The identification of nitrate (NO3-) sources and biogeochemical transformations is critical for understanding the different nitrogen (N) pathways, and thus, for controlling diffuse pollution in groundwater affected by livestock and agricultural activities. This study combines chemical data, including environmental isotopes (δ2HH2O, δ18OH2O, δ15NNO3, and δ18ONO3), with land use/land cover data and a Bayesian isotope mixing model, with the aim of reducing the uncertainty when estimating the contributions of different pollution sources. Sampling was taken from 53 groundwater sites in Comarca Lagunera, northern Mexico, during 2018. The results revealed that the NO3- (as N) concentration ranged from 0.01 to 109 mg/L, with more than 32% of the sites exceeding the safe limit for drinking water quality established by the World Health Organization (10 mg/L). Moreover, according to the groundwater flow path, different biogeochemical transformations were observed throughout the study area: microbial nitrification was dominant in the groundwater recharge areas with elevated NO3- concentrations; in the transition zones a mixing of different transformations, such as nitrification, denitrification, and/or volatilization, were identified, associated to moderate NO3- concentrations; whereas in the discharge area the main process affecting NO3- concentrations was denitrification, resulting in low NO3- concentrations. The results of the MixSIAR isotope mixing model revealed that the application of manure from concentrated animal-feeding operations (∼48%) and urban sewage (∼43%) were the primary contributors of NO3- pollution, whereas synthetic fertilizers (∼5%), soil organic nitrogen (∼4%), and atmospheric deposition played a less important role. Finally, an estimation of an uncertainty index (UI90) of the isotope mixing results indicated that the uncertainties associated with atmospheric deposition and NO3--fertilizers were the lowest (0.05 and 0.07, respectively), while those associated with manure and sewage were the highest (0.24 and 0.20, respectively).

Nitrate contamination in groundwater poses a significant threat to water quality and public health, especially in regions with limited data availability. This study addresses this challenge by employing machine learning (ML) techniques to predict nitrate (NO₃^--N) concentrations in Mexico's groundwater. Four ML algorithms-Extreme Gradient Boosting (XGB), Boosted Regression Trees (BRT), Random Forest (RF), and Support Vector Machines (SVM)-were executed to model NO₃^--N concentrations across the country. Despite data limitations, the ML models achieved robust predictive performances. XGB and BRT algorithms demonstrated superior accuracy (0.80 and 0.78, respectively). Notably, this was achieved using ∼10 times less information than previous large-scale assessments. The novelty lies in the first-ever implementation of the 'Support Points-based Split Approach' during data pre-processing. The models considered initially 68 covariates and identified 13-19 significant predictors of NO₃^--N concentration spanning from climate, geomorphology, soil, hydrogeology, and human factors. Rainfall, elevation, and slope emerged as key predictors. A validation incorporated nationwide waste disposal sites, yielding an encouraging correlation. Spatial risk mapping unveiled significant pollution hotspots across Mexico. Regions with elevated NO₃^--N concentrations (>10 mg/L) were identified, particularly in the north-central and northeast parts of the country, associated with agricultural and industrial activities. Approximately 21 million people, accounting for 10 % of Mexico's population, are potentially exposed to elevated NO₃^--N levels in groundwater. Moreover, the NO₃^--N hotspots align with reported NO₃^--N health implications such as gastric and colorectal cancer. This study not only demonstrates the potential of ML in data-scarce regions but also offers actionable insights for policy and management strategies. Our research underscores the urgency of implementing sustainable agricultural practices and comprehensive domestic waste management measures to mitigate NO₃^--N contamination. Moreover, it advocates for the establishment of effective policies based on real-time monitoring and collaboration among stakeholders.

This study aimed to determine the reliability of the double-clustering method to understand the spatial association and distribution of major and minor constituents in the groundwater of an arid endorheic basin in central Mexico (Comarca Lagunera Region). The results of the double-clustering approach were compared with well-known spatial statistics such as spatial autocorrelations (Moran index) and the local indicator of spatial association (LISA). Fifty-five groundwater samples were collected from diverse wells within the basin, and the major ions, metalloids, and trace elements were determined. Overall, the double-clustering analysis was an effective tool for identifying lithogenic/anthropogenic processes occurring in the basin and for establishing zones with high or low abundance of major ions and trace elements, even where processes affecting the groundwater quality were spatially dispersed. Although 89% of the samples showed As higher than the threshold value of 10 μg/L proposed by the World Health Organization for drinking water, both the double-clustering and LISA analyses identified As hotspots in the alluvial aquifer, where the extraction of deeper and warmer groundwater might promote the concomitant release of the metalloids As, Sb, and Ge and the trace elements V and W. Similarly, both statistical analyses identified mountainous sectors where the weathering of silicates and carbonates plays a key role in the abundance of HCO₃^-, Ga, and Ba. However, the LISA analysis failed to identify hotspots of carbonate-derived elements such as Ca, Mg, Sr, and U and silicate-derived elements such as Ca, Mg, K, Sr, Rb, Cs, Pb, Ni, and Y. Otherwise, the double-clustering analysis clearly defined high- and low-concentration zones for all these elements in the study region. Unlike the LISA analysis, the double-clustering approach was also successful in determining alluvial areas with high concentrations of Si and Ti and areas where the concentrations of Na, Cl^-, SO₄^2-, NO₃^-, B, Li, Cu, Re, and Se in groundwater were elevated, increasing the groundwater salinity. Overall, this study demonstrated that the double-clustering is an easy-to-apply approach, capable of visualizing disperse zones where specific anthropogenic processes may threaten the groundwater quality.

Saltwater intrusion is one of the most pressing environmental concerns in coastal areas with increased water demands. Water extraction decreases the level of fresh groundwater, reducing the water pressure and allowing saltwater to flow further inland. Tools for simulating, monitoring and managing saltwater intrusion can provide valuable support in decision-making for management options. In this work, such a tool was developed for the arid coastal aquifer of La Paz in Baja California, Mexico. A geomodel was generated by using a transient electromagnetic method (aquifer geometry, saltwater intrusion). This geomodel, in turn, was used to construct a three-dimensional density-dependent flow model to simulate groundwater flow and saltwater intrusion during the past decades. The results confirmed that a large cone of depression had formed due to excessive pumping in the agricultural area. This successively led to the inversion of the hydraulic gradient and seawater intrusion advancement on the order of 6–8 km inland in the northern-central portion of the aquifer. Freshwater recharge mostly originates from the mountainous southeastern portion of the basin. It supplies water for the city of La Paz and counteracts the saltwater intrusion advancement. The alternation of advancement and retreat of the freshwater–saltwater interface could be attributed to changing climate effects and/or policy changes. L’intrusion d’eau salée est l’une des préoccupations environnementales les plus pressantes dans les zones côtières, où la demande en eau augmente. L’extraction de l’eau diminue le niveau des eaux souterraines douces, ce qui réduit la pression de l’eau et permet à l’eau salée de s’écouler plus à l’intérieur des terres. Des outils de simulation, de surveillance et de gestion de l’intrusion d’eau salée peuvent fournir un soutien précieux dans la prise de décision pour les options de gestion. Dans ce travail, un tel. outil a été développé pour l’aquifère côtier aride de La Paz, en Basse Californie, au Mexique. Un géomodèle a été généré en utilisant une méthode électromagnétique transitoire (géométrie de l’aquifère, intrusion d’eau salée). Ce géomodèle a été utilisé ensuite pour construire un modèle d’écoulement tridimensionnel dépendant de la densité afin de simuler l’écoulement des eaux souterraines et l’intrusion d’eau salée au cours des dernières décennies. Les résultats ont confirmé qu’un large cône de dépression s’était formé en raison d’un pompage excessif dans la zone agrícole. Cela a conduit successivement à l’inversion du gradient hydraulique et à la progression de l’intrusion d’eau de mer de l’ordre de 6–8 km à l’intérieur des terres dans la partie centre-nord de l’aquifère. La recharge en eau douce provient principalement de la partie sud-est montagneuse du bassin. Elle fournit de l’eau pour la ville de La Paz et contrecarre l’avancée de l’intrusion d’eau salée. L’alternance d’avancée et de recul de l’interface eau douce-eau salée pourrait être attribuée aux effets du changement climatique et/ou aux changements de politique. La intrusión de agua salada es uno de los problemas ambientales más acuciantes en las zonas costeras con mayores demandas de agua. La extracción de agua disminuye el nivel de agua subterránea dulce, reduciendo la presión del agua y permitiendo que el agua salada fluya hacia el interior. Las herramientas para simular, monitorear y manejar la intrusión de agua salada pueden proporcionar un valioso apoyo en la toma de decisiones para las opciones de manejo. En este trabajo, se desarrolló una herramienta de este tipo para el acuífero costero árido de La Paz en Baja California, México. Se generó un geomodelo utilizando un método electromagnético transitorio (geometría del acuífero, intrusión de agua salada). Este modelo geométrico, a su vez, se utilizó para construir un modelo de flujo tridimensional dependiente de la densidad para simular el flujo de agua subterránea y la intrusión de agua salada durante las últimas décadas. Los resultados confirmaron que se había formado un gran cono de depresión debido al bombeo excesivo en el área agrícola. Esto condujo sucesivamente a la inversión del gradiente hidráulico y del avance de la intrusión de agua de mar en el orden de 6–8 km tierra adentro en la parte norte-central del acuífero. La recarga de agua dulce se origina principalmente en la parte sureste montañosa de la cuenca. Ella suministra agua a la ciudad de La Paz y contrarresta el avance de la intrusión de agua salada. La alternancia entre el avance y el retroceso de la interfaz agua dulce-agua salada podría atribuirse a los efectos cambiantes del clima y/o a cambios en las políticas. 海水入侵是沿海地区增加需水量最迫切的环境问题之一。开采地下水降低了地下淡水水位,减少了水压而使盐水进一步向内陆流入。用于模拟,监测和管理盐水入侵的工具可以为管理选择的决策提供有价值的支持。在本工作中,在墨西哥下加利福尼亚州La Paz的干旱沿海含水层开发了这种工具。采用瞬变电磁方法(含水层几何形状,盐水入侵)生成了地质模型。这个地质模型依次被用于构建三维密度依赖的流动模型,从而模拟过去几十年的地下水流和盐水入侵。结果表明,由于农业区地下水过度开采,已形成了一个大降落漏斗。这进而导致了含水层中北部6––8公里内陆区水力梯度和海水入侵推进的反转。淡水补给主要来自盆地多山的东南部。它为La Paz市供水,抵消了海水入侵的推进。咸淡界面推进和回退的交替可归因于气候变化和/或政策变化的影响。 Intrusão de água salina é uma das maiores preocupações ambientais em áreas costeiras com o aumento das demandas por água. A extração de água...