Hydrogeochemical Signatures and Processes Influencing Mineral Waters at Furnas Volcano (São Miguel, Azores)

Abstract

Furnas volcano, one of the three active central volcanoes of São Miguel (the Azores archipelago), hosts mineral waters with significant special variations, divided into hyperthermal (89.4–95.4 °C), thermal (29.9–70.0 °C), and cold (14.2–21.4 °C) waters. Groundwaters are classified as Na-HCO₃, with a neutral to slightly acidic pH, except one SO₄-Na acidic sample. The major elements are primarily influenced by rock leaching and volcanic input, patterns also reflected in the trace elements, including the rare earth elements. The major cations, along with lithium, iron, aluminum, rubidium, and strontium, indicate the influence of water–rock interactions. Some samples depict a higher influence in this input, shown by the similar REE behavior between them and the local rock behavior. The volcanic input is distinguished into two environments: an acid sulfate boiling pool, formed by steam heating, and neutral HCO₃-Cl waters, where bicarbonate-rich waters mix with a neutral chloride fluid from a deep reservoir. The deeper reservoir also provides boron, arsenic, antimony, and tungsten, also seemingly associated with a positive spike in europium due to rock dissolution at temperatures above 250 °C or a reducing environment. This interpretation is corroborated by the stability of the strontium isotopes between samples.

1. Introduction

Understanding the geochemical processes at play in water chemistry in active volcanic environments is crucial, as it helps to monitor volcanic systems [1,2,3,4] as well as detect groundwater contamination due to the intrusion of geothermal waters in shallow aquifers [5,6]. When a groundwater system is heated by an underlying heat source, it is designated as a hydrothermal system or as a volcanic hydrothermal system if related to a volcano [7,8,9]. Components degassed from magmas flow continuously from active volcanoes, affecting the fluid chemistry. The degassing comprises the volcanic flux from fumaroles to the atmosphere, the diffusion of emissions through volcanic soils, the hydrothermal flux into local surface and groundwater bodies, and components retained in hydrothermal reaction products [10,11,12].

In a volcanic hydrothermal system, the hydrothermal manifestations may originate from fluids released at a depth over the magma body and/or from acid waters produced when shallow groundwater absorbs the ascending volcanic vapor [10,11,12]. Volcanogenic acids, such as H₂SO₄, HCl, H₂CO₃, and HF, act as sources of protons in solution and enhance the dissolved loads of chemical elements. Thus, they may be responsible for a substantial part of the chemical weathering fluxes in active volcanic hydrothermal systems [13,14,15,16]. These gases have the potential to create extreme conditions in which weathering processes and the resulting geochemical mobility of major and trace elements are deeply modified [17]. In addition, there are other modifying processes that affect groundwater, such as dissolution–precipitation, ionic exchange, and redox reactions, which can make the evaluation of the processes involved in the chemistry of the waters even more difficult [18].

Aquifers hosted in volcanic rocks exhibit a wide range of chemical, mineralogic, structural, and hydraulic properties, leading to highly variable groundwater chemistry [19,20,21]. This variability is largely dependent on the type of rock, which in this case is primarily composed of silicate minerals, as well as their stability [20,21]. The weathering and dissolution of aluminosilicate minerals play a pivotal role in altering the hydrogeochemistry along the groundwater flow path [21]. The elements mobility will depend on the physico-chemical conditions during the weathering processes [22], which can be highly influenced by the volcanic components. In general, the volcanic hydrothermal fluids are a result of the magmatic gas inputs, weathering reactions involving the host rock, and physical processes, such as evaporation and condensation [7]. Due to its complexity, is important to use several tools to try to understand the processes involved in these systems, such as trace elements, rare earth elements (REEs) and isotopes (e.g., ⁸⁷Sr/⁸⁶Sr).

Trace elements, although present in lower concentrations, play a significant role in hydrosystems [23]. Trace elements are more fractionated by weathering and transport processes than major elements, providing clues for understanding the nature and intensity of those processes [23]. Besides that, there is a considerable amount of evidence that volcanic emissions significantly contribute to the natural cycling of trace elements in the uppermost geochemical spheres [24,25]. Volcanic gases can be an important source of metals to groundwaters, and their dissolution produces hot acidic reducing environments, leading to more efficient rock leaching and the release of trace metals into the weathering solution [24]. Among trace elements, rare earth elements (REEs) can be used as powerful markers of fundamental geochemical processes [25,26] due to their potential as sensitive tracers. They are widely applied in groundwater flow tracing [27,28,29,30], weathering processes, and environmental studies [31].

Strontium isotope ratios are commonly used as natural tracers in studies of water–rock interactions as well as in evaluating mixing processes [32], since Sr isotopes only fractionate slightly in geological environments [33,34,35,36]. Strontium isotope ratios in waters are controlled by variations in initial (atmospheric) inputs, differences in mineralogy and mineral dissolution along flow paths, and residence time. Consequently, the ⁸⁷Sr/⁸⁶Sr ratio in waters will reflect the ‘‘weatherable Sr” and the efficiency of exchange [35,37].

Mineral water manifestations spread across the Azores archipelago have been the focus of several studies, for example [38,39,40], with particular emphasis on São Miguel island [41,42], where about 75% of the archipelago discharges occur [38]. These scientific contributions try to characterize the chemistry of the mineral waters in order to fully assess any modifications that can possibly occur, namely, the effects of any stress changes associated with volcanic activity [38] or anthropogenic pressures [39]. However, trace elements, including the rare earth elements and strontium isotopes, have been overlooked, and this study aims to address this gap by providing a comprehensive understanding of the chemical complexity of these waters and identifying the main factors influencing their composition.

2. Characterization of the Study Area

2.1. Geological Setting

The Azores archipelago consists of nine islands and several islets of volcanic origin, located in the North Atlantic Ocean, spread along a WSW-to-ENE-trending lineament, between latitudes 37 °N and 40 °N (Figure 1a). The Azores archipelago is located close to the Middle Atlantic Ridge (MAR), near the triple junction between the Eurasian, the Nubian (African), and the American plates [43]. São Miguel island geology is dominated by three active central volcanoes [44], so called Sete Cidades, Furnas, and Fogo (Figure 1b).

Furnas volcano displays a nested caldera complex at its summit, which is roughly elliptical. The older (outer) caldera is approximately 8 by 5 km in diameter, with maximum width along an NE–SW direction. Enclosed within the older caldera, the inner caldera (6 × 3.5 km) intersects the outer one [45,46]. Within the caldera lie numerous craters, domes, maars, and pumice cones [45,46], with part of its floor occupied by a lake (1.87 km²) [47]. The volcano’s fault system exhibits WNW–ESE, NE–SW, N–S and NNW–SSE trends, manifested by volcanic alignments, linear valleys, and caldera outlines [48].

Furnas stratigraphy is divided into three groups: Lower (LFG), Middle (MFG) and Upper (UFG) Furnas Group [45]. The LFG and MFG comprise numerous trachytic pyroclastic units, with minor trachytic domes and basaltic cones [49], while the UFG comprises at least ten intra-caldera sub-plinian eruptions of trachytic pumice [46,50]. A petrogenetic study by [51] revealed that UFG pumice fall deposits are composed of alkali feldspar (~67 vol%), Fe-Ti oxides (~20 vol%), biotite (~10 vol%), clinopyroxene (~3 vol%), and apatite (accessory). The lava dome associated with Furnas I and J show similar mineral assemblages. Rare syenitic xenoliths appear in the pyroclastic surge units of Furnas J eruption and are dominated by cumulus alkali feldspar, and intercumulus phases include clinopyroxene, amphibole, Ti-magnetite, ilmenite, biotite, pyrrhotite, and rare zircon. A rare earth element analysis of UFG reveals a relatively uniform enrichment in LREEs relative to HREEs, with a pronounced negative Eu anomaly [51]. The results suggest that the trachyte primarily originate from extended fractional crystallization of alkali basalt parental magmas, occurring at depths between ~3 and 4 km [51]. These depths are in agreement with the depth of degassing recently defined by [52] that estimated a degassing source at depths higher than 2.5 km.

2.2. Furnas Hydrothermal Manifestations

Furnas volcano exhibits diverse types of secondary manifestations of volcanism, including boiling temperature fumaroles (95–100 °C), steaming ground, thermal springs, cold CO₂-rich springs, and diffuse CO₂ degassing areas [53]. Furnas is recognized as showing the most vigorous degassing areas in the archipelago [53], emitting fumarolic gas mainly composed of water vapor (steam) and CO₂, with smaller amounts of H₂S, H₂, N₂, O₂, CH₄, and Ar present in lower concentrations [54]. Most of the hydrothermal manifestations are located within the caldera, including Furnas Village, Furnas Lake, and Ribeira dos Tambores fumarolic fields. A fourth fumarolic field lies on the southern flank of the caldera, where multiple gas emissions are observed along the Ribeira Quente valley and at Ribeira Quente Village [53,54,55]. Main hydrothermal fumaroles and diffuse degassing anomalies occur along observed and inferred tectonic structures at Furnas volcano [55]. The equilibrium temperatures associated with the Furnas hydrothermal fumaroles range from 200 °C to 275 °C [54]. Geophysical studies carried out by [56] identified two conductivity zones (~100 m and 500 m depth) below Furnas Lake area, which were interpreted as resulting from the presence of aqueous fluids near boiling point at 500 m depth, with inferred temperatures of at least 250 °C, and should represent a broader extent of the Furnas hydrothermal system within the caldera. The shallowest conductivity zone, which is approximately 100 m beneath the surface, should correspond to a steam-dominated layer.

¹³C of the CO₂ released from Furnas fumarolic fluids indicates a mantellic origin, while ¹⁵N, ³⁶Ar, ⁴⁰Ar, and ⁴He compositions suggest a combination of a more crustal component and a magmatic component of mantle origin [54]. The volcanic soils at Furnas release approximately 968 t·d⁻¹ of diffuse CO₂ [53]. Gas fluxes from the hydrothermal fumaroles at Furnas Village and the north shore of Furnas Lake were studied by [57], which estimated a total CO₂ flux of 50 t·d⁻¹ and approximately 0.25 t·d⁻¹ of H₂S. Another significant pathway for CO₂ release is Furnas Lake, with a surface output estimated between approximately 52 and 600 t·d⁻¹ during early autumn and winter, respectively [47].

2.3. Hydrogeological Settings

In São Miguel, the average annual precipitation is 1722 mm·yr⁻¹, generally higher in the east sector and north flank of the island when compared with the south flank, and increases with altitude [58,59]. The rainy season (between October and March) accounts for approximately 75% of the annual precipitation, with the lowest rainfall occurring in July [60].

The groundwater from Azores islands is represented by two major aquifer systems: (1) basal aquifer systems, consisting of freshwater lenses floating over underlying seawater, and (2) perched water bodies that are confined by impermeable to very-low-permeability layers [40]. The aquifers occur mainly in fresh or weathered basaltic flows, with higher permeability in clinker levels, or coarse pyroclastic fall deposits [40]. The specific well capacity in São Miguel island is in the range of 0.49 to 100 L·s⁻¹·m (mean = 1.1 L·s⁻¹·m), and the transmissivity is in the range of 6 × 10⁻⁴–1.2 × 10⁻¹ m²·s⁻¹ (mean = 1.4 × 10⁻³ m²·s⁻¹) [39].

The composition of mineral water discharges in the Azores islands are a result of several hydrogeochemical processes: the evolution of deep hydrothermal fluids, incorporation of magmatic volatiles, steam heating of perched aquifers, and mixing of deep fluids with marine or near-surface hydrothermal fluids [38]. In São Miguel, the mineral waters are mainly located in Furnas and Fogo central volcanoes, being classified as Na-HCO₃, Na-Cl, and Na-SO₄ types [41]. The stable isotope composition (δ³⁴S_SO4, δ³⁴O_SO4, and δ¹³C_TDIC) of these waters indicates the composition result of several individual processes, namely, evaporation, the uptake of volcanogenic sulfur and carbon dioxide, the leaching of local volcanic rocks, and biological activity [41]. Ref. [61] developed a hydrogeological model of waters from Furnas volcano, based on their chemical composition. Cold waters primarily flow from below the caldera walls towards the northwest, while thermal and carbonated waters emerge along geological lineaments. The hydrothermal waters of Furnas are heated to approximately 160 °C in shallow aquifers (100–200 m), likely due to remnants of past volcanism beneath the caldera. The low pH of carbonated waters enhances rock leaching, contributing to significant dissolved solid fluxes. The study also notes the stability in the aquifers, suggesting a steady system, making Furnas waters ideal for the long-term monitoring of compositional changes.

3. Sampling and Analytical Techniques

A total of 39 mineral water springs discharging from perched water bodies in Furnas volcano (Figure 2) were collected every two months between December 2021 and December 2022. Besides that, two samples of soil pore water in the unsaturated zone (Figure 2a) were also collected using a MacroRhizon soil moisture sampler (Rhizosphere research products, The Netherlands). These capsules were installed in two different environments: one in the Furnas Lake area, where some of the higher values of CO₂ degassing are observed, and the second one near the Furnas football field, where lower values degassing are observed. The capsule in the Furnas Lake area was installed at a 0.5 m depth, while the one in the football field was installed at a 1.5 m depth. Both soil water samples were collected in sites not affected by nutrient inputs, as agriculture activity may affect soil water composition in the Azores archipelago [62].

Temperature, pH, electrical conductivity (EC), and oxidation–reduction potential (ORP) measurements were conducted in the field with specific portable equipment (WTW pH/Cond 340i/ORP T-900, WTW, London, England). Alkalinity and CO₂ titrations were also performed in the field, using well-described routine methods [63]. Alkalinity was determined by adding 0.05 M H₂SO₄ to a 100 mL aliquot until a pH of 4.4 was achieved, at which point the titrant volume was multiplied by 50. Carbon dioxide titrations were performed by adding NaOH (1/44 M) to a 100 mL aliquot until the pH reached 8.3 and then multiplying the final titrant volume by 10 [63]. After collection, the samples were filtered through a 0.45 μm cellulose membrane and divided into three aliquots, two of which were acidified with Suprapur^® nitric acid.

Ion chromatography (IC; Dionex integration HPIC thermo scientific, Thermo Fisher Scientific Inc., Massachusetts, USA) was applied to determine anions (Cl⁻, SO₄²⁻) of the non-acidified aliquot. The acidified samples were used to quantify the cations (Na⁺, K⁺, Ca²⁺, and Mg²⁺) and minor/trace elements (including REEs) by inductively coupled plasma mass spectrometry (ICP-MS; Agilent Technologies 7700 Series, Agilent Technologies, California, USA) at the Department of Geosciences of the University of Aveiro and to determine the ⁸⁶Sr/⁸⁷Sr isotopic ratios by thermal ionization mass spectrometry (TIMS; VG Micromass Sector 54, Micromass Ldt., Manchester, UK) at the Laboratory of Isotopic Geology of the University of Aveiro.

Rare earth elements are known to be sensitive elements, and their determination can be challenging in samples with high Ba [64], which can be the case in hydrothermal systems. Samples with high Ba/Eu (>10,000) can result in substantial positive Eu anomalies, which can potentially lead to some misinterpretation [65]. However, some studies show that spectrometers equipped with a collision/reaction cell, such as the ICP-MS used in this study, can be strategical for partial or total elimination of the polyatomic interferences [64,66]. Additionally, some studies indicate samples filtered with a 0.45 μm cellulose membrane can still have some small colloid particles [67], and this consideration will be incorporated in the interpretation of the results. The obtained data required normalization, by dividing the values in mg·L⁻¹ by the values of the chondrite from [68].

4. Results and Discussion

4.1. General Hydrogeochemical Characterization

Descriptive statistics for major ion hydrogeochemical data are presented in

Table A1. Physico-chemical parameters and chemical composition of the water samples.

Ref.	Sample Location (Designation)	Type	Statistical Parameter	T	pH	Eh	Cond.	CO2	HCO3−	Cl−	SO42−	Na+	Mg2+	K+	Ca2+
				°C		V	µS·cm−1	mg·L−1
Detection Limit										0.5	1	0.1	0.05	0.05	0.1
LF1	Caldeira da Lagoa das Furnas	Hyperthermal	Min	87.4	3.3	0.209	576.0	5.0	28.1	18.8	20.2	97.0	2.1	20.1	11.4
			Max	91.5	5.3		928.0	108.6	32.9	49.7	119.1	119.2	4.5	24.6	20.8
			Mean	89.4	4.1		768.1	50.2	30.5	34.4	70.7	105.2	3.1	22.7	14.2
			Median	89.1	3.8		795.0	23.6	30.5	35.5	62.4	101.9	3.0	22.7	13.5
LF2	Nascente da Ponte	Cold	Min	20.6	5.2	0.187	359.0	581.8	160.4	19.2	3.8	50.4	3.1	26.6	9.0
			Max	22.1	5.7		379.0	787.8	350.1	26.6	32.7	65.9	3.8	31.2	12.7
			Mean	21.0	5.5		366.0	653.4	245.1	22.9	14.7	55.8	3.4	28.5	10.5
			Median	20.8	5.4		364.0	644.6	259.3	22.4	11.5	53.6	3.4	27.8	10.3
LF3	Miguel Henriques	Cold	Min	20.4	5.2	0.212	355.0	407.6	148.8	19.9	3.8	51.0	3.2	26.9	9.4
			Max	21.1	5.5		376.0	736.1	243.4	25.6	17.3	66.1	3.8	31.4	11.9
			Mean	20.7	5.4		364.6	556.7	191.8	22.1	10.3	57.1	3.3	29.2	10.4
			Median	20.7	5.4		366.0	567.9	188.5	22.4	9.6	54.9	3.2	29.0	9.9
LF4	Água da Prata	Cold	Min	20.6	5.0	0.322	322.0	539.8	102.5	19.5	6.5	40.9	3.0	23.5	9.0
			Max	23.0	5.3		337.0	836.6	237.3	39.1	23.1	53.0	3.7	27.5	11.8
			Mean	21.4	5.1		328.4	669.9	134.3	25.2	16.7	45.4	3.2	25.4	10.4
			Median	21.2	5.1		329.0	618.8	119.6	23.8	16.3	43.5	3.0	25.5	10.6
LF5	Caldeirão	Thermal	Min	72.1	6.0	0.091	446.0	61.2	226.9	29.1	3.8	70.4	3.7	15.9	8.8
			Max	75.1	6.3		468.0	188.8	325.1	36.2	23.1	91.2	4.6	18.4	12.5
			Mean	73.0	6.1		455.3	108.0	253.2	32.7	9.4	78.9	4.0	17.1	10.0
			Median	72.8	6.1		454.0	84.3	242.8	32.7	6.7	76.6	3.9	17.2	9.5
LF6	Água da Prata 2	Cold	Min	15.8	4.7	0.345	176.0	549.7	119.6	18.5	3.4	30.8	3.5	18.5	7.5
			Max	20.2	5.5		279.0	911.0	503.9	22.0	25.0	39.9	4.1	21.5	9.4
			Mean	16.6	5.1		261.7	716.0	200.2	19.9	9.7	34.4	3.7	19.9	8.2
			Median	16.1	5.1		276.0	722.1	156.2	19.2	7.7	32.8	3.6	19.8	7.9
LF7	Azeda do Rebentão	Cold	Min	15.6	5.0	0.356	270.0	80.5	112.9	19.5	2.6	30.7	3.6	18.1	7.5
			Max	16.2	5.2		280.0	1105.0	298.9	22.4	19.2	40.1	4.4	21.6	9.7
			Mean	15.9	5.1		276.9	820.5	158.2	20.9	10.5	34.1	3.8	19.6	8.2
			Median	16.0	5.1		279.0	915.0	132.4	20.9	11.5	32.4	3.7	19.7	8.0
LF8	Água Santa	Hyperthermal	Min	86.4	7.0	−0.051	720.0	12.2	333.7	54.0	6.7	144.0	0.6	18.2	5.2
			Max	95.5	7.5		850.0	62.1	500.2	69.9	23.1	210.5	1.0	21.6	8.5
			Mean	91.9	7.3		772.1	45.7	396.2	60.0	13.2	172.2	0.9	19.6	6.7
			Median	93.2	7.3		772.0	51.3	402.6	58.9	11.5	166.7	0.9	19.4	6.6
LF9	Água da Prata 3	Cold	Min	16.3	5.0	0.248	294.0	462.8	103.7	18.1	4.2	33.7	3.4	20.1	8.0
			Max	20.5	5.3		301.0	818.1	203.1	23.4	20.2	43.9	4.7	23.9	11.2
			Mean	17.9	5.2		296.7	598.3	147.0	20.7	12.8	37.1	4.0	21.8	9.5
			Median	17.9	5.2		296.0	567.7	157.4	20.6	13.4	35.1	4.1	21.4	9.1
LF10	Azeda	Cold	Min	16.2	5.0	0.310	275.0	861.1	129.3	18.5	3.8	30.1	3.7	17.6	7.7
			Max	17.2	5.7		288.0	1085.0	190.3	21.3	16.3	38.6	4.4	21.1	9.8
			Mean	16.4	5.2		279.1	961.4	159.7	19.9	8.2	33.3	4.0	19.5	8.7
			Median	16.3	5.1		278.0	931.2	160.4	19.2	6.7	31.7	3.9	19.3	8.3
LF11	Tio José de Sousa 1	Cold	Min	16.3	5.2	0.241	303.0	243.4	70.8	21.3	2.8	40.2	2.2	21.8	6.4
			Max	18.4	5.9		315.0	556.2	151.3	24.9	19.2	50.6	2.7	25.8	8.0
			Mean	17.0	5.4		307.7	399.2	100.4	22.9	11.0	44.0	2.4	23.4	7.1
			Median	16.7	5.3		308.0	406.5	98.2	22.7	10.6	42.1	2.3	23.2	6.8
LF12	Tio José de Sousa 2	Cold	Min	15.4	5.1	-	274.0	518.0	92.1	20.6	2.6	33.2	3.2	18.1	6.6
			Max	16.2	5.9		282.0	927.1	136.6	23.8	15.4	41.5	4.0	23.5	8.6
			Mean	15.8	5.4		278.6	700.5	118.0	22.0	10.1	36.8	3.6	20.4	7.7
			Median	15.7	5.4		279.0	717.4	124.4	21.7	10.6	37.6	3.5	19.8	7.9
LF13	Tio José de Sousa 3	Cold	Min	15.4	5.1	-	275.0	410.2	81.1	19.9	2.6	32.8	3.3	18.2	6.9
			Max	16.2	5.7		298.0	932.8	141.5	23.1	16.3	41.4	3.9	22.0	13.3
			Mean	15.8	5.4		280.7	727.8	112.7	21.2	10.0	36.2	3.7	20.3	8.5
			Median	15.7	5.2		278.0	748.6	113.5	21.3	9.6	35.8	3.6	20.1	8.0
LF14	Água do Rêgo	Cold	Min	15.9	5.0	0.473	283.0	509.6	107.4	20.2	2.9	34.8	3.1	19.4	7.4
			Max	16.8	5.3		289.0	896.7	231.8	23.8	18.3	44.1	3.7	22.8	9.1
			Mean	16.3	5.2		285.1	664.4	156.2	21.4	8.9	38.9	3.4	21.3	8.4
			Median	16.2	5.2		285.0	690.2	123.2	20.6	8.6	37.8	3.6	21.4	8.6
LF15	Caldeira dos Inhames	Thermal	Min	59.8	5.4	0.192	225.0	49.4	56.7	19.2	13.4	30.6	4.2	16.7	8.6
			Max	63.8	6.0		274.0	131.6	175.7	60.4	32.7	39.9	6.1	19.6	16.8
			Mean	61.8	5.6		255.3	87.4	104.7	34.1	23.5	33.9	4.9	18.1	11.3
			Median	62.4	5.6		257.0	86.3	79.9	20.2	23.1	33.7	4.7	17.8	11.4
LF16	Caldeira dos Vimes	Cold	Min	17.5	5.2	0.250	264.0	237.6	109.8	19.2	3.8	31.4	3.4	16.9	6.8
			Max	24.3	5.5		270.0	467.9	162.9	53.3	15.4	40.9	4.3	21.1	14.0
			Mean	20.2	5.4		268.0	332.5	135.3	28.9	11.9	35.2	3.8	19.0	9.4
			Median	20.3	5.4		269.0	291.8	130.5	19.9	11.5	33.1	3.8	19.1	8.4
LF17	Caldeira do Esguicho	Hyperthermal	Min	93.1	7.5	−0.152	1574.0	23.9	630.7	42.6	10.6	345.4	0.2	18.1	1.6
			Max	96.5	7.9		1686.0	65.1	805.8	220.1	38.4	440.4	3.3	58.5	5.5
			Mean	95.4	7.6		1631.6	41.3	696.5	127.7	21.3	371.5	1.6	28.8	3.0
			Median	95.6	7.7		1628.0	35.8	672.8	141.3	19.2	359.4	1.4	20.0	2.6
LF18	Caldeira Asmodeu	Hyperthermal	Min	88.8	7.1	−0.192	2180.0	25.8	546.6	237.9	21.1	458.6	0.2	21.1	1.2
			Max	92.6	7.3		2350.0	76.6	690.5	305.3	92.2	593.4	0.9	25.2	30.9
			Mean	90.8	7.2		2245.7	52.2	637.2	270.4	65.6	514.3	0.4	23.2	6.0
			Median	91.3	7.2		2220.0	50.7	639.3	266.3	67.2	508.4	0.2	23.4	1.6
LF19	Caldeira Grande	Hyperthermal	Min	84.7	7.3	−0.176	1767.0	1.7	610.6	30.9	6.7	428.9	0.1	19.2	1.6
			Max	96.3	8.2		2050.0	41.4	868.0	312.4	84.5	538.4	0.6	22.4	13.5
			Mean	89.5	7.9		1965.6	22.1	745.2	253.8	32.5	458.6	0.3	20.2	3.5
			Median	88.7	8.0		1989.0	23.1	749.7	287.6	23.1	442.6	0.2	19.9	1.9
LF20	Água Padre José	Thermal	Min	61.6	5.9	0.123	694.0	82.0	303.8	32.3	5.8	108.0	5.1	36.5	13.3
			Max	62.8	6.3		729.0	195.6	503.3	67.5	38.4	132.3	5.9	42.5	15.7
			Mean	62.3	6.1		714.0	153.0	379.6	39.2	20.3	121.6	5.5	40.2	14.7
			Median	62.3	6.0		716.0	161.0	357.5	34.4	17.3	122.3	5.5	40.8	14.8
LF21	Poça da Dona Beija	Thermal	Min	38.3	5.7	0.119	418.0	122.6	196.4	61.8	3.8	70.6	5.9	15.7	11.2
			Max	40.2	6.0		542.0	360.0	224.5	85.2	30.7	83.1	6.4	17.8	12.4
			Mean	38.9	5.8		501.3	243.7	206.2	67.5	11.8	75.0	6.2	16.8	11.7
			Median	38.6	5.8		526.0	256.5	201.3	63.9	7.7	75.3	6.3	16.7	11.7
LF22	Dr. Bruno	Cold	Min	17.7	6.0	0.428	375.0	185.3	218.0	25.9	0.6	58.4	7.5	16.9	17.1
			Max	21.5	6.3		430.0	236.5	332.5	29.8	8.6	68.5	9.7	21.2	21.9
			Mean	19.8	6.1		401.9	212.4	261.2	27.6	5.7	63.8	8.4	19.0	19.4
			Median	19.7	6.1		405.0	221.2	248.9	26.6	7.7	62.4	8.0	19.0	19.3
LF23	Banhos Férreos I	Thermal	Min	37.2	6.2	0.222	1576.0	312.1	880.8	55.4	5.8	258.5	34.0	43.4	49.4
			Max	38.6	6.3		1588.0	439.1	1213.3	58.6	61.5	298.1	39.7	50.8	57.1
			Mean	37.5	6.2		1581.8	363.6	1074.7	56.7	21.1	275.9	36.2	46.8	53.0
			Median	37.2	6.2		1582.0	347.0	1146.0	56.8	11.5	276.4	36.0	46.5	53.3
LF24	Banhos Férreos II	Thermal	Min	32.6	6.5	-	1449.0	220.5	1011.4	81.7	46.1	264.7	35.3	48.5	56.2
			Max	32.6	6.5		1449.0	220.5	1011.4	81.7	46.1	264.7	35.3	48.5	56.2
			Mean	32.6	6.5		1449.0	220.5	1011.4	81.7	46.1	264.7	35.3	48.5	56.2
			Median	32.6	6.5		1449.0	220.5	1011.4	81.7	46.1	264.7	35.3	48.5	56.2
LF25	Banhos Férreos III	Thermal	Min	32.2	6.1	-	1410.0	118.3	823.5	50.4	6.1	250.6	30.4	41.4	46.3
			Max	37.0	6.7		1513.0	489.2	1099.2	57.9	9.6	274.5	32.7	47.4	56.4
			Mean	33.6	6.4		1449.3	249.6	945.8	54.2	7.8	260.6	31.8	43.3	50.1
			Median	32.6	6.4		1437.0	195.4	930.3	54.3	7.7	258.7	31.9	42.1	48.9
LF26	Água da Camarça	Cold	Min	14.4	5.7	-	184.0	11.2	76.9	16.3	0.9	21.5	4.5	8.3	5.4
			Max	17.0	7.2		189.0	52.3	131.8	142.0	7.7	295.8	17.5	40.1	37.6
			Mean	15.5	6.0		187.0	37.7	96.4	42.2	4.0	77.6	7.6	15.5	12.3
			Median	14.7	5.8		188.0	44.6	90.3	17.4	3.8	23.6	5.2	9.5	6.1
LF27	Poça da Tia Silvina	Thermal	Min	44.0	6.2	0.243	1416.0	68.9	706.4	88.8	5.8	251.9	17.0	39.0	36.0
			Max	45.2	6.5		1540.0	297.7	1032.7	134.9	23.1	314.7	19.1	44.2	40.5
			Mean	44.8	6.3		1464.7	194.2	870.6	97.5	13.2	284.7	17.9	41.5	38.1
			Median	45.0	6.3		1454.0	198.8	861.3	91.9	11.5	285.2	17.9	40.7	38.2
LF28	Morangueira	Thermal	Min	29.5	6.2	-	1611.0	44.0	23.1	92.3	7.7	298.8	19.3	43.7	40.8
			Max	35.7	6.9		1635.0	363.9	1051.0	131.4	23.1	348.6	20.7	49.1	46.3
			Mean	32.2	6.4		1620.6	248.7	783.1	99.7	12.6	323.4	20.1	46.2	43.4
			Median	31.9	6.4		1615.0	291.1	876.0	95.5	11.5	323.1	20.2	46.0	43.2
LF29	Quenturas I	Cold	Min	15.5	5.8	0.890	194.0	22.6	92.1	17.8	3.8	19.6	3.8	8.8	4.4
			Max	17.2	7.0		212.0	89.5	257.4	40.5	10.6	28.4	5.5	13.3	17.5
			Mean	16.3	6.2		204.4	57.1	166.8	21.8	6.3	25.2	5.0	11.6	7.2
			Median	16.1	6.0		205.0	50.2	126.9	18.8	5.8	25.9	5.2	12.3	5.7
LF30	Quenturas II	Thermal	Min	56.4	6.3	0.148	1294.0	124.6	681.4	66.7	7.6	98.0	5.5	17.5	12.0
			Max	58.1	6.5		1353.0	309.9	840.0	77.7	141.2	257.7	15.2	51.6	36.3
			Mean	57.2	6.4		1311.7	187.7	736.5	74.4	31.7	223.5	13.5	44.1	28.9
			Median	57.3	6.4		1308.0	191.1	703.3	74.6	15.4	240.9	14.9	47.6	30.2
LF31	Quenturas III	Thermal	Min	56.7	6.3	0.123	1310.0	137.2	14.6	73.5	5.8	90.5	5.0	16.2	11.2
			Max	58.2	6.8		1348.0	251.6	818.0	78.1	30.7	263.7	15.6	52.5	33.1
			Mean	57.5	6.4		1322.9	192.3	659.8	75.9	15.0	224.8	13.6	44.1	28.3
			Median	57.5	6.3		1316.0	187.5	744.8	76.3	15.4	246.1	14.8	47.1	30.4
LF32	Grutinha I	Thermal	Min	39.8	6.1	0.179	1474.0	36.6	766.8	85.6	5.8	276.2	14.9	35.1	31.1
			Max	45.4	6.5		1490.0	474.5	889.4	90.2	15.4	327.1	16.9	40.3	49.2
			Mean	41.0	6.2		1483.7	330.9	833.3	88.2	11.8	301.0	15.8	37.3	34.9
			Median	40.5	6.2		1486.0	369.8	836.3	88.0	11.5	300.5	15.8	37.1	32.6
LF33	Grutinha II	Thermal	Min	40.5	6.0	0.176	1196.0	147.2	729.6	76.0	5.8	225.2	12.1	33.4	26.1
			Max	43.9	6.4		1468.0	438.5	819.6	89.8	24.3	294.3	14.7	39.8	30.0
			Mean	41.7	6.1		1411.9	306.7	779.7	84.5	13.3	261.2	13.8	35.9	28.8
			Median	40.9	6.1		1445.0	315.7	780.2	86.6	14.9	257.9	14.0	35.6	29.2
LF34	Torno	Thermal	Min	38.9	6.1	0.180	1390.0	110.6	370.3	89.5	5.8	252.4	13.7	30.7	27.4
			Max	40.2	6.2		1421.0	476.8	870.5	93.0	19.2	306.9	15.5	34.1	30.0
			Mean	39.4	6.2		1409.7	238.0	744.3	90.8	12.8	284.0	14.5	31.9	28.7
			Median	39.3	6.2		1412.0	170.5	798.5	90.5	11.5	291.6	14.4	31.3	28.4
LF35	Nostra	Cold	Min	16.3	5.8	0.382	229.0	13.8	103.1	20.6	4.8	35.0	2.1	12.0	3.9
			Max	19.1	7.2		283.0	59.8	190.3	24.9	12.5	48.8	4.4	15.5	15.6
			Mean	18.0	6.5		261.5	38.0	138.5	22.7	7.5	45.2	2.9	13.6	6.6
			Median	18.0	6.4		264.5	38.1	126.3	22.7	7.2	46.8	2.6	13.6	4.9
LF36	Helena	Cold	Min	14.1	5.0	-	178.0	314.1	65.9	16.0	2.9	17.5	4.5	7.7	5.3
			Max	16.1	5.6		184.0	719.1	105.5	18.8	6.7	23.1	5.3	9.0	6.8
			Mean	15.2	5.3		180.8	438.8	80.8	17.2	4.6	20.1	4.8	8.3	6.3
			Median	15.5	5.1		181.0	399.9	78.1	17.0	3.8	20.5	4.7	8.3	6.6
LF37	Glória Patri	Cold	Min	14.1	6.3	0.384	199.0	9.0	84.2	17.4	3.8	21.7	4.1	9.7	4.8
			Max	14.8	7.5		219.0	99.3	100.0	20.6	6.7	26.4	5.5	12.9	6.3
			Mean	14.5	6.8		206.6	27.0	92.5	18.5	4.8	24.1	5.0	11.7	5.6
			Median	14.5	6.7		206.0	14.0	92.7	18.1	4.8	25.0	4.9	11.6	5.7
LF38	Estrada RQ	Thermal	Min	45.5	6.3	-	1398.0	61.4	576.5	150.2	8.6	117.6	10.4	15.2	36.4
			Max	46.3	6.5		1404.0	109.4	747.2	155.5	13.4	208.2	18.6	28.4	70.2
			Mean	45.9	6.4		1401.0	85.4	661.8	152.8	11.0	162.9	14.5	21.8	53.3
			Median	45.9	6.4		1401.0	85.4	661.8	152.8	11.0	162.9	14.5	21.8	53.3
LF39	Dizimo	Cold	Min	13.6	6.3	-	191.8	7.8	68.9	18.1	2.9	23.1	4.2	7.7	4.2
			Max	14.6	7.2		197.5	12.7	90.9	21.7	6.7	28.8	4.9	8.7	5.1
			Mean	14.3	6.6		194.3	11.2	83.7	19.8	4.8	26.1	4.4	8.2	4.6
			Median	14.4	6.5		194.9	11.7	87.5	19.9	4.8	26.2	4.3	8.2	4.5
CLag	Soil water, Furnas Lake	Interstitial water		19.9	5.9	-	84.3	-	-	5.3	1.8	8.6	0.4	20.0	0.6
CFut	Soil water, football field	Interstitial water		22.1	6.6	-	103.2	-	-	6.8	-	8.5	0.6	7.7	2.5

, showing a diverse range of chemical characteristics. Soil water depict low electric conductivity (EC), as well as a low contents of major elements (Table A1), reflecting their short residence time. Nevertheless, differences are observed between the two collected samples. The water collected in the lower degassing area (CFut) shows a higher EC and a slight increase in calcium, likely due to a minimal water–rock interactions once this was collected at a higher depth (1.5 m). Instead, the sample collected in the higher degassing area (CLag) has a lower pH and higher content in potassium, possibly due to an enrichment presented by the rainwater in this site, since the water was collected at a 0.5 m depth. Ref. [69] observed a similar lower pH and an enrichment regarding some major and minor elements in rainwater with proximity to the Furnas Village fumarolic field, which may also be inferred for the Furnas Lake fumarolic field.

Regarding the mean values of some physico-chemical parameters in groundwater, the temperature ranges between 14.2 and 95.4 °C, the EC ranges between 180.8 and 2245.7 µS·cm⁻¹, and the pH ranges between 4.1 and 7.9. Based on temperature differences, mineral waters can be classified as hyperthermal, thermal, and cold. Hyperthermal waters (LF1, LF8, LF17, LF18, LF19) were sampled at boiling pools, with the exception of Água Santa (LF8), the latter having mean temperatures that range from 89.4 to 95.4 °C. The pH values are approximately neutral (7.3 to 7.9) in the hyperthermal waters from Furnas Village and higher than the boiling pool located near the margin of Furnas Lake, which is acidic (mean pH of 4.1), while the EC values in this group of waters vary from 768.1 to 2245.7 µS·cm⁻¹. Thermal waters (LF5, LF15, LF20, LF21, LF23, LF24, LF25, LF27, LF28, LF30, LF31, LF32, LF33, LF34, LF38) have a slightly acidic pH (5.6 to 6.5) and a mean temperature ranging from 29.9 to 70.0 °C. Electrical conductivity values in thermal waters range between 255.3 and 1620.6 µS·cm⁻¹. Cold waters (LF2, LF3, LF4, LF6, LF7, LF9, LF10, LF11, LF12, LF13, LF14, LF16, LF22, LF26, LF29, LF35, LF36, LF37, LF39) show mean temperature values between 14.2 and 21.4 °C, EC values from 180.8 to 401.9 µS·cm⁻¹, and a slightly acidic pH (5.1 to 6.8). There are some cold waters that are CO₂-rich, reaching a maximum of 961.4 mg·L⁻¹ for dissolved CO₂.

The mineral waters’ major composition exhibits some seasonal variations, as suggested by the minimum and maximum values of the samples (Table A1). However, these variations show no significant variation with the years [61]. Based on that, average values were used for the data analysis, in order to assess the general groundwater composition. Groundwater in Furnas is mainly of the Na-HCO₃ type, with the exception of the boiling pool from Furnas Lake (LF1–Caldeira da Lagoa das Furnas), the only acidic water classified as Na-SO₄ type (Figure 3). The higher EC values and major ion content in groundwater, compared to soil water samples, suggest an evolution of groundwater chemistry since recharge by meteoric waters and along flow paths, consistent with the expected larger residence time in aquifers (Table A1). Mineral waters from Furnas volcano depict an enrichment in rock-forming elements (RFEs) that is particularly noticeable when compared to the seawater ratios of the main elements against sodium (Na⁺) (Figure 4a–d). This suggests the aquifer matrix rocks seem to have an important role in controlling the chemistry of these waters. Based on the main composition of the UFG [51], sodium and potassium are probably a result of the dissolution of the alkali feldspar, while calcium and magnesium are a result of minerals such as biotite (also with K⁺) and clinopyroxene. The hyperthermal waters show evidence of the incorporation of Ca²⁺ and Mg²⁺ in secondary minerals, as indicated by some precipitation processes shown by the lower Ca/Na and Mg/Na ratios (Figure 4b,c) and by the higher mineral saturation indices of minerals that incorporate these elements in the hyperthermal samples, as presented in Supplementary Materials. This is a result of the progress towards thermodynamic equilibrium for chemical species, such as Ca²⁺ and Mg²⁺, whose solubility products decrease with the increase in temperature. In contrast, potassium (K⁺) (Figure 4d) and Na+ tend to be dissolved with an increase in temperature and a decrease in pH [2]. The presence of secondary minerals like alunite and kaolinite in the calderas from Furnas Village and alunite, kaolinite, and smectite in Caldeira from Furnas Lake [70] confirms the presence of the precipitation processes.

Chloride behavior in the samples is variable, with the values varying from 17.2 mg·L⁻¹ (Helena—LF36) to 293.5 mg·L⁻¹ (Caldeira Grande—LF19) (Table A1). There is an enrichment observed in the hyperthermal waters from Furnas Village (Cl⁻ = 60—293.5 mg·L⁻¹) that is not explained by rock input, since the content of chloride in the rocks from Furnas is negligible [71], or by seawater intrusion, since the mineral waters discharge from perched aquifers. A plausible source is HCl, an acidic volcanic gas that is highly soluble in water, which condenses in shallow low-temperature zones of volcanic hydrothermal systems and is not released in the gas phase [7,72]. The deeply circulating fluid containing HCl is neutralized by the reaction with the rock and rises as a result of its decreased density, mainly via major fractures and faults in the volcanic edifice [73], mixing with the surface waters. The diagram of Li-Cl-B (Figure 4e) shows the relative content of Cl and B to be higher than that of Li, with most of the samples projecting closer to the Cl corner. However, the samples that exhibit an enrichment in chloride deviate from the pattern (LF5, LF8, LF17, LF18, and LF19), suggesting the absorption of high B/Cl steam. This projection seems to point towards an important degassing component in the water composition, as well as variations in Cl and B proportions in the steam influencing these samples.

For the case of SO₄²⁻, which is not present in rocks, it is possible to notice three different trends (Figure 4f): (a) a “seawater group” that depicts a SO₄/Cl ratio similar to that of seawater; (b) a group of waters that lie above the seawater SO₄/Cl ratio, comprising the majority of samples; and (c) some samples that present a lower SO₄/Cl ratio than the seawater. The higher SO₄/Cl ratio indicates an interaction between meteoric water and deep fluids with high sulfur content [8,73]. This phenomenon may be attributed to steam heating effects in shallow perched aquifers caused by deeper boiling aquifers, as suggested by [38]. The oxidation of H₂S to H₂SO₄ can explain the higher SO₄²⁻ content of the waters [38,74,75]. On the other hand, the projection of a few samples below the seawater line could be a result of the higher Cl⁻ concentration, not disregarding some precipitation processes, since alunite was identified in the calderas of Furnas Village.

Figure 4. Binary diagrams of (a) Cl vs. Na; (b) Na vs. Ca; (c) Na vs. Mg; (d) Na vs. K; and (e) Cl vs. SO₄. The seawater ratios were calculated based on the data from [76].

Figure 4. Binary diagrams of (a) Cl vs. Na; (b) Na vs. Ca; (c) Na vs. Mg; (d) Na vs. K; and (e) Cl vs. SO₄. The seawater ratios were calculated based on the data from [76].

4.2. Strontium and Strontium Isotope Ratios as Source Tracers

The concentration of strontium (Sr) in Furnas waters ranges from 5.81 to 538.53 µg·L⁻¹ (

Table A2. Trace element concentrations of the water samples.

Ref.	Name	Stat.	Li	Be	B	Al	P	V	Mn	Fe	Ni	Zn	As	Rb	Sr	Mo	Sb	Ba	W	Pb
			µg·L−1
Detection Limits			0.5	0.5	10	5.0	25	0.1	0.1	3	0.1	1	0.25	0.1	0.1	0.05	0.02	0.1	0.01	0.1
LF1	Caldeira da Lagoa das Furnas	Min	29.8	0.9	183.2	88.7	79.4	0.5	208.8	281.0	0.5	16.8	2.1	139.0	46.2	3.0	0.6	25.3	0.1	0.3
		Max	125.0	2.9	261.7	2674.6	422.8	4.3	486.2	3735.3	1.3	69.5	7.7	195.5	79.8	11.6	1.6	49.0	2.0	0.9
		Mean	87.6	2.0	221.2	1025.6	169.4	1.6	322.6	1928.4	0.9	33.9	3.5	177.8	57.7	5.5	1.0	37.8	0.6	0.5
		Median	105.4	2.0	217.7	673.1	121.4	1.6	284.9	1679.1	1.0	28.0	2.4	185.6	55.0	3.7	0.9	39.2	0.2	0.4
LF2	Nascente da Ponte	Min	14.4	2.7	19.4	526.6	93.3	0.1	796.7	5216.1	2.2	19.7	1.6	48.2	22.8	8.5	0.0	1.3	0.2	0.2
		Max	18.3	5.1	33.4	1026.6	153.8	1.8	1031.5	8449.6	2.7	37.3	2.2	52.1	65.9	10.8	0.1	1160.7	0.2	3.0
		Mean	16.7	3.6	29.4	688.4	115.7	0.5	873.0	5891.6	2.3	28.6	1.9	49.5	29.9	9.3	0.0	193.7	0.2	1.2
		Median	17.3	3.6	30.1	591.4	114.8	0.2	850.9	5503.0	2.3	26.8	2.0	49.1	24.1	9.2	0.0	8.2	0.2	0.7
LF3	Miguel Henrique	Min	14.4	2.7	20.7	539.3	91.1	0.1	827.5	5341.3	2.1	19.5	1.6	48.4	23.5	8.7	0.0	2.0	0.2	0.2
		Max	18.3	5.3	32.2	1081.2	118.6	0.7	904.8	7296.9	2.9	37.9	2.7	52.1	25.7	9.9	0.8	41.1	0.3	10.5
		Mean	15.9	3.5	26.5	662.8	109.2	0.3	855.2	5941.9	2.4	27.6	2.0	50.4	24.4	9.2	0.2	11.5	0.2	2.0
		Median	16.1	3.3	26.5	584.4	112.5	0.2	845.0	5598.7	2.4	26.5	1.9	49.8	24.3	9.2	0.0	5.2	0.2	0.6
LF4	Água da Prata	Min	8.4	2.2	14.9	755.2	61.7	0.1	536.0	3511.1	3.4	8.3	0.8	40.8	23.0	3.6	0.0	2.5	0.0	0.2
		Max	12.3	8.6	28.8	1660.4	99.4	0.5	723.7	4497.3	4.6	43.3	1.5	44.2	28.5	5.8	0.0	136.2	0.2	3.1
		Mean	10.0	3.9	22.9	999.6	78.0	0.3	610.6	3788.2	3.9	18.5	1.2	42.7	25.4	4.8	0.0	29.5	0.1	0.8
		Median	10.2	3.2	24.1	891.8	76.4	0.3	577.8	3709.2	3.8	11.2	1.3	42.4	25.4	4.8	0.0	7.8	0.0	0.4
LF5	Caldeirão	Min	33.1	1.5	755.1	104.0	144.4	0.1	922.7	304.9	0.2	2.8	18.3	63.7	24.0	0.1	0.1	3.1	3.2	0.3
		Max	40.8	3.2	911.4	800.1	263.5	0.5	1145.4	1563.1	0.7	43.9	27.3	68.4	27.3	0.3	0.7	125.7	4.4	0.9
		Mean	38.7	2.3	843.1	249.8	199.7	0.2	1003.8	794.8	0.5	17.4	22.5	65.4	25.8	0.2	0.3	41.0	4.0	0.6
		Median	40.0	2.5	841.9	176.4	196.4	0.2	943.1	600.6	0.5	13.4	22.5	65.2	25.3	0.2	0.2	30.3	4.2	0.5
LF6	Água da Prata 2	Min	6.9	2.3	24.1	802.9	112.9	0.1	563.3	5129.9	0.6	13.8	1.2	32.8	21.2	1.3	0.0	3.5	0.0	0.3
		Max	9.2	5.4	34.6	1200.3	166.7	0.6	805.6	6706.0	1.9	43.6	2.1	35.8	23.9	1.9	0.5	87.4	0.3	2.2
		Mean	7.8	3.7	28.4	971.4	136.4	0.4	663.2	5435.4	1.0	27.7	1.5	34.4	22.2	1.4	0.2	18.8	0.1	0.9
		Median	7.5	3.2	28.3	919.8	127.3	0.3	649.1	5231.5	1.0	27.7	1.5	34.3	21.5	1.3	0.0	8.0	0.1	0.7
LF7	Azeda do Rebentão	Min	6.6	2.1	17.8	721.1	135.1	0.2	539.8	5166.8	0.5	17.0	1.5	32.2	20.4	1.7	0.0	4.5	0.0	0.2
		Max	8.7	3.0	26.7	871.9	181.9	1.4	636.7	6073.6	1.5	29.1	7.7	35.0	22.7	2.0	0.3	18.1	0.7	1.0
		Mean	7.5	2.6	23.9	785.6	156.3	0.6	582.9	5587.8	0.8	23.4	2.5	33.4	21.4	1.8	0.1	8.1	0.2	0.7
		Median	7.3	2.7	25.6	764.1	157.9	0.7	581.1	5595.3	0.7	23.9	1.6	33.1	21.1	1.8	0.0	7.3	0.0	0.7
LF8	Água Santa	Min	63.2	0.9	2435.5	99.3	27.1	0.1	92.8	81.7	0.4	4.4	102.8	96.1	9.7	1.1	3.2	10.1	12.5	0.3
		Max	84.2	2.8	3328.8	827.3	74.4	0.9	367.1	1440.4	0.8	41.9	157.9	117.1	14.7	2.2	5.6	199.0	16.4	1.1
		Mean	72.6	2.0	2851.6	336.3	38.5	0.5	195.8	463.9	0.5	19.1	127.9	106.6	12.3	1.5	4.3	45.1	14.9	0.6
		Median	72.6	2.2	2827.1	302.5	31.0	0.5	197.1	271.4	0.5	14.3	123.2	109.4	11.9	1.3	4.3	13.6	15.1	0.7
LF9	Água da Prata 3	Min	7.6	2.3	25.5	761.9	62.5	0.2	591.4	2038.6	1.2	6.5	0.3	37.5	21.9	0.3	0.0	2.0	0.1	0.3
		Max	11.5	4.0	68.8	890.5	81.8	0.3	761.7	2775.9	2.4	24.2	0.8	41.3	25.7	0.6	0.1	95.1	0.1	1.1
		Mean	9.9	3.1	49.3	821.5	70.6	0.2	657.6	2357.6	1.8	13.6	0.4	39.2	24.1	0.5	0.0	17.4	0.1	0.6
		Median	10.1	3.0	59.4	823.5	72.8	0.2	632.7	2339.2	1.8	10.8	0.3	39.3	24.1	0.5	0.0	5.3	0.1	0.4
LF10	Azeda	Min	6.0	2.1	17.9	711.0	113.6	0.1	585.8	4823.4	0.4	19.4	0.8	39.0	22.4	0.5	0.0	3.0	0.0	0.4
		Max	8.3	3.2	36.7	933.7	144.9	1.0	752.0	6925.8	2.1	43.3	1.2	42.6	25.9	1.8	0.1	67.5	0.2	1.8
		Mean	6.9	2.6	30.7	814.9	131.5	0.3	662.6	5761.6	1.3	31.5	0.9	40.7	23.7	0.8	0.1	19.2	0.1	0.8
		Median	6.9	2.6	33.9	836.7	132.6	0.2	614.7	5617.9	1.1	33.3	0.8	41.1	23.1	0.6	0.0	9.9	0.1	0.7
LF11	Tio José de Sousa 1	Min	5.8	1.8	24.7	568.8	27.4	0.1	526.8	30.3	2.1	34.7	0.3	40.5	16.0	2.5	0.1	4.1	0.0	0.1
		Max	8.4	6.1	47.0	806.3	44.3	0.5	752.1	609.3	3.2	65.8	2.3	44.1	17.7	4.3	0.1	22.3	0.1	1.1
		Mean	7.2	2.8	36.0	665.6	36.3	0.2	609.9	239.2	2.6	45.2	0.7	42.0	16.8	3.7	0.1	7.9	0.0	0.5
		Median	7.5	2.1	38.0	640.1	36.7	0.2	600.3	158.7	2.5	43.0	0.4	42.0	16.5	4.0	0.1	5.5	0.0	0.4
LF12	Tio José de Sousa 2	Min	5.7	2.1	24.2	725.5	29.9	0.1	482.2	1495.6	0.3	14.3	0.3	38.0	19.1	1.7	0.0	2.9	0.0	0.1
		Max	7.6	3.2	30.4	953.6	69.0	0.6	676.5	4144.6	1.6	35.0	1.2	41.9	21.2	2.7	0.5	46.4	0.2	1.9
		Mean	6.5	2.7	27.3	820.5	46.5	0.3	535.4	2641.9	0.8	24.1	0.6	39.7	20.4	2.2	0.2	18.3	0.1	0.6
		Median	6.4	2.7	27.1	813.2	43.6	0.1	494.5	2238.0	0.7	21.5	0.6	39.5	20.5	2.2	0.1	13.9	0.0	0.5
LF13	Tio José de Sousa 3	Min	6.4	1.8	21.3	736.1	49.5	0.1	490.9	3245.0	0.4	14.1	1.4	38.8	20.1	2.7	0.0	1.8	0.1	0.2
		Max	8.3	4.4	29.8	1274.7	166.0	0.4	980.6	7831.4	2.1	36.4	2.9	40.7	26.7	4.2	0.1	12.2	0.3	4.6
		Mean	7.0	3.0	25.6	945.2	97.4	0.2	664.6	4776.8	1.0	23.5	2.1	40.0	21.6	3.4	0.0	7.6	0.1	1.3
		Median	6.8	2.6	25.8	871.1	82.9	0.2	674.2	3995.9	0.9	21.2	2.0	40.3	20.8	3.3	0.0	9.2	0.1	0.5
LF14	Água do Rêgo	Min	5.5	2.0	19.6	675.5	32.1	0.1	616.4	258.5	1.0	26.1	0.3	42.1	18.3	0.5	0.0	2.9	0.0	0.1
		Max	7.8	4.1	31.8	819.1	78.5	0.4	766.4	1868.8	2.0	40.1	4.2	45.0	20.9	0.6	0.1	192.7	0.1	0.6
		Mean	6.8	2.7	25.5	757.7	55.3	0.2	674.3	604.4	1.5	32.8	2.2	43.6	19.3	0.6	0.0	39.5	0.0	0.4
		Median	7.0	2.5	23.7	764.7	55.3	0.2	668.7	424.5	1.5	31.4	2.2	43.9	19.4	0.6	0.0	11.8	0.0	0.5
LF15	Caldeira dos Inhames	Min	6.3	1.8	14.5	175.2	29.4	0.1	728.9	1044.3	0.5	7.5	0.6	40.4	20.9	0.2	0.0	2.5	0.0	0.2
		Max	9.4	4.1	98.2	593.9	92.7	0.7	1896.7	1704.0	1.0	32.7	8.8	46.0	28.9	1.5	0.3	10.8	0.4	0.6
		Mean	7.2	2.9	30.5	258.9	59.2	0.3	1045.1	1436.5	0.7	13.7	2.1	43.7	24.4	0.6	0.1	7.0	0.1	0.4
		Median	6.8	2.8	18.3	214.0	57.4	0.2	938.0	1441.6	0.6	10.2	0.8	44.3	24.2	0.4	0.0	5.1	0.1	0.4
LF16	Caldeira dos Vimes	Min	5.7	1.9	17.9	501.9	55.7	0.1	566.7	3898.0	1.0	16.2	0.9	40.7	20.1	1.1	0.0	2.6	0.0	0.2
		Max	7.4	4.2	27.8	808.1	136.4	0.2	850.4	5555.8	3.4	40.8	3.2	44.6	27.2	2.6	0.1	41.0	0.2	1.1
		Mean	6.4	2.7	22.2	685.6	85.5	0.2	692.1	4514.7	1.5	29.4	1.4	42.7	22.4	1.5	0.0	13.6	0.1	0.5
		Median	6.2	2.5	22.0	724.0	82.4	0.2	657.8	4176.3	1.2	26.9	1.2	43.2	21.3	1.4	0.0	9.1	0.1	0.4
LF17	Caldeira do Esguicho	Min	131.4	1.3	8146.7	152.0	36.6	0.2	24.4	36.1	0.4	7.3	510.3	155.0	1.9	3.8	14.2	3.0	11.8	0.8
		Max	267.2	4.8	10,345.5	435.6	4479.0	0.6	353.3	651.9	4.3	43.0	616.9	286.7	11.7	12.2	20.1	95.7	51.6	3.9
		Mean	209.3	2.6	8899.2	281.0	2726.8	0.4	145.1	232.8	1.8	23.7	542.8	190.0	5.8	9.2	17.5	31.3	42.8	1.6
		Median	212.2	2.1	8856.4	249.7	3664.8	0.4	39.0	177.0	1.4	23.1	534.9	161.7	4.3	9.7	18.3	30.9	48.9	1.3
LF18	Caldeira Asmodeu	Min	162.9	2.6	11,754.7	224.7	53.5	0.4	24.6	29.3	0.6	6.3	1116.1	192.8	17.8	11.1	40.8	4.2	66.1	0.2
		Max	366.9	6.4	14,258.4	632.3	92.7	6.9	502.3	1988.8	3.2	49.1	1297.2	214.4	54.2	12.6	49.5	59.4	73.8	2.6
		Mean	275.1	4.4	12,559.3	411.8	73.1	1.5	171.4	865.3	1.2	20.0	1206.4	202.3	25.0	11.8	45.6	24.2	69.6	1.5
		Median	275.0	3.5	12,548.4	346.3	73.1	0.6	73.7	353.2	0.7	12.4	1213.9	200.2	21.2	11.5	45.2	17.5	68.2	1.3
LF19	Caldeira Grande	Min	140.7	2.6	13,733.0	162.2	69.6	0.7	21.4	34.6	0.5	7.1	1468.3	184.0	23.1	10.8	51.0	3.5	77.3	0.5
		Max	300.4	4.4	16,860.1	314.4	69.6	2.2	337.6	781.7	1.1	27.0	1713.9	198.0	32.5	31.9	58.9	24.4	87.1	2.6
		Mean	243.0	3.7	14,558.2	230.4	69.6	1.1	88.5	299.1	0.8	16.0	1589.0	191.7	25.4	16.1	54.3	15.0	82.9	1.5
		Median	246.1	3.8	14,358.3	231.8	69.6	0.8	51.6	294.7	0.9	15.8	1580.3	191.9	24.7	12.8	53.1	16.5	83.7	1.4
LF20	Água Padre José	Min	56.4	3.4	331.9	21.9	226.2	0.1	1224.5	2794.1	0.3	5.0	1.9	93.1	24.3	1.6	0.1	10.7	2.8	0.3
		Max	66.5	6.7	548.7	348.9	271.3	1.5	1753.5	4150.8	0.6	12.1	5.1	98.9	26.8	3.2	0.1	21.8	3.3	0.8
		Mean	60.7	4.9	413.3	130.1	247.8	0.5	1407.3	3393.6	0.5	8.7	3.0	95.8	25.4	2.1	0.1	14.9	3.0	0.5
		Median	61.9	4.8	415.7	67.5	246.6	0.3	1378.8	3348.9	0.5	9.9	2.9	95.5	25.3	1.8	0.1	14.2	2.9	0.5
LF21	Poça da Dona Beija	Min	36.3	1.7	187.0	14.5	62.9	0.1	851.0	8352.0	0.3	4.3	26.2	50.3	34.1	2.3	0.0	5.3	0.2	0.3
		Max	47.7	2.8	253.3	188.8	170.2	7.7	966.8	11,434.9	1.9	25.4	41.3	53.9	37.2	6.2	0.1	106.1	0.8	0.9
		Mean	40.3	2.3	211.6	113.1	136.2	1.7	901.3	10,154.0	0.8	11.7	36.7	51.2	35.2	5.5	0.1	28.8	0.6	0.6
		Median	39.2	2.5	207.4	124.3	147.2	0.1	894.5	10,469.8	0.7	7.4	40.1	50.8	35.0	6.1	0.1	13.2	0.7	0.6
LF22	Dr. Bruno/Peideira	Min	25.1	1.6	60.1	36.3	109.7	1.0	15.4	27.8	0.4	12.9	1.3	43.6	32.4	2.0	0.1	2.7	0.0	0.2
		Max	30.1	6.4	114.3	1224.5	182.0	1.3	578.1	4177.5	2.9	48.3	3.4	52.1	41.9	2.9	0.1	16.1	0.1	1.4
		Mean	27.1	2.8	75.0	262.2	134.8	1.1	154.4	755.1	0.9	23.6	2.0	47.6	36.4	2.6	0.1	6.3	0.1	0.5
		Median	27.0	1.7	73.0	62.4	131.5	1.1	40.6	262.6	0.5	19.9	2.0	47.4	35.7	2.6	0.1	3.9	0.1	0.4
LF23	Banhos Férreos I	Min	141.8	4.8	237.6	25.4	45.8	0.1	539.9	43.9	0.5	8.5	10.1	101.2	88.3	8.4	0.0	7.3	0.2	0.5
		Max	185.1	8.4	285.7	464.2	127.4	1.9	738.6	4803.3	1.7	35.6	13.3	109.0	92.8	8.9	0.1	20.1	0.2	1.2
		Mean	157.0	6.6	259.9	201.1	79.5	0.9	609.4	2020.1	0.9	18.3	11.3	105.2	90.5	8.7	0.0	14.2	0.2	0.8
		Median	153.4	6.9	257.2	113.9	65.2	0.7	581.8	2278.4	0.8	12.9	11.0	105.5	90.0	8.8	0.0	17.1	0.2	1.0
LF24	Banhos Férreos II	Min	136.4	5.5	244.0	146.5	226.5	1.3	553.9	1415.5	1.7	15.2	9.0	108.5	83.3	9.6	0.0	10.2	0.2	1.3
		Max	136.4	5.5	244.0	146.5	226.5	1.3	553.9	1415.5	1.7	15.2	9.0	108.5	83.3	9.6	0.0	10.2	0.2	1.3
		Mean	136.4	5.5	244.0	146.5	226.5	1.3	553.9	1415.5	1.7	15.2	9.0	108.5	83.3	9.6	0.0	10.2	0.2	1.3
		Median	136.4	5.5	244.0	146.5	226.5	1.3	553.9	1415.5	1.7	15.2	9.0	108.5	83.3	9.6	0.0	10.2	0.2	1.3
LF25	Banhos Férreos III	Min	140.9	2.0	219.2	9.9	141.1	0.1	300.9	64.2	0.2	5.6	8.5	95.2	82.3	7.7	0.0	2.3	0.1	0.4
		Max	162.0	8.3	288.3	327.4	316.1	2.3	616.5	5861.1	1.0	33.4	17.9	119.7	91.9	11.3	0.1	181.1	0.3	1.4
		Mean	150.8	6.2	249.9	99.8	242.6	0.8	460.4	3319.8	0.5	12.8	12.8	105.4	86.8	9.5	0.1	55.5	0.2	0.7
		Median	150.1	7.3	246.1	31.0	256.6	0.3	462.2	3677.0	0.3	6.2	12.4	103.3	86.6	9.5	0.0	19.3	0.2	0.5
LF26	Camarça	Min	2.4	0.6	13.8	31.3	50.8	0.1	8.3	54.1	0.4	4.9	1.6	12.6	14.1	2.6	0.0	5.4	0.3	0.2
		Max	234.5	9.5	441.5	327.5	213.0	9.5	567.4	2516.0	1.5	19.2	52.0	118.6	87.5	9.2	0.1	24.2	0.4	1.0
		Mean	49.6	5.0	109.0	123.2	151.9	7.1	143.5	803.7	0.8	12.8	12.0	36.0	31.2	4.4	0.1	12.2	0.4	0.6
		Median	3.0	5.0	30.4	94.0	158.3	8.9	49.2	347.8	0.5	12.6	2.2	15.3	17.5	3.3	0.1	5.9	0.3	0.6
LF27	Poça da Tia Silvina	Min	201.7	1.4	418.9	9.3	36.8	0.1	562.2	567.3	0.1	1.0	21.9	107.3	82.2	9.1	0.0	4.5	0.2	0.3
		Max	227.9	10.1	481.3	332.4	214.8	0.5	1299.5	4175.2	1.2	38.6	63.2	130.2	99.8	10.9	0.0	230.0	0.8	1.2
		Mean	210.5	7.4	448.1	129.3	97.1	0.3	691.5	2486.7	0.6	14.5	45.0	116.2	89.0	9.7	0.0	42.5	0.4	0.6
		Median	203.8	8.3	445.5	36.3	99.4	0.3	578.1	2538.2	0.5	11.0	47.5	115.9	88.0	9.5	0.0	11.6	0.3	0.5
LF28	Morangueira	Min	240.4	6.4	449.8	21.3	59.9	0.2	473.4	338.4	0.2	2.5	51.3	123.8	92.2	8.8	0.0	4.4	0.2	0.3
		Max	274.2	10.4	508.1	423.3	283.8	0.2	851.2	4342.3	1.7	15.8	73.1	145.4	113.4	9.7	0.1	15.3	0.3	1.2
		Mean	252.7	8.6	477.2	109.2	128.1	0.2	556.9	2500.4	0.6	7.4	60.0	130.7	98.8	9.2	0.0	9.0	0.2	0.6
		Median	246.7	9.4	477.5	49.6	89.9	0.2	513.5	2608.5	0.5	6.9	60.0	127.6	95.8	9.2	0.0	8.9	0.2	0.5
LF29	Quenturas I	Min	2.1	2.0	15.2	10.9	79.1	5.1	3.2	30.6	0.2	1.3	0.8	11.9	16.7	1.7	0.0	1.4	0.2	0.3
		Max	3.8	5.0	28.0	346.1	190.3	11.2	637.7	698.3	0.6	18.8	7.1	20.2	34.4	5.6	0.2	25.9	0.8	1.0
		Mean	2.5	3.5	22.3	110.9	144.2	8.2	128.1	312.5	0.3	9.1	2.3	16.8	24.4	3.0	0.1	8.3	0.3	0.6
		Median	2.3	3.5	22.3	61.3	149.4	8.8	8.7	262.9	0.3	8.9	1.5	17.0	24.2	2.7	0.1	5.1	0.3	0.6
LF30	Quenturas II	Min	60.1	2.7	304.6	10.0	94.2	0.1	170.7	636.4	0.3	2.1	9.3	42.4	24.0	1.5	0.0	1.2	0.8	0.2
		Max	156.6	10.5	862.0	288.3	206.8	2.4	1802.2	3582.3	2.6	86.1	24.9	140.0	82.4	5.1	0.0	41.8	2.6	1.2
		Mean	132.9	7.1	732.3	123.2	138.8	0.8	653.5	1229.4	0.9	25.7	21.3	113.0	65.8	4.2	0.0	14.5	2.1	0.6
		Median	140.8	7.6	783.4	44.4	134.9	0.3	476.1	811.9	0.6	9.5	23.7	119.7	68.8	4.6	0.0	9.2	2.2	0.5
LF31	Quenturas III	Min	54.3	2.5	273.3	7.4	85.8	0.1	159.3	111.4	0.1	1.8	9.8	39.3	22.3	1.4	0.0	2.1	0.7	0.3
		Max	161.0	7.5	880.8	230.0	177.1	0.6	585.7	1082.8	5.3	18.6	23.8	141.7	81.5	4.9	1.5	134.4	2.8	2.8
		Mean	132.5	5.7	724.4	68.1	136.0	0.3	435.7	557.3	1.0	7.8	20.3	113.7	64.9	4.2	0.3	25.7	2.0	0.9
		Median	143.5	6.1	771.6	41.9	131.2	0.2	438.8	689.7	0.3	4.4	22.3	122.1	70.1	4.5	0.0	8.2	2.2	0.4
LF32	Grutinha I	Min	193.2	10.0	410.0	105.8	114.0	0.1	809.4	4321.7	0.2	2.8	60.7	106.2	70.4	22.2	0.0	2.2	0.4	0.2
		Max	228.8	13.3	466.9	397.6	286.0	0.7	1342.6	6849.7	1.0	22.3	71.1	127.8	92.2	25.2	0.0	398.8	0.7	2.0
		Mean	209.2	11.7	434.7	190.0	182.0	0.3	929.5	5580.9	0.6	11.3	63.6	113.0	78.9	23.2	0.0	68.2	0.6	0.9
		Median	209.7	11.6	429.1	149.1	172.9	0.2	852.4	5349.6	0.7	9.3	62.1	110.7	76.4	22.9	0.0	8.0	0.6	0.7
LF33	Grutinha II	Min	139.8	7.8	424.3	83.7	67.1	0.1	777.4	4741.6	0.2	3.5	41.9	96.3	62.8	14.5	0.0	1.8	0.5	0.2
		Max	220.8	11.1	513.5	257.7	354.2	1.2	2032.8	6384.8	2.5	38.4	62.1	109.7	70.2	24.7	0.1	45.8	0.8	0.9
		Mean	180.5	9.6	455.7	149.1	187.7	0.5	1028.0	5831.1	0.8	14.1	52.9	103.0	67.5	20.2	0.1	14.8	0.6	0.5
		Median	193.4	9.1	444.4	146.5	173.9	0.4	873.8	5973.1	0.5	9.0	55.2	103.9	68.6	23.9	0.1	7.7	0.7	0.4
LF34	Torno	Min	181.6	8.9	353.4	135.2	72.5	0.2	907.3	3116.4	0.2	2.7	51.3	101.5	58.7	26.6	0.0	2.0	0.4	0.3
		Max	221.5	10.0	424.0	247.5	288.4	0.2	1013.9	7172.1	1.1	14.5	64.4	111.9	63.3	28.4	1.0	113.0	0.6	0.8
		Mean	195.4	9.4	391.3	167.0	141.3	0.2	961.4	5314.6	0.5	6.9	56.8	107.0	61.1	27.6	0.4	19.8	0.5	0.5
		Median	190.5	9.4	393.3	164.3	103.9	0.2	965.0	5604.9	0.3	5.8	57.6	107.2	62.0	27.5	0.4	5.0	0.5	0.6
LF35	Nostra	Min	11.1	0.5	23.9	68.3	59.5	1.1	13.0	56.2	1.0	12.2	2.8	25.9	8.9	5.0	0.1	3.1	0.1	0.5
		Max	15.1	4.6	45.7	456.7	100.6	1.7	195.6	934.7	1.5	38.9	3.4	35.1	50.5	6.8	0.2	18.8	0.2	1.0
		Mean	14.1	1.9	35.7	234.9	78.4	1.5	75.5	276.3	1.2	22.3	3.1	30.6	17.0	5.7	0.1	7.6	0.1	0.6
		Median	14.6	1.4	37.6	180.2	74.5	1.6	47.4	147.2	1.1	21.0	3.1	30.6	10.4	5.6	0.1	4.8	0.1	0.5
LF36	Helena	Min	2.1	0.6	13.2	152.0	113.3	6.6	40.5	263.5	0.4	13.5	1.1	16.0	16.4	3.0	0.0	3.9	0.1	0.5
		Max	3.6	0.9	23.7	347.7	188.5	7.7	429.7	539.5	1.0	44.0	2.1	19.3	19.5	3.7	0.2	13.6	0.5	0.8
		Mean	3.1	0.8	18.8	230.6	157.9	7.1	176.8	392.2	0.6	22.5	1.7	17.9	17.9	3.4	0.1	8.4	0.3	0.7
		Median	3.4	0.9	18.9	229.2	156.3	7.2	94.0	331.6	0.6	17.4	1.5	18.0	17.7	3.4	0.1	7.1	0.3	0.8
LF37	Glória Patri	Min	1.3	0.7	15.3	13.7	94.2	6.8	3.3	20.9	0.3	5.9	0.7	12.9	18.6	1.9	0.0	2.0	0.2	0.2
		Max	3.2	2.1	27.7	383.7	167.7	9.5	39.8	2752.1	1.6	32.3	1.7	18.2	28.0	6.6	0.1	155.7	0.4	1.1
		Mean	2.1	1.2	19.2	106.2	130.6	8.5	15.1	543.7	0.6	14.0	1.0	16.6	24.6	3.1	0.1	34.3	0.3	0.5
		Median	2.2	0.9	17.7	47.8	131.4	8.6	12.4	141.0	0.4	12.2	0.8	17.0	24.9	2.7	0.0	10.3	0.3	0.5
LF38	Estrada RQ	Min	55.3	2.7	123.1	55.8	144.9	0.1	606.5	382.6	0.4	13.9	3.2	45.3	351.5	1.3	0.0	65.6	0.1	0.5
		Max	94.5	6.3	206.1	72.6	144.9	0.1	1202.8	3156.7	0.6	14.2	6.8	94.3	725.6	2.4	0.0	126.0	0.1	0.5
		Mean	74.9	4.5	164.6	64.2	144.9	0.1	904.6	1769.6	0.5	14.1	5.0	69.8	538.5	1.9	0.0	95.8	0.1	0.5
		Median	74.9	4.5	164.6	64.2	144.9	0.1	904.6	1769.6	0.5	14.1	5.0	69.8	538.5	1.9	0.0	95.8	0.1	0.5
LF39	Dízimo	Min	3.6	0.6	10.4	16.1	203.3	3.9	4.1	22.6	0.4	5.6	1.4	14.3	14.3	5.9	0.0	3.1	0.1	0.3
		Max	4.7	0.6	22.4	165.2	226.2	4.4	23.2	1639.9	2.5	19.1	6.1	15.6	23.2	6.6	0.2	312.5	0.3	1.4
		Mean	4.0	0.6	16.2	71.0	214.4	4.1	9.2	500.0	1.0	13.3	2.3	15.0	16.8	6.4	0.1	64.3	0.2	0.8
		Median	3.8	0.6	15.7	55.1	215.3	4.2	5.7	57.5	0.7	12.9	1.5	15.0	15.8	6.5	0.0	17.6	0.1	0.8
CLag	Soil water, Furnas Lake		1.86	29.8	0.9	183.2	88.7	79.4	0.5	208.8	281.0	0.5	16.8	2.1	139.0	46.2	3.0	0.6	25.3	0.1
CFut	Soil water, football field		0.55	125.0	2.9	261.7	2674.6	422.8	4.3	486.2	3735.3	1.3	69.5	7.7	195.5	79.8	11.6	1.6	49.0	2.0

). Strontium is a refractory element that is added to groundwater through the chemical weathering of rocks [77]. To understand their source, Sr was plotted against calcium [34,35], where the positive correlation between them (Figure 5a,b) suggests that the Sr content in these samples is associated with rock weathering.

Soil waters display a similar ⁸⁷Sr/⁸⁶Sr ratio of the seawater (0.709590 and 0.710067;

Table 1. Strontium isotopic ratios of water samples. Previous values extracted from [42].

Reference	Name	87Sr/86Sr
		[42]	Winter	Summer
LF1	Caldeira da Lagoa das Furnas	-	0.705077 ± 0.000030	-
LF3	Miguel Henriques	-	0.705374 ± 0.000028	-
LF8	Água Santa	-	0.706185 ± 0.000028	0.705370 ± 0.000005
LF10	Azeda	0.705368	0.705783 ± 0.000018	-
LF18	Caldeira Asmodeu	0.705408	0.705528 ± 0.000025	-
LF19	Caldeira Grande	0.705432	0.705363 ± 0.000023	-
LF20	Padre José	-	0.705268 ± 0.000028	-
LF25	Banhos Férreos III	-	0.705035 ± 0.000028	-
LF26	Camarça	-	0.705409 ± 0.000030	-
LF29	Quenturas I	-	0.705231 ± 0.000025	0.705193 ± 0.000010
LF30	Quenturas II	0.705258	0.704771 ± 0.000030	0.705243 ± 0.000006
LF33	Grutinha II	-	0.705278 ± 0.000023	-
LF34	Torno	0.705235	0.705211 ± 0.000025	-
LF37	Gloria Patri	-	0.705212 ± 0.000023	-
LF38	Estrada RQ	-	0.705002 ± 0.000021	-
LF40	Dizimo	-	0.705750 ± 0.000024	-
CLag	Soil water, Furnas Lake	-	0.710067 ± 0.000007
CFut	Soil water, football field	-	0.709590 ± 0.000008

and Figure 6c). These values are also comparable to those observed in rainwater from São Miguel [69], where the higher ratios are attributed to the influence of continental dust. Regarding groundwater, the ⁸⁷Sr/⁸⁶Sr ratio ranges between 0.704771 and 0.706185 (winter values from Table 1 and Figure 6c). As shown in Figure 6c, mineral water discharges present an isotopic composition that differs from both seawater and the soil water, and this is related to the rock weathering process.

So far, there have been no studies characterizing the Sr isotopic composition of rocks from Furnas; however, some data are available about a layer of one eruption from Fogo volcano, the so-called Fogo A episode [78], of which outcrops are also present in Furnas area. By comparing our samples to the Sr isotopes from the Fogo A layer (whole rock = 0.7049–0.7061) [79], it is possible to suggest that the waters reached isotopic equilibrium with the adjacent lithology. In hydrothermal systems of active volcanoes, fluid compositions generally reflect the properties of rocks that have reacted with the fluids [36]. Other effects on the isotopic composition are negligible because of the highly accelerated fluid–rock interactions as a result of the hot and highly acidic fluid caused by volcanic gas dissolution [36]. This seems to be the case with the Furnas samples, since they have a different isotopic ratio from the seawater (responsible for part of the Sr in rainwater), and the concentration of Sr depicts a correlation with elements of lithological origin (e.g., Ca²⁺). Furthermore, based on the comparison between our data and previous Sr isotope results from [42] and some samples from the dry season, most of the samples show a steady–state behavior with no seasonal variations (Table 1) and similarities between samples.

Figure 5. Binary diagrams of (a,b) Ca vs. Sr and (c) the ⁸⁷Sr/⁸⁶Sr isotopic ratio of ground and soil pore water samples. Seawater values (blue stripe) are extracted from [30], and Fogo A ratios (black dotted rectangle) are from [79].

Figure 5. Binary diagrams of (a,b) Ca vs. Sr and (c) the ⁸⁷Sr/⁸⁶Sr isotopic ratio of ground and soil pore water samples. Seawater values (blue stripe) are extracted from [30], and Fogo A ratios (black dotted rectangle) are from [79].

Figure 6. Range of trace element concentrations projected in boxplots: (a) B, Al, P, Mn, Fe, and As; (b) Rb, Sr, and Ba; and (c) Be, V, Ni, Zn, Mo, Sb, W, and Pb. Binary diagrams of trace elements and physico-chemical parameters: (d) Li vs. temperature; (e) Li vs. conductivity; and (f) Li vs. HCO₃.

Figure 6. Range of trace element concentrations projected in boxplots: (a) B, Al, P, Mn, Fe, and As; (b) Rb, Sr, and Ba; and (c) Be, V, Ni, Zn, Mo, Sb, W, and Pb. Binary diagrams of trace elements and physico-chemical parameters: (d) Li vs. temperature; (e) Li vs. conductivity; and (f) Li vs. HCO₃.

4.3. Trace Elements Signatures

The trace element content of the sampled waters is presented in Table A2. The soil water samples display some differences regarding trace element content. In general, the soil water collected locally with higher degassing (CLag) depicts an enrichment in some elements, such as lithium (Li), boron (B), aluminum (Al), manganese (Mn), zinc (Zn), nickel (Ni), and barium (Ba), some twice as high compared to soil water (CFut) (Table A2). These enrichments can be associated with the fumarolic fluids that interact with the rainwater, which was previously detected in the calderas from Furnas Village [69].

Furnas mineral water discharges depict an enrichment in certain trace elements, such as B, Al, Mn, iron (Fe), phosphorus (P), and arsenic (As), with concentrations exceeding 1 mg·L⁻¹ (Table A2; Figure 6a). Boron reaches the highest concentrations, especially in the hyperthermal waters from the Furnas Village, which are projected as outliers (Figure 6a). Given that mineral waters in Furnas discharge from perched aquifers, and the geology of the site does not explain these values, the boron likely originates from volcanic degassing. Other trace elements, such as As, W, and Sb (Figure 6a,b) show a similar trend (LF19 > LF18 > LF17 > LF8), with higher concentrations in the hyperthermal water from the Furnas Village, suggesting a relation with neutral chloride fluid, as these enrichments are not as pronounced in the boiling pool near Furnas Lake (LF1). The enrichment in trace elements associated with the influence from fumarolic degassing activity has been also observed, for example, in the groundwater of Vulcano Island (Sicily) [17]. It was observed that the input of magmatic gases can produce reactive environments that enhance rock leaching and the release of trace metals into the weathering solutions or can contribute trace metals directly to the aquifer [17].

Lithium, generally associated with rock dissolution, does not show a correlation with temperature (R² = 0.354; Figure 6d) as expected. Nevertheless, the enrichment in Li is accompanied by an increase in EC (Figure 6e) and HCO³ content (Figure 6f), supporting its origin from rock weathering. Aluminum, another element frequently associated with rock input, does not show a linear correlation with lithium. This may have resulted from the tendency of Al to oversaturate in solid phases at higher temperatures, as shown by the higher concentrations presented by the cold waters (Table A2) and as corroborated by the presence of alunite, smectite, and kaolinite in the secondary minerals [70]. This is similarly applicable to Fe, which is influenced by temperature, pH, and redox potential, determining whether it remains in solution or precipitates.

The enrichment in phosphorus shown by Caldeira do Esguicho (LF17; Figure 7a) is also noteworthy. This behavior seems to be correlated with anthropogenic contamination, once there is a seasonal variation (36.6–4479.0 µg·L⁻¹), with the maximum value occurring during summer (August 2022). This spike is likely related to the tradition of cooking corn in the boiling pool during that season, which can transfer P to solution because plants naturally contain this component as a macronutrient or due to the presence of residual amounts of fertilizers enriched in P.

4.4. Rare Earth Element Patterns

The rare earth element concentration is depicted in Table S1 (Supplementary Materials). Furnas mineral waters show a lower concentration of REEs in comparison to the trachyte rock from Furnas J [51] (Figure 7a). This is an expected behavior since these waters are immature, these waters did not reach equilibrium, and, as mentioned before, these elements have sensitive behavior. When normalized to the chondrite values [68], Furnas waters depict an enrichment in light REEs (LaN/GdN > 1) in comparison to heavy REEs (YbN/GdN > 1) (Table S1; Figure 7), a pattern similar to the Furnas J trachyte and the one in soil water samples. Notably, soil waters show a slightly higher content of REEs compared to most of the groundwater samples, despite being sub-superficial waters. While the overall tendency is similar, there are some significant variations in the ∑REE and europium (Eu) anomalies.

The ∑REE concentrations of the groundwaters vary from 0.60 to 4.93 µg·L⁻¹, with the higher concentration observed in Caldeira da Lagoa das Furnas (LF1; ∑REE = 12.35 µg·L⁻¹), which also shows the lowest pH (pH mean = 4.08). This correlation reflects the significant role of pH in controlling REE concentrations in the groundwater, with lower pH generally leading to higher rare earth element concentrations [80,81,82,83]. In geothermal fields, acid sulfate waters typically have the highest REE concentrations [83]. In contrast, near-neutral chloride- and bicarbonate-type waters have lower overall REE concentrations, as they are usually present in or on suspended particles [83]. The influence of volcanic fluids could help in enriching the content in the REEs; however, there is some evidence that suggests that REEs are lost to solid phases upon vapor–liquid separation [83]. As outlined in the methodology, a portion of the REEs may be associated with the presence of small colloids that could still be present in the analyzed samples. Nevertheless, this influence appears to be minimal, as no significant correlation is observed between ∑REE and Fe (R² = 0.0004), Al (R² = 0.2915), and Mn (R² = 0.0160).

A Ce anomaly is only identified in the soil water collected in the area with less degassing (CFut), while the other samples show no pronounced Ce anomalies. The formation of a Ce anomaly can be associated with Fe-Mn colloids and surface coatings or with bacterial activity [84].

Europium displays variable behavior across the dataset, which is not necessarily associated with the water temperature (cold, thermal, and hyperthermal; Figure 7a), with differences in Eu patterns within each group (Figure 7b–d). Eu anomalies are often inherited from the host rock [85], showing a positive spike, if not observed in the whole rock, resulting from the dissolution of Eu-rich mineral phases, such as plagioclase and feldspar [86]. Europium can exist in trivalent (Eu³⁺) or divalent (Eu²⁺) forms, and Eu³⁺ can only be reduced to Eu²⁺ at temperatures greater than 250 °C or in an extreme reducing environment [83,84,85,86,87,88]. Furnas mineral water discharges presenting a negative europium anomaly inherited these characteristics from the rock and/or the soil water, as shown in Figure 7a. There are also samples with positive Eu anomalies, which can have different origins depending on the sample. The cold waters that present the positive spike (LF39-Dizimo, LF37-Gloria Patri, and LF2-Água da Ponte) are probably associated with a more superficial part of the aquifer, with less interaction with the surroundings, causing it to depict a positive Eu anomaly, similarly to some of the rainwater collected in Furnas [69]. The thermal and hyperthermal samples display a positive Eu anomaly that is possibly due to the presence of Eu²⁺ that results from water–rock interactions at high temperatures (≥250 °C) or unusual reducing conditions [84,86,87,88]. Incongruent dissolution of minerals could be the cause of the variations in europium; however, it would also affect the strontium isotopic ratios, which is not observed. Samples with no prominent spike show an interaction between several inputs. Positive anomalies were not detected in the previous data presented by [41], since the samples that present these spikes were not analyzed and there is also a seasonality factor associated with their presence (Table S1).

The remaining heavy rare earth elements depict irregular behavior, with many near-neighbor anomalies, associated with the seasonal variations in the content of these elements (Table S1).

5. Conceptual Hydrogeological Model

Based on all the hydrochemical information of the samples, an updated conceptual model of Furnas volcano is put forward (Figure 8, not to scale). The model is mainly based on the interpretation of the major ion content, more specifically the anions; however, with regard to the minor/trace element composition, we also managed to better understand the contribution of rock weathering and volcanic input.

The fumarole fields in Furnas are associated with a fault system, which gives a preferential pathway to the vapor/fluids that arise and react with the aquifer. Based on the behavior of the anions, associated with groundwater–volcanic gas interactions, it is possible to distinguish two different environments (Figure 8). Most sulfate- and bicarbonate-rich waters are derived by the adsorption of gas and steam in near-surface aquifers [73], which appears to be the case with Furnas volcano, as previously established [61]. The boiling pool from Furnas Lake (LF1—Caldeira da Lagoa das Furnas) is an acid sulfate spring, usually related to the rising of steam and volatile compounds that condense near-surface groundwaters and the H₂S that is carried in the steam and oxidized to form sulfuric acid [8,73,88]. The shallower aquifer in the Lake region is vapor-driven (100–200 m) and can reach temperatures up to 200 °C, where the cooling of ascending magmatic steam/fluids and mixing with meteoric water occur [56]. The water will percolate towards the village, interacting with the bedrock, becoming richer in major cations and anions, especially HCO₃⁻, due to water–rock interactions, which promotes a rise in pH. The fumarolic field in the Furnas Village is associated with an inferred fault that crosses this region. We suggest that this fault allows the rise of reservoir fluids, which may become diluted on the pathway to the surface and will transfer Cl⁻ and other magmatic volatiles to the hyperthermal waters in the village, also observed in some thermal water, though in lower amounts. Based on the higher enrichment in Cl⁻ and the associated trace elements, such as boron, Caldeira Grande (LF19) seems to be the sampling location with major similarity to the deep reservoir, due to the higher influence from the deep fluids. The less reactive components continue their route to the surface, where part of the CO₂ will react with the meteoric water, leading to the discharge of cold CO₂-rich springs. The compositional difference between the two fumarolic fields could be a sign that the fluid rich in HCl became dissolved somewhere along the path before reaching the shallow aquifer below Furnas Lake, since both fields have the same reservoir.

6. Conclusions

Groundwaters from Furnas volcano are mainly classified as Na-HCO₃ type, resulting from water–rock interactions, whose contents are magnified by the volcanic input, especially temperature and dissolved CO₂. Caldeira da Lagoa das Furnas is the exception, being classified as Na-SO₄ water type, which contributes steam and volatile compounds that condense near the surface and cause the H₂S to oxidize to sulfuric acid. In contrast, some hyperthermal waters discharging in Furnas Village present a neutral-HCO₃ with Cl composition, resulting from the mixing of HCO₃-rich waters with neutral chloride fluid from a deeper reservoir mixing with near-surface aquifers. This deep reservoir seems to also influence the content of several trace elements, causing an enrichment in boron, arsenic, antimony, and tungsten, particularly in the hyperthermal discharges from the Furnas Village, and also influencing the behavior of Eu, causing positive anomalies. The positive anomalies can be associated with the dissolution of the rock at temperatures higher than 250 °C or an extremely reductive environment. Mineral waters show similar ⁸⁷Sr/⁸⁶Sr ratios, indicating equilibrium with the rock, and no signs of seasonal variation or mineral incongruent dissolution are observed.

Overall, the combined hydrogeochemistry of the major ions, trace elements, rare earth elements, and strontium isotopes enhances the understanding of the Furnas hydrothermal system. It allows a better understanding of the influence of various factors, such as recharge by rainwater, water–rock interactions, heating by vapor, and the incorporation of fluids from deep reservoirs.