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Article

Comparing Recovery Volumes of Steady and Unsteady Injections into an Aquifer Storage and Recovery Well

by
Saeid Masoudiashtiani
1,* and
Richard C. Peralta
2
1
Larry Walker Associates (LWA), 1480 Drew Avenue, Davis, CA 95618, USA
2
Civil and Environmental Engineering Department, Utah State University, 4110 Old Main Hill, Logan, UT 84322-4110, USA
*
Author to whom correspondence should be addressed.
Earth 2024, 5(4), 990-1004; https://doi.org/10.3390/earth5040051
Submission received: 7 October 2024 / Revised: 28 November 2024 / Accepted: 28 November 2024 / Published: 9 December 2024
(This article belongs to the Topic Human Impact on Groundwater Environment)
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Abstract

:
Aquifer Storage and Recovery (ASR) can involve injecting available surface water into an unconfined aquifer and then extracting it to provide secondary water for irrigation. This study demonstrates a method for evaluating the appropriateness of steady injection versus unsteady injection for an assumed situation. In design, it can be important to affect the transient: the proportion of the injected water that would be subsequently extracted (versus that remaining in the aquifer) and the proportion within the extracted water that would be an injectate (versus ambient groundwater). These proportions can be predicted from the predicted value of an ASR well’s Recovery Effectiveness (REN)—the time-varying proportion of injectate that is extracted subsequently from the same fully penetrating well. Applying the demonstrated procedure with appropriately detailed data and simulation models can predict the REN values resulting from steady versus unsteady injection, followed by steady extraction. For convenience in displaying and computing REN, the injectate was assumed to have a 100 ppm conservative solute concentration. For this demonstration, a homogenous isotropic unconfined one-layer aquifer was assumed. The scenarios involved steady or unsteady injection for 61 days via a fully penetrating ASR well. Then, 91 days of steady pumping led to the extraction of a total volume equal to that injected. For the assumed hydrogeologic data—31 years of Salt Lake City, Utah, rainfall data and estimated captured runoff—the results show that steady injection is more likely to cause a predictable REN but might not cause a higher REN than daily varying injection of the same total volume. Assuming different runoff or hydrogeologic flows would lead to different REN values. Steady injection causes a predictable groundwater mound and can assure a sufficient vadose zone thickness for overlying plants. Augmentation and storage of captured rainwater can help to provide a steady injection rate. For a situation that requires REN management, appropriate simulations can help water managers design ASR systems that will achieve REN goals and increase sustainable groundwater availability.

1. Introduction

Escalating withdrawals of ambient surface water and groundwater for various uses in agriculture, industry, etc., can harm water sustainability. Improving water sustainability involves increasing beneficial use and preventing harm to life and the environment. The management method for recharging aquifers (i.e., the MAR) is a key strategy in sustaining water for a long time by utilizing various water resources (stormwater, treated wastewater, etc.) to recharge aquifers [1]. The MAR tools for injecting water into an aquifer (i.e., a saturated zone) are aquifer recharge (AR) wells and aquifer storage and recovery (ASR) wells. Also, the tools allowing the infiltration of water into an unsaturated zone above a water table are bank filtration via dry wells (drywells) and infiltration galleries [1,2].
Drywells are infiltration wells that penetrate the vadose (unsaturated) zone and are screened above the water table [3,4]. Injecting water into the vadose zone will cause a greater rise in a well’s water level than ASR at the same diameter [4,5]. Datry et al. [6] recommended minimizing contact between inflowing water and the organic sediments common in infiltration basins or galleries because organic sediments reduce the dissolved oxygen (DO) in the water that would otherwise re-oxygenate groundwater. Because of avoiding the sediments, ASR injection (i.e., the direct injection method) can increase groundwater DO content to a greater extent than infiltration basins or galleries.
ASR is a technological solution for treating and injecting clean water into an aquifer for temporary storage used by Minnesotans because most depend on groundwater [7]. In northern Cape May County, New Jersey, the USA, Wildwood Water Utility and Atlantic Electric Company have applied ASR to ensure sufficient water supply during the summer tourist season, with about 85% recovery, and prevent saltwater intrusion since 1967 [8]. The use of ASR in the United States, Europe, the Middle East, and Australia has been increased to secure and sustain the supply of freshwater seasonally [9,10].
ASR injectate could affect water quality within an aquifer, and subsequently, discharged water. The water quality of naturally discharged or ASR-extracted water can affect the well-being of the water users and the ecosystem. ASR wells are suitable for areas without sufficient space, with dense populations, and with growing use of groundwater extraction [11,12,13]. ASR can increase water storage in regions affected by both drought and intense precipitation [14]. When extra surface water is available, the considered ASR process involves injecting water into an aquifer via a vertical tube well. When surface water is unavailable, the well extracts a mixture of injected water (injectate) and native groundwater to meet water needs. Conservative contaminants such as chloride or dissolved nitrate [15,16,17] might exist within the injectate and/or the native groundwater. ASR well evaluation can involve predicting solute concentrations in the extracted water as well as estimating solute distribution and the remaining mass within the aquifer. Both estimation types are interesting to water users and environmental protection specialists. Ideally, the extracted water’s solute concentration will satisfy the intended use, and enough injectate will have been removed to protect the aquifer. Modeling such solute concentrations or remaining masses involves groundwater flow and solute transport simulations. These simulations help obtain values of recovery effectiveness—REN (i.e., the time-varying proportion of injectate that has been extracted)—for an ASR well. These simulations numerically model groundwater flow and solute transport for ASR under both steady and unsteady injection conditions. The evaluation of injectate recovery for ASR involves quantifying (a) the remaining amount of injected solute within the aquifer (i.e., 1.00—REN) and (b) the recovered amount (REN) within ASR-extracted water [18,19]. REN differs from recovery efficiency (RE), which has been applied to estimate the performance of ASR wells in brackish, saline, and coastal aquifers [20,21]. The RE value can be greater than one because it is the product of dividing the extracted volume without any required treatment by the injectate volume [22,23,24,25,26,27,28]. The REN is crucial for understanding how much of the injected water can be extracted later or how much remains in the aquifer. Modest mixing of (un)treated surface water or stormwater with groundwater in an aquifer is sometimes legally and environmentally acceptable. The REN can be used to predict the extent of blending that will occur. In other situations, legal water rights are involved. For instance, the Jordan Valley Water Conservancy District (JVWCD) in Utah injects extra surface water into a confined aquifer during wet months to secure additional groundwater extraction rights during dry months. If the JVWCD does not extract the injectate volume within one year after injection, the volume corresponding to the new water right decreases due to assumed losses within the aquifer.
Rather than assessing how much injectate escapes subsequent capture by extracting an ASR well, Forghani and Peralta [18] and Masoudiashtiani and Peralta [19] employed a counting molecule method to predict the REN of an ASR well. The relationship between the REN and RE is expressed as follows:
R E = R E N V E + V ( E , a m b ) V i n j
where V(E, amb) is the volume of ambient groundwater in the extracted water, VE is the total volume of extracted water, and Vinj is the total volume of injectate.
Applying an MAR method can lead to groundwater improvement or deterioration based upon (a) the water itself; (b) the applied MAR technique; and (c) the interaction between the injectate and the aquifer materials [29]. USEPA Underground Injection Control (UIC) programs address Class V ASR wells, AR wells, and other injection wells in many states, including California [30]. In California, any treated wastewater ASR injectate must meet drinking water standards at the well. The USEPA requires that the regional water quality control boards and the department of health services establish ASR discharge requirements and approve applications in this state.
In this study, we simulate the daily harvested rainwater (i.e., daily varying stormwater runoff) volume of a Salt Lake City block located in the northeast of the confluence of the Red Butte Creek and the Jordan River in Utah from April to May of 1986–2016 (31 years) by using WinSLAMM 10.4.1 software [31]. The simulated volumes provide modeled ASR injection water at unsteady and steady rates. Then, the REN (i.e., injectate recovery) evaluations of the modeled ASR show the impacts of the injection types on the recovery in the following sections. The objectives of this study are to present a contrast of the simulated volumes and injectate recovery of aquifer storage and recovery (ASR) for secondary use after the unsteady and steady injections of harvested rainwater into an unconfined aquifer.

2. Materials and Methods

2.1. Overview

This section explains assumptions, parameters, and procedures relating to obtaining REN values of ASR via flow [32] and solute transport [33] simulations. Here, the goal is to improve available groundwater during the dry period (June–August) by injecting excess surface water (i.e., harvested rainwater) into an unconfined aquifer during a preceding wet period (April–May) in a city block. Based upon work by Fetter [34], Bedient et al. [35], Pavelic et al. [23], Ward et al. [25,26], Bakker [21], Brown et al. [28], Smith et al. [14], Forghani and Peralta [18], and Masoudiashtiani and Peralta [19], in the following section, we use values of the hydrogeologic factors that impact the REN (i.e., injectate recovery) of ASR.
After the selection of approximately half-month durations for the flow and solute transport simulations, standard methods were used in estimating the advective plume length after two months (61 days) of injection; the longitudinal dispersivity; courant number; maximum time step size; total number of simulation time steps; and time steps per stress period. These estimates enabled preparing a groundwater aquifer model domain that was sufficiently large and assumed injection and extraction rates would not appreciably affect any of the employed boundary conditions. Inputting the hydrogeologic parameters for the selected site preceded the execution of the simulations. This study assumes that the aquifer is both isotropic and homogeneous, which might be an oversimplification given that real-world conditions often exhibit significant heterogeneity and anisotropy that can impact flow and solute transport. A single-site location might limit the generalizability of the findings to other geographical or hydrogeological contexts.

2.2. Selected-Site Information

Figure 1 shows parts of Salt Lake City and Salt Lake County in UT, USA. The assumed ASR well location is within a 15.271-acre residential city block (Site 5). The site is located to the northeast of the confluence of the westward-flowing Red Butte Creek and the northward-flowing Jordan River. It is (a) bounded on the north and south by Fremont and Lucy Avenues, respectively; (b) almost bisected from north to south by Jeremy Street; and (c) bounded to the west and east by South 900 W and South 800 W, respectively.
The hydrogeologic information on the properties Site 5 regarding the underlying shallow unconfined aquifer [36] includes (a) horizontal hydraulic conductivity of 18.17 m/d (59.61 ft/d); (b) initial aquifer (background) hydraulic gradient of 0.0029; (c) porosity of 0.3; (d) specific yield of 0.15; and (e) initial (original) saturated thickness of 10.23 m (33.56 ft). The basin-fill pre-historical geologic data were extracted from the Salt Lake Valley (SLV) groundwater model [36]. The observed groundwater level based on USGS observation well 4044441115505501 data at Site 5 (Figure A1) varied between 1.1 (3.6) and 1.4 m (4.6 ft) below ground surface in April and May (Figure A2). The following was assumed: (a) there was no groundwater flow between the layer and lower strata because of the short term (61 days) of injection and subsequent extraction, (b) there were no seasonal changes in storage capacity, and (c) the ASR well diameter at the site was 15.24 cm (6 inches). The potential water resources for injection were harvested rainwater (i.e., stormwater runoff) at Site 5 and/or diversion from Red Butte Creek (RBC). In this study, WinSLAMM 10.4.1 software [31] helped simulate daily varying stormwater runoff (i.e., assumed-to-be unsteady injection water) of Site 5 from April through May. This software is not free or open-source code. WinSLAMM is a tool used to estimate the water availability/injection rate for ASR [31]. The U.S. EPA has utilized it, but it is not recommended. Included properties for the simulation were (a) silty soil and ground cover consisting of nearly flat roofs (2.238 acres, 14.6%); (b) sidewalks (2.421 acres, 15.8%); (c) streets of intermediate texture (2.741 acres, 17.9%); (d) small landscaping features (3.935 acres, 25.7%); and (e) undeveloped area (3.936 acres, 25.7%). The daily April–May precipitation data for 1986–2016 (31 years) from the Salt Lake City (SLC) International Airport weather station, which is 5.91 km (3.67 miles) away, were used (Figure 1). Rain was distinguished from snow using the Static Temperature method and a 1 °C (33.8 ℉) threshold temperature [37] to simulate the runoff. To substitute for any missing precipitation data, the SLC Triad Center station, which is 3.38 km (2.1 miles) away from Site 5, was used (Figure 1).
To simulate a stormwater injection situation, the runoff volume during a particular day was injected into the aquifer at a steady rate during that day. To simulate a surface water situation, water was diverted from RBC at an assumed steady rate and then injected into the aquifer at the same rate.
For Site 5, the ASR-extracted water could irrigate turf based upon a defined irrigation schedule [38] from June through August.

2.3. Modeled System and Simulation Tools

For accurate REN prediction, the MODFLOW2005 [32] model, its Multi-Node Well (MNW2) package, and MT3DMS [33] were used. To distinguish the injected water from the native groundwater and facilitate solute transport simulation, a hypothetical concentration of 100 ppm of imaginary non-reactive solute was assigned to the injectate. In this study, a fully penetrating ASR well in a homogenous, isotropic, freshwater, one-layer, one-porosity, one-specific-yield, no-seasonal-change-in-storage-capacity, unconfined aquifer was modeled, and extraction volumes equaling injection volumes were used. Constant-head boundaries were defined along the eastern and western edges of a square model area, with no-flow boundaries along the northern and southern edges. The numbering of rows and columns starts from the top left in the MODFLOW grid. The numbers of rows and columns in the model grid are 129 and 129, respectively. Rows and columns from 1 to 55 and 75 to 120 include cell sizes of 10 m by 10 m. Rows and columns 56 to 74 have cell sizes of 7.5 by 7.5, 6.75 by 6.75, 5 by 5, 4 by 4, 3 by 3, 2 by 2, 1.25 by 1.25, 1 by 1, 0.75 by 0.75, 0.5 by 0.5, 0.75 by 0.75, 1 by 1, 1.25 by 1.25, 2 by 2, 3 by 3, 4 by 4, 5 by 5, 6.75 by 6.75, and 7.5 m by 7.5 m, respectively. An ASR well located at the center, as a block-center node in row 65 and column 65 (cell size of 0.5 m by 0.5 m), (Figure 2 and Figure 3) was also included in the assumptions. Preliminary simulations helped determine the horizontal domain size required to avoid an appreciable boundary condition impact from groundwater pumping.
For solute transport simulation, MT3DMS estimated longitudinal dispersivity via analytical equations found in a U.S. EPA online tool [39] that incorporates work by Gelhar et al. [40], Wilson et al. [41], and Xu and Eckstein [42]:
I f   L p ≤ 1   m :   α L = 0.1 × L p
I f   L p > 1   m :   α L = 0.83 × log 10 ⁡ L p 2.414
where Lp denotes advective plume length (m), equal to (v × injection duration); v denotes linear pore velocity (m/d), equal to (K × i/n); K denotes horizontal hydraulic conductivity (m/d); i denotes aquifer initial (background) hydraulic gradient; n denotes porosity; and αL denotes longitudinal dispersivity (m).
Also, the courant number (C) is an input parameter of the MT3DMS advective process used to reduce oscillations, enhance accuracy, and minimize numerical dispersion in cases where advection outweighs dispersion. The number is determined as follows: (v × ∆t)/∆x, where v represents linear pore velocity, ∆x is the grid cell size at 0.5 m (1.64 ft) inside the well, and ∆t is the maximum desired time step size [43].
To determine the appropriate simulation time step size in days for the preferred spatial discretization, the grid Peclet number, P, was estimated to be 2C [43]. By assuming that P is equal to (∆x/αL), the maximum desirable time step size for use during injection can be computed.
For simulation of ASR injection (i.e., injection of available rainfall, streamflow, and plant water) into aquifer and extraction, MODFLOW2005 and MT3DMS include (a) period 1, in which steady-state background heads were simulated; (b) transient periods 2–5, in which injection was employed; (c) periods 6–11, in which extraction was simulated; (d) identical numbers of time steps per period; and (e) MODFLOW2005 PCG solver with a 0.01 m head change criterion and 0.01 m residual convergence criterion. For advection and dispersion simulation, MT3DMS utilizes the total variation diminishing (TVD) package and the generalized conjugate gradient (GCG) solver. To minimize processing time, the extraction period was assigned a single time step, as using even 300 time steps for extraction increases REN by less than 0.005.
As mentioned above, we assigned 100 ppm of an imaginary non-reactive solute as an injectate to distinguish it from native groundwater. MT3DMS simulations provide both the mass of solute injected into the ASR well and the mass of solute recovered from the well. The REN is equal to extracted solute mass divided by injected solute mass. Each successful simulation provided the total mass of solute injected through the ASR well and the mass of solute recovered from the well. RENt values were computed after 15, 30, 45, 61, 76, and 91 days of simulated extraction (REN15, REN30, REN45, REN61, REN76, and REN91, respectively) from simulation results. This study’s intended use and purpose entail predicting the proportion of ASR recovery but not actual water quality. One hundred is a practical and convenient value for predicting the proportion.
As shown in Table 1, steady injected water could be diverted from RBC during April and May for ASR at Site 5. As the proposed RBC diversion for ASR steady injection, Demos 1 and 2 evaluate whether steady or unsteady injection results in extracting a predictable portion of the injectate.

3. Results and Discussion

Evaluating the responses of any aquifer storage and recovery (ASR) plan is required for water use and the environment (i.e., the aquifer). In this case, the ASR well was within a quasi-infinite, one-layer, one-porosity, one-specific yield, no-seasonal-change-in-storage-capacity, unconfined aquifer. The provided demonstrations (Demos) illustrate the responses of the flow (MODFLOW2005) and solute transport (MT3DMS) simulations for injectate recovery resulting from unsteady and steady ASR injections.
Here, for the selected site (Site 5), water-volume use of stormwater runoff (i.e., harvested rainwater) during the wet months (April and May) could provide ASR injection water. To quantify the volume, the April–May runoff volume of every year from 1986 to 2016 (31 years) at Site 5 was simulated using WinSLAMM 10.4.1 software. Figure 4 shows the annual volumes that were used for ASR injection from April to May of each year.
The steady injection of water into the aquifer could be diverted by surface water (Red Butte Creek, RBC) nearby. Signifying the beneficial use of RBC water steadily for ASR injection equaling the unsteady runoff volume for each of the 31 years is one of the goals of Demos 1 and 2 (Table 2). We acknowledged that a tributary can divert daily varying stormwater runoff (unsteady inflow) from Site 5 into RBC in exchange for steady RBC outflow into the ASR during the wet months.
Demos 1 and 2 explore which type of ASR injection can result in predictive recovery (REN) during extraction. For these Demos, the 100 ppm imaginary conservative contaminant for the ASR injectate was applied to evaluate the impacts of unsteady and steady injections on injectate recovery during extraction.
In Demo 1, the daily varying stormwater runoff (unsteady injection) during April and May (61 days) in each of the 31 years was injected, and the injection volume was steadily extracted during the dry months (91 days). For instance, Figure A4 presents unpredictable daily groundwater mounds that could be harmful to crops in 2001. Figure 5 shows that even though one year might have a greater total injection volume than another year, the REN resulting from the first year might not be greater than that of the other year.
For Demo 2, the runoff (i.e., harvested rainwater) volume in each of the 31 years was divided by the number of injection days (61 days) and calculated to provide the daily steady ASR injection rate. As a steady injection, the increasing rate of the continuous groundwater (steady) extraction results in increasing REN values (Figure 6). Thus, steady injection can provide greater confidence in including and extracting a predictable groundwater mound (Figure A4) to obtain a sufficient vadose zone for crops and a portion of the injectate (Figure 6), respectively.
When comparing the REN values resulting from the steady versus unsteady injection of the same total volume, it becomes clear that unsteady injection could achieve a higher or lower predicted REN than the steady one. For example, the simulated injection volumes for 1987 and 2001 (e.g., Figure A3 shows simulated flow rates of 61-day unsteady and steady injections and 91-day steady extraction for 2001) are 1392.81 m3 and 1738.17 m3, respectively. For 1987, the predicted REN values of the steady and unsteady injections are 0.288 (gm/gm) and 0.342 (gm/gm), respectively. For 2001, the respective REN values are 0.248 (gm/gm) for steady injection and 0.168 (gm/gm) for unsteady injection.
As mentioned, the water volume for ASR steady injection could be the 90%-probability runoff volume during the wet months (April and May) obtained after studying the historical data of any site. The volume can be diverted steadily from surface water nearby to apply the beneficial use of steady injection for ASR predictable injectate recovery. For Site 5, the 90%-probability runoff for the 31-year period (Figure 4) equals 1047.46 m3 (230,409 gallons). The assumed pre-existing groundwater 91-day extraction volume is the same as the 61-day injection for ASR. The ASR-extracted water volume can irrigate 1896.71 m2 (0.47 acre) of turf based on the irrigation schedule [38,44] from June through August (dry months, 91 days) at Site 5.
The evaluations can help water managers predict whether an ASR system increases water supply in aquifers and for uses (e.g., secondary irrigation). The model results from ASR steady injection and the 90% probability of the 31-year harvested rainwater show that water managers could increase groundwater availability for use during three dry months (the 91-day period of high demand) via the ASR system at Site 5.

4. Conclusions

Presented are the simulated results of injecting specific total water volumes into an aquifer using steady and unsteady rates over time and then steadily extracting the same volumes. The intent was to compare the recovery effectiveness achieved after extraction was completed. The comparisons are intended to aid water managers in ASR planning. The assumptions and simulation processes are as follows.
For current land use in a specific Salt Lake City (SLC) block, precipitation data from 1986 to 2016 were used to create a 61-day time series of springtime daily runoff for each year. All the runoff was assumed to be fully available for injection via one fully penetrating well into an unconfined homogenous isotropic one-layer aquifer (the storage coefficient was assumed to be stationary, unchanging with the seasons). For these short-term simulations, possible vertical recharge from rainfall, seepage with adjacent strata, and lateral flows with extensions of the aquifer were ignored.
Two types of scenarios of groundwater flow and transport simulations were performed for each year from 1986 to 2016. In one type, the above time series was used to simulate 61 days of injection of estimated daily runoff (i.e., harvested rainwater), followed by 91 days of steady extraction that removed a total volume of groundwater equivalent to the injectate volume. The other scenario type involved the simulation of steady injection at a daily rate equaling 1/61 of the total April–May runoff of the year examined. Again, 91 days of steady extraction removed a volume equal to the total injection. Conclusions concerning the simulated final achieved REN are as follows.
(a)
When comparing unsteady injection simulations, the unsteady injection time series has a greater impact on REN than the total injection volume; a year with a greater total injection volume might not yield a higher REN.
(b)
When comparing steady injection simulations, the greater the total injection volume, the greater the resulting REN.
(c)
When comparing unsteady versus steady injection simulations, the following was found:
i.
Scenarios in which water was injected at a steady rate usually yielded higher REN values than scenarios having random daily varying injection rates. For example, for the 1738 m3 injection volume of 2001, the final REN values are 0.25 (gm/gm) for steady injection and 0.17 (gm/gm) for unsteady injection.
ii.
Unsteady injection sometimes yielded a higher REN than steady injection. For the 1392.81 m3 injection volume in 1987, the REN values of the steady and unsteady injections are 0.288 (gm/gm) and 0.342 (gm/gm), respectively.
For one-well ASR situations where achieving a particular REN is desirable, steady injection through the well is preferable to injecting at random rates that depend upon daily runoff capture. Planned injection rates can be designed such that they do not exceed the likely amount of water available nor cause excessive groundwater mounding (preventing saturation in the root zone of the overlying vegetation). Steady injection and subsequent extraction rates can be designed to achieve RENs that prevent undesirable changes in ambient groundwater quality or to prevent undesirable salinity of the extracted water. In summary, utilizing REN values in an ASR system design can increase beneficial groundwater availability and use.

Author Contributions

Conceptualization, S.M. and R.C.P.; methodology, S.M. and R.C.P.; validation, S.M. and R.C.P.; formal analysis, S.M.; investigation, S.M. and R.C.P.; resources, S.M.; data curation, S.M.; writing—original draft preparation, S.M.; writing—review and editing, R.C.P.; visualization, S.M.; supervision, R.C.P.; project administration, R.C.P. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the U.S. EPA-STAR project under grant number [83582401], the Civil and Environmental Engineering (CEE) Department, the Utah Water Research Laboratory (UWRL), and the Utah Agricultural Experiment Station at Utah State University.

Data Availability Statement

All data generated and utilized during the study are included in the published article. Additional information can be obtained from the corresponding author upon request.

Acknowledgments

The authors express their gratitude for the support provided by the Center for High-Performance Computing (CHPC) at the University of Utah. This work was also supported by the Utah Agricultural Experiment Station at Utah State University. The authors extend their appreciation to R. Ryan Dupont for his leadership on the EPA-STAR grant project, as well as to Marv Halling and David G. Tarboton, the heads of the Civil and Environmental Department, and the Utah Water Research Laboratory at Utah State University, respectively.

Conflicts of Interest

Author Saeid Masoudiashtiani was employed by the company Larry Walker Associates (LWA). The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Appendix A

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Figure A1. USGS Observation Well no. 4044441115505501 (Hydrologic Unit no. 16020204), with a latitude of 40°44′45″, a longitude of 111°55′06″ NAD27, and a land surface altitude of 1283.2 m (4210 ft.) above NGVD29. The well is 15.0 ft. (4.57 m) below the land surface and located about 350 m (1148.29 ft.) away from the residential area (Site 5) in Salt Lake County, Utah, USA (URL: http://waterdata.usgs.gov/nwis/inventory?agency_code=USGS&site_no=404444111550501, accessed on 1 October 2007).
Figure A1. USGS Observation Well no. 4044441115505501 (Hydrologic Unit no. 16020204), with a latitude of 40°44′45″, a longitude of 111°55′06″ NAD27, and a land surface altitude of 1283.2 m (4210 ft.) above NGVD29. The well is 15.0 ft. (4.57 m) below the land surface and located about 350 m (1148.29 ft.) away from the residential area (Site 5) in Salt Lake County, Utah, USA (URL: http://waterdata.usgs.gov/nwis/inventory?agency_code=USGS&site_no=404444111550501, accessed on 1 October 2007).
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Figure A2. Available observed groundwater levels from 1982 to 1990 reported by USGS Observation Well no. 404444111550501 located about 350 m (1148.29 ft.) away from Site 5. The depth to groundwater level in April and May for the years is between 1.1 (3.6) and 1.4 m (4.6 ft.).
Figure A2. Available observed groundwater levels from 1982 to 1990 reported by USGS Observation Well no. 404444111550501 located about 350 m (1148.29 ft.) away from Site 5. The depth to groundwater level in April and May for the years is between 1.1 (3.6) and 1.4 m (4.6 ft.).
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Figure A3. Simulated daily flows at the well resulting from 61 days of unsteady and steady injections (positive magnitudes), followed by 91 days of steady extraction (negative magnitudes), for an ASR well at Site 5 in 2001.
Figure A3. Simulated daily flows at the well resulting from 61 days of unsteady and steady injections (positive magnitudes), followed by 91 days of steady extraction (negative magnitudes), for an ASR well at Site 5 in 2001.
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Figure A4. Simulated groundwater levels at the well resulting from 61 days of unsteady and steady injections, followed by 91 days of steady extraction, for an ASR well at Site 5 in 2001 (Note: the elevation datum is equal to zero).
Figure A4. Simulated groundwater levels at the well resulting from 61 days of unsteady and steady injections, followed by 91 days of steady extraction, for an ASR well at Site 5 in 2001 (Note: the elevation datum is equal to zero).
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Figure 1. Residential area (Site 5) and weather stations at the international airport and Triad Center in Salt Lake County, UT, USA.
Figure 1. Residential area (Site 5) and weather stations at the international airport and Triad Center in Salt Lake County, UT, USA.
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Figure 2. Modeled area for simulation of ASR well (top view) (not to scale).
Figure 2. Modeled area for simulation of ASR well (top view) (not to scale).
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Figure 3. Modeled area for simulation of ASR well (side view) (not to scale).
Figure 3. Modeled area for simulation of ASR well (side view) (not to scale).
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Figure 4. Total April–May runoff volumes of the 31 years in Site 5 simulated via WinSLAMM 10.4.1 software.
Figure 4. Total April–May runoff volumes of the 31 years in Site 5 simulated via WinSLAMM 10.4.1 software.
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Figure 5. REN (gm/gm) values of every half month during extraction for Demo 1; continuous (steady) extraction rate equals the injection volume divided by 91 days for every 31 years. Extraction volume equals the injection volume.
Figure 5. REN (gm/gm) values of every half month during extraction for Demo 1; continuous (steady) extraction rate equals the injection volume divided by 91 days for every 31 years. Extraction volume equals the injection volume.
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Figure 6. REN (gm/gm) values of every half month during extraction for Demo 2; continuous (steady) extraction rate equals the injection volume divided by 91 days for every 31 years. Extraction volume equals the injection volume.
Figure 6. REN (gm/gm) values of every half month during extraction for Demo 2; continuous (steady) extraction rate equals the injection volume divided by 91 days for every 31 years. Extraction volume equals the injection volume.
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Table 1. Characteristics of demonstrations (Demos) of ASR unsteady and steady injections and steady extraction.
Table 1. Characteristics of demonstrations (Demos) of ASR unsteady and steady injections and steady extraction.
IIIIIIIVVVIVII
DemoNumber of MODFLOW-MT3DMS simulationsInjection volume, in Julian Days, of 61-day inj. periodTotal 61-day injection vol.Extraction vol. in each of 91 daysTotal 91-day extraction vol.Type(s) of water qualityGoal(s)
1.1–1.3131Unsteady. For 61-day simulations for each of 31 years, the injection volume of each day in the year is as follows: injection volume = Site 5 runoff of day in the year.Total injection volume = sum of Column II daily injection volumes in the yearSteady. Daily extraction volume for year = (Total injection vol. for year/91 days)Total extraction vol. = Total injection vol.Assumed 100 ppm conservative injectatePresent recovery of unsteady stormwater injection via steady extraction
2.1–2.3131Steady injection volume in year = total injection volume/61 days““““Present recovery of steady injection of diverted surface water via steady extraction
Table 2. Selected results of demonstrations (Demos).
Table 2. Selected results of demonstrations (Demos).
DemoNumber of MODFLOW2005-MT3DMS SimulationsDescriptionTotal Inj. Vol.(Ext. Vol.)/(Inj. Vol.)
(-)
Avg. Flowrate
1.1–1.3131Injecting values of daily varying runoff for 31 seasons to compare REN values478.23 to 5048.26 m31.0
0.42 l/s or 6.58 gpm
2.1–2.3131Steady injection of the same annual volumes as Demo 2 to compare REN values”
””
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Masoudiashtiani, S.; Peralta, R.C. Comparing Recovery Volumes of Steady and Unsteady Injections into an Aquifer Storage and Recovery Well. Earth 2024, 5, 990-1004. https://doi.org/10.3390/earth5040051

AMA Style

Masoudiashtiani S, Peralta RC. Comparing Recovery Volumes of Steady and Unsteady Injections into an Aquifer Storage and Recovery Well. Earth. 2024; 5(4):990-1004. https://doi.org/10.3390/earth5040051

Chicago/Turabian Style

Masoudiashtiani, Saeid, and Richard C. Peralta. 2024. "Comparing Recovery Volumes of Steady and Unsteady Injections into an Aquifer Storage and Recovery Well" Earth 5, no. 4: 990-1004. https://doi.org/10.3390/earth5040051

APA Style

Masoudiashtiani, S., & Peralta, R. C. (2024). Comparing Recovery Volumes of Steady and Unsteady Injections into an Aquifer Storage and Recovery Well. Earth, 5(4), 990-1004. https://doi.org/10.3390/earth5040051

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