Innovative Machine Learning Model Evaluates Groundwater Quality for Irrigation

A research team from NIT Rourkela has developed a Machine Learning model to evaluate groundwater quality for irrigation in Odisha's Sundargarh district. This model helps assess groundwater for agriculture, crucial due to limited surface water and high agricultural demand, and offers insights for water resource management.

Researchers at the National Institute of Technology (NIT), Rourkela, have crafted a groundbreaking Machine Learning model to evaluate groundwater quality for irrigation. Conducted in Sundargarh district, Odisha, the study's findings have been published in the esteemed Water Quality Research Journal.

According to officials, this model can be employed nationwide to assess groundwater stress, essential for the district as agriculture constitutes a large part of the local economy. With limited surface water, groundwater becomes crucial for growing crops like paddy, which dominates 76% of the cultivable area.

Assistant Professor Anurag Sharma, from NIT Rourkela's Civil Engineering Department, states the model and statistical tools were pivotal in predicting water quality trends based on data from 2014 to 2021. The research highlights areas with stable as well as concerning groundwater conditions, signaling the need for effective water resource management.