# Assessment of the water quality in the coastal Yaqui valley (Mexico): implications for human health and ecological risks.

Aurélie Barats, Christophe Renac, Sofia Garrido-Hoyos, Beatriz

Gonzalez-Perez, Karina Garcia. Mendoza, Maria Vicenta Esteller-Alberich,

Martin Enrique Jara-Marini, Ariosto Aguilar-Chavez

► To cite this version:

Aurélie Barats, Christophe Renac, Sofia Garrido- Hoyos, Beatriz Gonzalez-Perez, Karina Garcia. Mendoza, et al.. Assessment of the water quality in the coastal Yaqui valley (Mexico): implications for human health and ecological risks.. Environmental Research, 2024, 264 (1), pp.120275. 10.1016/j.envres.2024.120275. hal-04784709

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Assessment of the water quality in the coastal Yaqui valley (Mexico): implications for human health and ecological risks.

Aurélie BARATS, Christophe RENAC, Sofia GARRIDO- HOYOS, Beatriz GONZALEZ-PEREZ, Karina GARCIA. MENDOZA, Maria Vicenta ESTELLER-ALBERICH, Martin Enrique JARA-MARINI, Ariosto AGUILAR-CHAVEZ

PII: S0013-9351(24)02182-0

DOI: https://doi.org/10.1016/j.envres.2024.120275

Reference: YENRS 120275

To appear in: *Environmental Research*

Received Date: 11 July 2024

Revised Date: 14 October 2024

Accepted Date: 30 October 2024

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Please cite this article as: BARATS, A., RENAC, C., GARRIDO- HOYOS, S., GONZALEZ-PEREZ, B., MENDOZA, K.G., ESTELLER-ALBERICH, M.V., JARA-MARINI, M.E., AGUILAR-CHAVEZ, A., Assessment of the water quality in the coastal Yaqui valley (Mexico): implications for human health and ecological risks., *Environmental Research*, https://doi.org/10.1016/j.envres.2024.120275.

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# Assessment of the water quality in the coastal Yaqui valley (Mexico): implications for human health and ecological risks.

Aurélie BARATS¹*, Christophe RENAC¹, Sofia GARRIDO-HOYOS², Beatriz GONZALEZ-PEREZ³, Karina GARCIA MENDOZA², Maria Vicenta ESTELLER-ALBERICH³, Martin Enrique JARA-MARINI⁴, Ariosto AGUILAR-CHAVEZ²

¹ Université Côte d'Azur, Observatoire de la Côte d'Azur, CNRS, IRD, Géoazur, 250 rue Albert Einstein, 06560 Valbonne, France

² Mexican Institute of Water Technology (IMTA), Paseo Cuauhnhuac 8532, Morelos, Jiutepec, Mexico

³ Instituto de Tecnología y Ciencias del Agua (ITCA). Universidad Autónoma del Estado de México, Carretera Toluca-Ixtlahuaca km 14.5 Toluca, Estado de México, México

⁴ Centro de Investigación en Alimentación y Desarrollo. Unidad Hermosillo. Carretera Gustavo Astiazarán Rosas 46, Colonia La Victoria, Hermosillo 83304, Sonora, Mexico

*Corresponding author: aurelie.barats@univ-cotedazur.fr

## Abstract

This study examines the water quality in the Yaqui Valley in Mexico, a semi-arid region impacted by mining, agriculture, and aquaculture. Contamination sources, health risks and ecological impacts are investigated. Freshwater was found to be contaminated by dissolved As, presumed to result from mining activities in the mountains. Drainage water revealed an overall contamination by dissolved As and by suspended particles enriched with Al, Fe and Mn, associated with runoff processes. Intermittent contamination of drainage water by Cu, K⁺, NO₃⁻ and PO₄³⁻ is attributed to the use of fertilizers or pesticides. In the coastal area, drainage water contains high concentrations of Na, Ca, SO₄²⁻ and Cl⁻, related to salinization processes, as well as higher concentrations of dissolved As, related to solid/liquid interactions that are enhanced by salinization. This drainage water discharges into the bay, degrading the seawater quality and increasing ecological risks. Outputs of this study can serve as a

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reference for the protection of this economically important coastal ecosystem. Concerning health risks, this study demonstrates that groundwater is also contaminated by dissolved As, believed to be associated with transfers from the geological basement to the dissolved phase of water, and other major chemicals related to salinization processes. The findings indicate that ingesting the groundwater poses a significant risk to human health with a primary exposure risk associated with dissolved As, particularly among children. This study presents crucial data for the Yaqui population, water managers and researchers, and provides novel insights into the management and mitigation of the identified risks.

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## Keywords

Water, quality, potential toxic element, transfer, flux, risks

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# 1. Introduction

About 70-75% of global marine pollution is the result of human activities. The importance of the contribution of rivers to the sea pollution was recognized early by the Food and Agriculture Organization of the United Nations (Rome, December 8-9, 1970). Rivers carry both organic and inorganic contaminants, from mining activities (acid solutions, metals, As), agriculture (pesticides, metals and nutrients) and other human activities (HAP, PCB, dioxins, oils and others). These contaminants induce irreversible consequences: transformation and deterioration of ecosystems and harmful effects on human health. In coastal hydrosystems, water resources are subjected to seawater intrusion related to the sea level rise and groundwater overexploitation, or due to managed aquifer recharge leading to restrained seawater intrusion. These processes degrade of the water quality due to water/mineral interactions and result in the release of metals and metalloids (especially As) into water resources (Dehbandi et al., 2019; Papazotos et al., 2020; Yuan et al., 2023).

In coastal area, the assessment of water quality is crucial for the sustainable management of water resources. Diverse tools are usually implemented for this task: ecological indicators, pollution indices, or human health risk assessment indices. An assessment of biodiversity (fishes, vegetables, etc.) can be performed to determine the water quality (Dippong et al., 2023; Dippong et al., 2024b). Water quality index and heavy metal pollution indices are also good tools used to examine the pollution status of water resource in various countries around the world (Dippong et al., 2022; Dippong et al., 2024a; Dippong and Resz, 2024b; Edet and Offiong, 2002; Ghaderpoori et al., 2018; Gopinath et al., 2019b; Jehan et al., 2020; Khadija et al., 2021; Khanoranga and Khalid, 2019; Mihali and Dippong, 2023; Mukate et al., 2019). Heavy metal pollution indices are more specific than the water quality index because they only take into account concentrations of the most toxic trace elements (Cr, Co, Ni, Cu, Zn,
Cd, Hg, Mn, Fe, and As) present in water. Metals and metalloids in coastal environments is one of the world's most harmful toxins (Hossain et al., 2020; Jannat et al., 2023; Kahal et al., 2020; Nour et al., 2019). Their persistence, non-biodegradability, bioaccumulation, toxicity, and environmental danger to life forms in aquatic ecosystems have attracted wide attention in the scientific community (Islam and Habibullah-Al-Mamun, 2017; Shaheen et al., 2016; Zhang et al., 2019). They tend to accumulate in soil, plants, and animals before entering humans via ingestion, cutaneous, or inhalation routes, creating persistently harmful effects on human health even at low levels of chronic exposure. The nature and the probability of adverse health effects in humans exposed to contaminated waters are usually evaluated with different human health risk indices such as the chronic daily intake and the hazard quotient (Dippong et al., 2024b; Kavcar et al., 2009). The carcinogenic risk due to exposure to a specific dose of metals and As can also be evaluated using the Incremental Lifetime Cancer Risk (Mohammadi et al., 2019). This risk is defined as the incremental probability of a person developing any type of cancer over their lifetime.

This study focused on the Yaqui Valley, an irrigated agricultural plain located between the Gulf of California and the Mountain of Sierra Madre Occidental (Fig. 1: longitude 108°53′ and 110°37′ west and latitude 26°53′ and 28°37′ north). In this valley, the city of Obregon is the largest population center in the Mexican state of Sonora. The area lies partly in the world desert belt, and consequently suffers arid climatic conditions. In Obregon city, the annual temperature averages 25.6 °C, rainfall ranges from 300 to 400 mm.y⁻¹, and evaporation from 2000 to 2600 mm.y⁻¹. Despite the sub-desert climatic conditions, agriculture and farming have been intensively developed in the Yaqui valley since the beginning of the twentieth century (e.g. the second state in Mexico in terms of for wheat crop and pork farming). The state of Sonora is also an area of economic importance for other anthropic activities: mining (the top state in Mexico, and the eighth country of the world), and for aquaculture (the top state for shrimp production).

In this region, the challenge of water resource management is to maintain economic activities while ensuring sustainability (McKinney et al., 2006). In the upper part of the Yaqui hydrosystem, mining activities occur and the runoff of the Yaqui river is regulated by four hydroelectric dams. The downstream dam mainly supplies water for agricultural use to the DR041 Río Yaqui irrigation district, an area of 2320 km², with an annual volume of 1600 Mm³. Only 49 Mm³ of water are delivered for urban public use. Downstream of this dam, there is no natural hydrosystem. The main network of channels is made up of the “high” and “low” channels with maximum capacities of 80 and 120 m³.s⁻¹, respectively. The high-channel covers the eastern part of the district and the low-channel covers the western part. Irrigation is restricted to the dry season, which runs from November to March, and is associated with the growing season of winter wheat. The high and low channels provide about 47% and 53% of the irrigation water, respectively, in the DR041 district, with the rest provided by rainfall and groundwater. In addition to the freshwater supplied by the dam, groundwater from 150 wells is used to
irrigate the Yaqui irrigation district and ensure the agricultural productivity of this economic region. This groundwater pumping usually represents from 2% to 20% of the total volume of water used for irrigation and up to 50% during drought (e.g. winter and summer 2004).

Previous studies on the hydrology of the DR041 district suggested interactions between infiltrated irrigation water and the aquifer or evaporation processes (Schoups et al., 2006; Schoups et al., 2005). With a total thickness varying from 50 to 250 m, three aquifer levels occur: the surface aquifer with a shallow horizon (0 to 5 m deep) of soils (clay-rich, gravel and sand); the upper alluvial aquifer (from 5 to ca. 100 m deep); and the lower aquifer (ca. 100 to 250 m deep) located above unconsolidated carbonate, basements of granite, and volcanic rocks (Grijalva-Montoya et al., 2011). Leaking channels, drainage systems, and flooded soils can episodically influence the recharge of the unconfined shallow horizon and upper aquifer. The Yaqui valley aquifer was recently demonstrated to be moderately recharged by infiltrated irrigation water (Almazán et al., 2022). Due to a high water table in the lower part of the irrigation district, inputs of groundwater reduce the salinity in soils. The excess water (runoff, shallow water table) is collected by a network of open drainage ditches of 1 to 2 m below the land surface, and subsurface drainage pipes. In this AR16 irrigation district, a total of 24% of all irrigation water is used for crops, 16% for aquifer recharge, and 60% is discharged into the bay through runoff of the drainage system (Almazán et al., 2022). Drainage water further discharges into the Tobari bay, used for aquaculture, and also a reservoir for nesting birds (Jara-Marini et al., 2020). This bay has been defined as a RAMSAR site by the Convention on Wetlands and declared by the Hemispheric Shorebird Reserves Network as a site of “International” importance. The inputs of drainage water into the Tobari bay have been estimated at around 350-450 $hm^3$ per year (Escofet and Bravo-Peña, 2007; Schoups et al., 2006). Maximum discharges occur at the end of January, the beginning of March and April and the end of November (Michael Beman et al., 2005), during periods of irrigation and discharge from aquaculture farms.

In Sonora, mining and agriculture activities are responsible for significant pollution of all compartments of the environment. Soils and subsequently the waters draining from this irrigation district are contaminated by pesticides, metals and metalloids (labelled PTEs, potential toxic elements) mainly due to mining activity in the upper part of the watershed and agriculture in the lower part (Cantu-Soto et al., 2011; Meza-Montenegro et al., 2012b; Rodrigo et al., 1996). Most PTEs released by mining activities are suggested to be trapped in dams because they occur mostly in particulate forms. Groundwater used for human consumption is also highly contaminated by PTEs, nutrients, pesticides and an increased salinity. These contaminants, particularly organochlorine, Pb and As, pose high health risks for the inhabitants of this region, especially children (Eskenazi et al., 1999; García-Rico et al., 2019; Meza-Montenegro et al., 2012b; Vega-Millán et al., 2021). Water from agricultural drains or other effluents are responsible for large inputs of contaminants into the Tobari lagoon, specifically fertilizers or other contaminants associated with mining, municipal sewage, farming, agriculture, burning of fossil
fuels, and atmospheric deposition (Gortáres-Moroyoqui et al., 2011; Jara-Marini et al., 2020; McCullough and Matson, 2016; Páez-Osuna et al., 2017). Unfortunately, aquaculture activities and fishing are also highly developed in this lagoon. All these inputs of contaminated water create ecological risks, with a degradation of coastal habitats, that has consequences for mangroves, breeding, and so on (Ruiz-Ruiz et al., 2023). In the Tobari bay, sediments are contaminated by PTEs (Jara-Marini et al., 2013b). Primary producers and primary consumers act as the main vectors in the trophic flux of contaminants, including metals (Ruelas-Inzunza and Páez-Osuna, 2008; Ruelas-Inzunza et al., 2014; Vizzini et al., 2013). Trace metal trophic transfer and biomagnification occur in marine organisms all along the food web (Jara-Marini et al., 2020; Jara-Marini et al., 2008; Jara-Marini et al., 2009; Jara-Marini et al., 2013a).

This investigation is focused on the quality of water resources in this Mexican coastal region. First, physicochemical parameters and the chemical composition of water samples (major ions and elements, and PTEs, such as metals and As) will be thoroughly monitored for a three years periods to better estimate the pollution status of water resources before entering the bay. New methodologies (statistical analyses, water quality index, pollution indices) will be applied to constrain the origin of the pollution, the degradation of water quality, and the mobility of PTEs. Second, the human health risks will be assessed using hazard quotients and incremental lifetime cancer risk estimates. This approach makes it possible, not only to identify the chemicals that pose a major risk but also to estimate the specific risks to health. The findings are expected to provide insights into how groundwater responds to stress from human activities, offering valuable recommendations for population health risk prevention and sustainable practices. The final purpose of this study concerns the assessment of PTE inputs from drainage waters into the Tobari bay, as previously mentioned a protected ecosystem due to its rich biodiversity and also a location with intense aquaculture. This research will provide new results on the degradation of the seawater quality, contributing to the prevention of future pollution and the preservation of this protected bay.

## 2. Materials and methods

### 2.1. Sampling strategy and field measurements

The DR041 Río Yaqui irrigation district is constituted by different agricultural modules with a secondary network of 10 drains distributing freshwater from the high and low channels. This study focuses on the AR16 module and its main drain, which collects irrigation returns and is one of the 5 drains reaching the Tobari bay (Fig. 1). This AR16 agricultural module has been selected as it is one of the most densely populated, with an estimated 4650 inhabitants, and it represents the largest irrigated surface area. This AR16 agricultural system of 209 km² is equivalent to approximately one tenth of the total DR041 irrigation district surface of which 196 km² was examined in this study. The unanalyzed area, between AR16-15 and the lagoon, represents 18.3 km², less than 10 % of the total surface of the
AR16 area. A network of channels irrigates agricultural modules of 0.04 to 0.4 km², while drains and ditches collect the water runoff from crop fields. The main drain, AR16, receives waters for different tributaries (TD). This drainage network also transports untreated municipal sewage discharge. All modules are not irrigated continuously, but at four periods per year for two or three weeks during November-December and March that correspond to the sowing of wheat and the growth of wheat seeds. The rest of the year, the area experiences sub-desert climate and irrigation channels are dry. In the three years of this study, irrigation water in the AR16 drain was mainly provided by freshwater from the Obregon dam through the high and low channels, supplemented by pumped groundwater.

The study sampled water of different sources: freshwaters from high and low channels used for irrigation (FW), pumped groundwater (GW) in villages (Cocorit, Teras, Pueblo Yaqui and Quetchehueca), wastewater from a local treatment plant, drainage water (DW) collected in the main drain (AR16) and in lateral tributaries (TD) from the AR16 irrigation district and seawater (SW) from 15 sampling sites in the Tobari bay or outside the bay (Fig. 1, Table A in Suppl. Info.). Fifteen sites were sampled in the irrigation zone: eight sites in the AR16 drain given odd numbers from AR16-1 to AR16-15, and seven sites in tributaries representing different groups of modules irrigated by channels, given even numbers from TD-2 to TD-14. The water sample named AR16-(n) contains a mixture of the water from TD-(n-1) and AR16-(n-2). Five sampling campaigns were carried out during irrigation periods for sowing (Nov. 2017, Dec. 2018 and Nov. 2019) and to sustain the plant growth (Mar. 2018 and Mar. 2019).

Field measurements were also performed. The flow rates were measured with the area-velocity method (ISO-748: 2007) with an acoustic Doppler Current profiler (Sontek-RiverSurveyor® model M9, ISO, 2005). These measurements were performed for four campaigns (Nov. 2017, Mar. 2018, Mar. 2019 and Nov. 2019) in the high- and low-channels, in the main AR16 drain and in TD tributaries. If no flow rate value is indicated, measurements couldn't be done due to low water depth (less than 20 cm) or the absence of the equipment. The following physicochemical conditions were also determined: Temperature (T in °C), Electrical Conductivity (EC in mS.cm⁻¹), pH, Oxydo Reduction Potential (ORP in mV), Dissolved diOxygen (DO in mg.L⁻¹), and Turbidity (in NTU). After calibrations in the laboratory, in-situ turbidity values in NTU could be converted into suspended particulate matter (SPM) loads in mg.L⁻¹ (1 NTU = 64.5 mg.L⁻¹). Total alkalinity (Dissolved Inorganic Carbon, DIC: CO₃²⁻ and HCO₃⁻ in mg.L⁻¹) was also measured in the field (LaMotte 4491-DR-01 kit).

## 2.2. Chemical analyses of water

Water sample collection, preservation and analysis were carried out in accordance with international recommended criteria. Waters containing both the dissolved phase and suspended particulate matter (SPM) are called “bulk waters”. Filtered water (<0.45 µm) is defined as the dissolved phase of water, containing only dissolved chemical species.
Chemical analyses of water samples were carried out in different laboratories. Anion concentrations (Cl⁻, F⁻, SO₄²⁻, NO₃⁻, PO₄³⁻, and Br⁻) were measured by HPLC-ion chromatography (Dionex ICS 2500); and total P and S by UV-Visible spectrophotometry, at the Instituto Mexicano de Technologia del Agua (IMTA). The determination was made according to the EPA 300.1 method with certified Inorganic Ventures IF-FAS-1A standards for calibration of the instrument. Drift corrections were carried out using a laboratory control Sample. Major elements (Ca, Mg, Na, K, Sr, Li, Fe, Mn, Al, Si, B and P) were measured by ICP-OES (iCAP 6500 Duo, Thermo Scientific, Laboratory of Environmental Geochemistry, Universidad Nacional Autonoma de Mexico, and in the laboratory of the Juriquilla city) and trace elements (Ba, Co, Ni, Cu, As, Cd, Pb) by ICP-MS (Elan DRCII Perkin Elmer, Géoazur lab, Université Côte d'Azur or for seawater, UT2A lab, Pau, France). Cu, Ni, As, Pb, Co, Cd, Ba, Fe, and Mn are considered and further named as potential toxic elements (PTE). The water chemistry was determined in both bulk waters and the dissolved phase of the water, except for anions. Quantification by ICP-OES followed the USEPA 200.7 method with mono-and multi elementary standards (Ventures brand and High Purity Standards brand) and completed with laboratory control samples (such as the quality control standard QCS-26), certified standards with NIST traceability. The analytical procedure used with ICP-MS was previously described (Barats et al., 2014; Barats et al., 2020). External and internal calibration (with <sup>74</sup>Ge and <sup>115</sup>Tb isotopes) were performed for ICP-MS analyses. The validity of these measurements was verified by analyses of a certified reference material: the riverine water SLRS-6 produced by the National Research Council of Canada. These chemical analyses respect the following rules: electrical balance of cations and anions is below 10 %, and elemental concentrations in the dissolved phase of water must be lower or similar than in bulk waters.

## 2.3. Data treatments

### 2.3.1. Statistics and water typology

The following descriptive statistics were computed from the data: the mean values, standard deviations, minimum values, maximum values, coefficients of variation, standardized skewness and kurtosis values for each physicochemical or chemical parameter, using Excel (Microsoft Office). Co- variations of the data were calculated using the excell XLStat Microsoft software (demo version).

The hydrochemical facies of water samples were determined using the hydrological software Diagramme (developed by Roland Simler from the laboratoire d'hydrogéologie, Université d'Avignon, France). The speciation of chemicals in samples was determined through geochemical modeling (pHReEqC software with the Laurence Livermore National Laboratory thermodynamic data base). Transfer events between the dissolved phase of water and SPM, such as precipitation or dissolution reactions, can be estimated using saturation indices (SI), where a result of log SI > 0 indicates precipitation reactions, whereas log SI < 0 indicates dissolutions. The water mixing model was used to examine the behavior of chemicals in the AR16 drainage system (Barats et al., 2014). If a chemical is conservative, its concentration (cᵢ) in the water from a downstream site (AR16-n) is related to its
concentration in the water from the upstream flow (AR16-(n-2)) and the tributary (TD-(n-1)) located between AR16-(n-2) and AR16-n, weighted by their flow rates (fr), according to the following equation:

$$c_{AR16-n} = (fr_{AR16-(n-2)} \times c_{AR16-(n-2)} + fr_{TD-(n-1)} \times c_{TD-(n-1)})/(fr_{AR16-(n-2)} + fr_{TD-(n-1)}) \quad (1)$$

The discrepancy (%discrepancy = ((measured - calculated) / measured) x 100) between the measured concentration of a chemical and the estimated concentration was calculated for each site. Large discrepancies highlight the non-conservative behavior of a chemical during the water mixing. This non-conservativity may be due to water/solid interactions, that is chemical transfers between the dissolved phase of the water and solids (such as suspended particulate matter, sediments, or soils) due for example to evaporation, precipitation or dissolution reactions along the drain.

For groundwater, a hydrochemical facies evolution diagram was used to better constrain the water salinization (Ghiglieri et al., 2012; Giménez-Forcada, 2014; Gopinath et al., 2019a). This method can distinguish between different processes: a mixing between freshwater and seawater if chemicals behave conservatively, seawater intrusion, or refreshing of already salinized freshwater.

### 2.3.2. Water quality assessment

The overall water quality was first evaluated with the Water Quality Index (WQI). The WQI accounts for different parameters: physicochemical conditions (Turbidity, pH, Electrical Conductivity) and chemical contents (Ca, Mg, K, Na, B, HCO₃⁻, Cl⁻, SO₄²⁻, NO₃⁻, F, Al, Fe, Ba, Mn, Ni, As and Cd) measured in water samples, which are compared with World Health Organization (WHO) standard guidelines for drinking water. WQI was calculated with Eq. (2):

$$WQI = \frac{\sum_i w_i \times Q_i}{\sum_i w_i} \quad (2)$$

where i is the parameter, wᵢ is the weight applied to each parameter based on its toxic effect on primary health and drinking suitability, and Qᵢ is the quality rating rate of the iᵗʰ parameter, calculated using Eq. (3):

$$Q_i = 100 \times \frac{c_i}{s_i} \quad (3)$$

where cᵢ is the measured value of each parameter and sᵢ is the WHO guideline for that parameter for drinking waters. The water quality can be divided into 5 categories as follows: (1) WQI < 50, an excellent water quality; (2) 50 < WQI < 100, a good water quality; (3) 100 < WQI < 200, a poor water quality; (4) 200 < WQI < 300, very poor; and (5) WQI > 300, water unsuitable for drinking purposes.

The water quality was then assessed with the Heavy metal Evaluation Index (HEI). This index takes into account the following chemicals: Al, Fe, Ba, Mn, Co, Ni, Cu, As, Pb and Cd; and is given by Eq. 4:
$$HEI = \sum_{i} \frac{c_i}{s_i} \qquad (4)$$

where i is the chemical, c_i is the measured concentration of each chemical and s_i the WHO guideline for that chemical in drinking water. There are three levels of pollution assigned by the HEI score. If the HEI is higher than 20, samples have a high pollution level; if the HEI is lower than 10, samples have a low pollution level. A score between 10 and 20 indicates a medium level of pollution (Dippong et al., 2024a; Dippong et al., 2023; Dippong and Resz, 2024a; Edet and Offiong, 2002; Ghaderpoori et al., 2018). Compared to the WQI, the HEI estimates only the level of contamination of the water by potentially toxic elements such as metals and metalloids.

### 2.3.3. Human health risk assessment

The human health risk assessment was performed on groundwater samples only because these water is used by inhabitants for drinking and domestic uses. Chronic Daily Intakes of several contaminants (CDI, µg.kg⁻¹.day⁻¹) were estimated for children (6 years old, weight of 15 kg) and for adults (30 years old, weight of 70 kg), for 10 chemicals (Al, Ba, Fe, Mn, Co, Ni, Cu, As, Cd and Pb) and for two pathways of contamination: ingestion via drinking groundwater (CDI_ingestion), or dermal contact (CDI_dermal). Average water compositions of the dissolved phase were used for this assessment. Dermal contact is likely to occur with the use of contaminated water during bathing, washing, swimming, or fishing. Inhalation and diet are other ways of contamination, but they are not accounted for in this study. These CDI values were calculated using Eqs. (3) and (4):

$$CDI_{ingestion} = \frac{c_w \times IR}{BW} \qquad (3)$$

$$CDI_{dermal} = \frac{c_w \times SA \times K_p \times CF \times EF \times ET \times ED}{BW \times AT} \qquad (4)$$

where CDI_ingestion/dermal are expressed in µg.kg⁻¹.day⁻¹; c_w is the average chemical content in the dissolved phase of waters (in µg.L⁻¹); IR is the ingestion rate (in L.d⁻¹), i.e., 2 L per day for an adult and 0.64 L for a child; SA is the surface skin area, i.e. 18000 cm² for adults and 6600 cm² for children; EF is the exposure frequency, which was taken to be 365 days per year; ED is the exposure duration in years, i.e., 30 years for adults and 6 years for children for non-carcinogenic risks and 70 years for lifetime carcinogenic risks; ET is the exposure time, i.e., 0.58 h.day⁻¹ for adults and 1.0 h.day⁻¹ for children; CF is the conversion factor, i.e., 0.001 L.cm⁻³; BW is the average body weight, i.e., 70 kg for adults and 15 kg for children; and K_p is the skin adherence time (in cm.h⁻¹). A total CDI was also estimated such as the sum of CDI_ingestion and CDI_dermal.

Non-carcinogenic risks related to each chemical were then evaluated by the hazard quotient (HQ) for the two exposure pathways, as shown in Eq. (5):

$$HQ_{ingestion or dermal} = \frac{CDI_{ingestion or dermal}}{RfD_{ingestion or dermal}} \qquad (5)$$
where RfD is the reference dose in µg.kg⁻¹.day⁻¹ (Table 1). Reference doses are the oral reference dose for HQingestion, and the dermal reference dose RfDdermal for HQdermal. Hazard quotients greater than 1 indicate health risks. The total hazard quotient (HQ) was also calculated as the sum of HQingestion and HQdermal. This HQ is specific to each chemical, and represents the overall toxicity potential posed by a chemical from direct ingestion or dermal absorption.

The Incremental Lifetime Cancer Risk (ILCR) was obtained using the Eq. 6:

$$ILCR = \frac{CDI_{ingestion} \times CSF}{1000} \qquad (6)$$

where, CSF is the cancer slope factor (in mg⁻¹.kg.day) and CDIingestion is the chronic daily intake in µg.kg⁻¹.day⁻¹ for an exposure duration, ED, of 24 h per day over 70 years. Only the ingestion exposure pathway was taken into account in this study due to the low dermal risks demonstrated in a following paragraph (3.4. Human health risks). A ILCR value of 10⁻⁵ indicates a probability greater than 1 chance in 100 000 of an individual developing cancer. Cancer risk is considered to be negligible for ILCR lower than 10⁻⁶, whereas values above 10⁻⁴ are considered unacceptable by most international regulatory agencies.

# 3. Results and discussions

## 3.1. Hydrological characteristics and field measurements

The daily potential evapotranspiration was estimated with meteorological data (rainfall volume, wind speed, relative humidity, maximum, minimum, and average temperature combined with solar and soil radiative fluxes and altitude temperature). Evapotranspiration values range from 4 to 10 L.m⁻², while normal rainfall varies from 2 to 4 L.m⁻² and maximum rainfall volume is about 20 L.m⁻² in August. These results and field observations confirm the aridity of the area and emphasize the need for irrigation to sustain agricultural productivity.

During the sampling from 2017 to 2019, the instantaneous flow rates in high and low channels varied from 53 to 82 m³.s⁻¹. Flow rate values increased along the AR16 drain, reaching 2.2 to 3.2 m³.s⁻¹ in the last sampling site of the AR16 collector before the Tobari lagoon. These flowrates in the AR16 drain are less than 5% of the flow rates in the high and low channels (Table B in Suppl. Info.). This difference is related to 1) the water supply to other agricultural modules, 2) the different plant needs according to irrigation periods and 3) evaporation and infiltration processes.

The load of suspended particulate matter in water was estimated from turbidity measurements. The descriptive statistics show high coefficients of variation (%CV > 37), demonstrating a high variability of turbidity values. High values of skewness and of kurtosis are observed in all water resources (except wastewater). These results indicate a non-normal distribution of these turbidity parameters, indicating a high temporal and spatial variability of the particulate load in water.
Groundwater (GW) and freshwater (FW) from channels generally present low turbidity values, below 5 NTU, the WHO acceptable value for drinking water (Tables B and C, in Suppl. Info.), supported by positive values of skewness (> 2). However, some high turbidity values are observed: (1) in all GW sampled in Mar. 2018, ranging from 15 to 90 NTU, (2) in most drainage water (DW) from the AR16 collector or tributaries TD, whatever the sampling period, averaging around 200 NTU, and (3) in seawater samples. The corresponding SPM load in DW from AR16 and TD is high, ranging from 13 to 1500 mg.L⁻¹. Fortunately, these DW resources are not used as drinking water. Even with similar flow rates, higher turbidities were measured in Nov. 2017, during the initial stage of irrigation. SPM inputs into the Tobari lagoon were calculated using SPM values and flow rates. SPM inputs into the Tobari lagoon were estimated to be 0.80 kg.s⁻¹ in Mar. 2018, 1.9 kg.s⁻¹ in Mar. 2019 and 2.5 kg.s⁻¹ in Nov. 2017. The lowest SPM inputs were observed in Mar. 2018, concomitantly with the highest flow rate (3.2 m³.s⁻¹), during the last stage of irrigation. The high inputs of SPM by DW would explain the high SPM content in seawater sampled in the Tobari Bay.

Statistical analyses reveal a low variability of pH and water temperatures, with %CV ranging from 6 to 18 whereas Oxidation Reduction Potential (ORP), dissolved O₂ and electrical conductivity (EC) values are demonstrated to be highly variable with %CV ranging from 28 to 96. Most of the water samples were neutral to slightly basic, with 73% of pH values ranging from 6.5-8.5. Water temperatures averaged 21-24 °C, close to the air temperature of Obregon (ca. 25°C) except in groundwater (31°C). Waters were well oxygenated with ORP and dissolved O₂ values averaging 150-330 mV and 5-8 mg.L⁻¹, respectively. EC values differed according to the source of the water. FW samples from channels in the upstream Yaqui basin presented low EC, from 0.2 to 0.5 mS.cm⁻¹. Higher EC values were measured in GW and DW, averaging 1.6 and 2.4 mS.cm⁻¹, respectively. Obviously, seawater had extremely high EC, averaging 54 mS.cm⁻¹, due to salts. Excluding seawater, 55% of the sampled waters presented EC values higher than 1.5 mS.cm⁻¹, the WHO quality standard for drinking water. Moreover, EC values in DW increased along the AR16 collector from 1.4 to 4.5 mS.cm⁻¹, highlighting the degradation of water quality during runoff. High values of skewness and kurtosis obtained for DW indicate a non-normal distribution of EC, which may be related to the water degradation. This is likely to be due to the inputs of chemicals during the runoff of water from the tributaries, or to solid/liquid transfers (for example, dissolution of minerals from soils, SPM, or dried drains) or salinization processes in the downstream part of the AR16 collector.

## 3.2. Hydrochemical characteristics

### 3.2.1. Major elements or ions

Concentrations of major elements or ions in the dissolved phase of waters are presented in Fig. 2 and Table D in Suppl. Info. As indicated by the low electrical conductivity, freshwater from high and low channels presents low concentrations of major elements and ions in their dissolved phase, below
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the recommended WHO guidelines for drinking water. The samples present calcium bicarbonate facies with Ca²⁺ concentrations ranging from 25-30 mg.L⁻¹, and HCO₃⁻ from 84-140 mg.L⁻¹. These FW samples present the best water quality among the different water resources available in this area. Except for NO₃⁻, %CV are lower than 20 for all major ions and elements. Values of standardized kurtosis are higher than 2 for Mg, Na, HCO₃⁻ + CO₃²⁻, NO₃⁻, B, Si and especially for Cl⁻ and Al (around 26). These statistical results highlight the low variability of major elements in freshwater sources studied.

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With %CV ranging from 28 to 79, concentrations of major ions and elements in groundwater sample were demonstrated to be highly variable (Fig. 2 and Table D in Suppl. Info). This variation is explained by inter-site differences. GW from Quetchehueca and Cocorit present low concentrations of major chemicals, also in accordance with WHO guidelines. Higher Ca²⁺ (120-200 mg.L⁻¹) and Cl⁻ (300-600 mg.L⁻¹) concentrations are measured in GW from Teras and Pueblo Yaqui, above WHO guidelines. GW samples present a mix of hydrochemical facies between Ca-HCO₃ and Na-Cl facies, except for the Quetchehueca samples which have a Na/Cl facies. GW are also usually SO₄²⁻ rich, except for Quetchehueca. A non-normal distribution of Na concentrations are indicated by high values of skewness (3.3) and kurtosis (12.6), suggesting a peaked distribution of the data and only occasional high Na concentrations. This result is consistent with the salinization of GW.

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A high variability of major ions and elements are indicated in drainage water (DW) from the different tributaries (TD) of the AR16 collector: %CV values range from 19 to 137 (Fig. 2 and Table D in Suppl. Info). High values of skewness and kurtosis (except for Si and F⁻) reveal a non-normal distribution of the data, with a long tail of high values. These statistical results suggest intermittent chemical inputs. For example, high K⁺ and Al concentrations are usually measured in TD drainage water, and are often higher than WHO guidelines. These water resources are also intermittently enriched with PO₄³⁻ (TD-2, ranging from 1.2-13 mg.L⁻¹) or NO₃⁻ (TD-10, TD-12), suggesting the use of fertilizers in agricultural modules. In some water samples from TD-10 and TD-12, NO₃⁻ concentrations are higher than WHO standards and reach close to 100 mg.L⁻¹. In the lower part of the AR16 sampling zone, Ca²⁺, Na⁺, B, SO₄²⁻ and Cl⁻ concentrations were higher than WHO standards (sites TD-6, TD-8, TD-10, TD-12 and TD-14). Hydrochemical facies of these drainage waters vary from the Ca-HCO₃ facies in the upstream part of the watershed to the Na-Cl facies observed in sampling sites closer to the sea.

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Similar to drainage water from TD tributaries, DW from the AR16 collector also show highly variable concentrations of major ions and elements: %CV range from 22 to 171 (Fig. 2 and Table D in Suppl. Info). Values of kurtosis are mostly higher than 2, except for K, HCO₃⁻ + CO₃²⁻, SO₄²⁻, F⁻ and Sr. This result indicates a non-normal distribution of most major chemicals. These statistical results agree with the change of chemical compositions along the AR16 collector. From upstream to downstream, concentrations of Ca²⁺, Mg²⁺, Na⁺, Cl⁻, SO₄²⁻, HCO₃⁻ + CO₃²⁻, B, and Br increase whereas NO₃⁻ concentrations are variable. DW from the first sampling point AR16-1 are enriched with K⁺, Na⁺, Cl⁻

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and SO₄²⁻ compared to FW from channels, which are the main supplier of irrigation water and contributor to this drainage water. Like DW from tributaries (TD), drainage water from the AR16 collector often has Al concentrations in the dissolved phase higher than WHO guidelines. These DW samples present a mix of hydrochemical facies between the Ca-HCO₃⁻ facies and the Na-Cl facies, with dominant Na⁺ cations and HCO₃⁻ anions. Concentrations of major ions in DW from AR16 sites are generally lower than the WHO guidelines, except for the downstream sites. Positive values of skewness for SO₄²⁻ and PO₄³⁻ would suggest intermittent water contamination. For example, K⁺, NO₃⁻ and PO₄³⁻ concentrations in water from AR16-3 and AR16-5, are locally increased after the addition of water from TD-2 and TD-4 tributaries. These contaminants are thus proved to be input in these two drained agricultural modules, suspected to be related to the use of NPK fertilizer or pesticides. Downstream of AR16-5, the high K⁺, NO₃⁻ and PO₄³⁻ concentrations are progressively reduced by the addition of water from tributaries. Downstream DW from AR16 collector presents high Na⁺, B and Cl⁻ concentrations, above WHO guidelines. High values of skewness for these three chemicals are explained by these intermittent high values. As for DW from TD, DW along the AR16 drain presents hydrochemical facies changing from Ca-HCO₃⁻ facies to Ca-HCO₃⁻ to SO₄²⁻ and Na-Cl facies downstream, with Na-Cl facies for the two last sampling sites close to the sea (AR16-13 and AR16-15).

Ca, Mg, Na, HCO₃⁻ + CO₃²⁻ concentrations in wastewater reveal low variability (%CV < 10), whereas large fluctuations are observed for SO₄²⁻, Br⁻, NO₃⁻, F⁻, B and Al (%CV > 41%). Values of skewness and kurtosis range from -2 to 2, indicating a rather normal distribution. Wastewater samples have a chemical signature ranging between that of FW and DW in the upstream part of the AR16 irrigation district, with a Ca-HCO₃⁻ hydrochemical facies. Most major chemicals present lower concentrations in wastewater than in DW, except for K, carbonates and PO₄³⁻ which are higher. Wastewater contains K and PO₄³⁻ concentrations higher than WHO guidelines, which may result from the use of fertilizers in this irrigation zone.

Seawater (SW) samples reveal rather constant concentrations of Ca, Mg, K, Ca, HCO₃⁻ + CO₃²⁻, Sr and B (%CV < 20) but highly variable concentrations of Cl⁻, SO₄²⁻, NO₃⁻, F⁻, Al (%CV > 55) (Fig. 2 and Table D in Suppl. Info). Values of skewness and kurtosis are also especially high for Cl⁻, SO₄²⁻, NO₃⁻, Al, suggesting that these four chemicals have a non-normal distribution. The variabilities may be related to FW/SW mixing in the bay depending on the season (flowrate depending on the irrigation period) and the geographical setting (sampling sites more or less close to the output of DW). Seawater from the Tobari Bay contains the highest concentrations of all major chemicals among all the water sources except for CO₃²⁻, HCO₃⁻, Si and PO₄³⁻. Na, Sr, Cl⁻, F⁻, B and SO₄²⁻ concentrations are extreme, largely above the WHO guidelines for Ca, Mg, K, Na, B, Cl, SO₄²⁻, and sometimes for F⁻. Higher contents of these major chemicals in GW and in DW from TD or from the main AR16 drain in the downstream part of the irrigation area and changes of hydrochemical facies from Ca-HCO₃⁻ to NaCl are suggested to be related to the mixing with seawater, or salinization processes.
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Because water samples had a high SPM content, the water chemistry was examined both in bulk waters and in the dissolved phase of waters. As shown in Fig. 2 and Table D in Suppl. Info., most chemicals occur as dissolved species (usually higher than 80%). However, B, Sr and Si can also be contained in suspended particulate matter and Al is mainly in particulate forms. In freshwater and drainage waters from the AR16 irrigation district, only 48% of B is in dissolved species. Along with Al, B presents its highest concentration in seawater, and a much higher fraction (almost double in each case) occurs as dissolved species in seawater than in FW or DW, especially B with 94% as dissolved species. This result suggests that Al and B are transferred from suspended particles to the dissolved phase of water.

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Geochemical modeling of DW at equilibrium also reveals that some major chemicals are present only in dissolved species, for example, K⁺, Li⁺, Br⁻, Cl⁻, and F⁻. This result is consistent with the conservative behavior of these elements during the transport and the mixing of waters. Some major chemicals may occur in two phases in the water sources: for example, in DW, as dissolved species (Na⁺, Ca²⁺, Mg²⁺, Sr²⁺, HCO₃⁻, SO₄²⁻) and in solid phases (Na-, Ca- or Mg-carbonates or Ca-, Mg- or Sr-sulfates). As observed and geochemically calculated, Al is more likely to be in particulate forms and especially in oxides or hydroxides. Geochemical estimates of saturation indices (SI) demonstrate that FW is in relative equilibrium with respect to calcite and dolomite (-1 < log SI < 1), and undersaturated with respect to halite (log SI = -13), gypsum and anhydrite (log SI = -4 to -2). DW from AR16 and TD is undersaturated with respect to halite (log SI = -13 to -11), anhydrite (log SI = -2.6 to -1), and gypsum (log SI = -2 to -0.8), and in equilibrium or oversaturated with respect to carbonate mineral (log SI Calcite = -0.2 to 2, log SI Dolomite = -0.7 to 4). These results of undersaturated water suggest the dissolution of halite especially, but also anhydrite and gypsum. Consequently, if water drains soils containing these minerals, solid/liquid transfers occur, and Na⁺, Cl⁻, Ca²⁺ and SO₄²⁻ are released in the dissolved phase of waters. Geochemical modeling reveals also that water is in equilibrium or under saturated with respect to amorphous alumina (log SI = -4 to +0.3). These results may also be consistent with a potential dissolution of alumina, and increasing concentration of dissolved Al in water. All these results support solid/liquid interactions.

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### 3.2.2. Potential toxic elements in waters

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Cu, Ni, As, Pb, Co, Cd, Ba, Fe, and Mn are considered potential toxic elements (PTEs). Their concentrations were measured in water samples and are presented in Fig. 3 and Table E in Suppl. Info. and compared to WHO guidelines.

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For all PTEs except for As, freshwater (FW) from high and low channels presents low concentrations, below WHO guidelines for drinking water (Fig. 3). Arsenic concentrations in FW average 8.79 µg.L⁻¹, close to the WHO guidelines (10 µg.L⁻¹) for drinking waters, and remain stable (%CV = 5.5). This result indicates a chronic As contamination of this FW resource from the upstream basin of the Yaqui River. PTE concentrations in FW are often above the average composition of global
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rivers (Gaillardet et al., 2014) (Table E). FW contains 14 times more As than rivers, and from 1.6 to 3.1 times more Fe, Mn, Co, Cu and Ba (3.1 times more Al). This comparison corroborates the presence of a considerable amount of As in FW prior to its entry into the irrigation zone, and potentially a minor contamination for other metals.

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Similar to FW, groundwater samples present low PTE concentrations that are below WHO guidelines, except for As and Fe (and the major element Al) (Fig. 3 and Table E in Suppl. Info.). The WHO guideline was sometimes exceeded for Fe (such as Al) at Quetchehueca, and for As for all samples at Cocorit (16 µg.L⁻¹). A strong variability of PTE concentration is revealed (%CV > 44).

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Drainage water (DW) contains significantly higher amounts of PTEs than FW and GW (Fig. 3 and Table E in Suppl. Info.). Some As, Fe and Mn concentrations reach values higher than WHO standards or the Mexican drinking water limit (for Mn, 0.15 mg.L⁻¹, NOM-127-SSA1-2021). DW from the AR16 collector usually has higher PTE content than DW from tributaries. PTE concentrations are found to be variable (high %CV). High values of kurtosis and skewness are revealed for As, Cu and Ba in DW from the AR16 drain and for Co, Ni, Cu, As, Pb, Cd in DW from TD tributaries. These statistical descriptors therefore suggest intermittent PTE inputs in this irrigation area. Some increases of PTE concentrations occur episodically according to a specific sampling date or to an element: for example, Cu increasing after inputs of DW from TD-2 (Fig. 4); Co in Nov. 2019; Ni and Cd in Dec. 2018 and Nov. 19. These intermittent inputs from tributaries have a low influence on the water chemical composition in the main AR16 drain. PTEs usually present similar concentrations from upstream to downstream the AR16 drain, except for As and Cu (Fig. 4). In the downstream area of the AR16 irrigation district, the concentration of dissolved As is significantly increased, reaching a maximum value of 23 µg.L⁻¹ at the AR16-15 site and 61.4 µg.L⁻¹ at the TD-14 site in Dec. 2018. These higher As concentrations in DW may be related to physico-chemical changes (T, EC, pH, oxygenation) in waters related to or enhanced by salinization processes (consistent with increased Cl⁻, SO₄²⁻, Na⁺).

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As shown for the major chemicals, PTE concentrations in wastewater are also lower than in DW, except for Cd. WHO guidelines are reached for Fe, Cd and sometimes As. High variability of PTE levels is demonstrated with %CV > 63 for Fe, Ni, Cu, Pb, Cd.

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Similar to wastewater, seawater (SW) samples also show lower PTE levels than DW (Fig. 3 and Table E in Suppl. Info.). The mean PTE concentrations are very variable (%CV > 51). Values of kurtosis and skewness are usually higher than 2, indicating a non-normal distribution. These statistical results agree with the ones obtained for major chemicals, and support high variability of PTE levels in seawater due to geographical and seasonal changes in the FW mixing into the bay. WHO standards are only exceeded by Fe and occasionally by As. Dissolved Al, Ba, Fe, Mn, Ni, Cu, and As concentrations in SW are 3 to 5 times lower than those in DW. These results reveal firstly that significant amounts of PTEs are discharged into the bay and secondly, that SW and wastewater cannot be the direct source of PTEs in DW. While increases in some major chemical concentrations (Cl⁻, SO₄²⁻ and Na⁺) in DW from downstream of the AR16 irrigation district can be directly related to the mixing with seawater, this
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cannot explain higher As concentrations in coastal DW. Instead, an indirect process induced by this mixing with seawater may only explain the increase of As concentrations in coastal DW.

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PTE concentrations in bulk waters were compared with those in the dissolved phase of waters (Fig. 3 and Table E in Suppl. Info.). The results suggest that As and Ba mainly occur as dissolved species, and Fe (similar to Al, see section 3.2.1) in particulate forms. Mn, Co, Ni, Cu, Cd, and Pb occur in dissolved and particulate species. Arsenic concentrations in the dissolved phase of water or in bulk waters were similar, revealing that As is mainly in dissolved species. Geochemical modeling confirms this result, revealing that As exclusively occurs as anionic species ($HAsO_4^{2-}$, $H_2AsO_4^{−}$) in water at equilibrium conditions. Al and Fe contaminations observed in groundwater are not observed in the dissolved phase, demonstrating that they occur in particulate forms. Geochemical calculations indicate also that, in water at equilibrium, Fe and Mn mainly occur in metal oxides or hydroxides. These results suggest the occurrence of suspended particles (SPM) enriched with Fe, Mn and Al, consistent with lower concentrations in the filtered water. During the water drainage process, eroded soils release large amounts of suspended particulate matters that are enriched with Fe, Mn and Al. Geochemical modeling also highlight the occurrence of Mn, Cd, Pb and Co both as dissolved species ($Mn^{2+}$, $MnCl_2^-$, $Cd^{2+}$, $CdCl_2^-$, $CdHCO_3^{+}$, and $HCoO_2^−$) and in particulate forms ($MnCO_3$, $MnSO_4$) in water at equilibrium conditions. DW samples are found to be always over-saturated with respect to amorphous Fe hydroxides (log SI = 0.2 to 3), minerals such as goethite (log SI = 6 to 9), and hematite (log SI = 14 to 20). These results are most suggestive of Fe precipitation. Potential adsorption of some PTEs (Ni, Cu, Cd, Co) on the surface of Fe particulate phases may explain the occurrence of these PTEs in particulate forms. In the wastewater from the AR16 drain, the distribution of PTEs between dissolved species or particulate forms also highlights changes in PTE speciation depending on the sampling dates and/or from upstream to downstream, indicating transfers between the solid and liquid phases. For instance, Co and Ni are predominantly found in dissolved form in Mar. 2018 and Dec. 2018, while in Nov. 2017, Mar. 2019 and Dec. 2019 they are mainly found in particulate forms, that is in suspended particles. During the sampling in Nov. 2019, Al, Fe, Mn and Ba occurred in particulate forms in the upper part of the Yaqui irrigation district at the AR16-1 site (more than 90% of the total Al, Fe and Mn concentrations, and 47% for Ba) whereas in the downstream part at the AR16-15 site, they are present almost exclusively as dissolved species (more than 80% of the total content). In accordance with these results, geochemical estimations at equilibrium for the Nov. 2019 samples also highlights that Mn occurs in both dissolved species ($48\%$ of $Mn^{2+}$ and $6\%$ of $MnHCO_3^+$) and particulate forms ($43\%$ under solid carbonates and $2\%$ under sulfates) in the upper part of the Yaqui irrigation district (AR16-1 site), whereas Mn is predominantly in dissolved species ($75\%$ of $Mn^{2+}$ and $4\%$ of $MnHCO_3^+$), and only $18\%$ as particulate matter ($7\%$ under solid carbonates and $11\%$ under sulfates) in the downstream part (AR16-15). Similar to Al and B, and unlike As which is always in dissolved species, the percentages of PTEs in dissolved species are higher in seawater than in DW. For instance, Mn release from riverine suspended particles has been observed due to changes in the salinity (Abril et al., 1999; Ouddane et al., 1997). These results on changes of PTE
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speciation confirm the occurrence of transfer events between suspended particulate matter and the dissolved phases of water, as suggested for major chemicals.

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### 3.3. Assessment of the water quality

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Despite specific contaminations, water quality indices (WQI) in freshwater, wastewater and groundwater were below 63 indicating an excellent to good water quality. Contaminants found were: As in FW, Ca and Cl⁻ in GW from Teras and Pueblo Yaqui, Al and Fe in GW from Quetchehueca, and As in GW from Cocorit. Except for one sample, FW, wastewater and GW samples present Heavy metal Evaluation Indices (HEI) below 5.9 for bulk water and below 3.7 for the dissolved phase of water. Because HEI values are largely below 10, these water resources are found to have low pollution levels, consistent with the WQI. For one wastewater sample in Mar. 2018, a high HEI of about 18 is observed only in the bulk water, indicating a medium pollution level of the water. This pollution was related to the occurrence of suspended particulate matters enriched with Fe: a measured concentration of 1.5 mg.L⁻¹ vs the WHO guideline of 0.3 mg.L⁻¹. In previous studies, low HEI values have also been reported in water resources from natural or protected hydrosystems: such as in groundwater or rivers in Romania (Dippong et al., 2024a; Dippong et al., 2023), in surface water from a karst river characterized by carbonate strata in China (Wang et al., 2022) and in drinking waters from a city in Iran (Ghaderpoori et al., 2018).

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In seawater, measured WQI values were always extremely high, above 300 and averaging 1000. These results were expected due to strong electrical conductivities and extreme concentrations of major chemicals (Na, Ca, Mg, K, Cl⁻, SO₄²⁻), and confirm the unsuitability of seawater for drinking purposes. Seawater samples presented low median HEI (2.2 for bulk water and 1.3 for the dissolved phase of water) and contrasting mean values (21 for bulk water and 2.3 for the dissolved phase of water). The P15 sampling site (outside the bay) presented HEI less than 1.1, for all sampling dates. These HEI results indicate an overall good quality of seawater concerning metals and As in seawater outside the bay, refuting the possibility that seawater may be a source of metals and As. HEI values are very variable (%CV > 117). Values of kurtosis and skewness are also largely higher than 2. These statistical results attest to a non-normal distribution and intermittently high values of HEI. In bulk seawaters, HEI varies from 0.41 to 360, indicating different levels of pollution. This variability is believed to be related to variable inputs of drainage water, according to sampling date and sampling site (for example, very variable and high values for sampling sites P5 to P14 sampling sites). Al, As and Fe concentrations in bulk waters, which exceed the WHO guidelines, are responsible for this high HEI. In the dissolved phase of seawater, HEI values were below 10 (except for two samples), highlighting a generally good pollution level. This drastic decrease in the HEI value in the dissolved phase of water is related to the removal of Al and Fe enriched particles. Nevertheless, two samples present medium values of HEI, 15 at the P7 sampling site in Mar. 2018 and 11 in the P10 sampling site in Nov. 2017, due to remaining high
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contamination by dissolved Al and Fe. WQI and HEI results can be explained by the contamination of seawater by dissolved major ions (Na, Ca, Mg, K, Cl⁻, SO₄²⁻), suspended particulate matters enriched with Al and Fe, and dissolved species of As.

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In drainage water, average WQI values (over the 5 sampling dates) for bulk water and the dissolved phase of water in the AR16 hydrosystem were summarized in Fig. 5. WQI values are always greater than 100 in bulk waters, increasing along the AR16 drain and reaching as high as 489 in DW from AR16-15 sampling sites. These results indicate that the quality of the drainage water is very poor to unsuitable, whatever the sampling period. In the dissolved phase of the water, WQI are drastically decreased and reveal values lower than 100, except in the downstream part of the AR16 drain (Fig. 5). This result confirms the suggestion made above the main role of SPM in the degradation of water quality. However, the WQI of the dissolved phase of DW can also exhibit intermittently high values, demonstrating a poor water quality: for example, a WQI of 271 in Mar. 2018, of 126 in Dec. 2018 at TD-6, or of 129 in Dec. 2018 at TD-10. With high values of WQI, a poor water quality was previously reported in water resources affected by industrial and agricultural inputs in India, and related to high Ca, Mg, Cl and NO₃⁻ concentrations (Mukate et al., 2019). In Pakistan, high values of WQI were attributed to groundwater contaminated by both Na and metals (Khanoranga and Khalid, 2019). In the coastal zone, the dissolved phase of DW from AR16-15 and from TD-14 reveal WQI values ranging from 66 to 185 and from 152 to 436, respectively. The water quality of these coastal DW samples remains very poor, even after the removal of SPM. This result indicates a water contamination with dissolved chemicals in DW. WQI thus confirms the degradation of water quality along the AR16 drain and the poor water quality in coastal DW, potentially related directly or indirectly to a salinization process (as observed with higher Na⁺, Cl⁻ and SO₄²⁻ concentrations). This result agrees with previous studies, indicating high values of WQI in groundwater subjected to seawater intrusion (Gopinath et al., 2019b) or in surface water with high sodium (alkalinity) and salinity hazards (Jehan et al., 2020). Concerning the metal contamination, drainage water samples reveal a mean HEI of 26 in bulk waters indicating a high pollution level, whereas the dissolved phase of water present a mean HEI of 4.7, indicating instead a good pollution level. As for seawater, high Al, Fe and As concentrations in bulk DW are responsible for high HEI values. The lower HEI values in the dissolved phase of DW are explained by the drastic decrease of Al and Fe concentrations due to the removal of suspended particulate matter (leaving only water contamination by dissolved As species). HEI values in bulk DW remain always above 10 and usually higher than 20 all along the AR16 drain and in TD tributaries, indicating a medium or high pollution everywhere in this irrigation zone. Similar high values of HEI have been recorded by other studies: in surface water from an Moroccan area subjected to mining and agriculture (Khadija et al., 2021), in groundwater and surface water from industrial areas in Bangladesh (Hossen and Mostafa, 2023; Rahman et al., 2020), and in a Turkish riverine water polluted by untreated domestic wastewater, agricultural and livestock activities and industrial effluents (Varol and Tokatlı, 2023). However, this
study also shows typical HEI values below 10 in the dissolved phase of DW, indicating a good water quality and confirming the huge amounts of PTEs in SPM. Nevertheless, high HEI values are also highlighted in the dissolved phase of DW for AR16-3 in Mar. 2018 due to high dissolved Al and Fe concentrations, and for sampling sites in the coastal zone (AR16-15 and TD14) due to higher As, Cu, Al and Fe concentrations. Al and Fe are demonstrated to be the main contributor for these high HEI values. Removing these two chemicals from the calculation drastically decreases HEI, giving values below 11 both in bulk and dissolved phase of water, thus improving the inferred water quality. In accordance with this study, Fe was also previously reported to contribute substantially to high values of HEI in waters even in a protected area in Romania (Dippong et al., 2022).

In agreement with previous sections, this assessment of water quality with WQI and HEI confirms the contamination of DW by Al- and Fe-enriched SPM, dissolved As and, particularly in the coastal zone, dissolved Na, Cl, As and Cu. Inputs of this contaminated DW further degrade the water quality in the Tobari bay, explaining the contamination of seawater with Al- and Fe-enriched SPM, and dissolved As. However, DW inputs are not responsible for the seawater contamination by dissolved major ions (Na, Ca, Mg, K, Cl⁻, SO₄²⁻).

## 3.4. Human health risks

Human health risks were evaluated with the calculation of chronic daily intake (CDI) and hazard quotient (HQ) values for groundwater, considering two pathways of exposure: dermal contact and water ingestion. CDI values are below the reference doses for Al, Ba, Fe, Mn, Co, Ni, Cu, Cd, and Pb in waters, resulting in HQ values largely below 1 for both adults and children (Table 1). The incremental lifetime cancer risk (ILCR) is negligible for Pb (below 10⁻⁶), acceptable for Cd (7.10⁻⁷ and 5.10⁻⁵ for adults and children, respectively). For children, carcinogenic risks due to Cd are indicated at Cocorit and Quetchehueca, but remain at an acceptable level. This result reveals that the level of health risk from the presence of Al, Ba, Fe, Mn, Co, Ni, Cu, Cd and Pb in the water is acceptable. Previous geochemical calculations indicate the occurrence of Al, Fe, Mn mainly in particulate forms in water, and Mn, Cd, Pb and Co in both particulate forms and dissolved species. The health impact is obviously reduced when the metal occurs in particulate forms, as only the dissolved content was considered for CDI or HQ calculations. An exposure assessment of pesticides, As and Pb were previously performed on children from this Mexican region (Meza-Montenegro et al., 2012a). This study reported blood Pb levels reported lower than guideline. This is in agreement with our study that indicates no health risks due to Pb. Health risks from metals in water can thus also be negligible in other countries, even in a region with an intense agriculture and industry such as in Turkey (Tokatlı, 2021).

High concentrations of As were observed in GW from the Yaqui hydrosystem. Arsenic is a toxic, colorless, tasteless, and odorless contaminant which is found at high levels in the groundwater of various countries in the world, especially in South-East Asia (Ahmad et al., 2018; Kemper and Minnatullah,
2005; Mihajlov et al., 2020; Rodríguez-Lado et al., 2013; Smith et al., 2000; Sø et al., 2018). For As, the average CDI values measured in this study are close to the reference dose for adults (0.28 µg.kg⁻¹.day⁻¹) and higher for children (0.41 µg.kg⁻¹.day⁻¹), resulting in HQ values averaging 0.92 and 1.4, respectively, for adults and children. For GW from Pueblo Yaqui, CDI values for As were below the reference dose, i.e. 0.16 and 0.24 µg.kg⁻¹.day⁻¹, respectively, for adults and children, and HQ values for As were below 1 (0.53 and 0.80, respectively, for adults and children). HQ values for As were higher than 1 for children in GW from Quetchehueca, Teras and Cocorit (HQ = 1.2; 1.2; 2.3, respectively), and for adults in GW from Cocorit (HQ = 1.53). These results support previous studies that warned of health risks due to As in this region (García-Rico et al., 2019; Meza-Montenegro et al., 2012a; Vega-Millán et al., 2021). Health risks due to As have also previously been shown using CDI and HQ, such as in a mountain ecosystem in Romania (Dippong et al., 2024a), or in a coastal aquifer submitted to agriculture and mining activities in Togo (Napo et al., 2021). In this study, the values of CDI by ingestion represent more than 99% of the total CDI, while the HQ related to ingestion represents at least 80% of the total HQ. Dermal contact is thus believed to be negligible. Drinking water was also previously shown not to be the largest contributor to urinary As concentrations in children living in this Mexican region (Roberge et al., 2012). However, this study is not accounting for all pathways of exposure. Food ingestion and inhalation should be considered to assess health risks related to metals and As, because they might be other important sources of exposure. In this same Mexican region, an important health risk has been revealed due to the inhalation of dust enriched with Ni (hazard index above 2.1), indicating probable adverse health effects in children (Meza-Montenegro et al., 2012b). Arsenic exposure through drinking water has previously been shown to significantly increase the risk of respiratory infections in children living in this Mexican region (Vega-Millán et al., 2021). This study also indicates an incremental lifetime cancer risk (ILCR) related to As ranging from 10⁻⁴ to 10⁻³ (the maximum value, for Children at Cocorit), demonstrating elevated cancer risks for adults and especially for children. Ingesting water containing As can also result in other significant immediate and/or prolonged health issues, including but not limited to vomiting, diabetes, heart diseases, cancer, spontaneous abortion, childhood cancer, and potentially death (Tantry et al., 2015).

## 3.5. Deciphering multiple sources and processes to explain the water pollution

### 3.5.1. Sources of As contamination

Arsenic contamination is found in all water resources sampled in this study. Before entering the drainage district AR16, FW from the high and low channels are contaminated by dissolved As species. This As contamination in FW is thus believed to originate from the upstream watershed before the Álvaro Obregón dam. It is likely to be related to the geological background or a combination of the geological background and mining activities in the upstream basin of the Yaqui River, and is dispersed as dissolved As species into the Yaqui irrigation district.
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With As concentrations averaging 16 µg.L⁻¹, GW at Cocorit is demonstrated to be contaminated (see section 3.2.2). As contaminations were also previously recorded in groundwaters from different cities from the Yaqui valley (Meza et al., 2004). Arsenic contaminations are frequently reported in coastal aquifers, and water/mineral interactions are usually responsible for the release of As into water, as observed in Bangladesh (Ahmad et al., 2018; Mihajlov et al., 2020; Smith et al., 2000), Vietnam (Sø et al., 2018) and China (Rodríguez-Lado et al., 2013). In this study, the As contamination in GW is suggested to result from As transfers from the geological basement to the dissolved phase of GW. Environmental conditions (pH, ORP, T), the water chemistry (ionic strength, the occurrence of competitive ions, organic matters) and the nature, abundance and characteristics of the solid phases (Fe-bearing phases, specific surface, surface charge, and crystallinity) control the As mobility (Amstaetter et al., 2009; Bissen and Frimmel, 2003; Grosbois et al., 2011; Haque et al., 2008; Inskeep et al., 2002; Oremland and Stolz, 2005; Sharma et al., 2011). Solid/liquid transfers of As are particularly found in coastal aquifers where seawater intrusions occur (Fakhreddine et al., 2021; Morelli et al., 2017; Yuan et al., 2023). In this study, As or dissolved As concentrations in GW are positively correlated with carbonates (r > 0.86 and p-values<0.0001) and no correlations are observed with others parameters or chemicals (such as pH, Cl, Fe...). Geochemical calculations indicate, for example, undersaturated GW at Cocorit with respect to As-oxides (saturation indices <100), suggesting these minerals are dissolved if they are present. A thorough mineralogical characterization of the geological substrate occurring in this Cocorit well (especially As- and Fe-bearing minerals) is necessary to better understand the exact mechanism involved in the As solid/liquid transfer.

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In the coastal area, DW samples exhibit elevated concentrations of As (approximately 20 µg.L⁻¹), which are subsequently discharged into Tobari Bay. This observation highlights significant inputs of As in the coastal zones, particularly as dissolved species (see section 3.2.2). Significant positive correlations are observed between As or dissolved As concentrations in DW from the AR16 drain and electrical conductivity (EC) and some total or dissolved major chemicals: Ca, Mg, Na, Sr, Cl, SO₄²⁻, B (r >0.73, p-value < 0.0001). As previously discussed in section 3.2.1, seawater samples are enriched with these major chemicals, but not with As (a mean value of 4.3 µg.L⁻¹). Seawater thus cannot be a direct source of As. However, the salinization of the water resource in the coastal zone is believed to induce transfer processes from the solid to the liquid phase (desorption or dissolution) responsible for higher As concentrations in these coastal DW samples. This hypothetical pathway agrees with geochemical calculations (section 3.1) that indicate undersaturated DW with possible dissolutions of halite, but also anhydrite and gypsum. These transfers may be promoted by physicochemical changes (such as EC) induced by salinization processes. This hypothesis is also supported by the observed changes in speciation for Mn, Ba, Al, and Fe, i.e. their repartition between particulate or dissolved species.
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### 3.5.2. Erosion and agriculture as a source of DW contaminations

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Unlike FW from channels, DW contains a large particulate load (high turbidities, see section 3.1). These suspended particles in water are demonstrated to be enriched with Al, Fe and Mn (see section 3.2.2). A significant co-variation is observed between Al and Fe concentrations in bulk DW and between Al and Fe in the dissolved phase of DW ($r > 0.98, p < 0.0001$). This statistical result confirms the common origin of Al and Fe in DW. This particulate contamination in DW is suggested to originate from the draining of the AR16 irrigation area. In the whole DR041 irrigation district, vertisol soil covers nearly the entire surface and is a recently developed soil with a thin and very clayey soil horizon (Almazán et al., 2022). These clay-rich soils have low permeability which favor runoff and evaporation during irrigation. Large amounts of Fe (around 3%) and Mn (around 600 $mg.kg^{-1}$) occur in this soils (Meza-Montenegro et al., 2012b). SPM are thus supposed to mainly originate from soil erosion. The runoff is then hypothesized to spread this contamination. In a recent study, Al, Fe and Mn was also demonstrated to be strongly related to SPM in coastal water (Su et al., 2024).

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DW from TD tributaries can be locally enriched with $NO_3^-$, $K^+$, $SO_4^{2-}$, $PO_4^{3-}$, Cu, Co, Ni, Cd, As (see sections 3.2.1 and 3.2.2). These water contaminations can occur locally in some tributaries and depend on the sampling date, as shown for Cu and As (Fig. 4). This episodic contamination in TD water further discharges into the main AR16 drain, but does not degrade the overall water quality downstream. The use of NPK fertilizers (e.g., ammonium sulfate, known to be used in this region), pesticides and manure/sewage evacuation can contribute to sporadic contamination (Liu et al., 2017; Meghdadi and Javar, 2018). A previous study evaluated the N budget in this irrigation district (Almazán et al., 2022) and found that 63% of the total N input for agriculture activities was utilized for plant needs, while 11% was lost through runoff, 7% leached into the aquifer, 18% remained in the soil, and 1% was volatilized. These results agree with the occurrence of high $NO_3^-$ concentrations in DW. The occurrence of episodic peaks in contamination, such as those observed for As, Cu, Co, Ni, and Cd, is also suspected to result from the intermittent use of fertilizers and pesticides/fungicides in these agricultural modules. As the result of the use of these agrochemicals, soils of this region contain high contents of Cr, Ni, Cu, Zn and Pb and present a high level of pollution (pollution load indices above 2) (Meza-Montenegro et al., 2012b). Soil erosion and runoff processes in the irrigation zone are then believed to carry these contaminants away through the irrigation district. This interpretation is consistent with previous studies reporting the transport of PTEs from the soil to the drainage system through runoff and/or soil washing (Basta and McGowen, 2004).

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### 3.5.3. Salinization of water resources

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Groundwater samples present mixed $Ca-HCO_3/Na-Cl$ hydrochemical facies, or $Na/Cl$ facies for those from Quetchehueca. Hydrochemical facies of DW changed along the AR16 drain from $Ca-HCO_3$ to $Na-Cl$ facies (see section 3.2.1). These results indicate a salinization of the water resource. During runoff, DW are progressively enriched with $Ca^{2+}$, $Mg^{2+}$, $Na^+$, $Cl^-$, $SO_4^{2-}$, Li, Sr, B, and Br concentrations.
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The concentrations of these major chemicals are mostly significantly correlated with each other, both in GW and in DW ($r > 0.8$ and p-value < 0.0001), confirming their variations have a common origin. As in many coastal areas, these large changes in the chemical concentrations in DW and GW can be interpreted as mixtures of seawater and freshwater (Alcalá, 2008; Cartwright et al., 2006). In the coastline of DR041 irrigation district, soils contained solonetz (Almazán et al., 2022). Solonetz soil has high concentrations of salts. The draining of these soils can also induce a salinization of DW.

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Figure 6 presents chemical signatures of different water sources: A/NO₃⁻/Cl⁻ molar ratio vs Cl⁻ concentration, B/Cl⁻/Br⁻ molar ratios vs 1/Cl⁻ concentrations, and C/ Ca²⁺/SO₄²⁻ vs Na⁺/Cl⁻ molar ratios (Fig. 6). In these graphs, two endmembers can be distinguished: one related to seawater and the other related to freshwater. Mixing lines were calculated between these two endmembers, assuming the chemicals to be conservative during the hypothetical FW/SW mixing. GW from Quetchehueca has Na⁺/Cl⁻ molar ratios close to 1, similar to SW, consistent with the salinization of GW resources already hypothesized in section 3.2.1. Results of some water resources lie close to or on these mixing lines. GW from Cocorit presents higher Na⁺/Cl⁻ molar ratios (ranging from 2.5 to 2.9) than seawater, but lower than FW. Results for these GW samples lie close to the FW/SW mixing line in the Ca²⁺/SO₄²⁻ vs Na⁺/Cl⁻ graph (Fig. 6C). For DW, 1/Cl⁻ concentrations increase from upstream to downstream of the AR16 watershed (Fig. 6B), with some DW results also distributed on the FW/SW mixing line. Similarly, Ca²⁺/SO₄²⁻ molar ratios in DW decrease from upstream to downstream of the AR16 watershed, reaching values similar to those measured in SW in some DW sampled close to the lagoon (sampling sites: TD12, TD14, or AR16-15), arguing for a salinization of DW. However, some chemical signatures of Ca²⁺/SO₄²⁻ and Na⁺/Cl⁻ molar ratios observed in DW may only be reached with very high proportion of SW (90 %) that is not compatible with the growth of plants. This result therefore suggests that another process is involved as well.

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### 3.5.4. What is the additional source of water contaminations?

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Since SW/FW mixing does not explain all the water compositions measured over the three years of this study, several other processes were considered, such as mixing with another water resource, evaporation, and dissolution precipitation or mineral phases in soils or ditches.

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Chemical signatures of some DW and GW were completely different than those obtained by FW/SW mixing: e.g., TD 4 to AR16-13 in March 2018, and occasionally others. These outliers revealed high NO₃⁻/Cl⁻, Cl⁻/Br⁻ and Ca²⁺/SO₄²⁻ molar ratios (Fig. 6). GW from Teras and Pueblo Yaqui present, for example, low Na⁺/Cl⁻ molar ratios (close to 0.5) which can be attributed neither to SW nor FW. DW presents high Ca²⁺/SO₄²⁻ molar ratios that cannot be explained by FW, DW from the upper part of AR16 irrigation district, GW, or the use of fertilizers enriched with SO₄²⁻ (would decrease the Ca²⁺/SO₄²⁻ ratio). Additional inputs of NO₃⁻, Cl⁻ or Ca²⁺ in the water or a reduction of Br and SO₄²⁻ concentrations are needed to explain the chemical signature of these outliers. While NO₃⁻ and SO₄²⁻ can originate from

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agriculture, Cl⁻, Ca²⁺ and Br⁻ in DW or GW are likely to be related to other sources. Rainwaters usually
has Cl⁻/Br⁻ molar ratios lower than those measured in the DW, FW and SW in this study (Alcalá, 2008;
Goni et al., 2001; Neal et al., 2007; Sadasivan and Anand, 1979), therefore mixing DW with rainwater
cannot explain the chemical signature of the DW outliers. Some groundwater presents high NO₃⁻/Cl⁻,
Cl⁻/Br⁻ and Ca²⁺/SO₄²⁻ molar ratios, but not as high as the DW outliers. Thus FW/GW/SW mixing cannot
account for the results obtained for DW outliers (Fig. 6). This ternary mixture is even less plausible if
the proportion of GW (< 10%) and FW (> 90%) in irrigation waters is taken into account. Cereal growth
could uptake some Br⁻ and thereby increase the Cl⁻/Br⁻ molar ratio (Uchida, 2011), but the present results
are not sufficient to test this possibility. Another potential additional input to explain the outliers could
be related to wastewater (Alcalá, 2008; Davis et al., 2004; Davis et al., 1998; Katz et al., 2011; McArthur
et al., 2012; Nissenbaum and Magaritz, 1991; Panno et al., 2006; Vengosh and Pankratov, 1998).
However, local wastewater did not present high Cl⁻/Br⁻ molar ratios (Fig. 6B), arguing against a mixing
between of FW, SW and wastewaters. The NO₃⁻/Cl⁻ molar ratio vs Cl⁻ concentration has previously been
proposed as a tracer of the water mixing between SW, FW and sewage (Su et al., 2020). The chemical
signature of sewage would represent a third endmember higher than the FW/SW mixing line. In this
study, a ternary water mixing with local wastewaters is therefore not demonstrated (Fig. 6A).

For groundwater, the hydrochemical facies evolution diagram has been previously used to better
constrain the groundwater chemical signature, solid/liquid transfers and ongoing processes concerning
salinization (Ghiglieri et al., 2012; Giménez-Forcada, 2014; Gopinath et al., 2019a); In this study, this
diagram confirms first that the chemical composition of GW cannot be related to a binary mixing
between SW and FW (results lie away from the red mixing line, Fig. A in Suppl. Info.). Second, it
demonstrates that chemicals do not behave conservatively. Solid/liquid interactions occur, leading to
chemical transfers. The chemical signature of GW makes it possible to discriminate between refreshing
processes or seawater intrusion (Ghiglieri et al., 2012; Giménez-Forcada, 2014; Gopinath et al., 2019a).
Only four GW samples were analyzed and they did not all exhibit the same behavior. These different
results can be attributed to different aquifer depths and distance to coast. GW from Cocorit, that is
situated in the f4 zone, exhibits a chemical signature close to the FW pole, indicative of a refreshing
aquifer. This result confirms the hypothesis that solid/water interactions explain the presence of As in
the GW from Cocorit (see section 3.5.1). Na and As are thus transferred simultaneously from the
geological substrate to the dissolved phase of the water. GW samples from Quetchehueca display a
chemical signature analogous to seawater, suggesting a relatively high salinization of the resource but
with an ongoing refreshing. In contrast, chemical signatures in GW from Teras or Pueblo Yaqui are
close to that of seawater, confirming that a process of salinization is underway. The geochemical
modeling also agrees with this result, revealing that GW are in relative equilibrium with respect to calcite
and dolomite, and undersaturated with respect to halite, gypsum and anhydrite. Consequently, if GW
drain these minerals, solid/liquid transfers occur, and Na⁺, Cl⁻, Ca²⁺ and SO₄²⁻ are released into the dissolved phase of waters.

In drainage water, water evaporation are expected to occur in this sub-desertic Sonora state and especially with 2018 being the hottest year of the twentieth and early twenty-first century (data from World Meteorological Organization). The effect of evaporation on the molar ratios has been therefore estimated with geochemical calculations considering FW and DW from AR16 and TD to be in equilibrium with soils at atmospheric pressure. Higher Cl⁻/Br⁻ molar ratios can be reached with SW/FW mixing and an evaporation of 50%. But, they are not sufficiently high to explain the chemical signatures of DW outliers. For FW, evaporation of 91% would produce residual waters with an EC of 1600 µS.cm⁻¹ and no change in Na⁺/Cl⁻ and Ca²⁺/SO₄²⁻ molar ratios. In DW from TD, evaporation of up to 98% would not change Na⁺/Cl⁻, but would increase Cl⁻/Br⁻ and Ca²⁺/SO₄²⁻ molar ratios due to precipitation of gypsum for example (Fig. 6C). These evaporation rates and small volume of residual waters with high concentrations of Na⁺, K⁺, Ca²⁺ and Cl⁻ and most SO₄²⁻ stored as gypsum can occur in modules that are mildly or extremely dried out. Ultimately, as in evaporated seawater, the evaporation would precipitate halite, epsomite (MgSO₄), carnallite (KMgCl₃), and finally calcite. The evaporation process cannot explain the concentrations and molar ratios observed in DW samples. However, these results argue for high Ca²⁺, Mg²⁺, Na⁺, Cl⁻, and SO₄²⁻ concentrations of residual water in soils (capillary fringe) and the precipitation of Ca²⁺, Mg²⁺, Na⁺, Cl⁻ as sulfate rich-minerals or halite in soils. This process would contribute to the soil salinization. Moreover, irrigation and runoff of DW, undersaturated with respect to halite and gypsum, can mix with residual water or cause the washing of salinized soils, leading to the dissolution of precipitated minerals. The dissolution of gypsum or halite could induce an enrichment of Na⁺, Cl⁻, SO₄²⁻ and Ca²⁺. The slow dissolution of gypsum would produce a decreased Ca²⁺/SO₄²⁻ molar ratio. The highest Na⁺, Cl⁻, Ca²⁺ and SO₄²⁻ concentrations are found in AR16-13, TD14, and AR16-15 sites, which are on the coastline with solonetz soils (Luers et al., 2003). Evaporation processes plus water drainage of halophile soils, the influence of foam and moisture from the Cortez Sea, and the possible mixing with brackish water from the Tobari bay may explained these increases of Na⁺, Cl⁻, Ca²⁺ and SO₄²⁻ concentrations in DW.

### 3.5.5. Chemical transfers from soils/SPM to drainage water

Thanks to complete measurements of flowrate all along the AR16 main drain and tributaries performed in Mar. 2018 (the driest sampling period), theoretical chemical concentrations of each chemical were estimated using the water mixing model, assuming its conservative behavior (see section 2.3 data treatment), and compared with measured chemical concentrations. The difference between this theoretical and measured concentrations was evaluated with discrepancy values. From AR16-1 to AR16-11, theoretical Ca, Mg, Sr, and As concentrations in DW from the AR16 drain are similar to measured ones (-10% < discrepancy < 10%), suggesting the conservative behavior of these chemicals and supporting that they mainly occur as dissolved species. Other chemicals do not behave conservatively.
NO₃⁻, K, HCO₃⁻ + CO₃²⁻, PO₄³⁻, and Cu have discrepancies lower than -10%, suggesting transfers from the dissolved phase of the water to the solid phase, such as sorption or precipitation. In contrast, Na⁺, Li, B, SO₄²⁻, and Cl⁻ show discrepancies higher than 10%, indicating transfers from solids to the dissolved phase of DW, that is the release of these chemicals. Other chemicals are observed to behave conservatively along the AR16 drain, or be precipitated, or released from solids, depending on the sampling sites. Non-conservativity behaviors have previously been observed : (1) for B, with transfers from solid hydroxides (B(OH)₂) to dissolved species (B²⁻, B(OH)⁻) depending on pH and temperature conditions (Hoefs, 2009); or (2) for Ba and Li during precipitation/dissolution of carbonate and sulfate (Füger et al., 2019; Mavromatis et al., 2018). In the coastal zone, most chemicals (Na⁺, Ca²⁺, Mg²⁺, SO₄²⁻, B, Sr, Li, Br⁻, Ni, Co, Cu, As; Table D and E in Suppl. Info.) have higher measured concentrations than those estimated by the water mixing model, especially for AR16-15 sampling site. The highest discrepancies were also observed in the coastal zone: 38% for Na⁺, 31% for Mg²⁺, 35% for Li, 33% for B, 53% for Br⁻, 49% for Ni. These results highlight significant transfer processes from solids to the dissolved phase of waters. All these results from the Mar. 2018 sampling suggest non-conservative behaviors of chemicals during the water drainage of this irrigation district, agreeing with previous suggestions for the whole dataset.

As demonstrated by the calculated saturation indices (see section 3.2.2), the specific signature of DW is related to chemical transfers from the solid phase (sediments or soils or SPM) and the dissolved phase of water. Water evaporation in agricultural modules may concentrate chemicals in residual water, which may remain stagnant. During drought periods, chemicals may precipitate in soils or dried-out ditches. Subsequent runoff from agricultural modules would promote chemical enrichments in water due to the mixing with residual waters or due to the dissolution of precipitated chemicals. In the coastal zone, soils are known to be halophilic. The runoff of these salty soils promotes the dissolution of precipitated minerals (halite, gypsum, carbonates) or fertilizers, and the subsequent release of chemicals into the water. Because DW also contain large amounts of SPM, transfer processes may also occur with the dissolution of SPM or desorption phenomena, resulting in chemical inputs of dissolved species in the water. This hypothetical pathway is strongly supported by the change of speciation of most PTEs (a higher proportion of Al, Fe, Mn as dissolved species) and higher As concentrations in DW from the closest sampling site to the bay (AR16-15) and in seawater. In the future, this interpretation could be checked by the mineralogical characterization and chemical analyses of soils, sediments from the drain, and SPM.

## 3.6. PTE transport into the Tobari bay

The sources and pathways of metals or metalloids in the coastal environment are complex because diverse processes play key roles in their passage from the land to the sea. In estuaries and lagoons, the composition of water may be modified by physicochemical processes, where strong
gradients of salinity, pH, and dissolved oxygen occur (Millward and Turner, 2001). Contaminant inputs from water constitute a threat for the coastal zone, particularly in this Mexican bay that is highly valued due to its rich biodiversity, high rates of biological productivity, and endemism. The biota contamination can be related either to the direct uptake of contaminated water, or to PTE transfers from SPM or sediments, or to trophic transfer. This study focusses on the PTE transport via DW because it accounts for the 2 pathways of biota contaminations.

In this study, DW are shown to contain higher PTE concentrations than SW. In seawater from the Tobari bay, variations in the concentrations of Al and PTEs in bulk waters and Cu, Ni and Pb in the dissolved phase of water are significantly correlated ($r > 0.83$, p-value < 0.0001), attesting to a common origin. As previously discussed in section 3.2.2, DW contains dissolved As species, Fe-, Al-, Mn-rich particles, or both dissolved or particulate Ni, Co, Cu, Pb. As suggested in section 3.3, the discharge of DW brings significant amounts of contaminants into the lagoon. The total fluxes of Al and PTE from DW to the Tobari lagoon were calculated using instantaneous flow rates (Table B in Suppl. Info.), their concentrations in bulk waters and in the dissolved phase for the most downstream DW sample site AR16-15 and for different sampling periods (Tables D and E in Suppl. Info.). Total and dissolved chemical fluxes are compared to better constrain the role of SPM in the transport of contaminations (Fig. 7 and Table F in Suppl. Info.). Moreover, these SPM settle in the bay as sediment, which can be a further source of contamination.

Total fluxes reaching the bay range from few hundreds to few thousands of kg.d⁻¹ for Al and Fe, few hundreds of kg.d⁻¹ for Ba and Mn, few kg.d⁻¹ for Co, Ni, Cu, As, Pb, and only few tenths of g.d⁻¹ for Cd. Significantly higher total fluxes are shown in Mar. 2018 for Al and Fe, the hottest year. For the other chemicals, total fluxes are of the same order of magnitude for all sampling periods. This can be explained by the similar flow rates (2-3 m³.s⁻¹) and PTE concentrations measured in DW. The novelty of this study is to highlight the nature of PTE transport (particulate or dissolved species) according to the sampling periods. As has similar total and dissolved fluxes in all sampling periods, demonstrating that it occurs under dissolved species and water pollution concerning As is chronic. For other chemicals, significant differences are observed in different sampling periods. While the total fluxes of Al, Fe or Mn are similar in Mar. 2019 and Nov. 2019, the dissolved fluxes of these elements are significantly different. In Mar. 2018 and Mar. 2019, inputs of Al, Fe and Mn from AR16 into the bay are mostly in the form of under suspended particles (more than 86%), whereas, in Nov. 2019, they are mainly in dissolved species (more than 82%). Co, Cu, Ni, Pb and Cd are transported to the bay either mainly in dissolved or particulate species, depending on the sampling period.

One of the harmful hazards identified in this study is associated with As. With regard to drain AR16, the inputs of dissolved or particulate arsenic are comparable and estimated to be approximately 3 kg per day (with a flowrate of 2.2 m³.s⁻¹). The AR16 drain supplies only 10% of freshwater inputs into
the bay. The total inputs of As reaching the Tobari bay are thus supposed to be 10 times higher to account for the five drains of the irrigation zone. The overall input, therefore, would be approximately 30 kg per day. For example, this result is considerably higher than the estimated flux of dissolved As (4.2 tons per year or 12 kg per day and considering the Var river flowrate of 49 m³.s⁻¹) reaching the Mediterranean sea by the Var River, a watershed with low anthropic activities (Barats et al., 2014). This comparison confirms that As fluxes in this Mexican coastal environment are a relevant threat and rather related to an anthropic origin (mining here). Significant degradations of drainage waters were also demonstrated to be related to SPM enriched with Al and Fe, and in a lesser extent Mn. For the AR16 drain, their total fluxes average 1840 kg.d⁻¹ for Al, 1143 kg.d⁻¹ for Fe, and 56 kg.d⁻¹ for Mn, corresponding to 7.9, 2.4, and 0.12 mol.s⁻¹, respectively. Considering that the AR16 drain supplies only 10% of freshwater inputs into the bay, the total inputs of metals and metalloids reaching the Tobari bay would be 10 times higher. These fluxes are higher than those measured in a large river (flowrate of 8000 m³.s⁻¹) reaching the Bay of Bengal: 7.07 mol.s⁻¹ for Al, 3.02 mol.s⁻¹ for Fe and 0.095 mol.s⁻¹ for Mn (Su et al., 2024). As these fluxes are drastically decreased in the dissolved phase, this study demonstrates that SPM in freshwater is an important vector for the mobilization of many contaminants. This result agrees with previous studies, suggesting that SPM can accumulate contaminants in drainage basins in relation to anthropogenic activities (Dumas et al., 2015; Lawson et al., 2001).

This study highlights the importance of SPM in the transport of chemicals, mainly for Al, Fe and Mn. SPM constitute also an important reservoir of Co, Cu, Ni, Pb and Cd from drainage waters, that are then input into the bay. The reactivity of this PTE-rich SPM needs to be better constrained to estimate potential PTE transfers from SPM to the water column, especially in an estuarine context with changes of physicochemical conditions (salinity, pH, T, etc.). As shown in this study, water/SPM interactions can favor transfers of PTEs from the solid phase to the dissolved phase of the water. SPM are clay minerals of soils (Si and Al), oxy-hydroxides (Fe and Al), and carbonates, and DW is undersaturated with respect to these minerals (saturation indices above 1). These minerals may be dissolved during the mixing of drainage water with seawater (higher ionic strength), and possibly more reducing conditions, leading to an increase in the concentration of several PTEs in the water. In order to reduce PTE fluxes into the bay, the mass of SPM might be reduced by establishing settling ponds at the mouth of the drainage basin. Nevertheless, this recommendation would not remove the high threat caused by PTE fluxes of dissolved species such as As, Cu and Cd. Indeed, these dissolved species are recognized to be bioavailable (Basta and Juhasz, 2014; Bowell et al., 2014; Shahid et al., 2017), toxic (Mitchell, 2014), and ultimately bioaccumulated in organisms living in the Tobari lagoon that are then harvested for aquaculture (Jara-Marini et al., 2020; Jara-Marini et al., 2008; Jara-Marini et al., 2013a).
974

## 4. Conclusion

975

976

977

978

979

980

981

982

983

984

985

986

987

988

989

990

991

The first highlight of this study is that the water quality and origins of contaminations in the yaqui valley are determined using WQI and HEI. Freshwater used for irrigation and groundwater present good pollution levels, despite contaminations from dissolved As species from the upper Yaqui basin, suspected to be related to mining activities, and from solid/liquid transfers in groundwater. The water quality of drainage water is demonstrated to be poor due to: (1) large amounts of SPM enriched with Al and Fe, related to the runoff on the irrigation area, (2) intermittent contaminations by Cu, $K^+$, $NO_3^-$ and $PO_4^{3-}$ due to fertilizers or pesticides used for agriculture, and (3) contaminations by $Na^+$, $Ca^{2+}$, $SO_4^{2-}$, $Cl^-$, and As in coastal drainage waters due to salinization or transfers from soils/SPM to the dissolved phase of water. Drainage waters, discharging into the Tobari lagoon, input large amounts of Fe- and Al- rich SPM and dissolved As. The seawater is consequently of the low water quality, with not only high concentrations of some major chemicals ($Na^+$, $Ca^{2+}$, $SO_4^{2-}$, $Cl^-$) and but also large amounts of SPM enriched with Al and Fe. Moreover, changes in salinity can promote the PTE release from SPM or settled SPM in sediments to the water column. Further studies on the mineralogy and the chemical composition of these SPM would provide a better estimation of transfer events. In the future, careful attention should be paid to these solid/liquid interactions, especially the physicochemical conditions (pH, T, $E_h$, ionic strength) that promote them, to better constrain the PTE exposure of coastal organisms and to estimate possible ecological risks.

992

993

994

995

996

997

998

999

1000

1001

This study provides also new results on the assessment of human health risks, offering insights into managing and mitigating the identified risks. Despite an overall good water quality for groundwater in this coastal Mexican area, this water resource was, for the first time, revealed to be influenced by former or recent seawater intrusion. Some water resources are refreshing whereas for others, salinization of the water resource is ongoing. The novelty of this study is also in showing that the main health exposure risk is associated with the ingestion pathway (rather than dermal contact) and due mainly to dissolved As in water. A significant cancer risk is demonstrated, especially for children. In the future, other contaminants such as agrochemicals (pesticides, etc.) should be integrated in this health risk assessment to better reflect the actual exposure. Particular attention should be paid to a possible cocktail effect, due to interactions between contaminants.

1002

1003

1004

1005

1006

This study proposes new water management tools to ensure access to clean water, a challenge due to agricultural practices that is compounded by a lack of awareness. The findings provide insights and offer valuable recommendations for preventing risks to population health, imporving sustainable practices (especially in this agricultural region) and mitigating ecotoxicological risks in the Tobari bay, a zone of interest due to economic activities (fishing and aquaculture).

1007
## 5. Acknowledgments

The authors would like to thank María Teresa RODRIGUEZ for technical support in sample collection, preparation and analysis and the Management office of irrigation district of the Yaqui River for the facilities provided to carry out field work and sampling. They are grateful to the following institutions for funding this research: the Mexican institute of water technology (IMTA, project "Estimación y dispersión de contaminantes en el río Yaqui (Sonora, México); evaluación y riesgos ambientales"), the Consejo Nacional de Ciencia y Tecnología (CONACYT, for the scholarship granted), the Universidad Autónoma del Estado de México, the Centro de Investigación en Alimentación y Desarrollo, the French national center of scientific research (CNRS, International Project of Scientific cooperation PICS2018, "Contamin'Yaqui"), and the Geoazur lab (projects: CSI2017 and BQR2020). This work was also supported by the French government through the France 2030 investment plan managed by the National Research Agency (ANR), as part of the Initiative of Excellence Université Côte d'Azur under reference number ANR-15-IDEX-01. The author would like to thank Jean Dumont et Fabienne Séby from the UT2A lab for PTE analyses of seawater.

1022

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<table><caption>Table 1: Assessment of human health risks from exposure to pollutants in groundwaters for children and adults with the mean total chronic daily intake (CDI) of PTEs (mg.kg⁻¹.day⁻¹) by oral ingestion and dermal contact and the proportion of CDI<sub>ingestion</sub>; and with the mean hazard quotient (HQ) and the proportion related to the ingestion pathway. Toxicological data used are for these calculations are: skin adherence time (Kp), ingestion and dermal reference doses (RfD) and cancer slope factors (CSF) (Kavcar et al. 2009).</caption><thead><tr><th rowspan="2"></th><th rowspan="2">Kp</th><th colspan="2">RfD ingestion</th><th colspan="2">CSF</th><th colspan="2">CDI total (µg.kg<sup>-1</sup>.day<sup>-1</sup>)</th><th colspan="2">CDI<sub>ingestion</sub>/CDI</th><th colspan="2">HQ</th><th colspan="2">HQ<sub>ingestion</sub>/HQ</th></tr><tr><th>cm.h<sup>-1</sup></th><th>µg.kg<sup>-1</sup>.day<sup>-1</sup></th><th>µg.kg<sup>-1</sup>.day<sup>-1</sup></th><th>µg.kg<sup>-1</sup>.day<sup>-1</sup></th><th>Adult</th><th>Children</th><th>Adult</th><th>Children</th><th>Adult</th><th>Children</th><th>Adult</th><th>Children</th></tr></thead><tbody><tr><td>Al</td><td>0.001</td><td>1000</td><td>1000</td><td>-</td><td>-</td><td>0.76</td><td>1.1</td><td>99%</td><td>99%</td><td>0.00076</td><td>0.0011</td><td>99%</td><td>99%</td></tr><tr><td>Ba</td><td>0.001</td><td>200</td><td>14</td><td>-</td><td>-</td><td>2.2</td><td>3.3</td><td>99%</td><td>99%</td><td>0.012</td><td>0.019</td><td>93%</td><td>87%</td></tr><tr><td>Fe</td><td>0.001</td><td>700</td><td>700</td><td>-</td><td>-</td><td>1.5</td><td>2.2</td><td>99%</td><td>99%</td><td>0.0021</td><td>0.0032</td><td>99%</td><td>99%</td></tr><tr><td>Mn</td><td>0.001</td><td>24</td><td>0.96</td><td>-</td><td>-</td><td>0.071</td><td>0.11</td><td>99%</td><td>99%</td><td>0.0033</td><td>0.0055</td><td>88%</td><td>80%</td></tr><tr><td>Co</td><td>0.0004</td><td>0.3</td><td>0.3</td><td>-</td><td>-</td><td>0.0049</td><td>0.0074</td><td>100%</td><td>100%</td><td>0.016</td><td>0.025</td><td>100%</td><td>100%</td></tr><tr><td>Ni</td><td>0.0002</td><td>20</td><td>5.4</td><td>-</td><td>-</td><td>0.0080</td><td>0.012</td><td>100%</td><td>100%</td><td>0.00040</td><td>0.00060</td><td>100%</td><td>99%</td></tr><tr><td>Cu</td><td>0.001</td><td>40</td><td>40</td><td>-</td><td>-</td><td>0.062</td><td>0.093</td><td>99%</td><td>99%</td><td>0.0015</td><td>0.0023</td><td>99%</td><td>99%</td></tr><tr><td>As</td><td>0.001</td><td>0.3</td><td>0.285</td><td>1.5</td><td>-</td><td>0.28</td><td>0.41</td><td>99%</td><td>99%</td><td>0.92</td><td>1.4</td><td>99%</td><td>99%</td></tr><tr><td>Cd</td><td>0.001</td><td>0.5</td><td>0.025</td><td>1.5</td><td>-</td><td>0.010</td><td>0.015</td><td>99%</td><td>99%</td><td>0.022</td><td>0.036</td><td>91%</td><td>83%</td></tr><tr><td>Pb</td><td>0.0001</td><td>1.4</td><td>0.42</td><td>0.0085</td><td>-</td><td>0.0063</td><td>0.0094</td><td>100%</td><td>100%</td><td>0.0045</td><td>0.0067</td><td>100%</td><td>100%</td></tr></tbody></table>
<figure><img src="image_4.png" /><figcaption>**Figure 1:** Map of the sampling zone of irrigation district DR041 in the Yaqui valley and a schematic representation of the sampling strategy: in orange, freshwater from the irrigation channels in the upper part of the AR16 watershed; in green, groundwater; in yellow, drainage water along the main AR-16 drain; and in blue, drainage waters in tributaries (TD).</figcaption></figure>
<figure><img src="image_5.png" /><figcaption>Figure 2: Boxplots of major concentrations in the dissolved phase in freshwater (FW), groundwater (GW), drainage water (DW) from the main AR16 drain and drainage water from TD tributaries in the DR041 irrigation district in the Yaqui valley.</figcaption></figure>
<figure><img src="image_6.png" /><figcaption>**Figure 3:** Mean concentrations of Al and potential toxic elements (PTEs) in bulk water (dark blue) and in the dissolved phase of water (light blue) from the different water sources: freshwater (FW), groundwater (GW), and drainage water (DW) from the main AR16 drain and from the TD tributaries in the DR041 irrigation district in the Yaqui valley, and according to WHO guidelines for drinking waters (red dashed line).</figcaption></figure>
<figure><img src="image_7.png" /><figcaption>Figure 4: Variations in total Cu and As concentrations (µg.L⁻¹) in drainage water (DW) along the main AR16 irrigation drain and from TD tributaries for two sampling periods: in blue at the beginning of the irrigation period (Nov. 17, Dec. 18 and Nov. 19) and in yellow and orange at the end (Mar. 18 and Mar. 19).</figcaption></figure>
<figure><img src="image_8.png" /><figcaption>**Figure 5:** Comparison of water quality indices (WQI: with color changes from high-quality in green to low quality in red) of bulk water (left part) and dissolved phases of water (right part) in the AR16 hydrosystem (irrigation district DR041, Yaqui valley) from different water sources: groundwater (GW, triangles), drainage water (DW, squares) and from tributaries (TD, circles).</figcaption></figure>
<figure><img src="image_9.png" /><figcaption>**Figure 6:** Chemical signatures of different water sources sampled in the AR16 irrigation module: freshwater (FW) from low and high channels, drainage water (DW) from the main AR-16 drain and from tributaries (TD), groundwater (GW), wastewater, and seawater (SW) from the Tobari bay: A) NO₃⁻/Cl⁻ molar ratio vs Cl⁻ concentration, B) Cl⁻/Br⁻ molar ratio vs 1/Cl⁻, and C) Ca²⁺/SO₄²⁻ molar ratio vs Na⁺/Cl⁻ molar ratio. The black dashed line represents a theoretical binary mixture between FW and SW, assuming the chemicals are conservative. The yellow stars in part C represent the theoretical water composition of DW with an evaporation rate of 98% or 99%.</figcaption></figure>
<figure><img src="image_10.png" /><figcaption>**Figure 7:** Daily PTE fluxes from the AR16 drained zone (irrigation district DR041, Yaqui valley) to the Tobari lagoon in different sampling periods: in dark and light blue for sampling performed at the beginning of the irrigation period and in yellow and orange for sampling performed at the end of the irrigation period. The percentages in brackets correspond to the proportion of dissolved PTE species in these total fluxes.</figcaption></figure>
## Highlights

* Mining, agriculture and salinization are damaging the water quality.

* Ingesting water enriched with dissolved As is the main health risk.

* Suspended particles enriched with Al and Fe threatens surface water quality.

* Salinization promotes the transfer of As from solid to dissolved species.

* Ecological risks due to significant chemical fluxes from drainage waters.
**Declaration of interests**

☐ The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

☒ The authors declare the following financial interests/personal relationships which may be considered as potential competing interests:

Barats reports financial support was provided by National Research Agency (ANR). Gonzalez-Perez reports financial support was provided by Consejo Nacional de Ciencia y Tecnología (CONACYT). If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.