Abstract
A decision tree -based approach is projected to predict surface water quality and is a good tool to assess quality and guarantee property safe use of water for drinking. The most objective of this study is to assess the surface water quality of the Daya watercourse to work out the quality of drinking functions. Samples were collected from designated locations throughout totally different seasons (winter, summer, rainy) over a amount of five years (2016, 2017, 2018, 2019, and 2020). Total dissolved solids, pH, alkalinity, chloride, nitrate, total hardness, calcium, magnesium, iron, fluoride, were all tested as well as total coliform, fecal coliform, and E. coli. The main goal is to use decision tree regression to construct a model to assess and predict water quality changes in the Daya geographic region of Odisha, India, and compare it to statistical methods.