Temporal hydrogeochemical evolution of karst groundwater discharging into a continental-type Ramsar site in the Huasteca Potosina, Mexico

doi:10.21203/rs.3.rs-4126656/v1

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Temporal hydrogeochemical evolution of karst groundwater discharging into a continental-type Ramsar site in the Huasteca Potosina, Mexico

https://doi.org/10.21203/rs.3.rs-4126656/v1

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Karst groundwater is the main source of water supply for ecosystems that are dependent on its discharges, such as wetlands, which are habitats for various species. Due to their characteristics and significance, it is imperative to conduct research aimed at elucidating the mechanisms governing the water quality and quantity in ecosystems reliant on karst groundwater discharges. The karstic systems are susceptible to contamination, and despite this fact, there is a dearth of information available, which hampers the accurate determination of water quality. The site study is the karst groundwater system discharging in the RAMSAR wetland Ciénaga de Tamasopo (Mexico) affected by the water extraction for the extensive sugar cane agriculture. The goal was to identify the groundwater flow systems discharging into the wetland by using hydrogeochemical and isotopic techniques. Additionally, it aimed to assess the temporal changes in physical and chemical parameters. It was determined that the chemical composition of the water changes with respect to residence time in the subsoil, and the predominant processes are the dissolution–precipitation of calcite, dolomite, and gypsum by water-rock interaction, mixing, and evaporation. This study facilitated the development of a conceptual model for understanding the movement of groundwater in karst systems in a warm, sub-humid climate. This conceptual model is crucial for enhancing water management strategies in the area.

Karst groundwater

hydrogeochemical

isotopic

dedolomitization

temporal variation

groundwater flow systems.

-Karstification derived by limestone and gypsum dissolution produces characteristic groundwater composition.

- The geochemical and isotopic signatures of karst groundwater allowed the identification of local, intermediate, and regional flow systems.

- The conceptual hydrogeological model facilitates the formulation of effective strategies for managing karst groundwater.

Karst aquifers cover some 15.2% of the earth’s land area, forming from the dissolution of carbonate rocks (Ordoñez and Benavente, 2014; Fiorillo and Malik, 2019). Groundwater from karst aquifers supplies approximately 25% of the world’s population (Kalhor et al., 2019). Karst aquifers play a crucial role in ecosystems that rely on discharges from these aquifers for their groundwater supply in terms of both quantity and quality (Siegel et al., 2023). The structure of an underground karst terrain is complex and heterogeneous; water is mostly found within fractures, rock capillaries, fissures, and conduits, which are located at the origin of preferential flow patterns with different chemical compositions (Pueyo Anchuela et al., 2015; Chuang-Bing et al., 2023). Water infiltrates these areas quickly due to their structure and hydrogeological behavior, which increases their susceptibility to transport of contaminants (Nanou and Zagana, 2018; Wu et al., 2021). Although karst aquifers are of great importance, the majority of research has been devoted to documenting the chemical composition of groundwater within these aquifers, which provides insight into the processes occurring within the basin (Moreno-Gómez et al., 2022; Jourde and Wang, 2023). Only a small number of studies examine changes in the chemical composition of karst groundwater due to variations in timing caused by climate and human activities (Adji et al., 2017; Bicalho et al., 2012; Dar et al., 2015). Water from karst aquifers can discharge into springs or wetlands (Gardner and Finlayson, 2018; White, 2019), the latter being an ecosystem that is fully or partially dependent on groundwater discharges (Green, 2007; Custodio, 2000b, 2010; Bring et al., 2020).

Wetlands are globally acknowledged for their ecosystem services (Ramsar, 2016), but there is a lack of data on how the chemical composition of water changes over time in these areas (Abdul Malak et al., 2019; Leibowitz et al., 2023; Lu et al., 2023). These variations can negatively impact ecosystem functions, resulting in habitat loss and species decline, as well as affecting activities crucial for the human population. There is a worldwide need to improve knowledge in hydrogeology and to incorporate ecological factors to enhance the development of sustainable groundwater management strategies for ecosystem preservation.

Therefore, it is crucial to understand the interactions and dynamics between ecosystems and groundwater in wetlands. The main natural hydrogeochemical processes that determine the chemical composition of groundwater in karst terrain are the water–rock interaction processes that give rise to the dissolution–precipitation of minerals, mainly carbonates (Bibiano et al., 2015; Liu et al., 2023). The study of variations in chemical composition will make it possible to infer the main processes to which groundwater is subjected during its trajectory through the subsurface, as well as to determine the state of health of the ecosystem under study.

The different trajectories that can be generated in karst terrain can easily be studied using the theory of groundwater flow systems proposed by Tóth (1962, 1963, 2000). According to this theory, there are three types of discharges determined by local, intermediate, or regional flows, each with different residence times, leading to unique chemical properties for each one. Connecting the theory with the geochemical and isotopic analysis of groundwater can assist in identifying the source of groundwater, leading to a more precise understanding of water movement underground and how different groundwater flow systems develop (Bicalho et al., 2017; Olea-Olea et al., 2019). The Craig (1961) global meteoric line is frequently utilized as a reference in this context.

This research was conducted in the Ciénaga (swamp) de Tamasopo wetland, which is situated in a karst area with a warm subhumid climate in the Sierra Madre Oriental (SMO) in the Huasteca Potosina region. This wetland, designated as RAMSAR site number 1814, is of continental type and provides various ecosystem services in its environs. The region is a conservation priority and a significant biodiversity hotspot, with the swamp crocodile (Cocodrilus moreletti) as its flagship species. Previous studies at the site have mainly concentrated on analyzing the chemical composition of groundwater discharges into the wetland and surrounding springs. However, there is a lack of evidence regarding any potential changes in chemical or isotopic composition over time due to the studies being conducted at single points in time (Morán-Ramírez et al., 2013; Krienen et al., 2017).

This study was conducted in a karst area with a warm sub-humid climate. Due to the absence of wells for hydraulic parameter data, the analysis focused on the temporal changes in groundwater chemical composition. By utilizing hydrogeochemical tools and isotopic data, the study identified recharge zones and mapped various groundwater flow systems discharging within the basin.

Data analysis was done through the multivariate statistics widely used for the analysis of geochemical data, in which the grouping of groundwater samples and establishment of correlation between variables facilitate their interpretation (Iwamori et al., 2017; Gregory-Udie et al., 2020; Malagón et al., 2021). Multivariate methods such as principal component analysis (PCA), PERMANOVA, and hierarchical cluster analysis (HCA) were applied in the present study.

The study aimed to determine the groundwater flow systems supplying water to wetland discharges, analyze the main source of major ions, and investigate the processes that change the chemical composition of karst groundwater discharged into the site over time and space. This work proposes to describe a conceptual hydrogeological model of groundwater flow systems in karst areas with warm sub-humid climates. This information can be utilized for future research to improve groundwater management and ecosystem conservation schemes that rely on karst aquifer discharges. No comparable reference exists in the literature to that generated in this research.

Geology and Hydrogeology Setting

Geographical Conditions

The study area, the continental wetland Ciénaga de Tamasopo (Fig. 1), is one of the few ecosystems of its type that exists within the Sierra Madre Oriental (SMO) in the portion of Huasteca Potosina (Torres, 2008); with coordinates 99°19'14.00.00'' W–99°16'57.00'' W and 21°52'03.00.00'' N–21°45'41.00.00'' N (Cruz-Santiago, 2022). It is located at an elevation of about 250 m in the SE part of the municipality of Tamasopo, Mexico. The Ramsar site covers an approximate area of 1364.2 ha (Zapata-Sánchez, 2021). The predominant climate conditions are warm, with a warm sub-humid climate, with the highest amount of rainfall during the summer (García, 2004). Based on the climatological analysis conducted by Ortiz-Enriquez (2023), the average rainfall is 1523 mm, with the wettest month being September with 300 mm and the driest December with less than 40 mm. The average annual temperature is 24°C, with maximum temperatures of 27°C in April and May, while minimum temperatures are below 18°C in January.

Figure 1

The vegetation present at the site ranges from riverian forest, aquatic vegetation of Typha, and induced palm grove to medium sub-evergreen forest and oak forest in the highest part. Part of this vegetation has been removed to dedicate the land to crop and livestock production. (Tapia et al., 2010). The predominant soil types in the area are leptosol-humic-vertic types, which are soils with little development, measuring less than 1 m deep, and found on calcareous material. The second most common is of the Phaeozem-vertic-rendizo type, which is a soil with a higher dark organic matter (OM) content. These are soils of poor drainage with a clay content of 20–30%, flooding in the rainy season, and very hard in the dry season (Tapia et al., 2010; Zapata-Sánchez, 2021).

Geological and hydrogeological features

The study area is located within the San Luis Potosi Valley Platform (SLPVP), in the physiographic province of the Sierra Madre Oriental (SMO). The local stratigraphic column (Fig. 2) is composed of rocks ranging in age from Jurassic to Recent. Outcrops are mainly of polymictic conglomerates, calcareous marine rocks (Cretaceous), sequences of carbonate and terrigenous rocks formed during the Cretaceous, rhyolites, andesites, and basalts (Pliocene-Miocene). Basin rocks and continental deposits (Tertiary) from alluvial deposits are erosional products of pre-existing rocks. The main lithologies that outcrop at the site are the El Abra Formation, which is the oldest geological unit in the area; this is classified into three facies of similar age: Pre-Reef Facies (Tamabra), of limestone with thick to thin stratifications; Arrecifal Facies (Taninul), of thickly stratified limestone; and Post-Arrecifal Facies (El Abra with 110 m thickness), composed of calcilutites, bioclastic limestones, and calcarenites with miliolids and toucasias; dolomite and partially dolomitized limestone, with secondary permeability. It is overlain by the Tamasopo Fm. formed in the Late Cretaceous, with intercalation of carbonates with shaly horizons and some isolated reefs, in addition to mixed deposits of the Upper Turonian-Upper Senonian interval, made up of massive limestones. These are structures related to karstic processes by dissolution, which gives them a secondary permeability. The Cárdenas Fm. corresponds to the Campanian–Maastrichtian and is composed of clayey-calcareous rocks of sandstone, shale, and sandy limestone. It is divided into three members: the lowest is a 180-m layer of shale intercalated with sandstone and biosparrudite, above it is an intermediate layer of 445 m of shale and siltstone, and the upper layer consists of 430 m of siltstone, sandstone, and biosparrudite, with secondary permeability. The Guaxcamá Fm. is considered a basement in the area. This is constituted by Mesozoic rocks that correspond to the Lower Cretaceous of evaporitic deposits, containing gypsum and anhydrite. It has a thickness greater than 2500 m, presenting little permeability, and is of Berriasian-Aptian age (Martínez-Pérez, 1965; DETENAL, 1990; López-Palomino and Piña-Arce, 2009; Morán-Ramírez et al., 2013;Planer-Friedrich, 2014; Romero-Hernández, 2014; Krienen et al., 2017; Yáñez-Rodríguez, 2019; Zapata-Sánchez, 2021 and Ortiz-Enriquez, 2023).

Figure 2

Based on the geological context, due to the nature of the contrasting environment, there is evidence of highly fractured areas and the presence of dominant karstic structures, mainly constituted by carbonates that correspond to the Tamasopo Fm. and a minimal part of the El Abra Fm. It also has alluvial material that fills the depressions in the karstic valleys.

The northwestern portion is the area with the most karstification, coinciding with the zone with the most intense precipitation. Large amounts of precipitation favor the dissolution of carbonate rocks, causing the formation of karst structures (sinkholes). This zone also has the highest topographic elevation. The karst structures, according to their maturity, allow precipitating water to infiltrate and move quickly to the discharge sites. Water that recharges at the high elevation discharges at single points in springs; along the structural polje in the valley where the wetland is located, which is filled with alluvial material in which the flow discharges diffusely; and finally through the runoff of water that reaches El Arroyo La Ciénaga. Hydrologically, the site has an aquifer and an aquitard. The free aquifer found in the Cretaceous sequences composed of the Tamasopo Fm. and El Abra Fm. shows evidence of karstification processes (primary and secondary porosity). The aquitard is made up of rocks of the Cardenas Fm., which is considered to have little or no permeability. Its location generates semi-confining characteristics in the underlying units. Part of the groundwater flow pattern travels through limestone rock, and another part travels over the internal part of the PVSLP, which allows it to interact with the evaporitic rocks of the Guaxcamá Fm. This could be considered the basement rock (Morán-Ramírez et al., 2013; Krienen et al., 2017; and Ortiz-Enriquez, 2023).

Environmental problems

The principal causes of the deterioration of wetlands worldwide are related to changes in land use as well as the irrational consumption of the resources they hold, such as water (Reddy et al., 2022). In the study site, given the economic activities such as sugar cane production and cattle raising, the natural conditions of the wetland are changing, due mainly to changes in land use, causing the substitution of native vegetation for species of agricultural interest. This has had a negative effect on the wetland’s productivity due to an increase in nutrients, causing a stressor effect on organisms and vegetation of this ecosystem. Among the organisms, we find the swamp crocodile (Crocodylus moreletii) and the freshwater snail (Pachylus sp.), in which toxic elements such as As, Pb, and Zn have been found, in addition to traces of organic products such as DDT, Lindane, and Atrazine. These reach the wetland due to the use of pesticides and fertilizers, or during the zafra period (burning of sugarcane for harvesting), which takes place from November to May (Pérez-Segura, 2018; Tellez-García, 2018; Castillo-Ipiña, 2019; San Juan-Meza, 2019; Rivas-Eguia, 2020; Cruz-Santiago, 2022).The presence of toxic metallic elements such as As, Cd, Fe, Mn, Ni, Pb, Se and Zn, has also been verified in aquatic plant species such as Typha dominguensis (Wong-Arguelles, 2020).

Recently, a relationship was identified between the increase in the sedimentation rate and the settlement of human communities (1927 to 1960), that generated the development of activities such as agriculture, which has extended from 12–34% of the land area within the micro-watershed in the period from 1982 to 2020. Therefore, it is evident that the manifestation of toxic elements is directly related to the increase in agricultural activities in the site, causing an increase in nutrients such as OM, nitrogen, and phosphorus, by carrying out oxidation–reduction reactions that enable the mobilization of potentially toxic elements such as Ni, Cu, As, and Pb, which as mentioned above are already present both in vegetation and in organisms that are dependent on the wetland (Centeno-Herrera, 2023). All of this is a cause for considerable concern since to date, extensive agriculture continues to be carried out at the site, and the overexploitation to which the wetland is being subjected is becoming increasingly evident. Understanding the interaction between this ecosystem and environmental and human activities in the watershed is crucial for proposing solutions to restore its balance.

Sample collection and chemical analysis

In this study, a hydrogeological and hydrogeochemical characterization of the Ciénaga de Tamasopo wetland was carried out, and the available information analyzed. The work carried out by Krienen et al. (2017) was taken as a basis. The study features data from 13 samples from springs (8) and streams (5) during a survey conducted in 2010. Building on this data, additional field work was carried out in the present study. A total of 164 groundwater and surface water samples (Table 1) were collected from springs, dug wells, drains, rivers, streams, and wells across the Ciénaga de Tamasopo wetland in 2018 and 2021 (Fig. 1). The data obtained were used to build the conceptual hydrological model of the aquifer system.

Table 1

Summary table of the location sampled during 2018–2021
Id	Type	Sampling campaigns		Number of samples
Id	Type	Rainy	Dry	Number of samples
1	Dug well	Jun (2018,2021); Jul (2020); Sept (2021)	Feb (2019), Nov(2019, 2021)	7
2	Spring	Jun (2018.2021);Jul (2020); Sept (2021)	Feb (2019); Nov(2019,2021)	7
3	Spring	Jun (2018,2021);Jul (2020); Sept (2020,2021)	Feb (2019), Nov (2019,2021)	8
4	Spring	Jun (2018,2021); Jul (2020); Sept (2021)	Feb (2019); Nov (2019,2021)	7
5	Spring	Jun (2018,2021);Jul (2020); Sept (2021)	Feb (2019), Nov (2019,2021)	7
6	Spring	Jun (2018); Sept (2021)	Feb (2019); Nov (2019,2021)	5
7	Spring	Jun (2018); Sept (2020, 2022)	Feb (2019); Nov (2019,2021)	6
8	Spring	Jun (2018,2021); Jul (2020); Sept (2021)	Feb (2019); Nov (2019,2021)	7
9	River	Jun (2018, 2021)	Feb (2019); Nov (2019,2021)	5
10	Spring	Jun (2018,2021); Jul (2020); Sept (2021)	Feb (2019); Nov (2019,2021)	7
11	Dug well	Jun (2018,202); Jul (2020); Sept (2021)	Feb (2019); Nov (2019,2021)	7
12	River	Jun (2018,2021); Jul (2020); Sept (2021)	Feb (2019); Nov (2019,2021)	7
13	River	Jun (2018,2021); Jul (2020); Sept (2021)	Feb (2019); Nov (2019,2021)	7
14	Dug well	Jun (2018,2021); Jul (2020); Sept (2021)	Feb (2019); Nov (2019,2021)	7
15	River	Jun (2018,2021)	Feb (2019)	3
16	River	Jun (2018)	Feb (2019)	2
17	River	Jun (2018)	Feb (2019)	2
18	River	Jun (2018)	Feb (2019)	2
19	River	Jun (2018)	Feb (2019)	2
20	River	Jun (2018)	Feb (2019)	2
21	River	Jun (2018)	Feb (2019)	2
22	Well	Jun (2018)	Feb (2019)	2
23	Well	Jun (2018)	Feb (2019)	2
24	River	Jun (2018)	Feb (2019)	2
25	River	Jun (2018)	Feb (2019)	2
26	River	Jun (2018)	Feb (2019)	2
27	River	Jul (2020); Jun, Sept (2021)	Feb (2019); Nov(2019,2021)	6
28	River		Feb (2019)	1
29	River		Feb (2019)	1
30	Spring		Feb (2019)	1
31	Spring		Feb (2019)	1
32	River		Feb (2019)	1
33	River		Feb (2019)	1
34	River		Feb (2019)	1
35	Spring		Feb (2019)	1
36	River		Feb (2019)	1
37	Spring		Feb (2019)	1
38	Spring		Feb (2019)	1
40	Drain	Sept (2021)	Nov (2019,2021)	3
41	Drain	Sept (2020)	Nov(2019)	2
42	Drain	Sept (2020)	Nov(2019)	2
43	Drain	Sept (2020)	Nov(2019)	2
44	Drain	Jul (2020); Jun, Sept (2021)	Nov (2021)	4
45	Spring	Jul (2020)		1
46	Spring	Jul (2020); Jun, Sept (2021)	Nov (2021)	4
47	Spring	Jul (2020); Jun, Sept (2021)	Nov (2021)	4
48	River	Jul (2020)		1
49	Stream	Jul (2020); Jun, Sep t(2021)	Nov (2021)	4
50	Drain	Sept (2020)		1
				164

On-site field water measurements were temperature (T), pH, dissolved oxygen (OD), oxidation reduction potential (ORP), and conductivity (EC). Alkalinity was determined by acid base titration on filtered (0.45 µm) samples (Gran method, 1.6 N H₂SO₄). Groundwater aliquots were collected, and all samples were filtered in the field through a 0.45 µm membrane. Major ions in the water samples were analyzed by spectrophotometry, except for NO₃¯, for which concentrated H₂SO₄ was added to avoid bacterial growth and prevent changes of concentration. Major and minor cations and some trace constituents were analyzed by acidifying the samples using ultrapure HNO₃, and the analyses were carried out either by ICP-OES (Inductively Coupled Plasma Atomic Emission Spectrometry, Thermo Scientific, ICAP 7400 DUO) or ICP-MS (Inductively Coupled Plasma Mass Spectrometry, Thermo Scientific, X Series-2). ICP-OES and ICP-MS were calibrated using certified standards. The accuracy of measurement was monitored using a 2% ultrex grade HNO₃ blank and analyzing a laboratory control sample of known concentration every ten samples.

Filtered aliquots for stable isotopes δ²H and δ¹⁸O were analyzed using a Picarro L2130-i isotopic liquid water analyzer and are reported relative to the Vienna Standard Mean Ocean Water (VSMOW). The precision of the measurements was ± 0.08 for δ¹⁸O and ± 0.35 for δ²H. The charge balance error was calculated to verify fulfillment of the electroneutrality condition. All samples showed an error of ˂10% (PHREEQC, 2021).

A consistent record of field parameters was achieved by using dataloggers (HOBO U24-001 Fresh Water Conductivity Data Logger), which were placed in seven springs, three in the Ciénaga. River and one at the boundary of the Ramsar site, with measured capacities for EC (0-2500 µS/cm) and temperature (2 to 35°C) (Fig. 1).

The hydrogeochemistry data were utilized to categorize groundwater using the graphical methods of Piper and Stiff through the Aquachem software package. The saturation index (SI) estimates for the minerals barite, calcite, celestite, dolomite and gypsum were obtained by using the PHREEQC Version 3 program.

Data analysis

The samples were analyzed for a great number of physical and chemical variables. In order to reduce the large data set, a multivariate statistical analysis was applied to the data using Principal Component Analysis (PCA). This method is commonly used for environmental, hydrologic, and hydrogeochemical studies since it allows the interdependence of variables to be analyzed and the dimensionality of the dataset to be reduced. This enables the samples to be ordered and classified, distinct groups to be defined, and yields correlations between physicochemical parameters from groundwater and surface water samples (Güler et al., 2000; Farnham et al., 2002; Cloutier et al., 2008; Matiatos, 2014; Ghesquière et al., 2015). The data was analyzed using the Statistics Primer version 6.1.13 software and Permanova + version 1.0.3 from PRIMER-E (Clarke and Gorley, 2015).

Principal Component Analysis was carried out on the geochemical and field parameters EC, pH, T, and Ca²⁺, Cl⁻, F⁻, HCO₃⁻, K⁺, Li⁺, Mg²⁺, Na⁺, NO₃⁺, Sr²⁺, SO₄²⁻, and the SI (barite, cacite, celestite,dolomite, gypsum). Type of sampling site, type of water, and season were added as supplementary variables and did not contribute to the analysis of the PCA.

Since the data do not follow a normal distribution (Table 2), all parameters were log-transformed, except pH and the saturation index, which already had logarithmic values. The data was normalized and standardized to produce a symmetric matrix; this ensured the reliability of the data for the PCA. A representation of the variation of the samples was obtained from the PCA, generating a classification among the variables analyzed (Melloul, 1992; Chou et al., 2012; Blake et al., 2016). Following these analyses, a PERMANOVA was applied to determine significant differences between the qualitative variables (type of sampling site, type of water, season), the groundwater and the surface water samples. Comparing equality between the groups produced the Euclidean distance matrices, yielding the pseudo-F value, and thus the significance of the relationship between the groups, as well as p values (Williams et al., 2015; Mereles-Aquino, 2018; Sánchez-Gonzalez, 2022). A hierarchical cluster analysis was performed to rank the geochemical data according to their similarity. Complete linkage was used, based on using the maximum of the Euclidean distances between groups to obtain a better clustering (Ghesquière et al. 2015).

Table 2

Descriptive statistical data for field parameters, in rainy and dry seasons, major and minor ions, and trace elements in groundwater and surface water samples. SD Standard deviation
	Rainy				Dry
Parameter (Units)	Min	Max	Mean	SD	Min	Max	Mean	SD
EC (µS/cm)	6.58	1688.00	937.64	433.09	441.70	3105.00	1143.24	459.96
pH^a	6.30	8.30	7.17	0.54	5.82	8.32	7.10	0.64
T (°C)	21.60	31.00	24.34	2.15	18.20	25.70	22.28	1.83
Ca²⁺ (mg/l)	49.61	352.31	163.81	65.15	83.52	455.39	180.76	64.52
Cl⁻ (mg/l)	3.61	94.57	15.39	14.33	7.94	100.06	25.07	18.12
F⁻ (mg/l)	0.00	1.45	0.48	0.37	0.01	1.88	0.63	0.40
HCO₃⁻ (mg/l)	91.65	483.12	293.81	85.58	119.59	491.12	295.61	75.60
K⁺ (mg/l)	0.01	4.93	1.41	0.73	-0.25	3.57	1.21	0.78
Li⁺ (µg/l)	0.01	65.43	18.44	19.62	0.01	46.08	18.72	15.11
Mg²⁺ (mg/l)	0.90	58.77	23.14	18.27	0.75	70.22	26.74	18.26
Na⁺ (mg/l)	0.08	28.12	3.17	4.03	0.16	27.62	5.32	6.41
NO₃⁻ (mg/l)	0.44	163.86	10.67	17.34	1.33	49.60	7.20	6.05
Sr²⁺ (µg/l)	0.01	5362.00	882.60	1407.61	143.40	10915.00	2164.98	1811.10
SO₄²⁻ (mg/l)	1.00	800.00	229.61	232.76	5.00	1240.68	305.07	254.64
SI Barite^a	-1.88	0.57	-0.45	0.58	-1.50	0.50	-0.22	0.54
SI Calcite^a	-0.63	1.21	0.22	0.45	-1.28	1.20	0.15	0.59
SI Celestite^a	-8.33	-0.55	-3.53	2.01	-3.92	-0.49	-1.65	1.07
SI Dolomite^a	-2.87	1.96	-0.27	1.15	-3.43	1.96	-0.39	1.33
SI Gypsum^a	-3.32	-0.43	-1.45	0.75	-2.64	-0.20	-1.22	0.67

^a pH and SI values are dimensionless.

Temporal variation of groundwater chemistry

The hydrogeochemical characteristics of the karst water have made it possible to interpret the effect caused by the geological, topographical, and climate conditions prevailing in the area, and how this directly influences the hydrodynamic behavior of the main springs, wells, streams, and rivers. Therefore, it was possible to identify the different trajectories followed by water within the basin from its recharge to its discharge, identifying effects from the temporal variation in the modification of the chemical composition of the water in the period 2018 to 2021.

Physicochemical parameters

The samples collected from the site were analyzed according to season as shown in Table 2. Overall, the temperature decreased slightly from the rainy to the dry season at all sampling locations. The pH remained relatively constant in both seasons, while electrical conductivity was higher during the dry season and lower during the rainy season. The higher EC values observed during the dry season suggest that a groundwater supply may have a deeper origin. The lower EC values observed in the rainy season were found in springs located in the foothills in the N zone of the basin, indicating recent infiltration. The small changes in pH value during different seasons confirm the dissolution–precipitation process of the different minerals that compose the karst aquifer and possibly the rapid infiltration of rainwater.

Major ions

The major ions show a varied distribution according to the season of the samples. The concentrations of Ca²⁺, Mg²⁺, and HCO₃⁻ in the rainy season showed the influence of the dissolution of limestone rocks that are characteristic of karst areas. During the dry season, there was an increase in the concentration of Ca²⁺ and Mg²⁺, which correlated with the values of Sr²⁺ and SO₄²⁻ during the same period. This suggests that the water discharge in certain springs originates from deeper sources where interaction with evaporitic rocks takes place. The rocks with this composition are in the Guaxcama Formation at the study site. The NO₃⁻ concentration is higher during the rainy season, indicating the impact of the intensive agriculture practiced in the region. The concentrations of chloride ions (Cl⁻) and sodium ions (Na⁺) could be affected by cation exchange mechanisms occurring in the geological formations present on the surface or by human interventions in the region.

The concentrations of major ions (Ca²⁺, Mg²⁺, Na⁺, K⁺, SO₄²⁻, HCO₃⁻, and Cl⁻) were plotted on the Piper diagram to assess the hydrochemical characteristics of the groundwater. The diagram revealed the natural tendency of karst waters to have high concentrations of Ca²⁺ and Mg²⁺ cations, as well as of anions such as SO₄²⁻ and HCO₃⁻. Figure 3 shows that three distinct water families were identified from the collected samples, with the most predominant being Ca-SO₄ (48%), attributed to the dissolution of evaporite minerals such as those in the Guaxcamá Fm. Another significant family was Ca-HCO₃ (46%), resulting from water interacting with the limestone present in the granular karst aquifers of the Tamasopo Fm. and El Abra Fm. The Ca-mix type water (6%) is a mixture of both groundwater inputs.

Figure 3

Hydrogeochemical processes

The main reactions that take place in karst aquifers are related to the dissolution processes of minerals that constitute limestone rocks such as calcite and dolomite, as well as other minerals of evaporitic composition, such as gypsum. By representing chemical relationships in binary diagrams, an interpretation of the processes that predominate in the area can be made in such a way that the different paths that the flow follows from its recharge to its discharge at the site can be inferred. Figure 4a of HCO₃⁻ vs Ca²⁺ shows that the samples above the slope (1:1) have higher HCO₃⁻ than Ca²⁺ content, implying that their main source is the dissolution of dolomite and calcite. In the samples, this behavior is reflected by a Ca-HCO₃ composition that is independent of the season (rainy/dry) (Wu et al., 2014; Morán-Ramírez, 2016). Samples with Ca-SO₄ and Ca-mix composition tend to increase more in their Ca²⁺ content rather than HCO₃⁻, indicating that this increase is related to the dissolution of minerals such as gypsum (Scanlon et al., 2009; Morán-Ramírez et al., 2013; Wu et al., 2014;Hassen at al., 2018; Feng et al., 2020).

Figure 4

The relationship of HCO₃⁻ vs Mg²⁺ shown in Fig. 4b indicates that there are processes of calcite dissolution shown by the samples that are located above the slope, which are mostly samples with HCO₃⁻ in rainy and dry seasons. There is an increase in the concentration of Mg²⁺ that can be distinguished in the waters with Ca-SO₄ and Ca-mix composition (rainy/dry seasons).This behaviour is confirmed by the dissolution of gypsum, given that the solubility of gypsum (CaSO₄.2H₂O) is greater than that of calcite (CaCO₃) and dolomite (CaMg(CO₃)₂) due to the co-ion effect. The precipitation of calcite is intended to maintain the equilibrium with the Ca²⁺ concentration. When calcite precipitation takes part of the HCO₃⁻ from the solution, the dolomite begins to dissolve to maintain the mass balance of the HCO₃⁻ concentration. This process is known as dedolomitization, and generates an increase in the concentration of SO₄²⁻ and Mg²⁺, which subsequently shows that the concentrations of HCO₃⁻ and Ca²⁺ remain constant (Zang et al., 2015; Qian et al., 2018; Baumann et al., 2019). This dedolomitization process can be seen more clearly in Fig. 4d.

It can be observed that for the Ca²⁺ vs SO₄²⁻ ratio in Fig. 4c, the samples are predominantly above the slope, suggesting that the samples with HCO₃⁻ composition (both seasons) tend to have a constant concentration of Ca²⁺ and do not have an increase in SO₄²⁻. A similar behaviour is seen in Fig. 4d, where the dedolomitization process described above can be inferred, while the samples with Ca-SO₄ and Ca-mix composition tend to increase in concentrations of SO₄²⁻ and Ca²⁺ regardless of the season, this being characteristic of gypsum dissolution.

The effect on EC of mineral dissolution is shown by the HCO₃⁻ vs. EC and SO₄²⁻ vs. EC ratios (Figs. 4e and 4f). These tendencies can be explained as increasing dissolution of minerals such as gypsum, explaining the higher SO₄²⁻ concentrations and EC observed in water with Ca-SO₄ and Ca-mix compositions. Unlike these, it is recognized that water with Ca-HCO₃ composition generally has a constant EC content, and although there is an increase in EC in some samples during the dry season, this increase is related more to the course of the water and possible evaporation effects.

Geochemical modelling

A loss of partial CO₂ pressure of groundwater upon discharge is controlled by atmospheric pressure (Bibiano et al., 2015). This degassing process assumes that water in karst systems tends to be oversaturated with respect to calcite, because the equilibrium dissolution of this mineral is dependent on the CO_2(g) content. Figure 5g shows samples of Ca-HCO₃ composition, most of them from both seasons. When subjected to degassing processes, they tend to be supersaturated with respect to calcite and dolomite. A few samples of this same composition are undersaturated with respect to calcite and dolomite, which may be related to the path of water and to soil conditions such as biological activity that generates some CO₂ contribution, supporting the precipitation of limestones. With respect to sulfate composition, samples from both seasons show a similar behavior since most of the samples show supersaturation, because as SO₄²⁻ concentrations increase, HCO₃⁻ concentrations begin to decrease, pushing the samples towards calcite saturation until they become supersaturated because of the dedolomitization reaction.

Figure 5

The samples as a whole show undersaturation with respect to gypsum, suggesting that this mineral dissolves along the groundwater flow (Fig. 5h). It can be observed that the Ca-HCO₃ samples from the dry season are mostly undersaturated with respect to gypsum and calcite, although a few dry season samples are in equilibrium and saturated with respect to calcite. This behavior is related to the loss of CO₂ from the water at the time of discharge. A similar behavior is observed in waters of Ca-HCO₃ composition from the rainy season. In this case most of the samples are in equilibrium and others are supersaturated with respect to calcite, possibly due to the rapid degassing of water at the time of discharge. Ca-SO₄ and Ca-mix type samples present conditions near saturation, and there is a similar increase in calcite saturation, reaching supersaturation, confirming the presence of dedolomitization processes.

Stable isotopes

Data on the isotopic composition from different seasons of the year from 2019 to 2021 were used to examine the spatial–temporal variation of the stable isotopic composition of water in hydrological processes, and to be able to determine the origin of the water source discharging in the surrounding area of the wetland. The data were analyzed using the data isotopic ratios of precipitation in three locations from the Huasteca Region (period 2008–2015) as a reference. The first source of precipitation data is located 37 km east-northeast of the study area in Ciudad Valles, the second is located 14 km north in Tamasopo, and the third one is located 68 km east-northwest of the study area in Río Verde. Two collection stations (Cd. Valles and Tamasopo) were used to determine the local meteorological line of the Huasteca Zone (LMLHZ) reported by Esquivel-González (2022), which is used to characterize stable environmental δ¹⁸O and deuterium isotopes in the study zone in this work.

The δ²H and δ¹⁸O isotopic compositions in the samples were obtained during a survey in the wetland in the period 2018–2021 (Fig. 6). The δ¹⁸O composition in November 2019 was between − 4.67 to − 6.90‰ and the mean value was − 6.15‰. The δ²H composition ranged from − 29.12 to − 41.37‰ and the mean value was − 36.97, corresponding to the rainy season. For July 2020, the isotopic composition was − 4.75 to − 6.83‰ and the mean value was − 6.21‰ of δ¹⁸O, and for δ²H, the range was − 29.48 to − 41‰ and the mean value was − 38.12‰. For September 2020, the δ¹⁸O the composition ranged from − 4.66 to − 6.82‰ and the mean value was − 5.60‰, and for δ²H the composition ranged from − 27.79 to − 41.05‰ and the mean value was − 33.32‰. For June 2021, the δ¹⁸O isotopic composition ranged from − 4.66 to − 6.82‰ and the mean value was − 5.93‰. For δ²H, the composition ranged from − 27.79 to − 41.05‰ and the mean value was − 35.81‰. The weighted averages calculated for the Cd. Valles and Tamasopo stations were also used, to calculate the elevation gradient that modifies the isotopic composition of the water discharging in the area. The values were − 6.03‰ for Tamasopo, − 6.01‰ for Ciudad Valles and − 8.2‰ for Río Verde and for δ²H, the values are − 33.45, − 33.49 and − 51.95‰ respectively for the same stations.

Figure 6

The GMWL (Global Meteoric Water Line) and LMLHZ were used to calculate the isotopic composition (Esquivel-González,2022). LMLHZ is similar to the GMWL with an equation of δ²H=8.49 δ¹⁸O + 17.34 (R²=0.9574). By comparing the results obtained from the different samplings, it can be observed that the values of the slope are less than 8, which indicates specific situations for each of the seasons when the samples were collected. First, the samples of November 2019 and July 2020, having slopes with a value of 5, indicate that the water in these periods was subjected to greater evaporation, meaning that relative humidity was lower, which is consistent with the season because in these two periods the monthly rainfall was 81 and 138 mm respectively. It is possible to differentiate the increase in the slope very well as the volume of precipitation increases, observing that the sampling with the higher slope value is from September 2020. This is consistent with the highest precipitation that occurred during the sampling period, which was 262 mm, a considerable difference from the sampling done in June 2021, where although the slope increased to 6, relative humidity was lower given the volume of precipitation, which was 148 mm. It can be observed that there is a slight variation in the isotopic composition due to evaporation effects. Considering this effect relevant to understanding the mechanisms of the recharge of the water that discharge to the site, the excess of deuterium was calculated (Fig. 7), employing the Dansgaard Eq. (1964) 𝑑= δ²H − 8 δ¹⁸O, which is related to the atmospheric humidity conditions of sampling.

Figure 7

Figure 8

This difference of the deuterium enables information to be obtained regarding the conditions of the area of origin of the humidity. The values obtained for the November 2019 season were from 8.26 to 13.86 with an average value of 12.19‰; for the July 2020 season the range was from 8.38 to 13.62 with an average value of 11.53‰, for September 2020 the range was from 9.73 to 13.05 with an average value of 11.48‰, and for the sampling in June 2021, the ranges were from 8.27 to 13.92 with an average value of 11.64‰. These values are consistent with the conclusions about the influence of moisture content from the amount of precipitation, taking the average value of 10‰ of global meteoric waters as a reference, derived from oceanic moisture sources (IAEA, 2006). Therefore, excess deuterium values lower than 10‰ indicate an evaporation effect, since there is a decrease in relative humidity and therefore there a reevaporation effect, before the water manages to touch the ground, while values above 10‰ indicate that there is a recirculation of convective moisture recycled in tropical storms (Wassenaar et al., 2009). It was observed that in November 2019 and July 2020 there were lower values of d-excess, indicating a greater influence on the modifications in the isotopic composition due to reevaporation (Peng et al., 2007), or by evaporation due to water travel. This may be the greatest influence on the evaporation of these samples, since they coincide with uses, such as rivers and wells that are more exposed to evaporation processes due to local climate effects, topography, and the recirculation of irrigation water.

Seasonal variation

In order to obtain a long-term record of the functioning of discharges in the study area, ten datalogger devices were used during the period from July 2020 to June 2022 (Fig. 1). T and EC records were obtained from the dry and rainy seasons. Dataloggers are the most useful types of discharge monitoring in karst areas (Stevanovic, 2015). These devices were distributed in perennial springs and were installed longitudinally along the Ciénaga stream at approximately evenly distributed intervals to capture differences along the flow direction. They were located at the beginning, middle, and outlet of the stream. The analysis of these parameters, together with the monthly precipitation data, enabled the predominant hydrogeological scenarios at the site to be inferred.

The results were categorized into three groups (Table 3) based on the location within the Ciénaga stream: the initial section (site 49), the middle section (site 44), and the final section (site 48). The remaining two groups are associated with springs and are classified based on their EC values. Group two includes springs 2 and 10, while springs 4 and 5 were combined due to their proximity and similar compositions. Group three consists of springs 8, 27, 46, and 47.

Table 3

Descriptive statistics of Temperature and Electrical Conductivity parameters recorded by datalogger devices in river and spring at Ciénaga de Tamasopo, Mexico during the period 2020–2022.
			Parameter
			Temperature (°C)			EC (µS/cm)
Group	Id	Type	Min	Max	Mean	Min	Max	Mean
1	44	River	15	34	25	489	1999	1578
	48		15	33	26	429	1802	1463
	49		16	31	25	456	1628	1409
2	8	Spring	23	25	24	591	1871	1787
	27		21	26	24	897	1792	1517
	46		23	25	24	1131	2038	1582
	47		24	24	24	657	1873	1673
3	2	Spring	24	26	25	482	681	629
	4 & 5		23	27	24	492	707	634
	10		23	25	24	321	667	585

Fluctuations in electrical conductivity (EC) and temperature (T) and reactions to weather conditions are noticeable. Group one (Fig. 9) displays temperature variations based on the stream locations. Site 49 had the lowest temperatures and the lowest electrical conductivity (EC) compared to the other two sites. The electrical conductivity (EC) value fluctuates during the rainy season. Higher rainfall leads to a noticeable decrease in this value, as observed in September and November 2020 and August 2021. EC values are higher during the dry season from October 2020 to March 2021 and from November to April 2022. Temperatures are higher during the rainy season and lower during the dry season (Centeno-Herrera, 2023). The effect of temperature on the springs was shown to be stronger during the summer, when solar radiation inputs are higher (Middleton et al., 2015). Water temperature decreased slightly during specific high precipitation events in spring and summer.

Figure 9

Site 44, located in the middle section of the stream, exhibited the highest temperatures and electrical conductivity (EC) values in this group. Site 49 exhibits a consistent pattern where major rainfall events lead to a slight decrease in temperature, while the lowest temperatures are recorded during the dry season. The EC rose significantly during maximum precipitation in July 2021, followed by a noticeable decline in August 2021. The trend for electrical conductivity (EC) indicates that higher precipitation volumes lead to a decrease in EC. As precipitation decreases, EC must rise and stay consistent until new precipitation events happen, leading to another decrease in this parameter. The rise in EC at this location may indicate increased karstification, leading to preferential zones for discharges reaching the site.

Site 48 experienced a slight rise in electrical conductivity (EC) during the rainy season from June to September 2021, with lower EC values, and with the highest values occurring in August 2020. Temperature varied with minimum values occurring during the dry season, and when the main precipitation event occurred in the rainy season, there was a slight decrease. Both the EC and temperature thus show an almost immediate response to precipitation events.

In the second group (Fig. 10), there is a significant contrast in temperatures between the highest temperature recorded during the low water period and the minimum temperatures during the dry season for springs 2, 4, and 5. There was a slight decrease in water temperature during certain high precipitation events in spring and summer. EC typically remains stable in most records, but higher precipitation amounts are related to a decrease in EC. Also, when the precipitation decreases, the EC values gradually increase and are maintained constant until new precipitation events occur, when EC values decrease again.

Figure 10

In this group, spring 10, unlike the other two springs in the group, has slightly lower temperatures, which may be related to the amount of solar radiation it receives and if the contributions to it are only groundwater and do not include surface water. Unlike the other springs, the increase in precipitation during the summer does not generate any change in temperature; however, a slight, gradual increase is observed during this period. The EC shows a significant decrease from July to August 2020 during the rainy season, possibly indicating an effect caused by the intensity and duration of precipitation. After this event, stable values are observed from October 2020 to February 2022, where a decrease in EC is observed in an inverse relationship with respect to temperature. Note that for July–September 2021, the data-logger was not available. The EC shows a significant decrease from July to August 2020 during the rainy season, possibly indicating an effect caused by the intensity and duration of precipitation. After this event, stable values are observed from October 2020 to February 2022, when a decrease in EC is observed, making this behaviour the inverse of the pattern of temperature, and for the same season. Note that for July–September 2021, data from the logger was not available.

In the third group (Fig. 11), spring 8 presents its lowest temperatures in the period of 2020, with significant gradual increases from December 2020 to May 2022. Its behaviour during rainfall events does not seem to have a significant effect on temperature variations, but it does show that for the dry season of 2022, temperatures tend to be more constant with slight increases during the spring (below 25°C).

Figure 11

A decrease in EC can be observed in September 2020, caused by the increase in the volume of precipitation. This was one of the most intense precipitation events recorded during the recording period; after this event, the EC increased slightly, remaining almost constant from October 2020 to July 2021, and then increasing gradually from September 2021 to the end of the recording period in 2022. Although these are not the maximum events, events with longer durations show a response to these events with a drastic change in EC, decreasing abruptly. After this response, it can be observed that precipitation begins to decrease, and with this there is a gradual increase in EC until it remains constant from September 2021 to the end of the record in 2022.

For the period July–August 2020 and during May 2021, spring 27 recorded the lowest values in terms of EC. For the periods from August 2020 on, the trend is an abrupt increase, and this season has the highest record of EC. After this, there is a maximum precipitation event that generates a decrease in EC, and when precipitation tends to decrease, influenced by the change from rainy season to dry season, the EC tends to increase until maintaining constant values until the spring of 2021, when there is a considerable decrease in the value of EC. The temperature shows that for this case there are no effects caused by rainfall events because their values are relatively constant; however, an increase in temperatures is observed in the spring of 2021, which may be related to the increase in solar radiation and to the flow at this time being slower.

Spring 46 presents a gradual increase in temperature until it remains almost constant, which is more noticeable from the low water season of 2020 to the spring of 2021. For EC, the same effect can be observed when there is a large precipitation event. There is a response by the EC; in this case, it tends to decrease during September 2020. After this event, EC increases gradually until April 2021, when it slightly decreases, originated in this case by the first rains of this season.

Spring 47 is the site with records for the period from July to December 2020, showing a decrease in EC in the period between July and August and during September of the same year and after November in response to the rains recorded. After the rains, EC tends to increase and remain relatively constant. A gradual increase in temperature is observed until the maximum temperature recorded for this site is reached, with only slight variations in temperature at the most intense rainfall events.

Principal Component Analysis

Primer V6 was used to calculate the Spearman correlation model; the principal components analysis (PCA) was applied to the geochemical data. Starting with the correlation matrix (Table 4), it is possible to identify the possible paths followed by the groundwater flow. From the correlation matrix, EC and Ca²⁺, Mg²⁺ and SO₄²⁻ correlate positively with Li⁺, F⁻, Sr²⁺ and SI celestite, SI gypsum and SI barite, which indicates the dissolution of minerals present in evaporitic sequences, suggesting longer residence time within the aquifer, giving them sufficient time in the subsurface to increase in concentration. The high correlation of pH with SI calcite and SI dolomite mainly indicates the effect of the biological action of the OM present in the subsoil, which favors the dissolution of minerals such as carbonates and dolomites, the minerals that are the main constituents in karst aquifers.

Table 4

Spearman correlation matrix. Values in bold are different from 0 with a significance level alpha = 0.05, n = 164
Variable	T	CE	Ca²⁺	Mg²⁺	Na⁺	K⁺	HCO₃⁻	Cl⁻	SO₄²⁻	F⁻	NO₃⁻	Li⁺	Sr²⁺	pH	SI calcite	SI dolomite	SI gypsum	SI celestite	SI barite
T	1.00
CE	-0.12	1.00
Ca²⁺	-0.10	0.91	1.00
Mg²⁺	-0.28	0.80	0.76	1.00
Na⁺	0.15	0.18	0.11	0.21	1.00
K⁺	0.14	0.23	0.14	0.33	0.42	1.00
HCO₃⁻	0.00	-0.16	-0.02	-0.39	-0.29	-0.47	1.00
Cl⁻	-0.20	0.21	0.15	0.07	0.27	0.17	-0.17	1.00
SO₄²⁻	-0.17	0.85	0.82	0.94	0.23	0.34	-0.45	0.16	1.00
F⁻	-0.08	0.79	0.74	0.79	0.38	0.43	-0.44	0.24	0.86	1.00
NO₃⁻	0.25	-0.36	-0.26	-0.46	0.02	-0.09	0.12	-0.14	-0.39	-0.28	1.00
Li⁺	-0.18	0.83	0.74	0.85	0.12	0.27	-0.29	0.11	0.86	0.75	-0.39	1.00
Sr²⁺	-0.19	0.47	0.39	0.47	0.39	0.24	-0.34	0.29	0.52	0.55	0.09	0.48	1.00
pH	0.03	0.00	-0.05	0.18	0.34	0.27	-0.50	0.11	0.20	0.27	0.14	0.17	0.30	1.00
SI calcite	0.08	0.11	0.10	0.19	0.33	0.20	-0.30	0.13	0.21	0.29	0.18	0.20	0.30	0.95	1.00
SI dolomite	-0.01	0.23	0.19	0.42	0.36	0.29	-0.45	0.14	0.41	0.43	0.02	0.39	0.37	0.94	0.95	1.00
SI gypsum	-0.18	0.86	0.85	0.93	0.20	0.31	-0.40	0.17	1.00	0.85	-0.38	0.86	0.51	0.17	0.20	0.40	1.00
SI celestite	-0.18	0.53	0.47	0.57	0.39	0.27	-0.40	0.27	0.63	0.63	0.03	0.53	0.97	0.29	0.28	0.38	0.62	1.00
SI barite	-0.26	0.78	0.73	0.80	0.29	0.30	-0.41	0.29	0.88	0.78	-0.30	0.72	0.57	0.14	0.16	0.33	0.88	0.66	1.00

From the results of the statistical analysis, four principal components were obtained, which explain 75.82% of the accumulated variance of the whole data (Table 5). These factors explain the main characteristics of the chemical composition of the groundwater. Figure 12i displays a factorial plot that compares components one and two. The first component, explaining 38.32% of the overall variance, shows positive loadings for cations Ca²⁺, Mg²⁺, Li⁺, and anions SO₄²⁻ and F⁻. SI gypsum and SI barite are also strongly related to the geochemical process of natural reactions that are derived from water–rock interaction. Water circulation at greater depths is specific to this component. 16.4% of the total variance is attributed to positive loading parameters for pH, SI calcite, and SI dolomite in terms of chemical composition for the second component. This component is related to groundwater that has infiltrated recently. An analysis was conducted to determine the spatial distribution of qualitative variables in relation to the principal components. Figure 12j displays the distributions for each category of water. The samples exhibit a distribution pattern with the following composition: Ca-SO₄ has a positive correlation with variables in component one and a negative correlation with HCO₃⁻ and NO₃⁻. Water with Ca-HCO₃ shows a positive correlation with component two and a negative correlation with component one. The central position of the Ca-mix water type reflects a combination of both water types.

Figure 12k shows a positive correlation between types with drains and most rivers for both components. There is a negative correlation in the trends of both components in dug wells and some spring samples. Other springs trend positively for component one; the streams are positively correlated for both components.

Figure 12

The first component is closely linked to the geochemical processes that result from significant water–rock interactions in karstic areas. In this case, it is suggested that water circulates through evaporitic rocks associated with the Guaxcamá Fm. in the region. The second component is related to the dissolution of limestone in the karstic aquifer. The third component shows positive loadings for variables of anthropogenic origin because of the economic activities carried out in the site, such as intensive agriculture and domestic wastewaters from the towns, such as NO₃⁻. The correlation between Sr²⁺ and SI celestite for this component suggests that groundwater flow at a deeper level significantly impacts discharges at the site. For this same component, the relationship between Sr²⁺ and SI celestite indicates that discharges at the site are strongly influenced by groundwater circulating at greater depth. The fourth component indicates positive loadings for Na⁺ and K⁺, which may be present in the form of nutrients caused by activities carried out at the site or cation exchange with geological material in the aquifer (Cardona et al., 2018).

Table 5

Loadings of the variables. Total explained variance of factors with Varimax rotation.
	Factor
Variable	1	2	3	4
CE	0.92
Ca²⁺	0.91
Mg²⁺	0.92
Na⁺				0.59
K⁺				0.77
SO₄²⁻	0.95
F⁻	0.82
NO₃⁻			0.50
Li⁺	0.89
Sr²⁺			0.81
pH		0.98
SI Ca		0.96
SI Do		0.95
SI Gyp	0.95
SI Cel			0.76
SI Ba	0.82
Eigenvalue	7.28	3.25	2.05	1.82
Variability %	38.32	17.13	10.81	9.56
Cumulative %	38.32	55.45	66.25	75.82

Hierarchical cluster analysis (HCA)

Classifying samples in a dendrogram enables a visual examination of their distribution, employing the previous PCA (Fig. 13). A line is drawn higher or lower on the dendrogram, resulting in a greater or a lesser number of clusters (Ghesquière et al., 2015). In this study, the line was drawn across the dendrogram at a linkage distance of 10; samples with a linkage distance lower than 10 are thus grouped into the same cluster, which produces a division of all the samples into three clusters.

Figure 13

The distance linkage between cluster 3 and the other clusters is slightly higher (8) than the other two clusters, which may be related to the composition being predominantly bicarbonate for this cluster. Cluster 1 is the least similar, with a linkage of 7 to cluster 2, indicating that the chemical composition of groundwater samples from these clusters presents similarity. The plot shows the Stiff diagram for each cluster, constructed by selecting a sample of different types of water as a representation of the predominance in the composition of each cluster. All the Stiff diagrams exhibit a consistent composition, with Ca²⁺, SO₄²⁻, and HCO₃⁻ being the predominant ions.

Cluster 1 (n = 32) and Cluster 2 (n = 66) consist of samples with varied compositions. Most samples are classified as Ca-SO₄ type water, with a smaller number of samples corresponding to the Ca-HCO₃ type water, and the fewest samples are categorized as Ca-mix-type water. The similarity of the clusters corresponds to the distribution of components one and two of the PCA, indicating that discharges in these locations are mainly linked to the natural reactions in karstic aquifers. Cluster 3 (n = 66) samples are predominantly characterized by Ca-HCO₃ type water and are closely linked to component 2 of the PCA. Only one sample has a composition Ca-SO₄, relating to component one.

Hydrogeochemistry is a tool that provides useful information that can be used to study the groundwater of the karst aquifer. In this study, the temporal variation of different parameters and chemical composition of water from springs, dug wells, rivers, streams, drains, and wells during the period from 2018 to 2022 using annual hydrological data is used. Using the data available on the hydrogeological response to periods of rain and dry seasons, from the variations it was possible to evaluate the changes in hydrogeochemistry between the different sampling points within the karstic system, identifying the different lithologies through which the different flow patterns have traveled. Furthermore, it is possible to infer the origin and residence time of the water discharging at the site (Cardona et al., 2018).

The stable isotope study enabled us to define the groundwater recharge sites that discharge within the site for the different types of points that were sampled. The isotopic content of surface reservoirs such as rivers, streams, and wells show values below the LMLHZ, suggesting some evaporation (Fig. 6). This behavior is more noticeable for the November 2019 sampling, which corresponds to the dry season due to the decrease in atmospheric humidity. The same behavior was reflected in July 2020 (Centeno Herrera, 2023), where, although it was already the rainy season, the amount of precipitation was lower than in the other samples collected in the same season. The value of their slopes was 5.93 for November 2019 and 5.02 for the sampling done in July 2020. The increase in precipitation for the sampling conducted in September 2020 and June 2021 tends to produce an increase in δ¹⁸O content and a slight increase in δ²H, suggesting that re-evaporation occurs upon infiltration (Valenzuela et al., 2013; Rivera-Armendariz et al., 2024). It should be noted that enriched values in isotopic composition may also reflect deforested soils, high temperatures, and low atmospheric humidity (Dansgaard, 1964).

It can also be observed that some samples from springs and drains located above and near the LMLHZ represent the composition of recent recharge with values of δ¹⁸O (− 4.75 to − 4.20‰) and δ²H (− 29.12 to − 23.86‰). The regional system water flow is represented by the decrease in the most negative isotopic composition for δ¹⁸O (− 6.90 to − 6.65‰) and δ²H (− 41.37 to − 40.41‰), considering that this variation is given by the groundwater flow path having a longer path through the subsurface, causing the depletion of heavy isotopes in precipitation (Wassenaar et al., 2009; Wu et al., 2019; Melo and Caro, 2020; Paternoster et al., 2020). It also suggests that mixing may occur along the flow line, which has damped seasonal and spatial variations (Clark, 2015).

The excess deuterium (Fig. 7) means that for most of the samples, a value greater than 10‰ is observed, suggesting the recycling of moisture from tropical storms, which are common on the eastern slope. The main source of this is the Gulf of Mexico, where atmospheric humidity conditions are at 77%. Samples with values below 10‰ indicate a possible surface evaporation that is common for shallow environments, indicating a re-evaporation effect before infiltration. This implies that variations in atmospheric humidity play a fundamental role in the isotopic content in the region.

The elevation gradient was determined by comparing the weighted averages of the stations within the Huasteca region (Ro Verde, Tamasopo, and Ciudad Valles) to obtain the variation of isotopic composition with respect to elevation (Fig. 8). The elevation effect indicates that the higher the elevation, the more impoverished the δ18O (Clark and Fritz, 1997). The elevation gradient for this region is − 0.25‰ of δ¹⁸O/100 m, which is consistent with the value reported for the region (Esquivel-González,2022). This indicates that regional recharge can occur at elevations of approximately 1000 m in the Río Verde mountains.

In the karst area, usually the dissolution–precipitation of carbonates and sulfate minerals prevails, as shown in the chemical composition. Figure 4 shows that the dominant reactions are the dissolution of calcite, dolomite, and gypsum (Wu et al., 2014; Morán-Ramírez, 2016), the latter being responsible for dedolomitization processes that prevail during the dry season, indicating the presence of a base flow of deeper origin. This behavior is confirmed by the increase in SO₄²⁻ concentration, being noticeable in Ca-SO₄ water types (Yuan et al., 2017; Tang et al., 2021). This is also reaffirmed by the isotopic composition, as it is a clear example of the existence of a flow that has traveled deeper and further distances and is recharged in areas of higher elevation. Although the water in the basin is known for its Ca-HCO₃ composition, recent observations have shown a connection between the dissolution of limestone rock formations and seepage. This suggests that the flow of water entering through vertical infiltration reacts quickly to precipitation events. The interaction between the CO₂ in the soil and the biological activity of microorganisms decomposing organic matter creates a slight acidity that aids in the dissolution of limestone. This reaction also produces a buffering effect, making it a common occurrence in karst aquifers. A shorter and shallower groundwater path can be inferred from these discharges, which are directly related to the granular karst aquifer found in the El Abra Fm. and Tamasopo Fm. Consequently, Ca-mix water type is the result of a mixture of discharge waters with different compositions (deep origin and seepage), which is more perceptible in the rainy season (Bicalho et al., 2017; Liu et al., 2023).

The SI (Fig. 5) enables us to define the main dissolution–precipitation processes of karst groundwater. It can be inferred that water samples that are supersaturated with respect to calcite are due to two mechanisms. One is the degassing that is best distinguished in the rainy season, which is the tendency of the samples with Ca-HCO₃ type water, where the water at the time of discharge loses CO_2(g) in a natural way; however, in this season it is influenced by the fact that the water travels faster. Therefore, the time that the mineral has for reaching equilibrium is rather short, and it tends to precipitate. In addition to these reactions, the influence of the increase in SO₄²⁻ concentration is also shown; in this case, it is seen how the oversaturation of calcite in the low water season shows that the Ca-SO₄ and Ca-CHO₃ type water, when receiving the base flow with SO₄²⁻ concentrations, favors the dedolomitization process. However, gypsum undersaturation tends to equilibrium, which is independent of the season. Also, it is evident in the samples that are undersaturated with respect to calcite and dolomite that as soon as dolomite dissolution is higher, calcite begins to decrease its undersaturation, following the trend toward equilibrium and oversaturation. The same behavior can be observed in the samples with Ca-SO₄ and Ca-mix compositions (Hassen et al., 2018; Zheng et al., 2018).

The PCA indicated that the hydrogeochemical characteristics of groundwater are typically controlled by water–rock interaction, including dissolution–precipitation limestone and evaporitic rocks, and anthropogenic activities such as the use of chemicals in agriculture. PCA analysis was carried out to evaluate the interelement relationship among major ions and field parameters such as temperature, CE, Ca²⁺, Mg²⁺, Na⁺, K⁺, HCO₃⁻, Cl⁻, SO₄²⁻, F⁻, NO₃⁻, Li⁺, Sr²⁺, pH, and the SI (calcite, dolomite, gypsum, celestite, and barite). Factors were extracted after varimax rotation using XLSTAT. This analysis was used to identify the dominant processes controlling the hydrogeochemical characteristics of groundwater in the study area (Morales-Casique et al., 2016; Tobin and Schwartz, 2016).

The classification obtained from the PCA represents defined characteristics for each type of process taking place at the site. The first two factors (1, 2) represent the geogenic conditions of the discharges at the site. The first component represents the flows that have remained in the subsoil for a longer time, including elements such as Li⁺, F⁻, characteristic of groundwater flows that have had a longer travel time and depth, giving them enough time in the subsoil to increase their concentration (Carrillo-Rivera, et al., 2002). Also in this same classification we find elements such as Ca²⁺ and Mg²⁺, whose increase is, as mentioned above, related to the dissolution of evaporite minerals; in this case gypsum (Edmunds et al. 1997; Kamel et al., 2013), which is grouped in this same factor. The EC associated with this is an indication of groundwater flows that have experienced longer water-rock interaction. The second component is related to recent infiltration flows. Calcite and dolomite SI are grouped in this component, corresponding to the lithology that is found outcropping at the site. The relationship of these with the pH resides first in the interaction of the CO₂ in the soil particles with the water that falls on it, and this causes a slight acidity that helps the dissolution of this type of mineral phase. At the time when the dissolution process takes place, there is a buffer effect that originates from the presence of ions that are released when limestones dissolve (CO₃²⁻, HCO₃⁻). The third component indicates a rather peculiar grouping, because while the association between Sr²⁺ and SI Cel continues to confirm the influence of discharges with longer water–rock interaction times, we also have NO₃⁻, which, due to the quantities, may be related to diffuse sources associated with intensive agricultural activities occurring in the area, possibly indicating irrigation return water. The fourth component confirms the effect that may be caused from the use of chemicals at the site, since these elements may be nutrients related to the use of the site.

The conductivity and temperature measurements were useful for identifying different water sources and the influence of recharge, seasonal changes, and mixing conditions between flows discharging at the sites where the data loggers were situated, as well as identifying meteorological conditions and their contribution to the flow of the springs and stream, which is very useful for improving our understanding of karst systems.

It is assumed that during periods of low water, the EC content remains relatively constant due to the contribution of a deeper base flow with a SO₄²⁻ composition, as well as a mixture with recently infiltrated water, defined as water with some HCO₃⁻ content. These mixtures suggest that dedolomitization processes are taking place, resulting in a decrease in EC during periods of high rainfall. The contribution of a base flow generated by a deeper flow is greater for groups 1 and 3, but for flows that discharge in group 2, it is inferred based on variations in EC content. It is primarily influenced by inputs of recently infiltrated water, which suggests this behavior is due to the HCO₃⁻ composition of the water at this location. It is inferred for this group that when EC decreases, it is caused by calcite precipitation, which is consistent with the short time that this mineral has for reaching equilibrium. It is also possible that the variations in water temperature are the result of the temperature-regulating effect produced by the solar radiation that affects the soil, and that the water, acting as a heat exchanger, can take in or give up heat, slightly dampening the environmental temperature (Matheswaran et al., 2014; Adji et al., 2017).

Hydrogeochemical conceptual model

From the analysis of the hydrogeochemical data, the existence of heterogeneity in the chemical composition of the water is determined. It shows that in the basin there are groundwater discharges from different sources that have different travel times, some of which have shallower circulation and recent infiltration and others that have traveled deeper and through the subsoil, which gives them specific characteristics that make it possible to infer their origin. It is therefore suitable to explain this type of behavior based on established models, such as that proposed by Tóth (1963, 2000), which exemplifies the different paths that water can take depending on topographic, climatic, and geological conditions, influencing the development of the flow systems that discharge at a given site.

Based on this model, three types of flow can coexist in a basin, local, intermediate, and regional. Each is associated with a different residence time and trajectory through the subsoil, from lesser to greater, which confers unique physicochemical characteristics. For the local flows, it is assumed that their discharges are distinguished by a lower content in EC values as a reflection of lower water–rock interaction and temperature close to the environmental average, and a recharge zone is inferred in high topographies close to sites where water emergence occurs. As the intermediate flows travel to an intermediate depth within the basin, the EC and temperature tend to increase. Regional flows are those that travel to greater depths, giving them more time for water–rock interaction, which generates greater dissolution of minerals, which can be seen reflected in the water–rock interaction (Tóth, 1963, 2000).

Considering this theory, we describe the hydrogeological functioning that is taking place in the karst terrain where the Ciénaga de Tamasopo is located, where the presence of three flow systems is assumed (Fig. 14). These are described as follows.

Figure 14

Local flow system

Water of Ca-HCO₃ composition can be related to local flows that are of shorter relative residence time in the aquifer (Nuñez-Peña et al., 2015), which has its recharge zone in the upper parts of the basin corresponding to mountainous areas in the northern portion of the basin, where the karstification effect is greater (dolines, uvales), inducing rapid infiltration. Due to its rapid movement, its route through the karst is short, making it more noticeable in the rainy season, when the response of some springs located in the foothills is almost immediate. Therefore, at this site, it is characterized by shallow travel over the limestone rocks of the El Abra Fm. and Tamasopo Fm., which is evident in its chemical composition. The EC content in the rainy season is 428 µS/cm and in the dry season 543 µS/cm. In the rainy season the water–rock interaction time is faster, and dissolution–precipitation processes occur quickly, so the EC value is lower. A notable increase occurs during the dry season, so it is inferred that the water that remains stored in the karst aquifer continues to dissolve the limestone and generates an increase in EC during this season.

Intermediate and regional flow systems

For this case, we deduce the existence of a regional flow system circulating over the Guaxcamá Fm. that is composed of rocks containing evaporite minerals such as gypsum (CaSO₄.2H₂O), where from a small contribution of water that circulates through this and manages to ascend through faults or fractures, we assume a mixture between waters with a greater predominance of SO₄²⁻, which is evidence of a longer travel time. During its journey towards the discharge zone, this water mixes with water of HCO₃⁻ composition. This intermediate flow has EC for the rainy and dry seasons of 1381 µS/cm and 1454 µS/cm, respectively. The increase that occurs during the dry season may be related to an increase in the contribution of the regional system, or to climate conditions that favor the evaporation process and thus generate a concentration of salts, increasing the EC.

The mixing between different flows occurs mainly during the rainy season, being considerable in the water of rivers and streams, where the convergence of the different flows can have both concentrated and diffuse discharges, as evidenced in Ca-mix-type waters.

This intermediate flow is considered a base flow that could be corroborated in the various types of water usage points that were sampled: springs, wells, rivers and streams.

The incorporation of isotopic data allowed us to deduce that the recharge zone is probably located at an elevation of about 1000 m, typical of mountainous regions characterized by prominent karstification, such as areas with dolines or poljes. Most springs show no evidence of evaporation. Sites experiencing evaporation effects are observed in surface water bodies, where there is a greater indication of mixing of discharge flows. The isotopic content confirms that the water is of pluvial origin and the increases in EC are mainly due to the dissolution of salts, mainly gypsum, from the Guaxcamá Fm.

In discharges that are considered local, water with a δ¹⁸O content of − 6.74 predominates. The δ¹⁸O isotopic content of the intermediate/regional discharge is − 6.90, suggesting greater depletion of this isotope as the distance from the recharge site of the latter flow increases.

This work included the use of hydrogeochemical tools, hydrogeochemical modeling, temporal variation in physical parameters (EC, temperature), and multivariate statistical methods that have been previously used as study tools in karst systems.

In the study area, the ecosystem depends on karst groundwater that discharges permanently, which helps preserve and conserve endemic species. The evolution of water within the basin ranges from Ca-HCO₃ and Ca-SO₄²⁻, to Ca-mix. In Fig. 14, the simplified conceptual hydrogeochemical model describes the evolution of the different groundwater flow systems. The recharge zones of regional flow systems were determined to be beyond the delineation of the study area. The presence of major ions (Ca²⁺, Mg²⁺, HCO₃⁻, SO₄²⁻, and F⁻) and trace ions (Sr²⁺, Li⁺) indicates a gradual change in composition along the flow path, suggesting progressive evolution.

The results indicate that the discharges are dominated by water–rock interaction processes, mixing, and evaporation.

The temporal evolution of the chemical composition of water at different types of usage points and its variations has provided information on the functioning of the karst aquifer. The distribution of EC enabled the identification of the different origins of the water discharging into the site, lower EC content being associated with discharges of shorter residence time with HCO₃⁻ composition, and noting the existence of a base flow that would correspond to a groundwater flow with a longer trajectory that shows an increase in EC and SO₄²⁻ type water. Groundwater flows related to local and intermediate flow systems are then defined, with evidence of the presence of regional flows that probably ascend through karst conduits that at some point mix and give rise to Ca-mix type waters. The above considerations were confirmed by geochemical modeling, confirming the dissolution processes associated with karst aquifers, which are the processes that constitute the conduits that facilitate the passage of groundwater. The isotopic data enabled us to identify the recharge zones and to determine that the recharge zone comes from the mountain areas of Río Verde.

The study highlights the significance of temporal analysis in karst areas, enabling us to discern the reaction of springs and streams to climate and anthropogenic changes occurring at the location. The information generated is crucial to improve our understanding of the relationship between hydrogeological and ecological processes that take place in karst systems, with the objective of refining management strategies for the conservation and preservation of karst groundwater, particularly in ecosystems dependent on its discharge, such as the study area.

Supplementary Information The online version contains supplementary material available on request.

Author contribution

Cynthia Del Carmen Cordova Molina: Conceptualization, Investigation, Formal analysis, Data curation, Visualization, Writing – original draft, Writing – review & editing.

Octavio Ortiz Enriquez: Investigation, Conceptualization, Data curation, Formal analysis.

Ma. Catalina Alfaro-De la Torre: Writing – review & editing, Writing – original draft, Resource, Funding acquisition, Project administration, Investigation, Supervision.

Juan Antonio Reyes Agüero: Writing – review & editing, Writing – original draft, Investigation, Supervision.

Antonio Cardona Benavides: Writing – review & editing, Writing – original draft, Resource, Funding acquisition, Project administration, Investigation, Supervision, Visualization, Conceptualization.

Funding This work was supported by the Consejo Nacional de Humanidades, Ciencias y Tecnologías, CONAHCYT, through project A1-S-27598 Evolution of the eutrophication process and environmental alteration affecting the RAMSAR site Ciénaga de Tamasopo (SLP) as a basis for proposing its integral management led by Ma. Catalina Alfaro-De la Torre and Doctoral fellowship (466139) for Cynthia Del Carmen Cordova Molina, and Master fellowship (1078421) for Octavio Ortiz Enriquez.

Data availability The datasets used and analysed during the current study are available from the corresponding author on reasonable request.

Acknowledgements

This work was supported by the Consejo Nacional de Humanidades, Ciencias y Tecnologías, CONAHCYT, through project A1-S-27598 Evolution of the eutrophication process and environmental alteration affecting the RAMSAR site Ciénaga de Tamasopo (SLP) as a basis for proposing its integral management led by Ma. Catalina Alfaro-De la Torre and Doctoral fellowship (466139) for Cynthia Del Carmen Cordova Molina, and Master fellowship (1078421) for Octavio Ortiz Enriquez.Special thanks to Dr. M. García and Eng. M. Cortina for the chemical analysis of the water in the laboratories of the Universidad Autónoma de San Luis Potosí, M.Sc. S. Alonso, Dr. I. Montes, M.Sc. H. González for their collaboration in the field work, M.Sc. A. Gardea for their helpful advice on the editing of Fig. 1 and design of Fig. 2. and Dr. C. Ilizaliturri for their support and advice on data analysis.

Ethics approval The study does not need ethical approval.

Consent to participate Not applicable.

Consent to publish All authors read, approved, and provided their consent on the publication of the final version of this manuscript.

Competing interests The authors declare no competing interests.

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Temporal hydrogeochemical evolution of karst groundwater discharging into a continental-type Ramsar site in the Huasteca Potosina, Mexico

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Abstract

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Highlights

Introduction

Geology and Hydrogeology Setting

Geographical Conditions

Geological and hydrogeological features

Environmental problems

Methodology

Sample collection and chemical analysis

Data analysis

Results

Temporal variation of groundwater chemistry

Physicochemical parameters

Major ions

Hydrogeochemical processes

Geochemical modelling

Stable isotopes

Seasonal variation

Principal Component Analysis

Hierarchical cluster analysis (HCA)

Discussion

Hydrogeochemical conceptual model

Local flow system

Intermediate and regional flow systems

Conclusions

Declarations

References

Supplementary Files

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