Prediction of pan evaporation in Chhattisgarh using machine learning techniques
Accurate measurement or estimation of evaporation loss is crucial for developing and successfully implementing water resource management strategies, irrigation planning, reservoir management etc. To predict the pan evaporation (EP) accurately for Raipur, Jagdalpur, and Ambikapur stations of Chhattisgarh, four deep learning models and three machine learning models were used and a hybrid model using Deep Neural Network (DNN) and Random Forest (RF) was proposed. Simulation results demonstrated that the hybrid model (DNN+RF) outperforms the rest with R2 of 0.964, 0.920, 0.894 for Raipur, Jagdalpur and Ambikapur respectively. It has been observed that the hybrid DNN+RF model demonstrated faster convergence compared to other models with high accuracy, making it efficient and well-suited for real-time applications such as irrigation scheduling and water resource management.
Authors
- R. Baloji Naik (ORCID: https://orcid.org/0000-0002-3564-3749)
- Diwakar Naidu (ORCID: https://orcid.org/0000-0002-3522-1431)
- Babita Majhi
Institutions
- Indira Gandhi Agricultural University (IN)
- Guru Ghasidas Vishwavidyalaya (IN)
Publication Details
- Journal
- Journal of Agrometeorology
- Published
- 2025-03-01
- DOI
- https://doi.org/10.54386/jam.v27i1.2731
- Primary Topic
- Hydrological Forecasting Using AI
- Type
- article
- Field-Weighted Citation Impact
- 0.00