Assessment of nitrate and heavy metal contamination of groundwater using the heavy metal pollution index: case study of Linares, Mexico

León-Gómez, Héctor de; Campo, M.A. Martin del; Esteller-Alberich, María V.; Velasco-Tapia, Fernando; Alva-Niño, Efraín; Cruz‐López, Arquímedes

doi:10.1007/s12665-020-09164-3

Cited by 11 publications

(5 citation statements)

References 35 publications

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“…Tunisia, along with all the nations on the southern shore of the Mediterranean, faces a significant deficiency in water resources., A set of factors, including population growth, climate change, and uneven spatiotemporal distribution of water, have led to a rise in water demand (Hamzaoui-Azaza et al, 2011). This situation has the potential to have serious repercussions on the quantity and quality of groundwater resources, which could impact the country's water security and economic development (De León-Gómez et al, 2020).…”

Section: Introductionmentioning

confidence: 99%

Employing Machine Learning Approaches and Multivariate Analysis to Assess Groundwater Quality for Irrigation in the Mornag Plain, Tunisia

Hfaiedh,

Gaagai,

Moussa

et al. 2024

Preprint

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The crucial assessment of water quality in the Mornag Plain, Tunisia, is fundamental for reservoir management, ensuring suitability for consumption, and preserving environmental integrity. Employing a diverse range of methodologies, such as water quality indices (WQIs), statistical analyses, geographic information systems (GIS), and decision tree (DT) model, provided a nuanced understanding of the compositional attributes of groundwater designated for irrigation. Detected categories of water, for instance Na-Cl, Ca-Mg-SO4, and a combination of Ca-Mg-Cl/SO4, displayed unique chemical signatures. These patterns were shaped by diverse processes including interactions between water and rock, the breakdown of dolomite, the concentration of minerals through evaporation, the swapping of ions, and human impact. Evaluating groundwater's suitability for irrigation purposes by employing measures like Na%, SAR, SSP, and MH, demonstrated that a significant portion of the samples conformed to approved norms. However, the analysis revealing 65.6% of the IWQI and every instance of PS falling within the spectrum of high to severe constraints, as well as ranging from detrimental to unsatisfactory classes, underscores the obstacles in sustaining superior irrigation water standards. The predictive model, DT, demonstrated robust results in forecasting all water quality indices. The DT-HyC-9 model stood out as the top performer in prediction accuracy, demonstrating a robust correlation with prime factors affecting IWQI, as shown by substantial R2 metrics in both the training and evaluation phases. Likewise, the DT-HyC-3 approach showcased remarkable precision in forecasting IWQI, highlighting the critical role of three essential factors. These results provide crucial guidance for policymakers engaged in managing water quality, laying the groundwork for the sustainable management of water resources within the Mornag Plain. The integration of advanced methodologies and predictive models enhances the understanding of groundwater dynamics, facilitating informed decision-making for the region's water sustainability.

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Section: Introductionmentioning

confidence: 99%

Employing Machine Learning Approaches and Multivariate Analysis to Assess Groundwater Quality for Irrigation in the Mornag Plain, Tunisia

Hfaiedh,

Gaagai,

Moussa

et al. 2024

Preprint

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“…The Mexican Official Standard NOM-127-SSAI-2021 states that the maximum permissible levels of nitrate nitrogen in water for human consumption are 11 mg L −1 , or its equivalence to nitrates of 48.62 mg L −1 [35]. Exceeding the permissible concentration limit can have severe and long-term detrimental effects on human health (e.g., methemoglobinemia in infants, congenital disabilities, health effects in adults such as stomach and liver damage, and can lead to cancer), depending on the exposure time [36][37][38][39]. Consequently, it is crucial to monitor concentration levels closely to prevent the consumption of contaminated water or, ideally, to take remedial measures at high concentration levels.…”

Section: Introductionmentioning

confidence: 99%

Vulnerability to Aquifer Pollution in the Mexican Wine Producing Valley of Guadalupe, México

Díaz-Gutiérrez,

Daesslé,

Del-Toro-Guerrero

et al. 2024

Hydrology

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Groundwater pollution is one of the main challenges in our society, especially in semi-arid Mediterranean regions. This issue becomes especially critical in predominantly agricultural areas that lack comprehensive knowledge about the characteristics and functioning of their aquifer system. Vulnerability to groundwater pollution is defined as the sensitivity of the aquifer to being adversely affected by an imposed pollution load. For the Guadalupe aquifer, various indicators including water level depth, level variation, aquifer properties, soil composition, topography, impact on the vadose zone, and hydraulic conductivity were evaluated to establish spatial vulnerability categories ranging from very low to very high. Two pollution vulnerability scenarios (wet and dry) were studied. The results were compared with the analysis of nitrate concentration and distribution (2001, 2020, and 2021) from samples collected in the field. In the Calafia area, which predominantly relies on viticulture, the primary recharge inputs were identified in areas with a high vulnerability to pollution. Surprisingly, these vulnerable areas exhibited lower nitrate concentrations. This scenario underscores the need for effective management measures to safeguard aquifers in agricultural regions.

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“…Studies on the physicochemical characteristics of groundwater and heavy metals have been carried out in Africa (Amoako et al, 2011; Beatrice et al, 2019; Boateng et al, 2019), Asia (Bhagure & Mirgane, 2011; Lou et al, 2017; Nagendrappa et al, 2010; Rezaverdinejad & Rahimi, 2017; Selvam, 2017; Shakerkhatibi et al, 2019; Shyamala et al, 2008; Wang et al, 2022; Zhai et al, 2022), Europe (Algül & Beyhan, 2020; Dippong et al, 2022; Stamatis et al, 2001; Zanchi et al, 2022), North America (de León‐Gómez et al, 2020), and South America (Custodio et al, 2021; Gimenez et al, 2013; Rupias et al, 2021). Many scholars including Adejuwon and Mbuk (2011) and Alabi et al (2013) based their studies on the physicochemical characteristics of groundwater water in Nigeria.…”

Section: Introductionmentioning

confidence: 99%

Physicochemical characteristics and heavy metals of groundwater during the wet and dry seasons at the Lafarge cement factory environment, Sagamu, Ogun State, Nigeria

Adejuwon

Odusote

2023

World Water Policy

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This study examined the physical, chemical, and heavy metals in groundwater from boreholes and hand‐dug wells at the Lafarge cement factory environment at Sagamu, Ogun State, Nigeria. Water samples were obtained from 20 sampling locations during the wet and dry seasons of 2019. The 17 parameters determined include the pH, temperature, electrical conductivity, total dissolved solids (TDS), total hardness, alkalinity, salinity, chloride, sulfate, phosphate, nitrate, calcium, magnesium, copper, lead, iron, and cadmium. The samples were analyzed using titrimetric and spectrophotometric methods. Correlation analysis was applied as part of the analytical tool in this study. The result indicated low physiochemical concentration of pH, total hardness, sulfate, nitrate, chloride, magnesium, calcium (>1% to 15%), and electrical conductivity (>1000 μS/cm) and fell within the Standard Organization of Nigeria (SON) and World Health Organization (WHO) desirable and maximum permissible limits for potable water during the wet and dry seasons. However, phosphate was above the standard limit for portable water of 6.5 mg/L in all sampling locations, whereas the total alkalinity was above the WHO standard limit (200 mg/L) in 12 locations in the wet seasons and a location in the dry season. Salinity was also above standards in one and four locations in the wet and dry seasons, respectively. Lead and cadmium were not detected in most locations, whereas iron, lead, cadmium, and copper were above standard limits in some locations. A significant relationship exists between the heavy metals and some of the physiochemical parameters at p ≥ .05 and p ≥ .01. The polluted water in most locations is capable of resulting in an adverse health hazard. Thus, this study explains the effect of physicochemical and heavy metals on water management at Sagamu and is important for water resource planning.

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Assessment of nitrate and heavy metal contamination of groundwater using the heavy metal pollution index: case study of Linares, Mexico

Cited by 11 publications

References 35 publications

Employing Machine Learning Approaches and Multivariate Analysis to Assess Groundwater Quality for Irrigation in the Mornag Plain, Tunisia

Employing Machine Learning Approaches and Multivariate Analysis to Assess Groundwater Quality for Irrigation in the Mornag Plain, Tunisia

Vulnerability to Aquifer Pollution in the Mexican Wine Producing Valley of Guadalupe, México

Physicochemical characteristics and heavy metals of groundwater during the wet and dry seasons at the Lafarge cement factory environment, Sagamu, Ogun State, Nigeria

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