Problem / Objective

Arsenic has been a menace in Eastern India especially along the banks of the Ganga for almost two decades now, putting millions of people at severe health risk. Researchers have been studying the distribution patterns of the contaminated groundwater for years to develop a large-scale ecological and environmental framework addressing this challenge in the region. The studies conducted until now were unable to offer an effective model for policy decisions due to the delineation of the local extent and geochemical mechanisms for arsenic pollution. The researchers from IIT Kharagpur thus opted for AI which is now being used across the world to successfully model the distribution of groundwater contaminants.

Solution / Approach 

In a breakthrough, a first of its kind, researchers from IIT Kharagpur have successfully predicted the distribution of groundwater arsenic and human health risk in the affected areas using AI algorithms on environmental and geological and human usage parameters. The researchers have delineated the high and low arsenic zones across the entire delta using artificial intelligence and quantify the number of people exposed. They have developed probabilistic models of arsenic occurrence, exposure and human health risk assessment within the delta region. The model shows a strong association of ‘surficial aquitard thickness’ and ‘groundwater-fed irrigation’ to regional-scale As-hazard.

Impact / Implementation 

While the predictive model framework would prove to be vital typically for the identification of drinking water sources in arsenic affected areas of West Bengal, it can be used in other parts of the country which are also suffering from severe groundwater pollutants. The outcome of this study provides the information for the location of safe groundwater, which is the primary source of drinking water for most of India. Eventually, all this information forms the baseline knowledge for the recently initiated Jal Jeevan Mission of the Government of India which aims to provide safe drinking water to every household of the country by 2024. Such successful use of artificial intelligence in geoscience enables us to find answers and build prima-facie understanding before undertaking further field-based investigation or validation.

Sources: The KGP Chronicle and Science of The Total Environment

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