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Article

A Community-Led Assessment to Identify Groundwater-Dependent Lakes in Parkland County (Alberta, Canada)

by
Brian Smerdon
1,*,
Jenna Bahija Tarrabain Maccagno
1,
Bradley Peter
2,
Walter Neilson
3,
Dave Mussell
3 and
David Trew
3
1
Department of Earth and Atmospheric Sciences, University of Alberta, Edmonton, AB T6G 2E3, Canada
2
Alberta Lake Management Society, Edmonton, AB T6E 4T3, Canada
3
Mayatan Lake Management Association, Parkland County, AB T7Y 2M3, Canada
*
Author to whom correspondence should be addressed.
Water 2025, 17(3), 440; https://doi.org/10.3390/w17030440
Submission received: 17 January 2025 / Revised: 29 January 2025 / Accepted: 2 February 2025 / Published: 5 February 2025
(This article belongs to the Section Hydrogeology)
Browse Figures
Versions Notes

Abstract

:
Responding to a growing concern about impacts from anthropogenic activity on several dozen lakes, a group of citizens initiated and led a water quality sampling program that included characterizing groundwater dependence. The small lakes are located on hummocky glacial terrain near Edmonton, Alberta, Canada. A team of volunteers collected lake samples for a variety of limnological and ecological analyses to document lake health and trophic state, and collaborated with a university research group to identify groundwater dependence using specific environmental tracers (δ2H, δ18O, and 222Rn). Water chemistry and isotopic measurements are largely explained by the position of a lake within the local groundwater flow system. A simple metric to express the likelihood of groundwater dependence was calculated using the total dissolved solids (TDS), δ18O, and 222Rn values. Across the relatively small study area, a greater likelihood of groundwater dependence was determined for lakes located downgradient from an elevated recharge area. In contrast, where the water table was relatively flat, a lower likelihood of groundwater dependence was found. These results were similar to the spatial pattern of a trophic state, indicating that groundwater dependence may be one of the factors responsible for lake ecological status. The data generated by citizens and the knowledge gained about the hydrology of this area will help discussions between landowners and decision makers on how to best manage land use in this diverse landscape.

1. Introduction

Citizen science can bring together local and scientific communities for a common goal to enhance water quality monitoring and fill gaps in watershed knowledge [1]. The participatory approach has thrived because local citizens are often passionate about water resources, can respond to environmental concerns by raising awareness within their community, and reduce the financial cost of data collection through volunteering [2]. In biological and ecological studies, citizen science has been very successful; however, it is still emerging in groundwater-related initiatives [3]. Monitoring groundwater levels using private water wells has proven to be a successful activity [4,5], with non-scientists completing data collection and gaining knowledge about a water resource that is often considered hidden. For groundwater-related studies, a participatory science approach can benefit both the research and public communities because education about groundwater can lead to locally relevant technical questions and more effective resource management [3].
Groundwater stewardship is described as any monitoring, characterization, and non-regulatory management activities that are critical in local decision making [6]. Often, it is local governments (e.g., a municipality or county within a province, state, or territory) that make land use decisions, which have a direct connection to the quantity and quality of water resources. For non-scientists contributing to a participatory science project, co-created stewardship and environmental monitoring activities help respond to local concerns [7] and foster trust between the local and scientific communities [8]. However, for more detailed investigations (e.g., characterizing the geological setting, hydrogeological properties, and water quality), there are very few examples of community-led initiatives, likely because of the technical expertise required [1].
Decades of research have resulted in well-established methods to quantify groundwater exchange with lakes and the role of groundwater in a lake water balance [9]. Lakes interact with groundwater to varying degrees [10], with the level of interaction based on the geology (i.e., the permeability of the sediments and bedrock) and topography of the terrain [11]. Small lakes can have anywhere from an insignificant to a significant amount of groundwater inflow and outflow compared to the volume of the lake, which has been shown to influence lake chemistry [12]. Lakes are described as groundwater-dependent when they are sufficiently well connected to a groundwater flow system, which in turn establishes consistent ecosystems and habitats [13].
In this study, we demonstrate that a watershed assessment and groundwater characterization is possible through a community-led project. Such an approach creates a connection between a complex science and concerned citizens, which can inform local management [14]. Responding to concern for the health of lakes in central Alberta, the citizen-based Mayatan Lake Management Association (MLMA) worked with the Alberta Lake Management Society (ALMS) to develop a regional water quality survey. Previous research indicated that groundwater may contribute to some of the lakes [15,16], but knowledge of groundwater dependence was not broadly known, leading the MLMA to engage with a university-based groundwater research group to address this gap in knowledge. Given the success of citizen science projects related to surface water monitoring and water quality, the goal of this study was to incorporate a groundwater perspective into a community-led assessment of lakes and advance the knowledge of groundwater characterization. The objective of the study was to identify groundwater-dependent lakes from a community-led water quality survey.

2. Study Area

The study area is in the rural municipality of Parkland County, located west of the City of Edmonton (Figure 1a) in central Alberta, Canada. The climate is humid continental with a mean annual air temperature of 2.4 °C and annual precipitation of 434 mm/year, of which 60% occurs during the May to August period [17].
Several dozen small lakes ranging in size from 0.003 to 2.8 km2 (mean of 0.3 km2) are located on the hummocky landscape near the City of Spruce Grove, Alberta, and follow an approximate northeast (NE) to southwest (SW) trend (Figure 1b). Located close to urban areas, some of the lakes appeared to be experiencing impacts from anthropogenic activity, including suspected changes to lake productivity. While much of this part of the Boreal Forest Natural Region [18] has been converted to agricultural lands or undergone rural residential development [19], some of the small lakes remain in a forested natural setting and are considered pristine.
The surficial geology in the region has been shaped by glacial and fluvial processes that have deposited glacial moraine and glaciolacustrine sediments and a pitted delta. Most sediments are glaciogenic diamict with a mixture of sand, silt, and clay [20,21]. The pitted delta likely formed where supraglacial rivers flowed off glacial ice and into a glacial lake centred on the Edmonton area. These pitted delta sediments are predominantly sand and gravel with clay to silt interbeds [22]. The ground topography is hummocky and was produced by the melting of glacial ice surrounded or covered by sediment as the Laurentide ice sheet retreat. The lakes in this study coincide with the pitted delta deposit, which has an approximate area of 525 km2 (Figure 1b). The thickness of sediments above bedrock [23] varies from 10 to 100 m in the pitted delta area (Figure 2a), with a lower discontinuous sand and gravel unit (Figure 2b–d). Below the sediments is the bedrock of the Horseshoe Canyon Formation, which is a bentonitic sandstone and shale with coal seams [24] that can form localized aquifers and be a residential water supply in the study area.
Groundwater mapping in Central Alberta [25] indicated that the water table is typically driven by ground surface topography, with subsequent mapping showing a shallow water table in the pitted delta area compared to the surrounding region [26,27]. From a detailed regional groundwater model, it was found that groundwater recharge occurs through the pitted delta sediments and creates a shallow water table [28]. The water table diverges away from the pitted delta recharge area, which directs groundwater flow to nearby creeks and downward into deeper buried valley aquifers (e.g., depicted on the right side of Figure 2c,d).

3. Methods

3.1. Regional Synoptic Survey

Given the large number of small lakes located across the pitted delta, a regional synoptic survey was developed by the community members to both update knowledge and stimulate broader interest about the lakes in the community. From the range of methods available to investigate groundwater dependence [9], chemical and isotopic methods [29] were considered to have the greatest success with volunteer community members [30]. The stable isotopes of water have been applied to lake budget studies for decades and their application has become relatively common [31,32]. The naturally occurring isotope radon-222 has also proved useful to identify groundwater discharge to lakes [33,34]. When combined, these isotopic tracers can provide insight to discharge rates [35].
The regional synoptic survey of this study focused on lake water quality and was designed in partnership with the ALMS. Field sampling occurred between 2020 and 2023. In 2020, 12 lakes were sampled to assess the methodology and examine phosphorus geochemistry to support a research project [15]. In 2021 and 2022, most of the fieldwork occurred, with 44 and 50 lakes sampled, respectively. Finally, in 2023, an additional 27 lakes were sampled.
The current study will focus on the 2021 and 2022 period, when 42 of the same lakes were sampled both years. The complete results of the field programs are reported by the ALMS [36,37] and water quality data are freely available [38]. The surveys were completed by citizens, with a small group of volunteers from the MLMA and ALMS collecting water samples under the direct supervision of a retired water scientist with experience in limnology. The volunteers typically had a technical or science background and were trained at the time of sampling for the field tasks. Thirty-one landowners were also engaged and provided access to lakes situated wholly on private property.

3.2. Citizen Water Sampling

The lakes were sampled once each year between early August and mid-October. The time of year was intended to capture lakes during the period of relatively high water temperatures, which would demonstrate that the deeper lakes were thermally stratified and displayed low surface nutrient and algal concentrations, whereas shallow lakes were likely well mixed and displayed higher nutrient and algal concentrations. From a groundwater dependence perspective, the time of year was expected to reflect the latter part of the evaporative open-water season when precipitation tends to be low in the region.
In 2021, water samples were collected from 0.5 m depth using a Van Dorn sampler. In 2022, vertically integrated water samples were collected from the upper 2.5 m of the water column using a weighted tube sampler with a one-way foot valve. Water samples were collected for a variety of limnological and ecological analyses (e.g., chemistry, nutrients, phytoplankton, chlorophyll-a). At the time of sample collection, field parameters including pH, water temperature, specific conductance, and dissolved oxygen were measured using a YSI ProSolo probe (YSI Incorporated, Yellow Springs, OH USA). To assess the groundwater dependence of each lake, university-based researchers had the volunteers collect water samples into specific containers, as shown in Table 1. The water samples were stored and transported in a cooler with ice, then refrigerated until delivered to each lab for analysis. 222Rn was measured at the end of each day of sampling using an RAD7 radon detector (Durridge Company Inc., Billerica, MA USA). For the synoptic sampling approach, the goal was to use specific indicators (i.e., δ2H, δ18O, and 222Rn) to assess the degree of groundwater dependence for each lake. Rather than invoking isotopic mass balance models to quantify fluxes, the concentrations of each lake were interpreted qualitatively (e.g., low, medium, high) relative to other lakes sampled and knowledge of waters in the region by the university researchers. Though simplistic, this allowed any spatial patterns to be understood by everyone involved in the assessment.

3.3. Regional Groundwater Chemistry

To place the lake chemistry results in a broader context, the sampling results were compared with regional groundwater chemistry data. Because wells were not sampled as part of the community-led program, and they are not necessarily positioned to characterize lake–groundwater interaction, a recent statistical summary of groundwater quality parameters developed by the Alberta Geological Survey [39] was used. The statistical summary was developed from publicly available water quality parameters from several sources, including well records, baseline groundwater assessments, government observation wells, and aggregated results of domestic water well testing. The water quality parameters were allocated stratigraphically based on depth and knowledge of the Geological Framework of Alberta [40]. Water quality parameters are summarized by quarter township using the Alberta Township Survey (ATS) system grid and include Ca, Mg, Na, K, NO3, SO4, Cl, HCO3, CO3, F, Fe, Mn, total dissolved solids (TDS), alkalinity, and hardness. For the current study, we used the median concentration values of water samples from wells completed in the sediments above bedrock for quarter township blocks (each approximately 23.5 km2) across the study area (n = 783).

4. Results and Discussion

4.1. Direction of Groundwater Flow

Using the regional groundwater model [28], a refined water table map was created for the pitted delta area by incorporating the specific elevation of each lake in the study area and perennial creeks (Figure 3) that were considered too small to be included in the regional groundwater model. The water table map has the same general trend that has been shown previously [26,27], with the water table being highest at the north end of the pitted delta, where both the ground surface topography and the deeper bedrock surface topography show a ridge (Figure 2d). The topography of the ground and bedrock surfaces likely establishes a localized groundwater divide that directs groundwater flow to the south through the pitted delta sediments. For the pitted delta area, the water table has a ‘saddle’ shape, with groundwater flow initially to the south from the elevated recharge area, then east and west toward perennial creeks (e.g., Kilini Creek). In the southern part of the pitted delta, the water table is relatively flat (Figure 3). The regional groundwater model also found that groundwater moved downward through the pitted delta sediments into either the Beverly buried valley aquifer at the base of the sediments or the underlying bedrock [28].

4.2. Water Chemistry

The distribution of median TDS for groundwater in the pitted delta sediments varied from 500 to 1500 mg/L (Figure 4). There is an approximately northeast (NE) to southwest (SW) trend, with lower TDS values in the NE part of the pitted delta compared to the SW. From a regional perspective (i.e., not at the scale of an individual lake), this is expected considering the direction of groundwater flow. Groundwater recharge occurring at the north end of the pitted delta is relatively fresh and the water chemistry is expected to evolve as it travels through the groundwater system, increasing the TDS. The NE-SW trend in TDS provides a convenient basis to define the general groupings of the lake sites (NE and SW, shown in Figure 4) for a discussion of the chemical and isotopic results.
The TDS of individual lakes sampled in 2021 and 2022 varied from 47 to 1800 mg/L (Figure 5a), with most of the lakes having less than 10% difference in TDS between 2021 and 2022. For lakes in the NE part of the pitted delta, the mean TDS was 325 mg/L with a maximum of 730 mg/L, whereas for the SW lakes, the mean TDS was 656 mg/L and the maximum was 1800 mg/L (Figure 5a). The results for the lakes reflects a similar NE-SW trend as the groundwater TDS (Figure 4) but also indicates greater lake-to-lake variability for the NE lakes compared to the SW lakes.
To compare the water chemistry of the lakes with groundwater in the pitted delta, a Piper diagram is used (Figure 6), which shows the net effect of major ions on the water composition. The lower TDS groundwater in the NE part of the pitted delta is plotted on the left side of the Piper diagram, which indicates Ca-HCO3-type water that is typical of precipitation and freshwater. The NE lakes are also plotted in this same region, with a slight trend along the SO4 + Cl axis indicating an evolution toward Ca-SO4-type water. In contrast, groundwater in the SW part of the pitted delta is mostly plotted on the lower part of the Piper diagram, indicating Na-HCO3-type water. Interestingly, the SW lakes are plotted in a different part of the Piper diagram, appearing to be more evolved Ca-SO4-type water than the NE lakes. The results shown in Figure 6 confirm earlier findings by [16], who studied six of the SW lakes and found that groundwater and lake water had distinctly different water from a geochemical perspective. These earlier findings suggest that a minimal amount of groundwater interacts with the SW lakes [16].
The results of the field programs for the study area [36,37] also include many limnological parameters (e.g., nutrients, phytoplankton, chlorophyll-a) that are relevant to understanding lakes but are beyond the scope of the current study. For context, total phosphorus is shown in Figure 5b because it represents one of the most important nutrients controlling the trophic level of lakes. Similar to the water chemistry, there is a wide range of total P across the pitted delta, which leads to classifications varying from hypereutrophic to oligotrophic. However, it should be noted that the lowest total P concentrations appear clustered in the NE lakes. Nine of these NE lakes were investigated in 2020 during the early part of the lake survey program [15]. By examining the lake water column and lakebed sediments, it was concluded that these oligotrophic lakes had a high fraction of phosphorus (calcium-bound P) in the sediments and that calcium from groundwater in the pitted delta likely helped regulate P in the lakes [15]. The findings of [15] suggest that a moderate amount of groundwater interacts with the NE lakes.

4.3. Isotopic Indicators of Groundwater Interaction

The stable isotope ratios of water are shown in Figure 7 relative to the local meteoric water line (LMWL) for the Edmonton area [16]. For the NE lakes, δ18O results vary from −15 to −7 per mil (‰), whereas for the SW lakes the δ18O results were across a narrower range of −9 to −6‰, as was found for a smaller subset of the SW lakes previously [16]. For all the lake sites there was less than 2‰ and 8‰ difference in δ2H and δ18O respectively between 2021 and 2022. The local evaporation line (LEL) for the lake samples is δ2H = 4.8δ18O−57.8 which is nearly the same as found previously (δ2H = 4.7δ18O−56) for a subset of the SW lakes in 2016 and 2017 [16], and similar to the LEL for other lakes in Central Alberta (4.8δ18O instead of 5.3δ18O) [31].
The co-isotope plot of Figure 7 demonstrates a difference between NE lakes and SW lakes, which is mapped in Figure 8a. Considering the consistency in values year to year, this indicates a difference in the hydrological process between the NE and SW areas of the pitted delta. The wider and more negative values for the NE lakes could suggest that these lakes are not experiencing the same evaporative effect as the SW lakes. Given that all the lakes are relatively small and in the same region, it is likely that the stable isotope variability is a result of different water sources rather than variation in climate. It was found previously that the δ18O of groundwater was in the range of −15 to −18‰ [16], which suggests that some of the NE lakes have a consistent inflow of groundwater as hypothesized [15].
Measured values of 222Rn (in 2021 only) varied from 0 to 13 Bq/L, with a mean value of 7 Bq/L for NE lakes and 3 Bq/L for SW lakes (Figure 8b). Groundwater from one of the buried valley aquifers in the Edmonton area was found to have a mean 222Rn of 9.4 Bq/L [41], and groundwater samples from the Government of Alberta observation wells completed in surficial sediments in other parts of Alberta exhibited a mean of 10.7 Bq/L [42]. Since 222Rn will only exist in the lake water column for a short period before either partitioning to the atmosphere or undergoing radioactive decay (the half-life of 222Rn is 3.8 days), the presence of 222Rn at about 8 Bq/L or higher could also indicate a consistent inflow of groundwater.

4.4. Identifying Groundwater-Dependent Lakes

To bring together the water chemistry and isotopic results, a simple metric was defined to indicate the likelihood of groundwater dependence. From the measurements of lake TDS, δ18O and 222Rn, a score was calculated based on whether a parameter indicates the possibility of groundwater inflow to a lake, as shown in Table 2. For each parameter, a rank of 1 to 3 was specified to qualitatively represent the likely degree of groundwater contribution, where 3 indicates the highest likelihood of groundwater inflow. Higher TDS and 222Rn were assumed to represent the contribution of groundwater composition to the lake. More negative δ18O was assumed to represent a dominance of groundwater inflow over evaporation in the lake water balance. Since the TDS value was influenced by several other processes in the local lake basin, the weight of its rank was set to 50% of the weight for δ18O and 222Rn. The minimum and maximum possible scores were 5 and 15, respectively.
For the NE lakes, the mean groundwater dependence score was 10, with a range of 5 to 15. For the SW lakes, the mean score was 7, with a range of 6 to 9. As expected, the scores reflect the findings described for the specific chemical and isotopic results described above. The lower score and narrower range for the SW lakes indicates a lower likelihood of these lakes receiving a significant amount of groundwater inflow (Figure 9). In contrast, there were six NE lakes with a score greater than 12, and many with a score between 8 and 12. Mapping the groundwater dependence scores with the water table map (Figure 9) reveals a regional relationship between individual lakes and their position within the pitted delta groundwater flow system. The NE lakes with a high groundwater dependence score are located at the convergence of groundwater flow paths. The SW lakes, which have low scores and a narrower range, are located where the water table is much flatter. For all the lakes in the study area, some degree of groundwater interaction will occur; however, the combination of water chemistry and isotopic measurements helps identify where clusters of lakes may have greater dependence. To validate the groundwater dependence score, a more detailed investigation for a subset of these lakes could be carried out in the future (e.g., three lakes from each score category shown in Figure 9). This subsequent research could focus on repeated measurements in different seasons and depth profiles for the lake water and attempt to sample local groundwater for comparison.
With the qualitative assessment of groundwater dependence, knowledge of the lakes within Parkland County continues to advance. The lake survey revealed diverse attributes and trophic conditions, with some lakes having low productivity and others having high nutrient levels and significant amounts of phytoplankton [36,37]. Groundwater dependence represents an additional piece to a multi-faceted puzzle. Characterizing the diversity of lakes contributes to local conservation and stewardship activities and provides a basis for the MLMA and ALMS to engage with local governments in land and water management discussions.

5. Conclusions

Synoptic surveys were completed in 2021 and 2022 to identify groundwater-dependent lakes in Parkland County, Alberta, Canada. The field program was initiated and led by citizens who had a concern about local impacts from anthropogenic activity, including suspected changes to lake productivity. While there was some knowledge about the lakes and general hydrology of the area, scientifically consistent information was not available for the dozens of small lakes. Water sampling was carried out by a team of volunteers in collaboration with local landowners. A variety of limnological and ecological analyses were completed (e.g., water chemistry, nutrients, phytoplankton, chlorophyll-a) to document lake health and trophic state, and specific environmental tracers (δ2H, δ18O, and 222Rn) were analyzed to assess the degree of groundwater dependence for each lake.
Water chemistry and isotopic measurements are largely explained by the position of a lake within the local groundwater flow system. The range of values for TDS, δ18O, and 222Rn were ranked (low, medium, or high) based on the likelihood that a value would be indicative of groundwater contribution to the lake composition and were summarized by a groundwater dependence score. For example, 222Rn > 8 Bq/L in lake water was considered to be influenced by groundwater, which is typically 10 Bq/L in the region. Similarly, δ18O < −11‰ were also assumed to be influenced by groundwater (typically −15 to −18‰), compared to lakes that experienced a greater amount of evaporation than replenishment by groundwater. The groundwater dependence scores indicate a higher likelihood of groundwater inflow for lakes in the NE part of the study area compared to the SW. The groundwater dependence score exhibited a spatial relationship between individual lakes and their position with the pitted delta groundwater flow system. Knowledge of groundwater dependence advances the characterization of lakes and hydrology in this area, and participating in the project helps non-scientists attain some knowledge about groundwater. Together, the data and education will help discussions amongst landowners and decision makers with Parkland County on how to best manage land use in this diverse landscape.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/w17030440/s1. Isotopic data from this study are provided in Table S1.

Author Contributions

Conceptualization, B.S. and D.T.; methodology, B.S., B.P. and D.T.; investigation, J.B.T.M., W.N., D.M. and D.T.; analysis, J.B.T.M. and B.S.; writing—original draft preparation, B.S.; writing—review and editing, J.B.T.M. and D.T. All authors have read and agreed to the published version of the manuscript.

Funding

The lake survey was supported by grants from the Land Stewardship Centre of Canada (LSCC), Parkland County, North Saskatchewan Watershed Alliance (NSWA), and the Stony Plain Fish and Game Association (SPFGA). University researchers were able to participate through funding from the Alberta Innovates—Water Innovation Program (Grant# G2020000145).

Data Availability Statement

Lake chemistry data and attributes are available from the Gordon Foundation’s DataStream, https://doi.org/10.25976/9h1b-ja71. Isotopic data from this study are provided in the Supplementary Materials.

Acknowledgments

The cooperation of individual landowners who enabled access to many of these lakes is gratefully acknowledged. The research team thanks Caleb Sinn for managing the water quality data for the ALMS and the Alberta Geological Survey for use of the RAD7 radon detector.

Conflicts of Interest

The authors declare no conflicts of interest.

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Figure 1. (a) Location of the Parkland County Lakes study area within the Province of Alberta, Canada. (b) Lake sampling sites.
Figure 1. (a) Location of the Parkland County Lakes study area within the Province of Alberta, Canada. (b) Lake sampling sites.
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Figure 2. (a) Lake sampling sites shown with the thickness of sediment above the bedrock surface [23] and cross-section locations. (b–d) Cross-sections through the study area showing the hummocky topography and the position and depths of lakes.
Figure 2. (a) Lake sampling sites shown with the thickness of sediment above the bedrock surface [23] and cross-section locations. (b–d) Cross-sections through the study area showing the hummocky topography and the position and depths of lakes.
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Figure 3. Colour-shaded water table map modified from [28] showing lake sampling sites. Water table contour line spacing is 10 m. Groundwater flow directions are indicated by the arrows.
Figure 3. Colour-shaded water table map modified from [28] showing lake sampling sites. Water table contour line spacing is 10 m. Groundwater flow directions are indicated by the arrows.
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Figure 4. The median total dissolved solids (TDS) concentration of groundwater from the sediments above bedrock for quarter township blocks [39] shown with the general grouping of the lake sites (NE and SW).
Figure 4. The median total dissolved solids (TDS) concentration of groundwater from the sediments above bedrock for quarter township blocks [39] shown with the general grouping of the lake sites (NE and SW).
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Figure 5. Values of (a) total dissolved solids and (b) total phosphorus for lakes sampled in 2021 [36,37]. Results are shown with the water table contours and groundwater flow directions (arrows) from Figure 3.
Figure 5. Values of (a) total dissolved solids and (b) total phosphorus for lakes sampled in 2021 [36,37]. Results are shown with the water table contours and groundwater flow directions (arrows) from Figure 3.
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Figure 6. Piper diagram summarizing water chemistry for lakes sampled in 2021 and 2022, along with median values for groundwater in sediments above bedrock for quarter township blocks in study area [39]. Results are differentiated by northeast (NE) or southwest (SW) position in study area.
Figure 6. Piper diagram summarizing water chemistry for lakes sampled in 2021 and 2022, along with median values for groundwater in sediments above bedrock for quarter township blocks in study area [39]. Results are differentiated by northeast (NE) or southwest (SW) position in study area.
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Figure 7. Stable isotope values (δ2H and δ18O) for lakes in Parkland County sampled in the current study, differentiated by northeast (NE) or southwest (SW) position within the study area. The local meteoric water line (LMWL), local evaporation line (LEL), and results of [16,31] are shown for comparison. Analytical error bars are less than the size of the marker.
Figure 7. Stable isotope values (δ2H and δ18O) for lakes in Parkland County sampled in the current study, differentiated by northeast (NE) or southwest (SW) position within the study area. The local meteoric water line (LMWL), local evaporation line (LEL), and results of [16,31] are shown for comparison. Analytical error bars are less than the size of the marker.
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Figure 8. The values of (a) δ18O and (b) 222Rn for lakes sampled in 2021. The results are shown with the water table contours and groundwater flow directions (arrows) from Figure 3.
Figure 8. The values of (a) δ18O and (b) 222Rn for lakes sampled in 2021. The results are shown with the water table contours and groundwater flow directions (arrows) from Figure 3.
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Figure 9. Groundwater dependence score calculated from lake TDS, δ18O, and 222Rn values. The results are shown with the water table contours and groundwater flow directions (arrows) from Figure 3.
Figure 9. Groundwater dependence score calculated from lake TDS, δ18O, and 222Rn values. The results are shown with the water table contours and groundwater flow directions (arrows) from Figure 3.
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Table 1. Summary of water sampling to assess groundwater dependence.
Table 1. Summary of water sampling to assess groundwater dependence.
AnalysesMethodLaboratoryPurpose
Routine water chemistry (major ions, alkalinity; 500 mL LDPE bottle)Ion Chromatography, Colourimetry, TitrationBureau VeritasGeneral chemical composition
δ2H and δ18O of water (0.2 μm nylon-filtered, 2 mL glass vial)Picarro Cavity Ring-Down Spectroscopy L2130-i Isotopic Water Analyzer (Picarro Inc., Santa Clara, CA, USA)University of AlbertaOrigin and movement of stable isotopes within hydrological cycle. Results expressed as δ values representing deviations per mil from Vienna standard mean ocean water (VSMOW)
222Rn (40 mL glass bottle with no headspace)
Measured in 2021 only		RAD7 Radon Detector (Durridge Company Inc.)University of AlbertaNaturally occurring radioactive gas with activity that increases in groundwater due to decay of uranium and radium in geological materials and rapidly decreases where it equilibrates with atmosphere. Useful tracer for identifying groundwater discharge to surface water
Table 2. Calculation of groundwater dependence score.
Table 2. Calculation of groundwater dependence score.
TDS (mg/L)TDS Rankδ18O (‰)δ18O Rank222Rn (Bq/L)222Rn Rank
>5003<−113>123
250 to 5002−11 to −825 to 122
<2501>−81<51
GW dependence score = (TDS rank) + 2(δ18O rank) + 2(222Rn rank). Moreover, >12 indicates high dependence on groundwater. Additionally, 5 to 12 indicates medium dependence on groundwater, and <5 indicates low dependence on groundwater.
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Smerdon, B.; Maccagno, J.B.T.; Peter, B.; Neilson, W.; Mussell, D.; Trew, D. A Community-Led Assessment to Identify Groundwater-Dependent Lakes in Parkland County (Alberta, Canada). Water 2025, 17, 440. https://doi.org/10.3390/w17030440

AMA Style

Smerdon B, Maccagno JBT, Peter B, Neilson W, Mussell D, Trew D. A Community-Led Assessment to Identify Groundwater-Dependent Lakes in Parkland County (Alberta, Canada). Water. 2025; 17(3):440. https://doi.org/10.3390/w17030440

Chicago/Turabian Style

Smerdon, Brian, Jenna Bahija Tarrabain Maccagno, Bradley Peter, Walter Neilson, Dave Mussell, and David Trew. 2025. "A Community-Led Assessment to Identify Groundwater-Dependent Lakes in Parkland County (Alberta, Canada)" Water 17, no. 3: 440. https://doi.org/10.3390/w17030440

APA Style

Smerdon, B., Maccagno, J. B. T., Peter, B., Neilson, W., Mussell, D., & Trew, D. (2025). A Community-Led Assessment to Identify Groundwater-Dependent Lakes in Parkland County (Alberta, Canada). Water, 17(3), 440. https://doi.org/10.3390/w17030440

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