Tracing environmental changes according to the spatiotemporal variability of the hydrogeochemical background of springs: a case of Lithuania

doi:10.21203/rs.3.rs-1739592/v1

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Research Article

Tracing environmental changes according to the spatiotemporal variability of the hydrogeochemical background of springs: a case of Lithuania

https://doi.org/10.21203/rs.3.rs-1739592/v1

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The qualitative status of groundwater is often underestimated. This is because distinguishing trends of hydrogeochemistry variation linked to anthropogenic pressure from natural trends in groundwater is challenging. The study aims to evaluate the effect of the natural processes on the limits of temporal variability of the natural background level (NBL) in springs draining aquifer units with different vulnerabilities. Shallow groundwater samples of eighteen natural springs were investigated. Statistical analysis and geochemical modelling were used. The results showed that the natural temporal variability limits of HCO₃⁻, Na⁺, K⁺, Cl⁻ and SO₄²⁻ in high vulnerability aquifers were narrower than in moderate and low vulnerability aquifers. This pattern was determined by the stronger buffering effect of carbonate equilibrium, sulphate reduction, and dilution processes on the variation of these major ions in high vulnerability aquifers. Meanwhile, natural temporal variability limits of TDS, Ca²⁺ and Mg²⁺ in high vulnerability aquifers were wider than in moderate and low vulnerability aquifers. This pattern was related to the stronger buffering effect of ion exchange on the variability limits of Ca²⁺ and Mg²⁺ in springs of moderate and low vulnerability aquifer units than the buffering effect of weaker carbonate dissolution and higher dilution intensity on the variability limits of Ca²⁺ and Mg²⁺ in springs of high vulnerability aquifer. The results of this research could be helpful for the reasonable integrated management and effective protection of groundwater resources.

Springs water

Shallow groundwater

Spatiotemporal variability

Natural background level

Hydrogeochemical processes

Major ions

Groundwater forms an essential source of potable water in Europe. Nevertheless, the quality of Europe’s groundwater resources has been under pressure from numerous anthropogenic activities exacerbated by climate change in recent decades (Barbieri et al. 2021; EEA 2019; McDonough et al. 2020; Lapworth et al. 2022; Lanini et al. 2021). Despite the efforts of the researchers, it is challenging to elucidate hydrogeochemistry variation trends linked to anthropogenic activity from natural trends in groundwater are challenging (Frollini et al. 2021; Szczucińska 2016; Zanotti et al. 2022). Therefore the qualitative status of groundwater is greatly underestimated (Huang et al. 2022). One of the main reasons is insufficient understanding of the spatiotemporal variability of natural background levels (NBLs) link with their generating natural processes (Preziosi et al. 2021). Therefore, future research on this topic is essential to ensure sustainable groundwater quality management.

The Groundwater Directive (2006/118 /EC) requires EU Member States to identify any significant and sustained trends (upward and reversed) in concentrations of anthropogenic contaminants and natural parameters in groundwater (Broers et al. 2008; EC 2012; Frollini et al. 2021). In order to implement these requirements, NBLs natural variability limits as the starting points of the significant upward trends of the concentrations of chemical components must be known (Broers et al. 2008; EC 2012; Frollini et al. 2021). Furthermore, the limits should be evaluated according to the vulnerability of the groundwater of a particular region (Zanotti et al. 2022). Recently, however, considerable efforts have been made to examine the dependence of the values of chemical components of geogenic origin on local hydrogeological settings (De Caro et al. 2017; Gao et al. 2020; Guadagnini et al. 2020; Herms et al. 2021a, 2021b; Huang et al. 2022; Parrone et al. 2019; Zanotti et al. 2022). However, according to the review studies by Preziosi et al. 2021, it is not yet possible to recommend a reliable method for determining NBLs and their variations that would be robust enough to be applied in most hydrogeological settings across Europe.

It is well known that the distribution concentrations of dissolved chemical components of natural origin in groundwater are directly related to natural processes such as redox, ion exchange, dissolution, precipitation, weathering, and dilution (Appelo and Postma 2005). Moreover, the intensity of these processes is closely related to the hydrological, geological, hydrogeological and soil properties controlling the vulnerability of particular aquifers (Chidambaram et al. 2011; Li et al. 2015; Sappa et al. 2014; Vishwakarma et al. 2018). However, the hypothesis raised by the authors of previous studies about the effects of natural processes on the spatiotemporal variability of NBL in research is often based on theoretical assumptions (Gao et al. 2020; Guadagnini et al. 2020; Herms et al. 2021a; Huang et al. 2022; Parrone et al. 2019; Zanotti et al. 2022). There is a shortage of in-depth quantitative research on the effects of natural processes on NBL (Zanotti et al. 2022)

Potable water resources in Lithuania are extracted only from groundwater. The groundwater resources available in Lithuania are estimated at over 3.75 million m³ per day, which is about six times more than the current (2011–2019 period) water extraction for centralised drinking water supply (LGS 2020). The groundwater of highly vulnerable shallow aquifers is also used for drinking water supply. The NBLs of the main shallow groundwater bodies in the territory of Lithuania were estimated using the BRIDGE project methodology (LGS 2016). However, the relationship between NBL and natural mechanisms in the groundwater of various aquifer units has not been investigated.

Therefore, the main aim of this study is to assess the effect of natural processes on the limits of temporal variability of NBL in springs draining shallow aquifer units of the Quaternary system with various vulnerability levels. Groundwater samples from springs are used because springs can be are more appropriate for monitoring environmental changes (Cervi et al. 2018; Chiaudani et al. 2019; Cruz and Andrade 2015; Jang et al. 2012; Panwar 2020). The main objectives of this study focus on identifying distribution patterns of i) NBL of physicochemical parameters, ii) limits of temporal variability of NBL of major ions and iii) percentage of speciations of major ions distribution, values of saturation indices of the main mineral phases and values of chloro-alkaline indices, in changes of groundwater vulnerability level. The results of the research could be helpful for monitoring and effectively protecting groundwater resources.

Study area

Over twenty-four descending (gravity) and regularly monitored natural springs of shallow aquifers discharging in the study area, among which eighteen are the most representative and were therefore selected as study sites (Fig. 1).

Geomorphological and geological conditions played a crucial role in the emergence of the studied springs. The study springs are descending contact (56%) and depression (44%) types (Kadūnas et al. 2017). The descending contact spring formed from contact between water-bearing sediments and the impermeable rock in the direction of the groundwater flow (Kresic et al. 2010). Meanwhile, depression type springs occur on the ground surface in depressions, formed in unconfined aquifers when the topography intersects the water table, usually due to the surface stream incision (Kresic et al. 2010).

The hydrogeochemistry and hydrogeodynamics of all springs were regularly monitored in period 2015–2020. In this period the mean annual temperature in the study areas was approximately 6.0–6.5°C (SE GIS-Centras 2020), the annual mean precipitation was approximately 600–650 mm (SE GIS-Centras 2020) and evaporation were approximately 520–540 mm (SE GIS-Centras 2020). In general, most precipitation (60–66%) in Lithuania falls in the warm season (April–October) (SE GIS-Centras 2020). The discharging rate of springs ranged from 0.02 to 1.0 l/s, with an average 0.42 l/s (LGS 2020). Spring recharge zones covering areas from 2.36 to 102 m², with an average 47.36 m² (LGS 2020).

Geological and hydrogeological settings

From the viewpoint of geological structure and hydrogeology, the study territory is located in the Baltic Sedimentary Basin, in the south-western part of the East European Craton and is characterised by a rather complex geological composition. The geological history recorded in the sedimentary cover of the territory is longer than 1.5 Ga. The 2100–2300 m thick sedimentary cover is composed of all Phanerozoic systems indicating a long-term subsidence history (Satkūnas et al. 2016). The E-W cross-section of the study area representing all geological systems from the Riphean–Vendian to the Quaternary shows the S-W deepening of the sedimentary strata from 200 m in the east to 1 km in the central part. The thickness of the sedimentary cover in the Baltic Sea offshore exceeds 2 km. The area was not subjected to intense folding and faulting was relatively weak resulting in the establishment of low-amplitude tectonic structures (Grigelis et al. 1994; Satkūnas et al. 2016). The study area topography was formed during the Last (Weichselian) and, partly, during the pre-Last (Saalian) continental glaciations as well as during post-glacial processes (Satkūnas et al. 2016).

The average thickness of the Quaternary formation, which is composed of glacial tills (70%), glaciofluvial and glaciolacustrine sands, gravels and clays (28%), is 130 m (Guobytė and Satkūnas 2011). There are no visible rocky formations on the surface, except for a few outcrops in river valleys in the northern part of the study area, where the Quaternary cover is a few metres thick. Lowlands below 100 m a.s.l. prevail, and only 20% of the territory is composed of hilly morainic highlands with the highest points not exceeding 300 m a.s.l. (Satkūnas et al. 2016).

The zone of active groundwater circulation, in which fresh groundwater is located, forms the upper part of the Baltic artesian basin. It is a multi-layered hydrodynamic system with a thickness ranging from 50–100 m in the plains to 300–400 m in the highlands, and has a direct connection with the atmosphere and the surface of the earth (Grigelis et al. 1994). From a structural point of view, the active groundwater circulation zone consists of the hydraulically connected aquifer layers of the groundwater and the inter-moraine upper and upper-middle Pleistocene of the Quaternary system.

The present study focused on shallow aquifers situated in the upper part of the sedimentary cover (up to 50 meters deep). In unconfined aquifers alluvial (various size sand, gravel and cobble), glaciofluvial (various size sand, gravel and cobble), marine (various and silty sand), glaciolacustrine (silty sand and silt) and glacial (clay and sandy loam) sediments prevail. The filtration coefficient ranges from < 0.0001 m/d to > 0.005 m/d.

The vulnerability of the active water exchange zone to anthropogenic pollution across the territory of Lithuania is influenced by different geological and hydrogeological characteristics, such as isolation (openness) and natural filtration properties in the upper part of the sedimentary column. These characteristics depend on the ratio between sandy and clay layers. Based on these characteristics, the Lithuanian territory is divided into four regions of shallow groundwater vulnerability (Fig. 1, Table 1).

Table 1

The study area delineation according to the vulnerability of shallow aquifers in the territory of Lithuania
Vulnerability level of the area ^a	Geologic-hydrogeological parameters of the shallow aquifer unit
Vulnerability level of the area ^a	Rate of groundwater recharge, mm/y ^b	Hydraulic conductivity, m/d ^b	Lithological structure ^b
High	> 200	1–100	Homogeneous sandy and gravel aquifers prevail, loose water-permeable rock.
Moderate	100–200	> 0.005	Heterogeneous layers, ratio of clay layers makes more than 40–50% of sedimentary section.
Low	50–100	0.001–0.005	Heterogeneous layers, ratio of clay layers makes more than 60% of sedimentary section.
Very low	< 50	≤ 0.0001	Homogeneous layers of low permeability, ratio of clay layers makes more than 90% of sedimentary section.

^a (Kanopienė 2004)

^b (Kanopienė 2004; Pūtys 2015)

The lithology of the dominant sediments in a hydrogeological system determines their inherent filtration properties: an increasing amount of clay particles decreases the potential of pollution filtration, i.e. pollutant filtration becomes more complex (Slavinskienė et al. 2018). The major vulnerability level occurs in sandy soil and is related to the maximum precipitation zone in the western part of Lithuanian. Maximum evapotranspiration is typical of loamy and boggy soil with a minimal depth of the groundwater table. Maximum runoff is related to clay soils and maximum precipitation sites. In general, groundwater recharge amounts to 82.4 mm/y. The total evapotranspiration value is 460.7 mm/y and runoff value is 147.7 mm/y. Total amount of annual groundwater recharge of non-urbanized territory of Lithuania amounts to 5,198 million m³ (Pūtys 2015).

Spring classification

Based on the maps of shallow groundwater vulnerability by Kanopienė (2004) and groundwater recharge the in the territory of Lithuania by Pūtys (2015), the study springs were classified into the following three groups:

Springs draining low vulnerability (LV) shallow aquifer unit with mean values of the rate of groundwater recharge of 94 mm/y.

Springs draining moderate vulnerability (MV) shallow aquifer unit with mean values of the rate of groundwater recharge of 142 mm/y.

Springs draining high vulnerability (HV) shallow aquifer unit with mean values of the rate of groundwater recharge of 212 mm/y.

Sampling, analytical techniques, and dataset preparation

Springs of shallow groundwater were sampled twice a year in the period 2015–2020 (LGS 2020). Overall, 216 samples from 18 springs were collected and analysed. Samples were collected into 500 ml plastic bottles prepared in the laboratory and deposited to a freezer in the laboratory within 24 hours. The chemical composition of these spring water samples was analysed in the laboratory of the Lithuanian Geological Survey licensed by the Lithuanian Environmental Protection Agency using methodologies approved by the Lithuanian Standards Board. Ten chemical parameters of the water samples were measured. Major ions (Na⁺, K⁺, Ca²⁺, Mg²⁺, Cl⁻, and SO₄²⁻) were measured by ion chromatography. HCO₃⁻ and permanganate oxidation COD_Mn were measured by titration, and biogenic components NO₃⁻ were determined using a spectrophotometric method. The physical parameters (reduction potential [ORP] and the potential of hydrogen [pH]) in these samples were measured in situ with a calibrated portable instrument. The total dissolved solids (TDS) were determined by calculating the total amount of anions and cations dissolved in the groundwater. The original dataset reliability was verified. Samples with incomplete major ions analyses or having a charge balance error > |10|% were discarded.

Statistical analysis

Descriptive statistics were used to evaluate and interpret the spatiotemporal variability of the dataset. The standard deviation parameter was employed to measure the temporal variability of major ions. In addition, the Pearson’s correlation matrix was used to determine the relationship between the standard deviation parameters of major ions. The probability (p) values for testing the results of the statistical analysis were calculated at the 95% significance level (ɑ). It was assumed that the correlation coefficient value in the range of 0.5–0.7 represents a moderate relationship between the chemical components, the value in the range of 0.7–0.9 shows a strong relationship and the correlation coefficient value ranging between 0.9 and 1.0 indicates a very strong relationship between chemical components (Čekanavičius and Murauskas 2001). The Statistical t-tests were applied to assess the similarities among the NBL of analysed springs, threshold values of the Lithuanian Standard and NBL of early references. The null assumption of these tests was that concentrations of specific ions were not significantly different between different sources. The null hypothesis was rejected when the p-value was less than the significance level (alpha = 0.05) (Čekanavičius and Murauskas 2001) The statistical software XLSTAT (version 2021 24.1.1289.0) was used for performing all mentioned statistical analyses.

Hydrogeochemical facies analysis

The Piper diagram (Piper 1944) was used to represent hydrochemical facies of the spring water graphically. The software GW_Chart (version 1.30.0) was used. The milli-equivalent percentage (meq%) of major ions was plotted in this diagram and further projected into the central diamond-shaped field to evaluate the hydrogeochemical facies and the types of water (Pant et al. 2018). The facies were classified by taking the ionic percentages in the relative decreasing order of their abundance and rejecting less than 25% of the total concentration as insignificant. The concept of hydrogeochemical facies is widely used to explain the distribution and genesis of principal groundwater types (Subba Rao et al. 2019).

Geochemical modelling

The geochemical modelling software PHREEQC (Parkhurst and Appelo, 2013) version 3 was used to calculate the speciation distribution of major ions and saturation indices of major mineral phases. Geochemical modelling is a useful tool for studying the hydrogeochemical evolution of processes (Bhardwaj et al. 2009; Li et al. 2015; Saou et al. 2020) because mineral equilibrium calculations for groundwater help understand the reactive minerals present in the system (Aminiyan and Aminiyan 2020). The saturation index was calculated by the following equation (Jebreen et al. 2018):

\(SI=\text{log}\left(\frac{IAP}{{K}_{s}\left(T\right)}\right)\)

(1)

where IAP is the ion activity product and K_s(T) stands for the temperature-dependent solubility constant of the mineral (Jebreen et al. 2018). Different saturation states reveal different stages of the hydrochemical evolution and help indicate which geochemical reactions are essential in controlling the chemical composition of water (Aminiyan and Aminiyan 2020). In theory it is assumed that when SI > 0, the solution is supersaturated and therefore a reversible reaction (mineral precipitation) occurs. When SI = 0, the equilibrium state of the water-rock system is established. When SI < 0, a direct reaction occurs and the solution is undersaturated (mineral dissolution occurs) (Parkhurst and Appelo 2013). The estimated saturation indices of the relevant minerals are approximate due to analytical and activity concentration uncertainties; they are assumed to be ± 0.3 accurate.

Chloro-alkaline indices analysis

The Schoeller (1967) chloro-alkaline indices (CAI) were used to indicate ion exchange processes between groundwater and its environment. CAIs were calculated using the following equations (Liu et al. 2015):

\(CAI 1=\frac{Cl-\left(Na+K\right)}{Cl}\)	(2)
\(CAI 2=\frac{Cl-\left(Na+K\right)}{{HCO}_{3}+{SO}_{4}+{CO}_{3}+{NO}_{3}}\)	(3)

The value of the Schoeller chloro-alkaline indices can be positive or negative (Olabode et al. 2020). Negative values of both CAI 1 and CAI 2 indicate an exchange between Ca²⁺ or Mg²⁺ in groundwater with Na⁺ and K⁺ ions in the aquifer medium, while positive values of these indices imply that the reverse cation exchange occurs (Maskooni et al. 2021). These reactions are known as cation-anion exchange reactions (Marghade et al. 2011).

NBL of physicochemical parameters

The statistical results of physicochemical parameters in spring water of various aquifer units are summarised in Table 2. The analysis of mean values of temperature and pH indicate that springs from all aquifer units were cold and neutral. The mean values of pH in springs of the HV aquifer were approximately 3% higher than those from the MV and LV aquifers. Meanwhile, the mean value of temperature was approximately 15% higher in springs of the LV aquifer than that of the other two aquifer units. The mean values of O₂ and ORP parameters indicated that the oxygen circulation was up to 17% more intense in springs of the HV aquifer than that of the other two aquifer units. This is also reflected in the concentrations of redox- sensitive forms. COD_Mn concentrations indicate an unfavourable environment for the development of microorganisms in groundwater. TDS in springs ranged from 270 to 748 mg/L with an average of 439.5 mg/L, therefore the springs of all aquifer units could be defined as brine (Hiscock and Bense 2014). The mean value of TDS in springs of the LV aquifer was approximately 40% higher than that in the other two aquifer units.

Table 2

Descriptive statistics of the physicochemical parameters in springs of various aquifer units
Parameter	HV aquifer			MV aquifer			LV aquifer			TV ^a	NBL^b sandy/clayey lithology
Parameter	min ^a	max ^b	mean	min	max	mean	min	max	mean	TV ^a	NBL^b sandy/clayey lithology
t (˚C)	6.80	9.60	7.69	7.20	8.90	8.06	7.80	12.90	9.10
O₂ (mg/L)	2.41	13.45	7.65	3.70	10.40	6.53	3.28	9.91	6.73
OPR (mV)	235.00	268.00	255.33	217.00	217.00	217.00	179.00	242.00	187.67
pH (pH unit)	7.55	7.72	7.61	7.43	7.56	7.51	7.29	7.52	7.37	6.5–9.5
TDS (mg/L)	270.00	444.33	349.00	375.00	500.00	477.33	390.25	748.50	589.44		273/460
Cl– (mg/L)	7.98	10.69	9.22	7.57	12.00	10.53	13.15	20.00	16.52	250	24.9/31.2
SO₄²⁻ (mg/L)	8.00	17.60	13.21	14.60	28.05	16.02	20.15	33.16	27.70	250	32.4/46.2
HCO₃⁻ (mg/L)	238.90	347.95	269.15	260.00	354.00	331.29	337.80	447.66	377.80		223/430
Na⁺ (mg/L)	2.95	5.20	3.77	3.82	6.54	5.84	7.40	10.62	9.26	200	15.9/18.5
K+ (mg/L)	0.51	1.50	1.13	1.76	2.49	2.09	2.32	3.10	2.69		5.7/4.7
Ca²⁺ (mg/L)	43.90	72.64	60.22	70.20	82.61	76.24	69.54	106.96	83.70		65/114
Mg²⁺ (mg/L)	12.10	24.60	15.46	22.00	24.00	22.15	21.80	36.01	23.12		15.2/29.2
NO₃⁻ (mg/L)	0.40	0.97	0.67	0.48	2.50	1.55	1.62	6.31	4.13		2.59/1.89
COD_Mn (mg/L O₂)	0.88	1.26	1.07	1.63	2.13	1.72	2.26	2.50	2.40

^a min: minimum

^b max: maximum

^c TV: threshold value by the Lithuanian Standard (MHRL 2003)

^d (LGS 2016)

The physicochemical parameters obtained in this study were compared with the threshold values (TV) specified in the Lithuanian Standard (Hygiene Norm of Lithuania) and NBLs of the sandy and clayey shallow groundwater bodies in the territory of Lithuania from early references (Table 2). Results showed that there was no significant difference between the levels of physicochemical parameters in this study and NBL assessments of early references in springs of all aquifer types (mean p-value 0.719 of t-test). However, the difference between the levels of physicochemical parameters in this study and the Lithuanian Standard was significant (mean p-value 0.023 of t-test). First, it should be noted that these findings indicate that the levels of physicochemical parameters obtained in this study were background levels in springs of aquifer units of all vulnerabilities suitable for drinking purposes. They also confirmed the hypothesis put forward by both the authors of this publication and other authors that the assessment of the groundwater quality status must necessarily take the unique local geological and hydrogeological conditions into account.

The general dominance of anions was in the order of HCO₃ > SO₄ > Cl > NO₃, while the dominance of cations was Ca > Mg > Na > K in springs of all aquifer types. All springs were characterised by the HCO₃–Ca–Mg water type (Fig. 2). This water type indicates carbonate mineral dissolution processes and represents recently recharged groundwater, and/or water in early stages of the geochemical evolution (Ahmed and Clark 2016; Jebreen et al. 2018; Saleh et al. 2021). These findings suggest the hypothesis that the analysed spring water hydrogeochemistry is of natural origin and controlled only by natural factors.

Correlation coefficients

As can be seen from Table 3, the link between the major ions varies from strong to very strong. This suggests that hydrogeochemistry of the analyzed springs was controlled only by natural factors and their processes.

Table 3

The correlation matrix among the major ions of springs samples
	TDS	Cl⁻	SO₄²⁻	HCO₃⁻	Na⁺	K⁺	Ca²⁺	Mg²⁺
TDS	1.00
Cl⁻	0.88	1.00
SO₄²⁻	0.79	0.91	1.00
HCO₃⁻	0.96	0.86	0.85	1.00
Na⁺	0.82	0.88	0.91	0.81	1.00
K⁺	0.93	0.93	0.91	0.93	0.85	1.00
Ca²⁺	0.92	0.69	0.77	0.88	0.66	0.79	1.00
Mg²⁺	0.86	0.79	0.92	0.84	0.75	0.91	0.86	1.00

The main driving forces in hydrogeochemistry variability were geological-hydrogeological conditions which determined the intensity of hydrodynamic and hydrogeochemical processes in the aquifer. As a result of these natural processes, hydrogeochemistry of springs and changes in the groundwater regime were formed. A strong correlation between Cl^– and other chemical components indicates a significant dilution impact of all major ions on variability.

Meanwhile, correlation coefficients of HCO3⁻, Ca^+ 2 and Mg^+ 2 indicate a strong effect of carbonate equilibrium processes. This was also demonstrated by the water type analysis (Fig. 2). A significant correlation between SO₄²⁻ and HCO₃⁻ means that the sulphates reduction was one of the hydrogeochemical processes. Ca^+ 2 and Mg^+ 2 participate in cation exchange with Na⁺ and K⁺ in rock formations with good sorption properties. A strong correlation between these major ions suggests that ion exchange processes have shaped the hydrogeochemical composition and its change patterns.

Limits of temporal variability of NBLs of major ions

The standard deviation (SD) of chemical components is are widely used statistical parameter for identifying the hydrogeochemical variability level (Ishaku et al. 2011; Scanlon et al. 2002). The values of SD_TDS in springs of HV, MV and LV aquifer units ranged in intervals of 18 to 43.84 mg/L (Table 4). The highest mean values of SD among all major ions in springs of all aquifer units were identified for SD_HCO3 and SD_SO4. Meanwhile the lowest values were of SD_Na and SD_K (Table 4).

Table 4

Descriptive statistics of the standard deviation values of major ions in springs of various aquifer units
Parameter ^a	HV aquifer			MV aquifer			LV aquifer
Parameter ^a	min ^c	max ^d	mean	min	max	mean	min	max	mean
SD_TDS ^b	± 35.79	± 43.84	± 40.50	± 31.00	± 33.83	± 31.84	± 18.00	± 25.90	± 17.40
SD_SO4	± 2.08	± 8.23	± 22.09	± 4.54	± 8.23	± 20.83	± 6.69	± 25.42	± 12.32
SD_HCO3	± 4.60	± 8.00	± 6.39	± 9.58	± 12.88	± 13.29	± 15.72	± 23.17	± 22.15
SD_Ca	± 1.89	± 7.81	± 5.86	± 2.13	± 7.51	± 3.72	± 0.37	± 3.69	± 0.53
SD_Mg	± 6.19	± 8.00	± 6.85	± 2.20	± 3.05	± 3.05	± 2.49	± 4.01	± 2.63
SD_Cl	± 2.55	± 2.73	± 2.64	± 2.32	± 2.48	± 2.48	± 1.80	± 2.28	± 2.12
SD_Na	± 0.50	± 0.79	± 1.06	± 1.18	± 1.23	± 1.21	± 1.18	± 1.76	± 1.32
SD_K	± 0.21	± 0.36	± 0.36	± 0.59	± 0.65	± 0.69	± 0.51	± 1.20	± 1.04

^a All parameters are expressed as mg/L

^b SD_i: standard deviation of i^th major ion

^c min: minimum

^d max: maximum

Analysis of the spatial distribution of SD of NBL, showed that with an increase in the rate of groundwater recharge by approximately 53.13% (106.25 mm/y) the mean values of SD_TDS, SD_Ca and SD_Mg increase by 48–54%, whereas SD_Cl, SD_Na, SD_K, SD_HCO3 and SD_SO4 decrease by 56–69% (Fig. 3).

Speciations of major ions and saturation indices of the main mineral phases

The spatial distribution of percentage of calcium, magnesium, bicarbonate and sulphate species are presented in Fig. 4. The major factors controlling species percentage distribution of the total ions are pH, OPR, ionic strength, and different mineral phases during the water-rock interaction process (Manoj et al. 2018). Hence, it is essential to know the dominant species to predict their migration and distribution for a hydrogeochemical variability analysis (Manoj et al. 2018).

In this study, the computed CO₂ partial pressure (pCO₂) in springs of the HV aquifer was 10^− 3.66 (atm), while in those of MV and LV aquifer units it was 10^− 3.48 (atm) and 10 ^− 3.28 (atm), respectively. Sulphate, carbonate, calcium and magnesium ionic migration forms dominated in springs. With increasing groundwater vulnerability, calcium and magnesium carbonate migration and sulphate forms decreased and ionic forms increased. The average percentage of calcium and magnesium carbonate (CaHCO₃⁺, MgHCO₃⁺) and free ion (Ca^+ 2, Mg^+ 2) of the total Ca and Mg species in the analysed springs was 3.64% and 94.75%, respectively. Thus, the percentage of CaHCO₃⁺ and MgHCO₃⁺ species in springs of the HV aquifer was on average 22.37% lower than those in MV and LV aquifers. In addition, the percentage of Ca^+ 2 and Mg^+ 2 in springs of the HV aquifer was on average 1.37% higher than that in other springs.

In the analysed springs, the average percentage of carbonic acid (H₂CO₃) and free ion (HCO₃⁻) species of the total HCO₃ was 7.36% and 90.59%, respectively. Meanwhile, the percentage of H₂CO₃ and HCO₃⁻ species in springs of the HV aquifer was on average 38.95% lower (H₂CO₃) and 4.25% higher (HCO₃⁻) than in MV and LV aquifer units. As shown in Fig. 4, the average percentage of magnesium sulphate (MgSO₄⁰), calcium sulphate (CaSO₄⁰) and free ion (SO₄ ^− 2) species of the total SO₄ was 4.91%, 13.05%, and 81.96%, respectively. The percentage of CaSO₄⁰ - MgSO₄⁰⁻ and SO₄ ^− 2 species in springs of the HV aquifer was on average 16.49% lower (CaSO₄⁰ - MgSO₄⁰⁻) and 3.45% higher (SO₄ ^− 2) than in MV and LV aquifers.

The spatial distribution of saturation indices (SI) of carbonate minerals are shown in Fig. 5. The calculations of SI showed that springs of all aquifer units were in an equilibrium state (0.14 to 0.22) with respect to carbonate minerals such as calcite, dolomite and aragonite. In addition, the values of SI_calcite, SI_dolomite and SI_aragonite in springs of the HV aquifer were 11–40% lower than in springs of MV and LV aquifer units.

Meanwhile, the values of SI_anhydrite, SI_gypsum and SI_Msgnesite were between − 2.79 and − 0.85 and indicated that springs of all aquifer units were in an unsaturated state (mineral dissolution condition) with respect to these minerals. This result means that these minerals had no significant effect on the variation in the values of carbonate components.

Chloro-alkaline indices

The values of the chloro-alkaline indices CAI 1 and CAI 2 ranged from − 0.45 to 0.44 (average value − 0.039) and from − 0.02 to 0.02 (average value − 0.001), respectively. The negative average values of CAI 1 and CAI 2 were observed in springs of the LV aquifer unit (–0.015 to − 0.33) and the MV aquifer unit (–0.007 and − 0.23). Meanwhile, the positive average value (0.014 to 0.32) was found in springs of the HV aquifer unit. These results indicate that the springs of LV and MV aquifer units reflect some ion exchange.

Effect of natural processes on the limits of variability of NBL of major ions

Patterns of the spatial distribution of the limits of variability of NBL of major ions can be explained by the strength of the buffering effect of natural processes in the particular aquifer unit. The main highlights are discussed in this section.

The study results show that in springs of the HV aquifer, the limit of the variability of HCO₃⁻ was narrower than that in MV and LV aquifer types. According to the findings of geochemical, geochemical modelling and correlation analyses, this pattern was mainly associated with a weaker carbonate equilibrium and more intensive dilution in springs of the HV aquifer than in other aquifer units.

The mechanism of carbonate dissolution processes is mainly controlled by the behaviour of CO₂ (Eq. (4)) (Parkhurst and Appelo 2013; Vinnarasi et al. 2021).

CO₂ may be derived from various sources, including the release of CO₂ through the oxidation of organic matter and the interaction of groundwater with carbonates (Ahmed and Clark 2016; Jebreen et al. 2018). When dissolved in groundwater, CO₂ converts into the weak form of carbonic acid H₂CO₃ (Eq. (4)). which dissolves carbonate minerals (Jebreen et al. 2018). McDonough et al. (2020) pointed out that these relationships can vary locally between dissolved CO₂ and control variables due to site-specific factors. In the current study, pCO₂ values in springs of the HV aquifer were similar to those in the atmosphere. Therefore, the percentage of H₂CO₃ in springs of the HV aquifer was lower than that in the springs of MV and LV aquifer types. The springs of the HV aquifer have a more open contact with the atmosphere and, therefore, higher amounts of CO₂ are released during oxidation (Marghade et al. 2021; Lu et al. 2020). It implies that the reaction of lower concentrations of CO₂ with the springs of the HV aquifer results in the formation of a lower concentration of carbonic acid (H₂CO₃), which subsequently dissociates to produce a lower amount of H⁺ and HCO₃⁻. These findings mean that the weaker carbonate equilibrium process prevails in springs of the HV aquifer and acts as one of buffering mechanisms on the limits of variability of HCO₃⁻. Meanwhile, due to low oxygen content and destruction of organic matter, the pCO₂ values in springs of MV and LV aquifers were higher than those in the atmosphere. Therefore, higher concentrations of H₂CO₃ were formed and dissolution of carbonate minerals intensified (Jebreen et al. 2018). Due to this reasons, the limits of variability of HCO₃⁻ in springs of MV and LV aquifers were wider.

The impact of the dilution effect on the limits of variability of HCO₃⁻ (including on other species of major ions) in springs of all aquifer types was represented by values of Cl⁻ variability. Chloride is a non-reactive chemical parameter (Christensen et al. 2001). Therefore, its variation in groundwater is controlled only by hydrodynamic processes such as advective-dispersion (Yadav and Roy 2022) (Eq. (5)) and dilution (Eq. (6)) processes (Van Breukelen et al. 2004).

\(D\frac{{\partial }^{2}C}{\partial {x}^{2}}=\frac{\partial C\bullet n}{\partial t}\)	(5)
\({C}_{1} {V}_{1}={C}_{2} {V}_{2}\)	(6)

where D is dispersion coefficient, m²/s; C is the concentration of a chemical component, mol/m³; x is position, the dimension of which is length, m; t is time example s; n is porosity; C₁ and C₂ are starting and final concentrations, respectively; and V₁ and V₂ are starting and final volume, respectively, L. The study results show that the limit of variability of Cl⁻ in springs of the HV aquifer was narrower than in other aquifer units. This pattern shows that the buffering effect of dilution and dispersion on the limits of variability of HCO₃⁻ (including other major species) in springs of the HV aquifer was stronger than that in springs of other aquifer units. This trend can be associated with higher hydraulic conductivity values, which in sandy deposits of the HV aquifer are higher than in clay deposits of MV or LV aquifers (Lu et al. 2008). For this reason, more intensive processes of dilution and dispersion of chemicals are taking place in aquifers, resulting in a more uniform distribution of chemicals (Ahmed and Clark 2016; Lasagna et al. 2013). Consequently, the concentrations of chemical components are less vulnerable to the seasonal effects on nutrient infiltration.

In addition, higher dilution intensity causes more intense hydraulic exchange and augmentation of the dissolved oxygen in groundwater (B. sheng Huang et al. 2017). It implies that higher dilution accelerates CO₂ release into the atmosphere in springs of the HV aquifer. In the meantime, lower hydraulic conductivity and longer resistance time determined irregular inflow of oxygen and dilution with atmospheric precipitation in springs of MV and LV aquifer units. Accordingly, this resulted in higher levels of HCO3⁻ concentrations and their variability limits in these aquifer units.

In springs of the HV aquifer, the limits of variability of Ca²⁺ and Mg²⁺ were wider than in MV and LV aquifer types. The correlation results indicated that this pattern was mainly related with stronger buffering effect of ion exchange on the limits of variability of Ca²⁺ and Mg²⁺ in springs of MV or LV aquifers than the buffering effect of weaker carbonate dissolution and higher dilution intensity on the limits of variability of Ca²⁺ and Mg²⁺ in springs of the HV aquifer.

The lower concentration of carbonic acid (H₂CO₃) was directly related with lower saturation index values, the percentage of calcium magnesium carbonate (CaHCO₃⁺, MgHCO₃⁺) species and concentration of Ca²⁺, Mg²⁺ and HCO₃⁻ in springs of the HV aquifer. The lower saturation index indicates the lower intensity of dissolution of carbonate minerals (Eq. (7)–(8)) (Marghade et al. 2021). Such conditions determine a weaker electrostatic interaction between Ca²⁺ (Mg²⁺) and HCO₃⁻ (Appelo and Postma 2005), which was respectively reflected in a smaller percentage of carbonate species in groundwater.

\({CaCO}_{3}+{H}_{2}O+{CO}_{2}\leftrightarrow {Ca}^{2+}+2{HCO}_{3}^{-}\): calcite dissolution	(7)
\(2C{O}_{2}+2{H}_{2}O+{CaMg\left({CO}_{3}\right)}_{2}\leftrightarrow {Ca}^{2+}+{Mg}^{2+}+4{HCO}_{3}^{-}\): dolomite dissolution	(8)

In the meantime, negative values of the chloro-alkaline index indicated that Na⁺ and K⁺ were released by Ca²⁺ and Mg²⁺ exchange in springs of MV and LV aquifer types (Eq. 7). Based on a very strong positive correlation between the variability of K⁺ (Na⁺) and that of Cl⁻, Ca²⁺, Mg²⁺, it can be stated that the main mechanisms controlling K⁺ and Na⁺ variability in spring water are dilution and ion exchange (Lu et al. 2020). In addition, K⁺ and Na⁺ are known to be highly soluble chemical components (Christensen et al. 2001; Jebreen et al. 2018). The current study findings support these hypotheses. Negative values of the chloro-alkaline index indicated that Na⁺ and K⁺ were released by Ca²⁺ and Mg²⁺ exchange in springs of MV and LV aquifer types (Eq. (9)). The ion-exchange mechanism determined that in springs of the above-mentioned aquifer unit, the limit of variability of Ca²⁺ and Mg²⁺ was narrower than the limit of variability of Na⁺ and K⁺.

\(2{Na}^{+}+Ca\left(Mg\right)clay\leftrightarrow Na-Clay+{Ca}^{2+}\left({Mg}^{2+}\right)\)

(9)

The variability of SO₄²⁻ in springs of the HV aquifer was lower than that in MV and LV systems. It is known that the variability of sulphate in groundwater is mainly associated with the activity of sulphate-reducing bacteria (Ludvigsen et al. 1999). This hypothesis is suggested by the existence of a very strong positive correlation between the variability of SO₄²⁻ and pH in this study (r = 0.84). That is because pH parameter is associated with oxidation-reduction conditions in groundwater. As to favourable oxidation conditions for sulphur bacteria in springs of the HV aquifer, kinetics of sulphate reduction (Eq. (10)) is slow and, therefore, contributes to the low variability condition of SO₄²⁻ (Kneeshaw et al. 2011). In addition, due to a very strong positive correlation between the variability of SO₄²⁻ and Cl⁻, Ca²⁺, Mg²⁺, the high dilution effect increased SO₄²⁻ stability in springs of the HV aquifer.

\(S{O}_{4}^{2-}+2{C}_{org}+2{H}_{2}O\to 2HC{O}_{3}^{-}+{H}_{2}S\)

(10)

Meanwhile, the low content of oxygen in springs of MV and LV aquifers favours the breeding of sulphate reducing bacteria (Microspira desulfurans, Vibrio desulfurans) (Ren et al. 2019). Reduction of sulphates leads to the formation of sulphutic hydrogen, hydrocarbonate, carbon dioxide, and sulphric acid which causes changes in carbonate equilibrium and a higher variability of SO₄^2– (Eq. (11)) (Christensen et al. 2001).

\({S}_{2}+3{O}_{2}+2{H}_{2}O\to 2{H}_{2}S{O}_{4}\)

(11)

Differences in the impact of the above-mentioned processes on water of different aquifer units are reflected in SO₄ speciation. The weaker carbonate equilibrium and sulphate reduction in springs of the HV aquifer determine a weaker electrostatic interaction between SO₄²⁻ and Ca²⁺ (Mg²⁺) than that in other aquifer units. Therefore, the percentage of sulphate species (CaSO₄⁰, MgSO₄⁰) in springs of the HV aquifer was lower than in MV and LV aquifer units.

In this study, the effect of natural processes on the limits of the natural temporal variability of NBL of major ions in springs discharging from various shallow aquifers was analysed. Based on this analysis, new key points for more reliable indicators for tracing the qualitative changes in the groundwater status are highlighted.

The results show that there are no environmentally significant trends in the NBL of physiscochemical parameters in shallow groundwater in the analysed territory. Based on this result, it is concluded, that the hydrogeochemical background is unaffected by anthropogenic activity and the effects of climate change. However, research must be conducted periodically on any change to the hydrogeochemical background due to the non-linearity of the impact of climate change on natural systems and the inertness of groundwater in respect of environmental change.

The limits of temporal variability and the buffering effect of controlling natural processes have spatial distribution within the study territory. This means that even small changes in hydrogeological conditions affect the quality of groundwater. It is therefore clear that in-depth research on the local spatiotemporal variability of NBL for assessment of complex groundwater quality status in the regional and wider scale is required in the future.

The limits of the temporal variability of HCO₃⁻, Na⁺, K⁺, Cl⁻ and SO₄²⁻ in a high vulnerability aquifer is narrower than in moderate and low vulnerability aquifer units. This pattern is determined by the stronger buffering effect of carbonate equilibrium, sulphate reduction, and dilution processes on the variation of these major ions in a high vulnerability aquifer. Meanwhile, limits of temporal variability of Ca²⁺ and Mg²⁺ in high vulnerability aquifers are wider than in moderate and low vulnerability aquifers. This pattern is related to a stronger buffering effect of ion exchange on the limits of the variability of Ca²⁺ and Mg²⁺ in springs of moderate vulnerability or low vulnerability aquifer units than the buffering effect of weaker carbonate dissolution and higher dilution intensity on the variability limits of Ca²⁺ and Mg²⁺ in springs of high vulnerability aquifers.

The results of this study may be useful for verifying NBLs and the starting points of the significant upward/reversal trends of concentrations of chemical components according to particular geological-hydrogeological parameters of aquifers. The results would also be useful for calibrating the mathematical modelling of NBL outputs or of statistical techniques in groundwater and furthermore for identifying or predicting environmental changes in groundwater according to values of natural processes’ indicators. In addition, an active groundwater zone is a hydrogeodynamic system in which shallow aquifers and intertill aquifers are hydraulically interconnected. Therefore, these results may be useful for better protection of intertill groundwater, which is most often used for drinking purposes. We assume the results of the study would be useful for monitoring and management of water resources according to the Groundwater Directive. Analysing the variability limits of chemical components in the groundwater of urbanised territory will be the focus of future studies.

Acknowledgements This study was supported by the Lithuanian Ministry of Education, Science and Sport, the programme: "An influence of the climatic and anthropogenic driven factors on the status of the ecosystems and their behaviour, services provided and the sustainability of the resources” (20220419/V-585). The authors are thankful to anonymous reviewers and editors for their valuable comments, which helped improve the manuscript. Simultaneously, the authors also are grateful to Laima Monkevičienė for her assistance with editing the manuscript. Finally, thanks are also expressed to Zdislav Zanevskij for his technical support.

Funding The research received no external funding.

Authors contributions All authors contributed to the study conception and design. Idea generation. data processing and interpretation, and writing/reviewing were performed by GS, JS, JT and RL. JA and AB provided study materials and performed data editing. The first draft of the manuscript was written by GS and all authors commented and revised on previous versions of the manuscript. All authors read and approved the final manuscript.

Data availability The data that support the findings of this study are available from the Lithuanian Geological Survey. but restrictions apply to the availability of these data, which were used under license for the current study, and so are not publicly available. Data are, however, available from the authors upon reasonable request and with permission of the Lithuanian Geological Survey.

Ethics approval and consent to participate Not applicable.

Consent for publication Not applicable.

Competing interests The authors declare that they have no competing interests.

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No competing interests reported.

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Tracing environmental changes according to the spatiotemporal variability of the hydrogeochemical background of springs: a case of Lithuania

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