Predictive Analysis of Groundwater Resources Using Random Forest Regression

The lack of water is one of the most crucial problems of our day; therefore, optimized water resource management and predictions gathered by patrons are of utmost importance. In the turmoil of a country like India, which lives a variety of lifestyles and has a complicated network of rivers, the urgent need for an active point of view to take care of water shortages becomes exceptionally vital. In this study, India’s groundwater, available at the district level for the year 2017, was the area of focus, with this analysis utilizing a dataset of 689 rows, each representing a district, and 16 columns describing the various groundwater extraction and recharge metrics. The study involves five regression models…