Groundwater quality assessment in Mexico using machine learning

What is it about?

This study examined the quality of groundwater in Mexico. Researchers analyzed water samples from over a thousand locations across the country. They used machine learning, a type of artificial intelligence, to classify the water into different types based on its chemical makeup. The study also looked at common pollutants in the water and how water quality varies across different regions of Mexico. This analysis helps us understand the state of Mexico's groundwater resources. This study conducted a comprehensive evaluation of groundwater quality at 1,068 monitoring sites across all hydrologic-administrative regions in Mexico. Based on the analysis, 41% of the sites presented good water quality, while 23% and 36% of the sites presented regular, and poor, respectively. Sites with good water quality exhibited lower concentrations of major ions (Ca, Mg, Na, K, SO4, Cl, and HCO3) compared to sites with regular and poor water quality. Water nomenclature was also estimated to be using the VL model based on Support Vector Machines with linear kernel, statistical techniques, and Monte Carlo simulation. This model classified 87% of the monitoring sites into four basic water classes: Na HCO3 (47%); Na Cl (18%); Ca HCO3 (17%); and Na SO4 (5%). Furthermore, the t-SNE computational algorithm was applied to reduce the dimensionality of the data (chemical concentrations of major ions and contaminants) and visualize it in a 2D plot. This algorithm obtained a clustering consistent with the water nomenclature estimated by the VL model. The contaminant study results revealed that all hydrologic-administrative regions presented at least one physicochemical-microbiological parameter that exceeded the acceptable levels defined by regulations of Mexico. Therefore, the implementation of environmental sanitation strategies is crucial to ensure the availability of high-quality water resources that are safe for human health.

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Photo by Yoann Boyer on Unsplash

Photo by Yoann Boyer on Unsplash

Why is it important?

This research is important for several reasons: • Comprehensive Assessment: It provides a broad overview of groundwater quality across all of Mexico, which is crucial for water resource management. • Advanced Classification: The use of machine learning offers a more accurate way to classify water types compared to traditional methods, giving us a better understanding of water chemistry. • Pollution Identification: The study highlights the presence of various pollutants in groundwater, which is essential for addressing contamination issues and protecting water sources. • Regional Insights: It identifies regional differences in water quality and pollution levels, allowing for targeted interventions and management strategies. • Tool Development: The researchers used and highlighted a software tool (WCSystem) that can be used by others to classify water, making this type of analysis more accessible. Ultimately, this research contributes to better water management practices and helps ensure the availability of safe water for people in Mexico.

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