–45 m depth) to a sprinkler infiltration system. Comparison between
infiltration trenches and spreading basins demonstrated that trenches
are promising to enhance infiltration when compared to spreading ba­
sins (Heilweil et al., 2015; Heilweil and Watt, 2011). In all of thesestudies, the well geometry was not identical to a drywell, and water was
injected directly into the water table. Furthermore, differences in vadosezone storage and stochastic subsurface heterogeneity were not consid­
ered in these works.
MAR techniques are highly dependent on soil textural properties andthe subsurface heterogeneity that controls both the permeability andflow fields. For example, the infiltration capacity will vary with thevadose zone thickness and the presence and distribution of high and low
permeable soil layers and their connectivity to the underlying aquifer(Mantoglou and Gelhar, 1987; O’Geen et al., 2015; Schilling et al., 2017;
Xie et al., 2014; Yeh et al., 1985a, 1985b). Many parts of the US have soil
horizons (layers) that are cemented or consist of claypans or layers withstrongly contrasting particle size distributions. These layers can have
exceptionally low saturated hydraulic conductivity (Ks) values thatseverely limit the vertical movement of infiltrated water (O’Geen et al.,2015). This restricts the site suitability and operation of IBs and does notguarantee that aquifer recharge from IBs will occur over short timeframes (in some cases, it may be several years).
The objective of this study is to compare groundwater recharge from
DWs and IBs under various homogeneous and heterogeneous subsurface
conditions. The HYDRUS (2D/3D) software was used to directly simu­
late cumulative infiltration and recharge volumes from DWs and IBs.
Constant head conditions were considered in DWs and IBs to determine
the comparable upper limit for recharge. Subsurface heterogeneity wasdescribed in this model by generating stochastic realizations of soil
2

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Journal of Hydrology 594 (2021) 125720

hydraulic properties. The performance of DWs and IBs were assessed
based on simulated values of cumulative infiltration and recharge, thenumber of DWs required to achieve similar or improved behavior to an
IB, and the long-term operational benefits and costs. The approach andnumerical model tool in this research can be used to screen MAR designs
for a specific site applications.

shows a schematic of an example model domain, geometry, initialconditions, and boundary conditions that were employed in the IB
simulations. The axisymmetric flow domain was 60 m (H, Height) × 50
m (W, Radius). The IB had a height of 2 m and a diameter of 10, 20, 30,
40, 50, 60, or 70 m, and was continuously ponded with a water height of
0.6 m. The model domain was discretized using a two-dimensional
triangular finite element mesh with the MESHGEN tool available
within HYDRUS (2D/3D). The mesh was refined at the top boundary ofthe domain, where infiltration from the IB was simulated. To reduce themass balance error, the finite element mesh was adjusted such that thesize of elements was smaller (0.05–0.1 m) near the IB surface, and thegrid size was gradually increased with the radial distance from the IB,with a maximum element size of 0.5–0.75 m. The quality of the finite
element mesh was assessed by checking the mass balance error reported
by HYDRUS (2D/3D) at the end of the simulation. Mass balance errors
were always below 1%, and these values are generally considered
acceptable (Brunetti et al., 2017).
A no-flux boundary condition was assigned to nodes between the IB
surface and the upper right corner, and the whole right and left sides ofthe flow domain (Fig. 1A). Nodes at the bottom boundary (z = -60 m)
were assigned a free drainage boundary condition (i.e., the water table
was assumed to be far below this point). Note that numerical experi­ments in this study do not account for the effect of the water table, andfuture site-specific analyses and modeling studies are therefore war­
ranted. A constant pressure head condition was considered in this study
to evaluate the continuous long-term performance of an IB, and poten­
tial application of a DW as an independent or integrated infrastructurewith an IB. To represent a continuously filled IB (0.6 m), the total head
(H = h + z) at the upper boundary (at z = -1.4 to − 2 m) was constant, i.
e., the pressure head decreased linearly with depth from 0.6 m at thebottom of the IB (z = -2 m) to 0 at the water level (z = -1.4 m) (Fig. 1).
The initial condition in the flow domain was specified in terms of the soil
water pressure head h (x, z) and was set equal to a constant pressure
head of − 0.5 m (Fig. 1) (Sasidharan et al., 2020).

2. Materials and methods
2.1. Mathematical model
The HYDRUS (2D/3D) software package version 3 (Šejna et al.,2018; Šimůnek et al., 2018, 2016) was used to simulate infiltration,
redistribution in the vadose zone, and groundwater recharge from DWs
and IBs. HYDRUS (2D/3D) numerically solves the 2-dimensional
axisymmetric form of the Richards equation using the van Genuchten(1980) and Mualem (1976) unsaturated soil hydraulic functions. Input
parameters, initial conditions, and boundary conditions that were
employed in these simulations were generally based on the results from
DWs located in Fort Irwin, CA (Sasidharan et al., 2020). Table 1 provides
a summary of hydraulic parameters that were employed in experiments I
and II of this study, including the saturated soil hydraulic conductivity,
Ks = 0.046 m day− 1; the shape parameter in the soil water retentionfunction, α = 9.17 m− 1; the residual soil water content, θr = 0.043 [-];
the saturated soil water content, θs = 0.39 [-]; the pore-size distribution
parameter in the soil water retention function, n = 2.76; and the tor­
tuosity parameter in the hydraulic conductivity function, l = 0.5. In
numerical experiments III (Table 1), default values of hydraulic pa­
rameters for various soil textural classes were taken from the HYDRUS(2D/3D) Soil Catalog (Carsel and Parrish, 1988).
The data for axisymmetric DW simulations presented in this work
(one-year constant head simulation) was adapted from our previously
published work, Sasidharan et al. (2020). This manuscript provides
details about the expanded simulation domain, model parameters, andthe dynamics of water infiltration, redistribution, and recharge. These
results are compared with similar simulations for IBs in this work. Fig. 1

Table 1The soil hydraulic parameters for different soil materials employed in the numerical experiments.
Experiments

I

Soil

Fort Irwin Soil (Sasidharan et al., 2020)

II

III

DomainHomogeneous

Heterogeneous

Sand
Loamy Sand
Sandy Loam
Sandy Clay LoamClay

IB Size(Radius)[m]

Simulation
Duration[minoryear]

Heterogeneity

5
10
15
20
25
30
35
35

2 yearNA2104 min

X = 10; Z = 0.1; σ=1
X = 1; Z = 0.1; σ =1
X = 0.1; Z = 0.1; σ=1
X = 1; Z = 1; σ = 1
X = 1; Z = 2; σ = 1
X = 1; Z = 0.1; σ =0.5
X = 1; Z = 0.1; σ =0.25
LayeredSoil Hydraulic Parameters
θr *
[-]

θs *
[-]

α*

[m− 1]n*[-]Ks *[mday− 1]

l*
[-]

0.043

0.39

9.17

2.76

0.046

0.5

0.045
0.057
0.065
0.1
0.068

0.43
0.41
0.41
0.39
0.38

14.5
12.4
7.5
5.9
0.8

2.68
2.28
1.89
1.48
1.09

7.13
3.49
1.06
0.31
0.048

0.5
0.5
0.5
0.5
0.5

*The residual soil water content (θr ), the saturated soil water content (θs ), the shape parameter (α), the pore-size distribution parameter (n), the saturated isotropic
hydraulic conductivity (Ks ), and the tortuosity parameter (l)3

S. Sasidharan et al.

Journal of Hydrology 594 (2021) 125720

Fig. 1. The geometry, dimensions, initial conditions, the boundary conditions, and X and Z directions for correlation length scales for the 2D-axisymmetricalinfiltration basin (A) and DW + infiltration basin (B) flow domains. The detailed DW geometry, the water flow dynamics, and justification for initial and bound­ary conditions were presented in our previous studies (Sasidharan et al., 2018, 2020).

2.2. Numerical experiment

Constant head IB simulations that employed stochastic realizations
were conducted to accurately capture and compare the infiltration andrecharge behavior of IBs with published constant head stochastic DW
simulations (Sasidharan et al., 2020). Soil hydraulic parameters for theFort Irwin soil (Table 1) were employed in conjunction with stochastic
scaling factors in these simulations. Constant head simulations wereused to determine I and R after two years in experiment II (Table 1).
Multiple realizations of the stochastic parameters were employed, andthe mean values of I (μI) and R (μR) and associated standard deviations
were calculated. The following hypothetical combinations of scaling
factors with variable σ (σ = 0.25, 0.5, and 1 forX = 1 m andZ = 0.1 m), X(X = 0.1, 1, and 10 m forσ = 1 andZ = 0.1 m), and Z (Z = 0.1, 1, and 2 mforσ = 1 andX = 1) were used. Similar parameter ranges have beenmeasured in the field (Freeze, 1975; Sudicky and MacQuarrie, 1989) andemployed in previous modeling studies (Sasidharan et al., 2019, 2020).
Only ten realizations were considered for these stochastic heterogeneity
parameter combinations to minimize the computational time and cost.
Our previous research demonstrated that ten realizations were sufficientto accurately capture the mean and variance of the infiltration behavior
of DWs in the heterogeneous realizations of the numerical experiments(Sasidharan et al., 2019, 2020). Mean parameter values and 95%-Con­
fidence Intervals (CI) were calculated for all parameters from the ten
simulation realizations of the IB after two years. The calculated values of
μI and μR for IBs were compared with those for DWs (Sasidharan et al.,2020) with the same heterogeneous domain after 1 year.
We also compare the steady-state performance of a combined systemwith a 70 m diameter IB and a DW over two years in order to develop
recommendations on how a DW can replace or complement an IB.
Figure S1 demonstrates that the steady-state infiltration (i) and recharge(r) rates were reached in constant-head DW (Sasidharan et al., 2020) andIB simulations after one and two years, respectively. These values of iand r were multiplied by a selected duration to determine the total
steady-state volume of I and R, respectively, after two years. The cor­
responding steady-state volume change of water in storage (S) in the

2.2.1. Homogeneous domain
Numerical experiments I (Table 1) were conducted to determine thevalues of cumulative infiltration (I) and cumulative recharge (R) after
730 days (2 years) as a function of the area of IB when considering ahomogeneous Fort Irwin soil. The hydraulic parameters for the Fort
Irwin soil (Table 1) were taken from Sasidharan et al. (2020). The valueof I was collected over simulated time as the total volume of water
infiltrated from the IB. Similarly, the value of R was calculated as thetotal volume of water drained through the bottom free drainage
boundary. Note that all this information was available in output files ofthe HYDRUS (2D/3D) software.
2.2.2. Heterogeneous domain
Numerical experiments I considered idealized homogeneous soil
systems. However, most field-scale soil profiles are highly heteroge­
neous, with hydraulic parameters changing over short distances. In thisstudy, highly permeable horizontal and vertical soil layers/lenses wererepresented using the Miller-Miller similitude geostatistical approach,which has been widely used in previous research (Feyen et al., 1998;
Roth, 1995; Roth and Hammel, 1996; Sasidharan et al., 2019, 2020;
Vereecken et al., 2007). The HYDRUS (2D/3D) computer software hasan option to generate stochastic distributions of hydraulic conductivity(αK) and pressure head (αh) scaling factors using the Miller-Miller
similitude approximation (Miller and Miller, 1956), which links these
two scaling factors as follows: αK = α-2
h . A lognormal distribution of
scaling factors was employed, and the stochastic field was generatedusing the standard deviation (σ ) of log10(αK), and its correlation length
in the lateral (the X-correlation length, X) and vertical (the Z-correlation
length, Z) directions. Procedures for generating autocorrelated or un­correlated scaling factor fields and the original algorithm used in
HYDRUS have been described in detail in the literature (El-Kadi, 1986;Freeze, 1975; Mejía and Rodríguez-Iturbe, 1974).
4

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Journal of Hydrology 594 (2021) 125720

vadose zone was determined as I-R. Steady-state values of μI, μR, and μS,
and their associated 95% confidence intervals over a two-year duration
were determined and compared for all DW and IB simulations (70simulations for each MAR approach). Steady-state IB results were also
compared with multiple DWs (up to 5) over 20 years of operation. In thiscase, values of μI, μR, and μS for two years were divided by two to obtainyearly results and then multiplied by the number of years of operationand the number of DWs. Parameters μI*, μR*, and μS* denote mean
cumulative infiltration, recharge, and storage, respectively, understeady-state conditions using the 70 simulations.
As discussed in the introduction, fine-textured soil layers can lead to
reductions in soil permeability and recharge. Additional simulations
were, therefore, conducted to investigate the use of various MAR stra­tegies to overcome these challenges in a profile with sand, loamy sand,sandy loam, sandy clay loam, and clay layers (Experiment III, Table 1).
Soil hydraulic parameters for various soil textures were taken from the
HYDRUS (2D/3D) Soil Catalog (Table 1). MAR simulations considered asingle DW and IB separately, as well as a DW integrated into an IB(Fig. 1B and S2).

3.1.1. Homogeneous soil profiles
Numerical experiment I was conducted to better understand therelationship between the size and the infiltration and recharge behaviorof an IB in a homogeneous soil domain. IBs with a diameter of 10, 20, 30,
40, 50, 60, and 70 m were considered in this study. It should be
mentioned that some existing IBs are much larger (1000 acre = 4 millionm2) and can infiltrate up to 308 million m3 of water (Hutchinson et al.,2017). However, this work only considers a small IB with a maximum
diameter of 70 m in order to minimize the computational time and costassociated with simulations on larger flow domains, and to stay within
the empirical experience (catchment basin size) at the Fort Irwin study
site. Fig. 2 shows the simulated water content (θ) profiles for IBs ofdifferent sizes after a 2-year, constant head, numerical simulation.
Figs. 3 and 4 present corresponding information about I and R in thesesame simulations. Fig. 3A shows a plot of I versus time for two years(730 days) of numerical simulation. Fig. 3B shows a plot of I versus the
IB area after one and two years. The value of I increases in nearly a linear
fashion over time (Fig. 3A) and with the IB area (Fig. 3B).
The design and operation standards for IBs are set by various states
and counties. For example, in Virginia, the maximum drainage area ofan IB is restricted to 50 acres, and the basin should be emptied within 48
h (Yu and Kaighn, 1992). In contrast, Los Angeles County in California
requires that the 85th percentile of a 24-hr runoff event be infiltrated
within 96 h (LACDPW, 2014). However, acquiring the needed land area
for an IB can be expensive and challenging, especially in an urban area.
Engineers, therefore, often seek ways to minimize the surface area of anIB, but this can be challenging because it may require a ponding depththat is either impractical or violates design parameters. Besides, theactual configuration of an IB is largely dependent on the site-specifictopography and other constraints (Yu and Kaighn, 1992). IBs may,therefore, not be an ideal BMP or MAR technique when suitable loca­
tions are not readily available, such as in highly urbanized landscapeswith utilities, in karst areas, and when surface slopes are higher than 20
percent (Yu and Kaighn, 1992).
Fig. 4A, 4B, 4C, and 4D show plots of cumulative recharge R as afunction of time (over one year) and depth when the IB diameter was
equal to 10, 30, 50, and 70 m, respectively. The value of R was negligible

2.2.3. Cost-analysis for DW and IB
A brief economic analysis of the installation and operational costs of
IBs and DWs was also conducted. Literature values and data collectedfrom various commercial operators were used for this purpose.
3. Result and discussions
3.1. Performance of an IB in different soil profiles
The infiltration, recharge, and vadose zone storage volume for an IBwith a diameter of 10–70 m were investigated as a function of time (1–2
years) and depth (7–60 m) using HYDRUS (2D/3D) numerical modelingexperiments. Selected numerical experiments were conducted for ho­
mogeneous and stochastic (Fort Irwin) soil profiles to understand theeffect of subsurface soil heterogeneity on IB performance.

Fig. 2. The cone of infiltration for a 10 m, 20 m, 30 m, 40 m, 50 m, 60 m, and 70 m diameter infiltration basins during a constant head simulation presented as watercontents (θ) after two years of simulation.
5

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Journal of Hydrology 594 (2021) 125720

demonstrate that the IB design will determine the arrival time forgroundwater recharge. In some cases, this may take several years, evenfor a homogeneous soil profile with high permeability.
3.1.2. Heterogeneous soil profiles
In reality, the natural subsurface is inherently heterogeneous, andthe layering of soil structures is very common (Hencher et al., 2011;
Phillips and Lorz, 2008; Sasidharan et al., 2019; Sidle et al., 2000; Smithet al., 2008; Uchida et al., 2003; USDA, 2016). Fig. 5 shows represen­tative θ distributions in stochastic domains under a 70 m diameter IBthat had constant head conditions for two years. The Fort Irwin soil
hydraulic parameters and stochastic parameters X = 0.1, 1, and 10; Z =0.1, 1, and 2; and σ = 0.25, 0.5, and 1 were employed in these experi­
ment II simulations (Table 1). Heterogeneous domains with X = 10, 1,
and 0.1 (lateral layering, Fig. 5A, 5B, and 5C) display wider θ distribu­
tions in the saturated area under the IBs compared to other heteroge­
neous domains. However, constant head simulation results indicate thata DW (Sasidharan et al., 2020) with a 1.8 m diameter can create asimilar-sized cone of infiltration as a 70 m diameter IB (Fig. S3). The
operation of IBs is mainly controlled by gravity-driven vertical water
flow, but the pressure head for an IB is very small (0.6 m). In contrast, a
DW can have a pressure head of up to 38 m that pushes water initiallylaterally through high permeable zones, and then water flows verticallyby gravity. Therefore, a DW with a very small surface footprint cancreate a recharge zone as big as a 70 m diameter IB. In particular, thesurface area of a 70 m IB is 3857 m2, whereas it is only 2.54 m2 for a DW.
Fig. 6 shows values of μI and μR, and their 95% confidence intervals
after 365 days as a function of σ (Fig. 6A), X (Fig. 6B), and Z (Fig. 6C) for
the DW (Sasidharan et al., 2020) and IB. Sasidharan et al. (2020) pre­viously demonstrated in DW simulations that the infiltration volume,the distribution and volume of trapped water in the flow domain, andthe subsequent recharge are highly dependent on the subsurface het­
erogeneity. Similarly, Fig. 6A shows that μI and μR tended to increase
with σ (Fig. 6A) for both IB and DW. An increase in σ leads to the for­mation of more permeable regions, which enhance infiltration (Sasid­haran et al., 2020). The μI was higher for the IB than for the DW, but μR
for the IB was smaller than for the DW. The value of μI and μR for the IB
and DW overlapped for X (Fig. 6B), and in some cases μI and μR werehigher for the DW than for the IB. In contrast, the value of μI was higher
and μR smaller for the IB in comparison with the DW for various Z(Fig. 6C). An increase in X and Z creates larger horizontal and verticallenses that can enhance the rapid movement of the wetting front inhorizontal and vertical directions, respectively (Sasidharan et al., 2019,2020). The above numerical modeling observations can be explained bydifferences in the vadose zone storage and the time to reach steady-stateflow conditions. In general, the DW has less vadose zone storage andtherefore reaches steady-state flow conditions faster than the IB(Fig. S3). Recharge from the IB is, therefore, smaller than from the DW inthe short-term. Researchers have previously reported extensive lateralwater movement but limited vertical water movement in different sub­surface soil profiles (Mantoglou and Gelhar, 1987; Routson et al., 1979;
Sinai et al., 1974; Yeh et al., 1985a, 1985b).
It is important to understand the infiltration, recharge, and arrival
time behavior during short-term DW and IB operations to identify thebest technique to infiltrate or recharge water rapidly. Fig. S4 shows aplot of μI and μR as a function of time (365 days) for IB simulations whenσ = 0.25, 0.5, and 1, and when X = 1 m and Z = 0.1 m. The value of μI
and μR tended to increase with σ, but μR was orders of magnitude
smaller than μI due to vadose zone storage. The value of μR was equal tozero after one year for the IB when σ = 0.25, whereas the recharge
arrival time for a DW was approximately 100 days when σ = 0.25
(Sasidharan et al., 2020). Fig. S5 shows a plot of μI and μR for the IB
when X = 0.1, 1, 10 m, Z = 0.1 m, and σ = 1. The values of μI and μR
decreased with increasing X. These trends reflect increasing water
spreading with X due to larger lenses in the lateral direction with highpermeability (Sasidharan et al., 2020). The value of μR was again orders

Fig. 3. The cumulative infiltration volume (I) as a function of time (2 years or
730 days) (A) and the area of the infiltration basin (B).

for all IBs with a 60 m deep soil profile during the first year. This hap­pens because most of the infiltrating water below the IB contributes tothe change in the vadose zone storage until the pore space is filled. The
size of the IB influences the arrival time of the infiltrating water at a
specified depth. In particular, a decrease in the IB diameter produced alater arrival time. For example, the arrival time at a depth of 22 m for an
IB with a 10 m diameter was 164.8 days, whereas it was 126.8 days
when the IB diameter was 70 m. This occurs because lateral spreading
plays a relatively more significant role for smaller diameter IBs (Fig. 2).
Fig. 4E shows a plot of R as a function of the IB area at depths of 7, 22,
and 60 m after one and two years. The value of R was very small or
negligible after one year when the depth was 60 m, but then rapidly
increased when the vadose zone storage filled, and the simulation
approached a steady-state condition at the end of the second year. For
example, the value of R at a depth of 60 m after 2 years was slightly lessthan R at a depth of 7 m after 1 year (Fig. 4E). This reflects the differencein the vadose zone storage and the time needed to reach steady-state
conditions at these depths. It also indicates that IBs may not be theideal MAR strategy when rapid groundwater recharge is needed. For
example, the Central Valley in California is one of the most productive
agricultural regions in the world, which heavily relies on surface water
diversions and groundwater pumping for crop irrigation (Faunt et al.,2016). Greater reliance on groundwater during droughts has caused
large scale land subsidence (Harter, 2015), and the loss of up to 10 m ofaquifer storage in some parts of the Central Valley (Scanlon et al., 2016).
Rapid recharge within a short period is, therefore, essential for miti­
gating land subsidence and irreversible loss in aquifer storage in shallow
aquifers (60–70 m). However, our experiment I simulation results
6

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Journal of Hydrology 594 (2021) 125720

Fig. 4. The cumulative recharge volume (R) at different depths as a function of time (1 year 365 days) for an infiltration basin with diameter = 10 m (A), 30 m (B),
50 m (C), and 70 m (D). The value of R as a function of the area of the infiltration basin at depths of 7 m, 22 m, and 60 m at Year 1 and Year 2 (E).

of magnitude smaller than μI due to the vadose zone storage. The arrival
time for the worst-case recharge scenario (X = 10, Z = 0.1 m, and σ = 1)
was approximately 250 days for the IB (Fig. S5B) compared to about 68
days for the DW (Sasidharan et al., 2020). Fig. S6 shows a plot of μI andμR as a function of time (365 days) for IB simulations when Z = 0.1, 1,
and 2, X = 1 m, and σ = 1. The presence of highly permeable verticallenses facilitates the faster downward movement of water and, thus, anearly arrival time (Sasidharan et al., 2020). However, even for the bestcase recharge scenario (X = 1, Z = 2, and σ = 1), the arrival time for the
IB was approximately 135 days (Fig. S6B), whereas it was only about 34
days from the DW (Sasidharan et al., 2020). The above results clearly
demonstrate that DWs have a much faster recharge arrival time than IBs.

3.2. Performance comparison between IB and DW
An IB has several benefits when used as a MAR technique. However,the biggest constrain on the installation of an IB often is land avail­ability, both in urban and rural areas. Direct injection wells such as
Aquifer Storage and Recovery has gained attention as a solution to thisproblem. However, injection water needs to meet strict water quality
standards before being injected, which are achieved using energyintensive treatments, which makes this technique very expensive. Dry­
wells usually are considered as a Low Impact Development (LID) BMP
for capturing episodic stormwater, mostly in urban areas. However, thisstudy proposes its potential use as a MAR under constant head7

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Journal of Hydrology 594 (2021) 125720

Fig. 5. Water content (θ) profiles for heterogeneous Fort Irwin soil profiles after the 2-year constant head simulation. Heterogeneity parameters in these simulations
were: (A) X = 10, Z = 0.1, σ = 1; (B) X = 1, Z = 0.1, σ = 1; (C), X = 0.1, Z = 0.1, σ = 1; (D), X = 1, Z = 2, σ = 1; (E), X = 1, Z = 1, σ = 1; (F), X = 1, Z = 0.1, σ = 0.5;
and (G) X = 1, Z = 0.1, σ = 0.25.

simulations was to demonstrate the potential application of a drywell as
an independent MAR technique in place of an IB, or its use in conjunc­tion with existing IB infrastructure. Such a combination of a DW with an
IB has never been systematically investigated before.
Section 3.1. demonstrated that a single DW could infiltrate andrecharge less, equivalent, or more water than a 70 m diameter IB
depending on specific subsurface heterogeneity conditions. Additional
calculations were conducted in this section to compare the overall per­formance of multiple DWs and an IB. Fig. 7 shows plots of mean steadystate values of μI*, μR*, and μS* for simulations with an IB and a DW (70for each MAR scenario) in heterogeneous domains as a function of thenumber of DWs. The value of μI* and μR* for a 70 m diameter IB and asingle DW were very close to each other (Fig. 7A and 7B). However,increasing the number of DWs at a location increases values of μI* andμR* over the IB correspondingly to their numbers. Interestingly, thevalue of μS* for a single DW was smaller than that for an IB, but the 95%CI for the vadose zone storage volume for five DWs overlapped that of asingle IB. These results demonstrate that five DWs can easily replace a
70 m diameter (a surface area of 3847 m2) IB to achieve significantly
higher infiltration and recharge.
Additional calculations were conducted to compare the performanceof five DWs with a 70 m diameter IB that was operated for up to 20 years(Fig. 8). The results demonstrate that five DWs can infiltrate andrecharge significantly higher volumes of water than an IB even after 20
years of continuous operation. These results have important implica­
tions for MAR operations. IBs often require a large surface area toinfiltrate source water within the recommended time to minimize
flooding and ponding (LACDPW, 2014; Yu and Kaighn, 1992). The
implementation of IBs as a BMP in urban areas is especially challenging
due to the limited land availability. Figs. 7 and 8 clearly demonstratethat the installation of up to 5 DWs with a minimal footprint can easily
replace a 70 m diameter (surface of 3847 m2) IB. DWs offer uniquedesign opportunities to install such devices in places where space is very

Fig. 6. The mean cumulative infiltration volume (μI) and the mean cumulative
recharge volume (μR) (from 10 simulations) and the corresponding 95% Con­fidence Intervals as a function of σ (σ = 0.25, 0.5, 1) whenX = 1 andZ = 0.1 (A),X (X = 0.1, 1, 10 m) whenσ = 1 andZ = 0.1 (B), and Z (Z = 0.1, 1, 2 m) whenσ= 1 andX = 1 (C) for a heterogenous Fort Irwin soil flow domain with an IB or
DW (Sasidharan et al., 2020) after 1-year constant head simulation.

conditions, where the installation and continuous operation of an IB are
not feasible. Therefore, additional numerical experiments were con­ducted to compare the infiltration and recharge performance between a
DW and an IB under various scenarios. The purpose of these specific8

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Journal of Hydrology 594 (2021) 125720

Fig. 7. The mean cumulative infiltration volume (μI*) (A), the mean cumulative recharge volume (μR*) (B), and the mean cumulative storage volume (μS*) (C) (from70 simulations) as a function of the number of DWs (solid red line) after 2-year constant head simulations for the Fort Irwin soil flow domain. The solid blue line
represents the corresponding value for a 70 m diameter infiltration basin (IB). (For interpretation of the references to colour in this figure legend, the reader isreferred to the web version of this article.)tight, such as parking lots, parks, and streets. Figs. 5, 7, and 8 demon­
strated that IBs require a large volume of water to saturate the vadosezone (μS*) before recharge can occur. This leads to a significant loss
when the source water is seasonal (stormwater, rainwater, and peakriver flow) or expensive (recycled wastewater). A previous study on
vadose zone trenches demonstrated that infiltration increased between
parallel trenches with increasing spacing and number of trenches, andwhen trenches were continuously full (Heilweil et al., 2015). DW offers
flexibility to install with adequate spacing between each unit to enhance
the infiltration and recharge, even in urban areas. The presented nu­
merical modeling tool can be used to predict the best distribution of
DWs, and it can be done with high accuracy when the site-specificsubsurface heterogeneity information is available.
IBs are generally considered as the MAR technique of choice toenhance aquifer recharge and achieve groundwater sustainability(Teatini et al., 2015). However, expected long-term declines in the
groundwater level could result in compaction of fine-grained deposits,
which causes land subsidence (Galloway et al., 1999). For example, land
subsidence from groundwater pumping in the San Joaquin Valley ofCentral California began in the mid-1920 s, and by 1970 about 13500
km2 of land had subsided more than 0.3 m (Bertoldi et al., 1991; Poland
et al., 1975). The Sustainable Groundwater Management Act (SGMA)
recognizes that groundwater is best managed at the local level due tovariabilities in geographic, geologic, and hydrologic parameters. The
SGMA provides 20 years to implement reliable groundwater manage­
ment plans to achieve long-term groundwater sustainability (Faunt
et al., 2016). There is, therefore, an urgency for rapid recharge of these
depleted aquifers before the aquifer storage space is irreversibly lost.

Maples et al. (2019), in their modeling study on the infiltration basin atCentral Valley, CA, demonstrated that geologic heterogeneity plays ahuge role in the arrival time of recharge at the water table. The rechargepotential from an IB is highly dependent on subsurface geologic struc­ture, with a nearly two orders-of-magnitude range of recharge across thedomain. They suggested that networks of interconnected coarse-texture
facies provide a pathway for rapid infiltration and that the fine-texture
facies accommodate a substantial fraction of the total recharge volume,even for coarse-dominated sites (Maples et al., 2019). Similarly, thisresearch demonstrates that it can take several years for an IB to begin
recharging an aquifer, depending on its size and the subsurface het­
erogeneity and permeability. In contrast, DWs can rapidly achieve sig­
nificant amounts of recharge in a shallow unconfined aquifer within amuch shorter time frame.
Natural geologic processes in sedimentary basins tend to produce soil
textural layers and lenses that form parallel to the soil surface. Theselayered soil profiles can often involve highly permeable sand layers
followed by less permeable clay lenses with extensions and thicknessesof several tens to hundreds of meters (Phillips and Lorz, 2008). Nu­
merical experiments III (Table 1) were therefore conducted to study the
influence of a shallow clay layer under an IB on infiltration andrecharge. A layered soil profile with sand, loamy sand, sandy loam,
sandy clay, loam, and clay was considered in these simulations(Table 1). Fig. S2 shows an illustration of the simulation domain and soil
layers when considering an IB, a DW, and a DW integrated into an IB(denoted as DB + IB). Independent IB and DW scenarios were used tobetter understand the infiltration and recharge behavior in the layeredsoil profile with these two structures. In contrast, the DW + IB approach
9S. Sasidharan et al.

Journal of Hydrology 594 (2021) 125720

Fig. 8. The mean cumulative infiltration volume (μI*) (A), the mean cumulative recharge volume (μR*) (B), and the mean cumulative storage volume (μS*) (C) (from70 simulations) as a function of operation duration for five DW (solid red line) and a 70 m diameter infiltration basin (solid blue line) for the Fort Irwin soil flow
domain. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)(Fig. 9B) allowed us to assess the potential benefits of this MAR system.
Fig. 9A and 9B show the water content (θ) and pressure head (h) profiles,
respectively, for all three flow domains after 1.5 days. The results
demonstrate that once the moisture front reached the clay layer, water
started spreading laterally. The effect of a low permeable soil layer on
the infiltration rate and downward migration from an infiltration basin
was previously demonstrated using numerical experiments (D’Anielloet al., 2019). This enhanced lateral movement of water in the clay layer
can be attributed to the fact that at higher tension, the hydraulic con­ductivity of fine-textured materials can be higher than in coarsetextured materials, and water may prefer to spread laterally in a fine
bed than to move vertically through coarser ones (Routson et al., 1979;
Sasidharan et al., 2020). The presence of such geological formations
under an IB could delay groundwater recharge from 1 to more than 100
years. In contrast, a DW that penetrates tight clay layers and releases
water below them can facilitate rapid infiltration and recharge. A DW
can, therefore, be an ideal engineering solution to use in conjunction
with an existing IB or when planning a new MAR site when there areshallow clay layers, and recharge is the primary goal.
The average one-time installation cost of a drywell (MaxWell IV,
TorrentResources, USA, Personal Communication, 2020) is between$28,000 and $35,000 US Dollar. The MaxWell Plus (TorrentResources,
USA) drywell with additional pre-treatment can cost $38,000-$45,000
US Dollar or higher. The average yearly maintenance cost (vacuuming
the sedimentation chamber to remove the debris and sediments) for one
drywell is about $1,000 US Dollars per year. Since a drywell has a verysmall surface footprint, developers do not usually “lose” any land when

installing a drywell. The land cost for a drywell can, therefore, be
assumed to be nearly zero (DeJong, 2020). Consequently, the installa­tion and operation of a drywell over 20 years can cost around $48,000$65,000 US Dollar, whereas those for five drywells can cost up to$240,000-$325,000 US Dollar.
The Orange County Water District (OCWD) of California, USA im­
plements extensive MAR programs using seasonal stormwater (185million m3 per year) and recycled water (123 million m3 per year) for
aquifer replenishment or recharge, seawater intrusion control, water
quality protection and improvement (Hutchinson et al., 2017). The
major cost associated with IBs is the acquisition of land, especially inhighly urbanized areas with little available land. For example, the
OCWD spent $4M US Dollars per ha in 2014 to purchase land for agroundwater spreading basin (Hutchinson et al., 2017). In addition,
clogging of the recharge facility is the biggest hurdle to maximizing thecapacity of existing infrastructure. A recent study conducted by the
OCWD on a riverbed filtration system (RFS) demonstrated that thistechnique was highly effective in removing suspended solids in recharge
water and increasing the recharge capacity of the receiving basin.
However, the installation of an operational scale RFS at the site has anannualized cost of $5.1 M US Dollar (Hutchinson et al., 2017). Con­straints on land availability and costs of land acquisition and mainte­
nance, therefore, make it difficult to transfer these MAR techniques toother parts of the world, especially in developing countries.

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Journal of Hydrology 594 (2021) 125720

Fig. 9. The water content (θ) (A) and pressure head (h) (B) profiles for a 70 m diameter infiltration basin, a DW, and a DW + an infiltration basin for a layered(Fig. S5) soil flow domain.

by preventing the mobilization of in-situ contaminants to groundwater.
Additional field-scale research is warranted to assess the full implica­
tions of this practice on in-situ contaminant transport and groundwater
quality.
A DW provides additional benefits over an IB. For example, thesurface area for a 70 m IB is 3857 m2, whereas it is only 2.54 m2 for a
DW. The acquisition of land for an IB operation can be expensive, or theavailability of land that meets IB engineering criteria might be scarce inan urban area. In contrast, drywells in the urban area often look similar
to a utility hole and do not obstruct the development or landscape of
infrastructures such as parking lots, streets, or pavement. Furthermore,
drywells have minimal or zero evaporative losses in comparison with an
IB since all of its infiltration area is underground. Therefore, drywells
may be more attractive than an IB, especially in highly urbanized arid
and semiarid regions of the world. One of the biggest challenges in thecontinuous operation of IBs is the sedimentation of colloidal particles on
the surface and the formation of a clogged surface layer, which requires
a complete halt in operation and scrapping of the surface. IBs also
require additional maintenance such as vector control, vegetation andlandscape maintenance, and testing of sediments from IBs for theaccumulation of toxins, metals, and hydrocarbons (CABMP-Handbook,2003). In contrast, drywells offer an opportunity for pre-treatment of thesource water before injecting it into a drywell without altering its
operation efficiency. Therefore, DWs can potentially replace IBs when
the operation of IBs is not ideal, or when DWs can be installed inconjunction with IBs to improve their efficiency. This study provides
new design considerations and applications for DWs in combination
with IBs based on numerical modeling. Note that DWs are often
considered as a BMP for periodically capturing stormwater for recharge
under transient water flow conditions. However, this study considers the

4. Conclusions
Numerical simulations using HYDRUS (2D/3D) were conducted toevaluate the performance of an IB for infiltration and recharge undervarious design parameters (i.e., diameter and area) in a homogeneous
soil domain. The infiltration and recharge from an IB increase in a linear
fashion with the IB’s area. However, the arrival time of recharge at a
depth of 60 m increases with decreasing IB area. Therefore, installationof a large (greater than70 m diameter) IB is required when rapid
recharge to a deep aquifer is essential.
Additional numerical simulations were conducted to evaluate theperformance of a 70 m diameter IB and a 38 m deep DW for infiltration,
recharge, and storage under various stochastic heterogeneity conditions.
The water content profiles for the IB and DW systems showed that after a
2-year constant head simulation, the areas of infiltration and recharge
were similar for both DW and IB. The result demonstrated that during
the first year of operation, cumulative infiltration and recharge would behigher for a single DW than an IB under the same stochastic heteroge­neity conditions. Additional comparisons between the mean cumulative
infiltration and recharge volume from 70 stochastic simulations understeady-state conditions demonstrated that five DWs could easily replacea 70 m diameter IB to achieve significantly higher infiltration andrecharge, with a comparatively smaller volume of water lost to storage.
Benefits from drywells were most pronounced during the first couple ofyears but still held under steady-state conditions over 20 years ofoperation. Additional numerical experiments were conducted to un­derstand the effect of a layered soil profile on DW, IB, and DW + IB
performance. Results demonstrate that drywells could potentially be
used in combination with an IB to bypass low permeability layers such asa claypan. Bypassing clay-rich layers can provide an additional benefit
11

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Journal of Hydrology 594 (2021) 125720

use of a DW as a MAR technique under constant head or continuous
infiltration conditions. DWs also offer an opportunity to design a tran­sient (falling head) MAR system by merely turning on or off the source
water pipe to control the residence time for contaminant attenuation.
However, field-scale validation and long-term monitoring are essential
to demonstrate these potential benefits, and this will be explored infuture projects.

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CRediT authorship contribution statement
Salini Sasidharan: Conceptualization, Investigation, Methodology,
Data curation, Software, Formal analysis, Validation, Visualization,
Writing - original draft. Scott A. Bradford: Conceptualization, Software,
Resources, Supervision, Project administration, Funding acquisition,
Writing - review & editing. Jiří Šimůnek: Conceptualization, Software,
Resources, Supervision, Project administration, Funding acquisition,
Writing - review & editing. Stephen R. Kraemer: Project administra­tion, Funding acquisition, Writing - review & editing.
Declaration of Competing Interest
The authors declare that they have no known competing financial
interests or personal relationships that could have appeared to influence
the work reported in this paper.
Acknowledgment
Funding for this research was provided by the U.S. Environmental
Protection Agency (US EPA) through an interagency agreement with theUnited States Department of Agriculture (EPA DW-012-92465401; ARS
60-2022-7-002). The views expressed in this article are those of theauthors and do not necessarily represent the views or policies of the U.S.
Environmental Protection Agency. The mention of commercial products
does not constitute an endorsement. We thank the two anonymous re­viewers whose comments/suggestions helped improve and clarify thismanuscript.
Appendix A. Supplementary data
Supplementary data to this article can be found online at https://doi.
org/10.1016/j.jhydrol.2020.125720.
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