A Tracer-Based Method for Classifying Groundwater Dependence in Boreal Headwater Streams
Abstract: Ecosystem protection requires a better definition of groundwater (GW) dependence and tools to measure this dependence. In this study, a classification method for the GW dependence of headwater streams was devised based on the fact that GW affects discharge, thermal regime, and water quality. The method was tested in three boreal headwater streams discharging from two esker aquifers. Spatial and temporal variability of GW dependence were studied in the stream continuum at several locations, by combining continuous measurements of temperature, electrical conductivity, and discharge with discrete sampling of environmental tracers (e.g., stable water isotopes, silica, chloride). The stream tracer index method developed was used to classify stream sections into GW-dominated, GW-surface water (SW) transition, and SW-dominated zones. We found that, spatially, GW dependence along the stream varied widely, with calculated stream tracer index values ranging from 33 to 94%. The GW-dominated areas extended at least 745, 1 682, and 4 202 m downstream from the main GW discharge points in the three streams studied. A stream located in a pristine peatland-dominated catchment was more prone to rapid change from GW- to SW-dominated than two streams located in catchments dominated by peatland forestry. These results suggest that to evaluate the GW dependence of streams, it may be sufficient to sample stream sections only once, during summer low-flow conditions. The proposed method can serve as a water management tool, especially for streams of exceptional ecological importance or in places where anthropogenic activities are expected to change local hydrology and ecology.
Summary (4 min read)
- The authors combined continuous measurements of discharge, temperature (T), and electrical conductivity (EC) with use of stable water isotopes and other environmental tracers to study the GW-SW transition zones in three boreal streams known to have high proportions of GW from esker aquifers.
- The authors expected to find a transition zone within which a spring-originated stream turns into a SW-dominated system.
- By definition, SW is the water in surface storage units (e.g., lakes, streams, rivers, wetlands) and GW is the water underground.
- This work addresses the following research questions: i).
2 Materials and methods 2.1 Study sites
- The three streams selected for the study are located in Rokua and Viinivaara esker aquifer areas and are 60 km from each other.
- The study sites belong to a mid-boreal coniferous forest belt.
- In the Rokua esker area, the authors selected two streams, Siirasoja and Lohioja, where surrounding peatlands are intensively drained for forestry.
- The average channel widths and average maximum depths along the streams studied are presented in the Supporting Information Table S1 .
2.1.1 Siirasoja and Lohioja streams in Rokua esker aquifer
- The aquifer itself is unconfined, but the heavily drained peatlands in the surroundings partly confine the GW [Rossi et al., 2012] .
- The catchments are located next to each other and the land use consists mainly of peatland forestry and some agricultural land (Table 1 ).
- Some of the ditches in Siirasoja catchment have no flow and some fully penetrate the peat layer and reach the mineral soil beneath, causing increased GW discharge to the stream.
- GW discharge has been found to be either diffuse seepage or point type, and is induced by high pressure underneath the peat layer (Rossi et al. 2012) .
2.1.2 Mesioja stream in Viinivaara esker aquifer
- The authors study stream, Mesioja, discharges from a spring located at the break of slope where the sandy aquifer meets the peat formation and flows partly underground between measurement locations M2 and M3 (Table 1 ).
- The lower catchment area is mostly pristine peatland with bog-type vegetation.
- The GW dependence of the peatland area varies widely; spatial isotope studies by Isokangas et al. (2017) showed that the stable isotopic composition of the peatland pore water is not uniform near Mesioja stream, with δ 18 O values ranging between approximately -8‰ and -13‰ at 10 cm depth during the period 4-11 August 2014.
2.2 Field measurements
- Stable isotopic composition of water samples was analyzed using cavity ring-down spectroscopy with a Picarro L2120-i analyzer and the isotope ratios were expressed in δ notation relative to Vienna Standard Mean Ocean Water , with precision for δ 18 O and δ 2 H values of ±0.1‰ and ±1.0‰, respectively.
- Nutrients, alkalinity, and geochemical parameters were analyzed using Finnish national standards in an accredited (SFS-EN ISO/IEC 17025:2005) laboratory at the Finnish Environment Institute (SYKE) [National Board of Waters, 1981] .
2.2.1 Local groundwater and surface water quality
- The measurement locations are presented in the map in Supporting Information Fig. S1 .
- The nearest SW sampling locations of SYKE are situated 27 km (Nuorittajoki suu station) and 9 km (Nuorittajoki Töntönkoski station) from Mesioja catchment.
- Most of the parameters were analyzed using samples from Töntönkoski station and, although the measurements were performed before their stream sampling campaign, the data were assumed to be representative for the study period because there had not been any major changes in land use in the area.
- The SW sampling location of Nuorittajoki suu station is located rather far from their study stream but, as the land use is relatively similar to that in Mesioja catchment (Supporting Information Fig. S1 ), the data were assumed to be representative for the study area.
- In Rokua, the measurements by SYKE were also used as a reference for SW.
2.3 Data analysis
- To reduce the dimensionality of the dataset while retaining as much of its variation as possible, the authors performed principal component analysis (PCA) for the stream data (chemical and physical water quality parameters and discharge).
- It is preferred over the princomp function because of its better numerical accuracy [Anderson, 2013] .
- The authors also scaled and centered the data using the prcomp function.
- The authors performed the analysis for two datasets; the average values of all measurements for each site and the average values for the low-flow situation (July measurements).
- As each stream had almost the same number of sampling locations, they had similar weighting in the analysis and PCA was deemed suitable for use, although the autocorrelation between samples was borne in mind when analyzing the results.
2.3.1 The stream tracer index method
- 𝑛 where x variable is the classification value based on the chosen water quality variable.
- The classification values are determined by evaluating whether the tracer in question indicates a clear GW signal (x=1), a mixture of GW and SW (transition zone, x=0.5), or a clear surface water signal (x=0).
- After the appropriate values are chosen, the stream tracer index values can be calculated using equations ( 1) and ( 2).
3.1 Stream discharge and its origin
- Based on the stable water isotope dataset, the water origin in all three streams was mainly GW (Fig. 6 and Supporting Information Fig. S2 ).
- In Siirasoja and Lohioja streams at Rokua, the isotopic composition remained relatively stable except during the rain events in November 2014 (Fig. 3 ), when the isotopically more enriched SW increased the delta values of the streams.
- In Mesioja, the water isotope responses were more complex than in Lohioja and Siirasoja.
- At upstream locations, the isotopic composition resembled GW, but further downstream the delta values increased, indicating larger contributions from enriched surface runoff and soil water.
- At the furthest downstream locations, the delta values were again more negative, indicating GW discharge into the stream also at downstream locations (Fig. S2 ).
3.2 Spatial and temporal variations in stream water temperature
- During summer, water temperature generally increased from headwater to downstream in all streams (June-September, mean air T at Pudasjärvi airport 14.0 ºC and at Vaala-Pelso station 13.3 °C).
- The streams generally had different diurnal variations (Fig. 4 ).
- The coefficient of variation for temperature was smallest for headwater locations in both warm (June-September) and cold (April, May, October, November) seasons.
- This shows that GW sustains stable thermal regimes in both warm and cold seasons.
- In Lohioja and Siirasoja streams, water temperatures at different measurement points were more similar than in Mesioja.
3.3 Spatial and temporal variations in stream chemical properties
- In Lohioja, Clconcentrations indicated that the first measurement location (L1) had a clear GW signal and the other locations were in the GW-SW transition zone.
- In Siirasoja, the first three locations had Clconcentrations near to the GW reference value, the next two belonged to the GW-SW transition zone, and the last measurement location had a clear SW signal.
- In the Rokua area the reference values showed a clear distinction from each other.
- For all measurements, 75% of the variation in the data was explained by the first two principal components (PCs), while for low-flow measurements these two PCs explained 79% of the variation.
- Thus, generally low PC1 loadings indicated high GW influence.
3.4 Groundwater and surface water dominance of streams
- The authors results show that boreal headwater streams can be highly GW-dependent.
- Changes in GW discharge would particularly affect the position and length of the GW-SW transition zone in the stream continuum and could thus alter stream ecosystems.
- As GW supports stream flow, especially at upstream measurement locations, their study streams would most probably dry out without GW input at least occasionally.
- Earlier snowmelt due to climate change may also lower GW levels in the region during summer months, exacerbating the impacts of drought [Okkonen et al., 2010; Okkonen and Kløve, 2011] .
4.2 Thermal properties change radically in the stream continuum
- The authors results showed that GW plays a major role in the thermal sensitivity of the streams studied, such that GW-dependent areas were less sensitive to changes in air temperature, although still responded to it.
- The water temperature at these locations still showed diurnal variations and during exceptionally warm days the water temperature increased.
- Fortunately, these events were relatively short (some days) and the highest temperatures were only short-term mid-day events (e.g., on 1 July 2013, T in Siirasoja stream, location S3, increased to 10 °C for 45 minutes).
- Jyväsjärvi et al. (2015) showed that even a 1 °C increase in mean water temperature of springs can affect the species present in water and alter bryophyte and macroinvertebrate communities in streams discharging from springs.
- In addition, salmonid fish in particular have been found to be extremely sensitive to the current warming trend and thermal refuges are becoming even more important for preserving their populations [Isaak et al., 2015] .
4.3 The applicability of local groundwater and surface water reference values
- Moreover, GW quality reflects the local geology.
- The piezometers were sampled quarterly during 2010-2012.
- This suggests that SiO 2 and Clare more reliable tracers in this area.
- In addition, temporal variations in GW and SW quality were detected in both the Rokua and Viinivaara areas.
- The average coefficient of variation for the GW reference variables used (excluding PO 4 3--P) was 7.5% and that for the SW reference variables was 17.4%.
4.4 Surface water input causes changes in water quality in the stream continuum
- A disadvantage is that expert knowledge is needed to choose appropriate tracers for a selected area and the classification values for those tracers.
- The method resembles other management tools, such as 42 analytic hierarchy process [Subramanian and Ramanathan, 2012] , so in that regard it should be rather easy to adopt in decision making.
- Furthermore, the stream tracer index method could be especially helpful in the intense monitoring programs required in areas of exceptional ecological importance [Bertrand et al., 2014] .
- The method could also be applied in places where anthropogenic actions are expected to change the local hydrology and affect stream ecosystems.
- In addition, available historical data could be applied in some cases if there have not been any major changes in the catchment area.
- It is important to classify boreal headwater streams, owing to their ability to act as refuges, supporting stable conditions vital for specific aquatic biota in a changing climate.
- The results of this study suggest that it might be sufficient to sample stream sections only once, during summer low-flow conditions, when evaluating the groundwater dependence of streams.
- The stream tracer index method could serve as a useful management tool, especially at sites of exceptional ecological importance or at sites where anthropogenic measures are expected to change the local hydrology.
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Cites background from "A Tracer-Based Method for Classifyi..."
...…abstraction legislation under climate change projections, there is a need to understand (a) the relative role of different water sources (Isokangas et al., 2019), both in terms of water quantity and quality (specifically, temperature) (b) the resilience of these sources under different…...
...…to air temperatures, suggest that the narrow, short, north facing stream was relatively sheltered from radiation inputs (Dick, Tetzlaff, & Soulsby, 2015; Isokangas et al., 2019; MacDonald, Boon, Byrne, Robinson, & Rasmussen, 2014) allowing the imprint of groundwater temperatures to be maintained....
...This ensured that, although EMMA is approximate, ‘end-members’ of source types delimited the range of values so that themixing space of different source contributions to S3 could be understood (Abbott et al., 2016; Isokangas et al., 2019)....
...…has been shown in many tracer-based studies in Scotland (Blumstock et al., 2016; Geris et al., 2015; Scheliga et al., 2018; Soulsby et al., 1998), and elsewhere (Botter, Bertuzzo, & Rinaldo, 2011; Isokangas et al., 2019; Rinaldo et al., 2011; Tetzlaff et al., 2018; Zuecco, Penna, & Borga, 2018)....
Cites background from "A Tracer-Based Method for Classifyi..."
...Such regions of GW seepage near streams can create biogeochemically distinct environments (Isokangas et al., 2019; Lupon et al., 2019) that act as hotspots for microbial activity and the carbon source to streams....
...Such regions of GW seepage near streams can create biogeochemically distinct environments (Isokangas et al., 2019; Lupon et al., 2019) that act...
"A Tracer-Based Method for Classifyi..." refers background or methods in this paper
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...1057 Fenn., 39(October), 235–251. 1058 The R Foundation (2019), The R project for statistical computing. Retrieved May 3, 2019, 1059 from https://www.r-project.org/. 1060 Tweed, S., N. Munksgaard, V. Marc, N. Rockett, A. Bass, A. J. Forsythe, M. I. Bird, and 1061 M. Leblanc (2016), Continuous monitoring of stream δ18O and δ2H and storm flow 1062 hydrograph separation using laser spectrometry in an agricultural catchment, Hydrol. 1063 Process., 30, 648–660, doi:10.1002/hyp.10689. 1064 United States Environmental Protection Agency (2000), Guidance for Data Quality 1065 Assessment: Practical Methods for Data Analysis: EPA QA/G-9 QA00 Update, 1066 Washington DC....
...1057 Fenn., 39(October), 235–251. 1058 The R Foundation (2019), The R project for statistical computing....
"A Tracer-Based Method for Classifyi..." refers background in this paper
...Furthermore, the hyporheic 609 processes and interchanges between GW and SW can increase the contact time 610 between stream water and subsurface material and intensify biochemical activity, 611 which can be seen in changes in water quality [Sophocleous, 2002]....
...Groundwater (GW) is generally 46 a major contributing factor to maintaining the baseflow of headwater streams [Sophocleous, 2002; 47 Winter, 2007] and has specific geochemical, physical, and biological characteristics that differ 48 from surface water (SW) [Bertrand et al., 2012]....
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