Madras Agricultural Journal
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Research Article | Open Access | Peer Review

Precision in Prediction: Groundwater Level Forecasting with Random Forest Regression in Coimbatore's Upper Bhavani River Basin Area

Volume : 112
Issue: March
Pages: 52 - 57
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Abstract


This study presents a highly accurate method for predicting groundwater levels using Random Forest Regression (RFR) in Coimbatore, India's Upper Bhavani River Basin area. Daily groundwater level data from 1995 to 2021 were analysed along with relevant environmental factors. The model demonstrated exceptional presentation, with R² values of 0.9999 and 0.9994 for training and testing datasets.

DOI
Pages
52 - 57
Creative Commons
Copyright
© The Author(s), 2026. Published by Madras Agricultural Students' Union in Madras Agricultural Journal (MAJ). This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium, provided the original work is properly cited by the user.

Keywords


Groundwater level prediction Random Forest Regression Upper Bhavani River Basin Machine learning
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