A week of automated continuous measurements of temperature, pH and specific conductance in a mining-polluted river in Sardinia (Italy): The effect of rainfall as a case of serendipity

A week of automated continuous measurements of temperature, pH and specific conductance in a mining-polluted river in Sardinia (Italy): The effect of rainfall as a case of serendipity | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article A week of automated continuous measurements of temperature, pH and specific conductance in a mining-polluted river in Sardinia (Italy): The effect of rainfall as a case of serendipity Franco Frau This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7786219/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract This study is an example of serendipity applied to hydrogeochemistry. Starting with the aim of continuously measuring for one week some parameters (temperature, pH and specific conductance) at two different sampling points along a river heavily contaminated by past mining activity, due to the occurrence of an undesirable climatic change consisting of heavy rainfall distributed over the week of measurements, unexpected hydrogeochemical data were collected that required a different processing and interpretation approach from the standardized one that was thought to apply when the above study was conceived for stable climatic conditions. Earth and environmental sciences/Climate sciences Earth and environmental sciences/Environmental sciences Earth and environmental sciences/Hydrology Mining-polluted river Diel cycles Automated continuous measurements Rainfall effects Hydrogeochemical serendipity Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Introduction Present and past mining activities often have a negative impact on surface and groundwater quality, and many studies report information on spatial variations of contaminants along a river and monitoring over a period that can span up to several years. On the other hand, short-term temporal variations (the so-called “diel cycling”) of contaminants and physical-chemical parameters have also been studied (Nimick et al. 2007 ; Frau et al. 2012 ; Gammons et al. 2005a , 2015 ), but the results obtained are rarely used in characterization and monitoring plans of active and abandoned mine sites. In some cases, the diel variation of a certain parameter at various points along a river can be so high that in a standardized sampling that parameter may show an increasing or decreasing trend from upstream to downstream depending on whether the sampling is conducted from upstream to downstream or vice versa throughout the day. However, in most cases the diel variation of major ions and physical-chemical parameters (e.g. pH, Eh, specific conductance) is very low, but some trace elements (e.g. As, Zn, Mn) have been shown to be particularly sensitive to diel cycling so that, in heavily contaminated environmental contexts, the variation can even be in the order of tens of µg/L (Frau et al. 2015 ; Gammons et al. 2007 , 2015 ). Rivers with variation of pH along the course from acidic to neutral or vice versa are particularly interesting because allow to better understand the diel behavior of trace elements, which, under near-neutral to alkaline conditions, is normally linked to reversible pH- and temperature-dependent adsorption processes (Nimick et al. 2003 ; Jones et al. 2004 ; Gammons et al. 2005b , 2015 ), whereas under acidic conditions it is frequently controlled by light-sensitive and bacteria-mediated Fe redox reactions (McKnight et al. 2001 ; Gammons et al. 2005a , 2015 ). In this article we report the results of a week of automated continuous measurements of temperature, pH and specific conductance in two different sampling points along the Rio Irvi (Sardinia, Italy), a river strongly affected by pollution related to past mining activity at the Casargiu mine. Although the initial idea was to collect physicochemical data for a sufficiently prolonged period under stable weather conditions, the unexpected occurrence of intense rainfall produced interesting results on the effects caused by the dilution of the Rio Irvi water with rainwater. This is a case of serendipity applied to environmental hydrogeochemistry. Study area Casargiu is one of the abandoned mines belonging to the Montevecchio-Ingurtosu mining system in SW Sardinia (Italy) characterized by Pb-Zn sulfide veins hosted in Palaeozoic silicate-dominant rocks. Mineralization at Casargiu mainly consists of sphalerite with an ankerite-siderite gangue (Frau et al. 2015 ). At Casargiu, exploitation reached 180 m below the elevation of the Casargiu gallery, whose entry is 158 m above sea level. The mine closure in the 1980s led to the shutdown of pumping systems needed to keep the galleries dry, thereafter a highly polluted drainage flowing out of the Casargiu gallery was observed beginning in 1997 (Frau et al., 2015 ). The Casargiu drainage flows into the Rio Irvi that after about 6 km merges with the Rio Piscinas, which in turn flows into the Mediterranean Sea after about 2 km (Fig. 1 ). The hydrological basin of the Rio Irvi has an area of about 15.4 km 2 and a length of about 11 km. Due to climatic conditions mainly characterized by long periods of heat and drought and relatively short rainy periods, the outflow from the Casargiu gallery (20–70 L/s) still represents the main water contribution to the Rio Irvi throughout the year (Frau et al. 2015 ; De Giudici et al. 2018 , 2019 ; Rigonat et al. 2019 ; Dore et al. 2020 ). Sampling and methods Temperature, pH and specific conductance were measured every 15 minutes in two different sampling sites (RIV3 and RIV10) along the Rio Irvi (Figs. 2 and 3 ) using two in-situ multi-parameter sondes, which were calibrated before placement. Measurements at the RIV3 site (corresponding to the CAS4 sampling site in Frau et al. 2015 ) began at 13:30 on 5 May 2016 and ended at 12:15 on 11 May 2016, while measurements at the RIV10 site (corresponding to the CAS9 sampling site in Frau et al. 2015 ) began at 15:30 on 5 May 2016 and ended at 14:15 on 11 May 2016. On 5 May 2016 a complete water sampling was carried out at the two sites RIV3 and RIV10 (Table 1 ), while only temperature, pH, Eh, specific conductance and dissolved O 2 were measured at the other points along the Rio Irvi, starting from the Casargiu gallery (CAS1). Table 1 Chemical composition of Rio Irvi at the two sampling points RIV3 and RIV10. Milliequivalents per liter of Fe were calculated considering it as Fe 2+ . Δ is the charge balance error calculated as (Σcat – Σan)/(0.5 ∙ (Σcat + Σan)). TDS means Total Dissolved Solids. Alk is the alkalinity expressed as HCO 3 − . Old name CAS4 CAS9 New name RIV3 RIV10 Flow L/s 55 58 T °C 24.3 28.7 Eh mV 183 498 pH 6.29 3.89 Cond mS/cm 4.11 4.19 O 2 mg/L 7.23 7.36 TDS g/L 5.43 5.27 Ca mg/L 390 370 Mg mg/L 252 246 Na mg/L 78 93 K mg/L 15 18 Cl mg/L 87 132 Alk mg/L 65 SO 4 mg/L 3525 3450 SiO 2 mg/L 17.5 19.2 Fe mg/L 152 108 Mn mg/L 70 68 Zn mg/L 775 770 Cd µg/L 2110 1940 Pb µg/L 140 660 Ni µg/L 2480 2320 Sb µg/L 0.37 0.21 Co µg/L 1480 1375 Ca meq/L 19.46 18.46 Mg meq/L 20.72 20.23 Na meq/L 3.39 4.04 K meq/L 0.38 0.46 Cl meq/L 2.45 3.72 Alk meq/L 1.07 0.00 SO 4 meq/L 73.44 71.88 Fe meq/L 5.44 3.87 Mn meq/L 2.55 2.48 Zn meq/L 23.71 23.56 Σcat meq/L 75.67 73.10 Σan meq/L 76.96 75.60 Δ -0.02 -0.03 Variation (Var) of a parameter was defined as the difference between the maximum value (V max ) and the minimum value (V min ): Var = V max - V min (1). Delta percentage (D%) of a parameter was calculated according to the following equation: [(V max – V min )/V min ] * 100 (2). Speciation-solubility calculations were performed using the computer program PHREEQC Interactive (version 3.7.3.15968 released on December 2, 2021; Parkhurst and Appelo 2013 ) with the included thermodynamic database ‘‘wateq4f.dat’’. The solubility product ( K sp ) of sulphate green rust (GR) was added to the thermodynamic database (Frau et al. 2015 ). Results and discussion Temperature-Specific Conductance relationship Figure 4 shows the comparative trends of temperature (T) and specific conductance (SC) at the two sites RIV3 and RIV10 throughout the period of measurements with the multi-parameter sondes. In the time span before the first rainfall, at the RIV3 site a constant SC can be observed, while T follows the typical sinusoidal pattern related to the alternation between day and night (Var = 9°C; D% = 58). As SC is a conductivity measurement corrected to 25°C, its invariance between day and night is expected, unless there are external water inputs. With the beginning of the first rainy period, it is interesting to note that the day-night thermal effect on T is cancelled out, while SC decreases abruptly three times due to dilution with rainwater but always returns to the initial value, first very quickly and then more gradually (about 30 hours). The rising speed of SC is obviously influenced by the amount of rain falling in the unit of time, always taking into account that the Rio Irvi for most of the year is mainly fed by groundwater coming out of the Casargiu gallery (CAS1). The rain on 9–10 May almost halves SC which takes about 24 hours to return to its initial value. In this case it is interesting to note that the daily variation of T is less influenced by the rain, maintaining a general sinusoidal trend. Similar trends are observed at the RIV10 site, although here the SC measurements are more unstable and the curve strongly jagged. The main differences with RIV3 are that: i) the range of T is much wider (Var = 18°C; D% = 165); ii) during the first rainy period SC decreases progressively instead of falling and rising; iii) the minimum SC is reached about 12 hours after the 9–10 May rainfall. All this can be explained by the fact that the RIV10 site is several kilometers downstream of RIV3, it is located in the coastal plain quite close to the sea, it is less readily affected by groundwater input from CAS1 and collects a larger volume of runoff during rainfall. Temperature-pH relationship Figure 5 shows the comparative trends of temperature (T) and pH at the two sites RIV3 and RIV10 throughout the period of measurements with the multi-parameter sondes. At the RIV3 site the pH is mildly acidic, ranging from 5.75 to 6.45 (Var = 0.70; D% = 12), and its trend is highly symmetrical to the T trend. A discordant T-pH trend is also present at the RIV10 site where the pH is acidic, ranging from 3.76 to 4.34 (Var = 0.58; D% = 15). This discordant relation between T and pH has already been shown in other studies but is still rather uncommon since the literature generally reports a concordant T-pH relation linked to the photosynthesis-respiration cycles of aquatic life (at least in rivers with neutral or slightly alkaline pH) according to the following reactions where (org) and (aq) stand for organic and aqueous, respectively (Gammons et al. 2015 ): daytime T increase photosynthesis: CO 2 + H 2 O + sunlight → CH 2 O (org) + O 2 (3) pH increase: HCO 3 − + H + → CO 2(aq) + H 2 O (4) nighttime T decrease respiration: CH 2 O (org) + O 2 → CO 2 + H 2 O (5) pH decrease: CO 2(aq) + H 2 O → HCO 3 − + H + (6). Even in metal-polluted rivers where there may be very little aquatic life, the effect of temperature on CO 2 solubility would lead to the result described above in each case. However, if we focus on the production-consumption of O 2 related to the photosynthesis-respiration cycles, other oxidation-reduction reactions can be influenced such as those involving the Fe species that, together with SO 4 , Zn, Mg and Ca, dominate the chemical composition of the Rio Irvi water (Frau et al. 2015 ). In particular, when the following reactions are considered: Fe 2+ + 0.25O 2 + H + ↔ Fe 3+ + 0.5H 2 O (7) Fe 3+ + 3H 2 O ↔ Fe(OH) 3(am) + 3H + (8) Fe 2+ + 0.25O 2 + 2.5H 2 O ↔ Fe(OH) 3(am) + 2H + (9) where (am) stands for amorphous and reaction (9) is the combination of reactions (7) and (8), it is apparent that daytime O 2 production from photosynthesis shifts the reaction (9) to the right, generating acidity, while nighttime O 2 consumption from respiration shifts the reaction (9) to the left or simply slows it down, consuming or not-producing acidity and partially redissolving the previously precipitated Fe(III)-hydroxide. As described in a previous study (Frau et al. 2015 ), the reaction (9) predominates at the RIV10 site, while the RIV3 site is characterized by the precipitation of “green rust” (GR) according to the following reaction: 6Fe 2+ + SO 4 2− + 0.5O 2 + 19H 2 O ↔ Fe II 4 Fe III 2 (OH) 12 (SO 4 ) ∙ 8H 2 O + 10H + (10) which is analogous to reaction (9) in determining the pH trend opposite to the T trend. In both cases the effect of temperature on O 2 solubility should not be so important since O 2 is much less soluble in water than CO 2 . An opposite relation between T and pH could also be due to photoreduction of aqueous Fe(III) according to such a reaction: Fe 3+ + 0.5H 2 O + sunlight → Fe 2+ + 0.25O 2 + H + (11). Gammons et al. ( 2005a ) also suggested the importance of aqueous Fe 3+ speciation in determining a diel cycle of pH analogous to that described in this paper, according to the following reaction: Fe(SO 4 ) + + 0.5H 2 O ↔ Fe 2+ + SO 4 2− + 0.25O 2 + H + (12). However, Fe speciation at both RIV3 and RIV10 sites is by far dominated by the free Fe 2+ ion, while the dominant Fe(III) species are Fe(OH) 2 + and Fe(SO 4 ) + , respectively, but with concentrations 3–4 orders of magnitude lower than Fe 2+ . Therefore, it seems very unlikely that changes in pH during 24 hours are determined by the formation/dissociation of the aqueous Fe(SO 4 ) + complex. There is no doubt that the complex biological/microbial activity present in the Rio Irvi, which is still at an early stage of study and understanding, has a decisive influence on the Fe (and other metals) cycle in solution and in precipitates, and consequently also on pH (see e.g. Morris et al. 2005 ; Gammons et al. 2015 ; Lueder et al. 2020 ; Paganin et al. 2021 ). Rainfall effect It is also interesting to observe the effect of the first rainfall period in which T and pH remain almost constant at the RIV3 site, while at the RIV10 site a relative constancy of T is accompanied by a clear increase in pH. This can be explained by the fact that dilution with rainwater, to which a pH of 5.65 (pure rain in equilibrium with atmospheric CO 2 ) can be attributed, does not substantially change the mildly acidic pH of the river water at the RIV3 site, while it causes the increase of the markedly acidic pH at the RIV10 site. A simulation was carried out with PHREEQC to estimate the volume of rain needed to raise the pH at the RIV10 site; Fig. 6 shows that, starting from pH 3.89 in the absence of rain, a progressive mixing of rain up to 70% of the water flowing in the Rio Irvi is needed to achieve pH 4.30 at the end of the rainfall period from 7 to 8 May. It is evident that the slope of the two curves shown in Fig. 6 cannot be the same as the simulation does not take into account the time as a variable in the mixing of river water and rainwater. The effect of rainfall on river chemistry can potentially influence the precipitation/dissolution of a mineral phase, especially when it is an unstable phase as in the case of the formation of GR in the first stretch of the Rio Irvi, where Fe(II) still persists into solution together with Fe(III). To highlight this process, a simulation was carried out with PHREEQC. Figure 7 shows that, starting from the chemical composition at the RIV3 site reported in Table 1 , the initial oversaturation (SI = 0.72) with respect to GR progressively shifts to saturation (SI = -0.02) and then to a marked undersaturation (SI = -1.21) when respectively 40% and 70% of the water flowing in the Rio Irvi is represented by rain. This process may be periodically important in contributing to the metal load discharged from the Rio Irvi and other polluted rivers to the sea (Frau et al. 2015 ). Indeed, a phenomenon of partial removal of Fe precipitates from the Rio Irvi bed has sometimes been observed during heavy rainfall. In that case there is a probable concomitance of a dissolution process of river bed precipitates, as a result of undersaturation caused by the dilution of river water with rainwater, with a physical transport of particles of river bed precipitates, due to the increase in the flow rate of river water. Comparative trends at the two sampling sites Figure 8 A shows the comparative trends of pH at the two sites RIV3 and RIV10. The maxima and minima of the curve during the non-rainy periods at the RIV10 site are shifted forward a few hours compared to the curve at the RIV3 site. Similar shifts are also observed for T (Fig. 8 B) and SC (Fig. 8 C). As previously explained, this is mainly due to the fact that the RIV3 site is located upstream in a mountainous area, while the RIV10 site is located several kilometers downstream near the Piscinas beach. Conclusions The effect of flow regime has very rarely been considered in water quality studies in mining-polluted rivers because such studies are normally carried out under stable low-flow conditions in the absence of rainfall. An interesting study conducted during rainfall runoff on a remediated stream reach (Runkel et al. 2016 ) demonstrated that a high release of metals was related to some hydrological mechanisms such as resuspension of streambed solids, erosion of alluvial tailings, and overland flow. Another study (Valencia-Avellan et al. 2017 ) simply confirmed the complexity of processes affecting the mobility of metals, particularly Pb, during rainfall events. In our study, the unexpected occurrence of intense rainfall during a week of automated continuous measurements of temperature (T), pH and specific conductance (SC) in a mining-polluted river, finalized to investigate the diel cycles of the above-cited parameters, produced a case of serendipity applied to hydrogeochemistry. Some interesting results can be summarized as follows: 1) precipitation of a solid phase from river water (specifically the “green rust” at the near-neutral RIV3 sampling site) can be inhibited during a rainy period due to a shift from oversaturated to saturated conditions, and in cases of strong dilution of river water with rainwater, it can also result in marked undersaturated conditions that favor dissolution processes of the solid phase previously precipitated in the riverbed; 2) to raise the acidic pH of river water (specifically a pH of 3.89 at the RIV10 sampling site located several kilometers downstream of the RIV3 site) by less than 0.5 pH units requires strong dilution with rainwater (about 70% by volume). Declarations Ethics approval and consent to participate Not applicable Consent for publication Not applicable Availability of data and material The datasets used during the current study are available from the corresponding author on reasonable request. Competing interests Not applicable Funding Not applicable Author contributions F.F. wrote the entire paper. Acknowledgement The author would like to thank the Autonomous Region of Sardinia and the University of Cagliari (Sardinia, Italy), which through the “Visiting Scientist” program (D.R. n.1026 of July 17, 2015) funded the project “Diel (24-hour) metal cycles in the Rio Irvi, Sardinia - Quantifying short-term geochemical processes in a metal-contaminated stream to facilitate long-term remediation” which allowed scientific collaboration with Dr. David A. Nimick (USGS researcher at the time of the project) who produced the data on which this paper is based.Special thanks to David A. Nimick for his teachings, collaboration on the project, and his enthusiasm and kindness. 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Frontiers in Microbiology 12:778199, 16 p. https://doi.org/10.3389/fmicb.2021.778199 Parkhurst DL, Appelo CAJ (2013) Description of input and examples for PHREEQC version 3 - A computer program for speciation, batch-reaction, one-dimensional transport, and inverse geochemical calculations: U.S. Geological Survey Techniques and Methods, book 6, chap. A43, 497 p. https://doi.org/10.3133/tm6A43 Rigonat N, Podda F, De Giudici G, Medas D (2019) Geochemical and mineralogical datasets on waters and stream precipitates from an abandoned mining site: Montevecchio-Ingurtosu district, Rio Irvi (SW Sardinia). Data in Brief 24:103951, 8 p. https://doi.org/10.1016/j.dib.2019.103951 Runkel RL, Kimball BA, Nimick DA, Walton-Day K (2016) Effects of flow regime on metal concentrations and the attainment of water quality standards in a remediated stream reach, Butte, Montana. Environmental Science & Technology 50(23):12641–12649. https://doi.org/10.1021/acs.est.6b03190 Valencia-Avellan M, Slack R, Stockdale A, Mortimer RJG (2017) Effect of episodic rainfall on aqueous metal mobility from historical mine sites. Environmental Chemistry 14(8) :469-475. https://doi.org/10.1071/EN17133 Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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19:24:14","extension":"html","order_by":20,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":78925,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-7786219/v1/6923b0e7ea8ceab2d5787620.html"},{"id":94226296,"identity":"65a86822-83b2-40c4-8adc-2ecdbc085f4a","added_by":"auto","created_at":"2025-10-23 19:40:13","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":216407,"visible":true,"origin":"","legend":"\u003cp\u003eSchematic map of the Arburese mining district (black square in the inset with Sardinia) showing the location of the Casargiu mine, the sampling site CAS1 at the water outlet from the Casargiu mining gallery, the sampling sites from RIV1 to RIV9 along the Rio Irvi, and the RIV10 sampling site after the confluence of Rio Irvi with Rio Piscinas. The latter was completely dry during the sampling period.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-7786219/v1/5313f607fded05173c3be2db.png"},{"id":94225722,"identity":"d52153e4-42fc-4a89-9ffb-4e275a0a2a05","added_by":"auto","created_at":"2025-10-23 19:32:13","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":1152905,"visible":true,"origin":"","legend":"\u003cp\u003eA: Water outlet from the Casargiu mining gallery (CAS1); B and C: The RIV3 sampling site in the Rio Irvi where “green rust” formation is evident; D: “Green rust” on 0.45 µm filter collected filtering water from the Rio Irvi at the RIV3 sampling site; E: Same filter as D after 24 hours where the colour change is due to oxidation of Fe(II), present in the composition of the “green rust”, to Fe(III).\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-7786219/v1/2177163aef522635a5d31ada.png"},{"id":94224842,"identity":"d53e5b06-e02b-46b4-a914-3ce7b14a97cd","added_by":"auto","created_at":"2025-10-23 19:24:13","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":905291,"visible":true,"origin":"","legend":"\u003cp\u003eA, B and D: The RIV10 sampling site in the Rio Irvi where precipitation of Fe(III)-hydroxides (HFO) is evident; C: HFO collected on 0.45 µm filter filtering water from the Rio Irvi at the RIV10 sampling site.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-7786219/v1/012e93c214259c8a017acece.png"},{"id":94224844,"identity":"f3d3ff0e-6b5f-46cd-b2cc-8e59d649e65c","added_by":"auto","created_at":"2025-10-23 19:24:13","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":343892,"visible":true,"origin":"","legend":"\u003cp\u003eComparative trends of temperature and specific conductance at the two sites RIV3 and RIV10 throughout the period of measurements with the multi-parameter sondes.\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-7786219/v1/79c97a9c155e1a421c51951b.png"},{"id":94226298,"identity":"2aa7575d-909f-4877-a07c-f9bdfc51d856","added_by":"auto","created_at":"2025-10-23 19:40:13","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":293326,"visible":true,"origin":"","legend":"\u003cp\u003eComparative trends of temperature and pH at the two sites RIV3 and RIV10 throughout the period of measurements with the multi-parameter sondes.\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-7786219/v1/12c388010423f2cb4c6ac6f1.png"},{"id":94225724,"identity":"d42075ca-5e78-46ac-9a30-5ecc72c1818f","added_by":"auto","created_at":"2025-10-23 19:32:13","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":99589,"visible":true,"origin":"","legend":"\u003cp\u003eMeasured and simulated pH trends at the RIV10 site during a rainfall period.\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-7786219/v1/6af0886cd85055488c3e6ae1.png"},{"id":94225730,"identity":"9efe78bc-bc61-4145-8963-49a239e336af","added_by":"auto","created_at":"2025-10-23 19:32:14","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":63465,"visible":true,"origin":"","legend":"\u003cp\u003eSimulated variation of saturation index (SI) of sulphate green rust at the RIV3 site as a consequence of dilution due to rainfall.\u003c/p\u003e","description":"","filename":"7.png","url":"https://assets-eu.researchsquare.com/files/rs-7786219/v1/9d27361396c401ffa92d9946.png"},{"id":94224867,"identity":"1525043e-aa6d-4dd3-8f8d-f0ee2ddf32dd","added_by":"auto","created_at":"2025-10-23 19:24:14","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":260769,"visible":true,"origin":"","legend":"\u003cp\u003eComparative trends of pH (A), temperature (B) and specific conductance (C) at the two sites RIV3 and RIV10 throughout the period of measurements with the multi-parameter sondes.\u003c/p\u003e","description":"","filename":"8.png","url":"https://assets-eu.researchsquare.com/files/rs-7786219/v1/f695533b844b80a4f5e7a22d.png"},{"id":97664549,"identity":"1e8d0491-ef6e-4fe6-a3c9-e93fad71ebc4","added_by":"auto","created_at":"2025-12-08 09:09:41","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":4206606,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7786219/v1/86c8820b-ca32-457b-81f2-c6a8d07052a5.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"A week of automated continuous measurements of temperature, pH and specific conductance in a mining-polluted river in Sardinia (Italy): The effect of rainfall as a case of serendipity","fulltext":[{"header":"Introduction","content":"\u003cp\u003ePresent and past mining activities often have a negative impact on surface and groundwater quality, and many studies report information on spatial variations of contaminants along a river and monitoring over a period that can span up to several years. On the other hand, short-term temporal variations (the so-called “diel cycling”) of contaminants and physical-chemical parameters have also been studied (Nimick et al. \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Frau et al. \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Gammons et al. \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2005a\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2015\u003c/span\u003e), but the results obtained are rarely used in characterization and monitoring plans of active and abandoned mine sites. In some cases, the diel variation of a certain parameter at various points along a river can be so high that in a standardized sampling that parameter may show an increasing or decreasing trend from upstream to downstream depending on whether the sampling is conducted from upstream to downstream or vice versa throughout the day. However, in most cases the diel variation of major ions and physical-chemical parameters (e.g. pH, Eh, specific conductance) is very low, but some trace elements (e.g. As, Zn, Mn) have been shown to be particularly sensitive to diel cycling so that, in heavily contaminated environmental contexts, the variation can even be in the order of tens of µg/L (Frau et al. \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Gammons et al. \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2007\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2015\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eRivers with variation of pH along the course from acidic to neutral or vice versa are particularly interesting because allow to better understand the diel behavior of trace elements, which, under near-neutral to alkaline conditions, is normally linked to reversible pH- and temperature-dependent adsorption processes (Nimick et al. \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2003\u003c/span\u003e; Jones et al. \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2004\u003c/span\u003e; Gammons et al. \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2005b\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2015\u003c/span\u003e), whereas under acidic conditions it is frequently controlled by light-sensitive and bacteria-mediated Fe redox reactions (McKnight et al. \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2001\u003c/span\u003e; Gammons et al. \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2005a\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2015\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eIn this article we report the results of a week of automated continuous measurements of temperature, pH and specific conductance in two different sampling points along the Rio Irvi (Sardinia, Italy), a river strongly affected by pollution related to past mining activity at the Casargiu mine. Although the initial idea was to collect physicochemical data for a sufficiently prolonged period under stable weather conditions, the unexpected occurrence of intense rainfall produced interesting results on the effects caused by the dilution of the Rio Irvi water with rainwater. This is a case of serendipity applied to environmental hydrogeochemistry.\u003c/p\u003e\n\u003ch3\u003eStudy area\u003c/h3\u003e\n\u003cp\u003eCasargiu is one of the abandoned mines belonging to the Montevecchio-Ingurtosu mining system in SW Sardinia (Italy) characterized by Pb-Zn sulfide veins hosted in Palaeozoic silicate-dominant rocks. Mineralization at Casargiu mainly consists of sphalerite with an ankerite-siderite gangue (Frau et al. \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). At Casargiu, exploitation reached 180 m below the elevation of the Casargiu gallery, whose entry is 158 m above sea level. The mine closure in the 1980s led to the shutdown of pumping systems needed to keep the galleries dry, thereafter a highly polluted drainage flowing out of the Casargiu gallery was observed beginning in 1997 (Frau et al., \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). The Casargiu drainage flows into the Rio Irvi that after about 6 km merges with the Rio Piscinas, which in turn flows into the Mediterranean Sea after about 2 km (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). The hydrological basin of the Rio Irvi has an area of about 15.4 km\u003csup\u003e2\u003c/sup\u003e and a length of about 11 km. Due to climatic conditions mainly characterized by long periods of heat and drought and relatively short rainy periods, the outflow from the Casargiu gallery (20–70 L/s) still represents the main water contribution to the Rio Irvi throughout the year (Frau et al. \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; De Giudici et al. \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2018\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Rigonat et al. \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Dore et al. \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e"},{"header":"Sampling and methods","content":"\u003cp\u003eTemperature, pH and specific conductance were measured every 15 minutes in two different sampling sites (RIV3 and RIV10) along the Rio Irvi (Figs.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e and \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e) using two in-situ multi-parameter sondes, which were calibrated before placement. Measurements at the RIV3 site (corresponding to the CAS4 sampling site in Frau et al. \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2015\u003c/span\u003e) began at 13:30 on 5 May 2016 and ended at 12:15 on 11 May 2016, while measurements at the RIV10 site (corresponding to the CAS9 sampling site in Frau et al. \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2015\u003c/span\u003e) began at 15:30 on 5 May 2016 and ended at 14:15 on 11 May 2016. On 5 May 2016 a complete water sampling was carried out at the two sites RIV3 and RIV10 (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e), while only temperature, pH, Eh, specific conductance and dissolved O\u003csub\u003e2\u003c/sub\u003e were measured at the other points along the Rio Irvi, starting from the Casargiu gallery (CAS1).\u003c/p\u003e\u003cdiv class=\"gridtable\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eChemical composition of Rio Irvi at the two sampling points RIV3 and RIV10. Milliequivalents per liter of Fe were calculated considering it as Fe\u003csup\u003e2+\u003c/sup\u003e. Δ is the charge balance error calculated as (Σcat – Σan)/(0.5 ∙ (Σcat + Σan)). TDS means Total Dissolved Solids. Alk is the alkalinity expressed as HCO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e−\u003c/sup\u003e.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003c/colgroup\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOld name\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eCAS4\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eCAS9\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNew name\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eRIV3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eRIV10\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFlow\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eL/s\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e55\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e58\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eT\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e°C\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e24.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e28.7\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEh\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003emV\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e183\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e498\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003epH\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6.29\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3.89\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCond\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003emS/cm\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4.11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4.19\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eO\u003csub\u003e2\u003c/sub\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003emg/L\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e7.23\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e7.36\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTDS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eg/L\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5.43\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e5.27\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCa\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003emg/L\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e390\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e370\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMg\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003emg/L\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e252\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e246\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNa\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003emg/L\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e78\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e93\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eK\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003emg/L\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e18\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCl\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003emg/L\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e87\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e132\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAlk\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003emg/L\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e65\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSO\u003csub\u003e4\u003c/sub\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003emg/L\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3525\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3450\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSiO\u003csub\u003e2\u003c/sub\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003emg/L\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e17.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e19.2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFe\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003emg/L\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e152\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e108\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMn\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003emg/L\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e70\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e68\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eZn\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003emg/L\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e775\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e770\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCd\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eµg/L\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2110\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1940\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePb\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eµg/L\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e140\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e660\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNi\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eµg/L\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2480\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2320\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSb\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eµg/L\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.37\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.21\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eµg/L\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1480\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1375\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCa\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003emeq/L\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e19.46\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e18.46\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMg\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003emeq/L\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e20.72\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e20.23\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNa\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003emeq/L\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3.39\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4.04\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eK\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003emeq/L\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.38\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.46\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCl\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003emeq/L\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.45\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3.72\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAlk\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003emeq/L\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.00\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eSO\u003csub\u003e4\u003c/sub\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003emeq/L\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e73.44\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e71.88\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFe\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003emeq/L\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5.44\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3.87\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMn\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003emeq/L\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.55\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.48\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eZn\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003emeq/L\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e23.71\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e23.56\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eΣcat\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003emeq/L\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e75.67\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e73.10\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eΣan\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003emeq/L\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e76.96\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e75.60\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eΔ\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-0.03\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/table\u003e\u003c/div\u003e\u003cp\u003eVariation (Var) of a parameter was defined as the difference between the maximum value (V\u003csub\u003emax\u003c/sub\u003e) and the minimum value (V\u003csub\u003emin\u003c/sub\u003e):\u003c/p\u003e\u003cp\u003eVar = V\u003csub\u003emax\u003c/sub\u003e - V\u003csub\u003emin\u003c/sub\u003e (1).\u003c/p\u003e\u003cp\u003eDelta percentage (D%) of a parameter was calculated according to the following equation:\u003c/p\u003e\u003cp\u003e[(V\u003csub\u003emax\u003c/sub\u003e – V\u003csub\u003emin\u003c/sub\u003e)/V\u003csub\u003emin\u003c/sub\u003e] * 100 (2).\u003c/p\u003e\u003cp\u003eSpeciation-solubility calculations were performed using the computer program PHREEQC Interactive (version 3.7.3.15968 released on December 2, 2021; Parkhurst and Appelo \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2013\u003c/span\u003e) with the included thermodynamic database ‘‘wateq4f.dat’’. The solubility product (\u003cem\u003eK\u003c/em\u003e\u003csub\u003esp\u003c/sub\u003e) of sulphate green rust (GR) was added to the thermodynamic database (Frau et al. \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2015\u003c/span\u003e).\u003c/p\u003e"},{"header":"Results and discussion","content":"\u003cdiv id=\"Sec5\" class=\"Section2\"\u003e\u003ch2\u003eTemperature-Specific Conductance relationship\u003c/h2\u003e\u003cp\u003eFigure \u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e shows the comparative trends of temperature (T) and specific conductance (SC) at the two sites RIV3 and RIV10 throughout the period of measurements with the multi-parameter sondes. In the time span before the first rainfall, at the RIV3 site a constant SC can be observed, while T follows the typical sinusoidal pattern related to the alternation between day and night (Var\u0026thinsp;=\u0026thinsp;9\u0026deg;C; D% = 58). As SC is a conductivity measurement corrected to 25\u0026deg;C, its invariance between day and night is expected, unless there are external water inputs. With the beginning of the first rainy period, it is interesting to note that the day-night thermal effect on T is cancelled out, while SC decreases abruptly three times due to dilution with rainwater but always returns to the initial value, first very quickly and then more gradually (about 30 hours). The rising speed of SC is obviously influenced by the amount of rain falling in the unit of time, always taking into account that the Rio Irvi for most of the year is mainly fed by groundwater coming out of the Casargiu gallery (CAS1). The rain on 9\u0026ndash;10 May almost halves SC which takes about 24 hours to return to its initial value. In this case it is interesting to note that the daily variation of T is less influenced by the rain, maintaining a general sinusoidal trend. Similar trends are observed at the RIV10 site, although here the SC measurements are more unstable and the curve strongly jagged. The main differences with RIV3 are that: i) the range of T is much wider (Var\u0026thinsp;=\u0026thinsp;18\u0026deg;C; D% = 165); ii) during the first rainy period SC decreases progressively instead of falling and rising; iii) the minimum SC is reached about 12 hours after the 9\u0026ndash;10 May rainfall. All this can be explained by the fact that the RIV10 site is several kilometers downstream of RIV3, it is located in the coastal plain quite close to the sea, it is less readily affected by groundwater input from CAS1 and collects a larger volume of runoff during rainfall.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eTemperature-pH relationship\u003c/h3\u003e\n\u003cp\u003eFigure \u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e shows the comparative trends of temperature (T) and pH at the two sites RIV3 and RIV10 throughout the period of measurements with the multi-parameter sondes. At the RIV3 site the pH is mildly acidic, ranging from 5.75 to 6.45 (Var\u0026thinsp;=\u0026thinsp;0.70; D% = 12), and its trend is highly symmetrical to the T trend. A discordant T-pH trend is also present at the RIV10 site where the pH is acidic, ranging from 3.76 to 4.34 (Var\u0026thinsp;=\u0026thinsp;0.58; D% = 15). This discordant relation between T and pH has already been shown in other studies but is still rather uncommon since the literature generally reports a concordant T-pH relation linked to the photosynthesis-respiration cycles of aquatic life (at least in rivers with neutral or slightly alkaline pH) according to the following reactions where (org) and (aq) stand for organic and aqueous, respectively (Gammons et al. \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2015\u003c/span\u003e):\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\n\u003ch3\u003edaytime T increase\u003c/h3\u003e\n\u003cp\u003ephotosynthesis: CO\u003csub\u003e2\u003c/sub\u003e\u0026thinsp;+\u0026thinsp;H\u003csub\u003e2\u003c/sub\u003eO\u0026thinsp;+\u0026thinsp;sunlight \u0026rarr; CH\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e(org)\u003c/sub\u003e\u0026thinsp;+\u0026thinsp;O\u003csub\u003e2\u003c/sub\u003e (3)\u003c/p\u003e\u003cp\u003epH increase: HCO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e\u0026minus;\u003c/sup\u003e + H\u003csup\u003e+\u003c/sup\u003e \u0026rarr; CO\u003csub\u003e2(aq)\u003c/sub\u003e\u0026thinsp;+\u0026thinsp;H\u003csub\u003e2\u003c/sub\u003eO (4)\u003c/p\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003enighttime T decrease\u003c/h2\u003e\u003cp\u003erespiration: CH\u003csub\u003e2\u003c/sub\u003eO\u003csub\u003e(org)\u003c/sub\u003e\u0026thinsp;+\u0026thinsp;O\u003csub\u003e2\u003c/sub\u003e \u0026rarr; CO\u003csub\u003e2\u003c/sub\u003e\u0026thinsp;+\u0026thinsp;H\u003csub\u003e2\u003c/sub\u003eO (5)\u003c/p\u003e\u003cp\u003epH decrease: CO\u003csub\u003e2(aq)\u003c/sub\u003e\u0026thinsp;+\u0026thinsp;H\u003csub\u003e2\u003c/sub\u003eO \u0026rarr; HCO\u003csub\u003e3\u003c/sub\u003e\u003csup\u003e\u0026minus;\u003c/sup\u003e + H\u003csup\u003e+\u003c/sup\u003e (6).\u003c/p\u003e\u003cp\u003eEven in metal-polluted rivers where there may be very little aquatic life, the effect of temperature on CO\u003csub\u003e2\u003c/sub\u003e solubility would lead to the result described above in each case. However, if we focus on the production-consumption of O\u003csub\u003e2\u003c/sub\u003e related to the photosynthesis-respiration cycles, other oxidation-reduction reactions can be influenced such as those involving the Fe species that, together with SO\u003csub\u003e4\u003c/sub\u003e, Zn, Mg and Ca, dominate the chemical composition of the Rio Irvi water (Frau et al. \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). In particular, when the following reactions are considered:\u003c/p\u003e\u003cp\u003eFe\u003csup\u003e2+\u003c/sup\u003e + 0.25O\u003csub\u003e2\u003c/sub\u003e\u0026thinsp;+\u0026thinsp;H\u003csup\u003e+\u003c/sup\u003e \u0026harr; Fe\u003csup\u003e3+\u003c/sup\u003e + 0.5H\u003csub\u003e2\u003c/sub\u003eO (7)\u003c/p\u003e\u003cp\u003eFe\u003csup\u003e3+\u003c/sup\u003e + 3H\u003csub\u003e2\u003c/sub\u003eO \u0026harr; Fe(OH)\u003csub\u003e3(am)\u003c/sub\u003e\u0026thinsp;+\u0026thinsp;3H\u003csup\u003e+\u003c/sup\u003e (8)\u003c/p\u003e\u003cp\u003eFe\u003csup\u003e2+\u003c/sup\u003e + 0.25O\u003csub\u003e2\u003c/sub\u003e\u0026thinsp;+\u0026thinsp;2.5H\u003csub\u003e2\u003c/sub\u003eO \u0026harr; Fe(OH)\u003csub\u003e3(am)\u003c/sub\u003e\u0026thinsp;+\u0026thinsp;2H\u003csup\u003e+\u003c/sup\u003e (9)\u003c/p\u003e\u003cp\u003ewhere (am) stands for amorphous and reaction (9) is the combination of reactions (7) and (8), it is apparent that daytime O\u003csub\u003e2\u003c/sub\u003e production from photosynthesis shifts the reaction (9) to the right, generating acidity, while nighttime O\u003csub\u003e2\u003c/sub\u003e consumption from respiration shifts the reaction (9) to the left or simply slows it down, consuming or not-producing acidity and partially redissolving the previously precipitated Fe(III)-hydroxide. As described in a previous study (Frau et al. \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2015\u003c/span\u003e), the reaction (9) predominates at the RIV10 site, while the RIV3 site is characterized by the precipitation of \u0026ldquo;green rust\u0026rdquo; (GR) according to the following reaction:\u003c/p\u003e\u003cp\u003e6Fe\u003csup\u003e2+\u003c/sup\u003e + SO\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e2\u0026minus;\u003c/sup\u003e + 0.5O\u003csub\u003e2\u003c/sub\u003e\u0026thinsp;+\u0026thinsp;19H\u003csub\u003e2\u003c/sub\u003eO \u0026harr; Fe\u003csup\u003eII\u003c/sup\u003e\u003csub\u003e4\u003c/sub\u003eFe\u003csup\u003eIII\u003c/sup\u003e\u003csub\u003e2\u003c/sub\u003e(OH)\u003csub\u003e12\u003c/sub\u003e(SO\u003csub\u003e4\u003c/sub\u003e) ∙ 8H\u003csub\u003e2\u003c/sub\u003eO\u0026thinsp;+\u0026thinsp;10H\u003csup\u003e+\u003c/sup\u003e (10)\u003c/p\u003e\u003cp\u003ewhich is analogous to reaction (9) in determining the pH trend opposite to the T trend. In both cases the effect of temperature on O\u003csub\u003e2\u003c/sub\u003e solubility should not be so important since O\u003csub\u003e2\u003c/sub\u003e is much less soluble in water than CO\u003csub\u003e2\u003c/sub\u003e.\u003c/p\u003e\u003cp\u003eAn opposite relation between T and pH could also be due to photoreduction of aqueous Fe(III) according to such a reaction:\u003c/p\u003e\u003cp\u003eFe\u003csup\u003e3+\u003c/sup\u003e + 0.5H\u003csub\u003e2\u003c/sub\u003eO\u0026thinsp;+\u0026thinsp;sunlight \u0026rarr; Fe\u003csup\u003e2+\u003c/sup\u003e + 0.25O\u003csub\u003e2\u003c/sub\u003e\u0026thinsp;+\u0026thinsp;H\u003csup\u003e+\u003c/sup\u003e (11).\u003c/p\u003e\u003cp\u003eGammons et al. (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2005a\u003c/span\u003e) also suggested the importance of aqueous Fe\u003csup\u003e3+\u003c/sup\u003e speciation in determining a diel cycle of pH analogous to that described in this paper, according to the following reaction:\u003c/p\u003e\u003cp\u003eFe(SO\u003csub\u003e4\u003c/sub\u003e)\u003csup\u003e+\u003c/sup\u003e + 0.5H\u003csub\u003e2\u003c/sub\u003eO \u0026harr; Fe\u003csup\u003e2+\u003c/sup\u003e + SO\u003csub\u003e4\u003c/sub\u003e\u003csup\u003e2\u0026minus;\u003c/sup\u003e + 0.25O\u003csub\u003e2\u003c/sub\u003e\u0026thinsp;+\u0026thinsp;H\u003csup\u003e+\u003c/sup\u003e (12).\u003c/p\u003e\u003cp\u003eHowever, Fe speciation at both RIV3 and RIV10 sites is by far dominated by the free Fe\u003csup\u003e2+\u003c/sup\u003e ion, while the dominant Fe(III) species are Fe(OH)\u003csub\u003e2\u003c/sub\u003e\u003csup\u003e+\u003c/sup\u003e and Fe(SO\u003csub\u003e4\u003c/sub\u003e)\u003csup\u003e+\u003c/sup\u003e, respectively, but with concentrations 3\u0026ndash;4 orders of magnitude lower than Fe\u003csup\u003e2+\u003c/sup\u003e. Therefore, it seems very unlikely that changes in pH during 24 hours are determined by the formation/dissociation of the aqueous Fe(SO\u003csub\u003e4\u003c/sub\u003e)\u003csup\u003e+\u003c/sup\u003e complex.\u003c/p\u003e\u003cp\u003eThere is no doubt that the complex biological/microbial activity present in the Rio Irvi, which is still at an early stage of study and understanding, has a decisive influence on the Fe (and other metals) cycle in solution and in precipitates, and consequently also on pH (see e.g. Morris et al. \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e2005\u003c/span\u003e; Gammons et al. \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Lueder et al. \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Paganin et al. \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eRainfall effect\u003c/h3\u003e\n\u003cp\u003eIt is also interesting to observe the effect of the first rainfall period in which T and pH remain almost constant at the RIV3 site, while at the RIV10 site a relative constancy of T is accompanied by a clear increase in pH. This can be explained by the fact that dilution with rainwater, to which a pH of 5.65 (pure rain in equilibrium with atmospheric CO\u003csub\u003e2\u003c/sub\u003e) can be attributed, does not substantially change the mildly acidic pH of the river water at the RIV3 site, while it causes the increase of the markedly acidic pH at the RIV10 site. A simulation was carried out with PHREEQC to estimate the volume of rain needed to raise the pH at the RIV10 site; Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e shows that, starting from pH 3.89 in the absence of rain, a progressive mixing of rain up to 70% of the water flowing in the Rio Irvi is needed to achieve pH 4.30 at the end of the rainfall period from 7 to 8 May. It is evident that the slope of the two curves shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e cannot be the same as the simulation does not take into account the time as a variable in the mixing of river water and rainwater.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eThe effect of rainfall on river chemistry can potentially influence the precipitation/dissolution of a mineral phase, especially when it is an unstable phase as in the case of the formation of GR in the first stretch of the Rio Irvi, where Fe(II) still persists into solution together with Fe(III). To highlight this process, a simulation was carried out with PHREEQC. Figure\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e7\u003c/span\u003e shows that, starting from the chemical composition at the RIV3 site reported in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, the initial oversaturation (SI\u0026thinsp;=\u0026thinsp;0.72) with respect to GR progressively shifts to saturation (SI = -0.02) and then to a marked undersaturation (SI = -1.21) when respectively 40% and 70% of the water flowing in the Rio Irvi is represented by rain. This process may be periodically important in contributing to the metal load discharged from the Rio Irvi and other polluted rivers to the sea (Frau et al. \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Indeed, a phenomenon of partial removal of Fe precipitates from the Rio Irvi bed has sometimes been observed during heavy rainfall. In that case there is a probable concomitance of a dissolution process of river bed precipitates, as a result of undersaturation caused by the dilution of river water with rainwater, with a physical transport of particles of river bed precipitates, due to the increase in the flow rate of river water.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\n\u003ch3\u003eComparative trends at the two sampling sites\u003c/h3\u003e\n\u003cp\u003eFigure \u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003eA shows the comparative trends of pH at the two sites RIV3 and RIV10. The maxima and minima of the curve during the non-rainy periods at the RIV10 site are shifted forward a few hours compared to the curve at the RIV3 site. Similar shifts are also observed for T (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003eB) and SC (Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e8\u003c/span\u003eC). As previously explained, this is mainly due to the fact that the RIV3 site is located upstream in a mountainous area, while the RIV10 site is located several kilometers downstream near the Piscinas beach.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eThe effect of flow regime has very rarely been considered in water quality studies in mining-polluted rivers because such studies are normally carried out under stable low-flow conditions in the absence of rainfall. An interesting study conducted during rainfall runoff on a remediated stream reach (Runkel et al. \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2016\u003c/span\u003e) demonstrated that a high release of metals was related to some hydrological mechanisms such as resuspension of streambed solids, erosion of alluvial tailings, and overland flow. Another study (Valencia-Avellan et al. \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2017\u003c/span\u003e) simply confirmed the complexity of processes affecting the mobility of metals, particularly Pb, during rainfall events.\u003c/p\u003e\u003cp\u003eIn our study, the unexpected occurrence of intense rainfall during a week of automated continuous measurements of temperature (T), pH and specific conductance (SC) in a mining-polluted river, finalized to investigate the diel cycles of the above-cited parameters, produced a case of serendipity applied to hydrogeochemistry. Some interesting results can be summarized as follows: 1) precipitation of a solid phase from river water (specifically the \u0026ldquo;green rust\u0026rdquo; at the near-neutral RIV3 sampling site) can be inhibited during a rainy period due to a shift from oversaturated to saturated conditions, and in cases of strong dilution of river water with rainwater, it can also result in marked undersaturated conditions that favor dissolution processes of the solid phase previously precipitated in the riverbed; 2) to raise the acidic pH of river water (specifically a pH of 3.89 at the RIV10 sampling site located several kilometers downstream of the RIV3 site) by less than 0.5 pH units requires strong dilution with rainwater (about 70% by volume).\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003e\u003cem\u003eEthics approval and consent to participate\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eConsent for publication\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eAvailability of data and material\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets used during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eCompeting interests\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eFunding\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eAuthor contributions\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eF.F. wrote the entire paper.\u003c/p\u003e\n\u003ch2\u003eAcknowledgement\u003c/h2\u003e\n\u003cp\u003eThe author would like to thank the Autonomous Region of Sardinia and the University of Cagliari (Sardinia, Italy), which through the “Visiting Scientist” program (D.R. n.1026 of July 17, 2015) funded the project “Diel (24-hour) metal cycles in the Rio Irvi, Sardinia - Quantifying short-term geochemical processes in a metal-contaminated stream to facilitate long-term remediation” which allowed scientific collaboration with Dr. David A. Nimick (USGS researcher at the time of the project) who produced the data on which this paper is based.Special thanks to David A. Nimick for his teachings, collaboration on the project, and his enthusiasm and kindness.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eDe Giudici G, Medas D, Cidu R, Lattanzi P, Podda F, Frau F, Rigonat N, Pusceddu C, Da Pelo S, Onnis P, Marras PA, Wanty RB, Kimball B (2018) Application of hydrologic-tracer techniques to the Casargiu adit and Rio Irvi (SW-Sardinia, Italy): Using enhanced natural attenuation to reduce extreme metal loads. Applied Geochemistry 96:42-54. https://doi.org/10.1016/j.apgeochem.2018.06.004 \u003c/li\u003e\n\u003cli\u003eDe Giudici G, Medas D, Cidu R, Lattanzi P, Rigonat N, Frau I, Podda F, Marras PA, Dore E, Frau F, Rimondi V, Runkel RL, Wanty RB, Kimball B (2019) Assessment of origin and fate of contaminants along mining-affected Rio Montevecchio (SW Sardinia, Italy): A hydrologic-tracer and environmental mineralogy study. Applied Geochemistry 109:104420, 12 p. https://doi.org/10.1016/j.apgeochem.2019.104420 \u003c/li\u003e\n\u003cli\u003eDore E, Fancello D, Rigonat N, Medas D, Cidu R, Da Pelo S, Frau F, Lattanzi P, Marras PA, Meneghini C, Podda F, Rimondi V, Runkel RL, Kimball B, Wanty RB, De Giudici G (2020) Natural attenuation can lead to environmental resilience in mine environment. 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Science of The Total Environment 373(1):344-355. https://doi.org/10.1016/j.scitotenv.2006.11.008 \u003c/li\u003e\n\u003cli\u003ePaganin P, Alisi C, Dore E, Fancello D, Marras PA, Medas D, Montereali MR, Naitza S, Rigonat N, Sprocati AR, Tasso F, Vacca S, De Giudici G (2021) Microbial diversity of bacteria involved in biomineralization processes in mine-impacted freshwaters. Frontiers in Microbiology 12:778199, 16 p. https://doi.org/10.3389/fmicb.2021.778199 \u003c/li\u003e\n\u003cli\u003eParkhurst DL, Appelo CAJ (2013) Description of input and examples for PHREEQC version 3 - A computer program for speciation, batch-reaction, one-dimensional transport, and inverse geochemical calculations: U.S. Geological Survey Techniques and Methods, book 6, chap. A43, 497 p. https://doi.org/10.3133/tm6A43\u003c/li\u003e\n\u003cli\u003eRigonat N, Podda F, De Giudici G, Medas D (2019) Geochemical and mineralogical datasets on waters and stream precipitates from an abandoned mining site: Montevecchio-Ingurtosu district, Rio Irvi (SW Sardinia). Data in Brief 24:103951, 8 p. https://doi.org/10.1016/j.dib.2019.103951 \u003c/li\u003e\n\u003cli\u003eRunkel RL, Kimball BA, Nimick DA, Walton-Day K (2016) Effects of flow regime on metal concentrations and the attainment of water quality standards in a remediated stream reach, Butte, Montana. Environmental Science \u0026amp; Technology 50(23):12641\u0026ndash;12649. https://doi.org/10.1021/acs.est.6b03190\u003c/li\u003e\n\u003cli\u003eValencia-Avellan M, Slack R, Stockdale A, Mortimer RJG (2017) Effect of episodic rainfall on aqueous metal mobility from historical mine sites. Environmental Chemistry \u003cstrong\u003e14(8)\u003c/strong\u003e:469-475. https://doi.org/10.1071/EN17133\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Mining-polluted river, Diel cycles, Automated continuous measurements, Rainfall effects, Hydrogeochemical serendipity","lastPublishedDoi":"10.21203/rs.3.rs-7786219/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7786219/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThis study is an example of serendipity applied to hydrogeochemistry. Starting with the aim of continuously measuring for one week some parameters (temperature, pH and specific conductance) at two different sampling points along a river heavily contaminated by past mining activity, due to the occurrence of an undesirable climatic change consisting of heavy rainfall distributed over the week of measurements, unexpected hydrogeochemical data were collected that required a different processing and interpretation approach from the standardized one that was thought to apply when the above study was conceived for stable climatic conditions.\u003c/p\u003e","manuscriptTitle":"A week of automated continuous measurements of temperature, pH and specific conductance in a mining-polluted river in Sardinia (Italy): The effect of rainfall as a case of serendipity","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-10-23 19:24:09","doi":"10.21203/rs.3.rs-7786219/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"dbf6a47a-6ecf-4904-9ee1-e04689571777","owner":[],"postedDate":"October 23rd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":56641330,"name":"Earth and environmental sciences/Climate sciences"},{"id":56641331,"name":"Earth and environmental sciences/Environmental sciences"},{"id":56641332,"name":"Earth and environmental sciences/Hydrology"}],"tags":[],"updatedAt":"2025-12-03T14:09:15+00:00","versionOfRecord":[],"versionCreatedAt":"2025-10-23 19:24:09","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7786219","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7786219","identity":"rs-7786219","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}