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This review covers the most recent related studies to provide the most recent snapshot of machine learning applications in the water industry. Groundwater quality assessment and prediction (gqap) is vital for protecting groundwater resources. Traditional gqap methods can not adequately capture the complex. Artificial intelligence (ai) has become a useful tool in numerous domains, including environmental science.
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Groundwater quality for irrigation purposes varies across regions, countries, and specific locations, primarily due to factors such as groundwater extraction and utilization. To ensure safe drinking water sources in the future, it is imperative to understand the quality and pollution level of existing groundwater. This review explores the application of machine learning and deep learning, as ai. Using conventional methods to evaluate the irrigation water quality is usually expensive and laborious for the farmers, particularly in developing countries.
