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REVIEW article
Front. Water
Sec. Water and Climate
Volume 7 - 2025 |
doi: 10.3389/frwa.2025.1553732
Comprehensive Analysis of Methods for Estimating Actual Paddy Evapotranspiration – A Review
Provisionally accepted- 1 Department of Soil and Water Conservation Engineering, College of Agricultural Engineering & Technology, OUAT, Bhubaneswar, Odisha–751003, India, Bhubaneswar, India
- 2 Indian Institute of Water Management (ICAR), Bhubaneswar, Orissa, India
- 3 Department of Agronomy, College of Agriculture, OUAT, Bhubaneswar, Odisha–751012, India, Bhubaneswar, India
- 4 AgFE Department, Indian Institute of Technology Kharagpur, Kharagpur, West Bengal–721302, India, Kharagpur, India
- 5 The ICAR Research Complex for North Eastern Hill Region (ICAR RC NEH), Umiam, India
- 6 ICAR-Agricultural Technology Application Research Institute, Zone VII, Umiam, Meghalaya-793103. India, Shillong, India
Evapotranspiration (ET) has considerable significance in the water cycle, especially in farming areas where it determines crop water needs, irrigation plans, and sustainable management of water resources. This study stresses the need for accurate ET estimation in paddy fields where rice is grown because of its high-water sensitivity and consumption which has implications for water use efficiency and food security. The study attempts to address the problem of by estimating rice ET: Standard procedures like the Penman-Monteith equation, lysimeters, and even remote sensing procedures such as SEBAL and METRIC are all investigated. Furthermore, an attempt is made to combine remote sensing data with machine learning techniques for refined ET estimation. Utilizing modernized technologies and hybrid models, the research investigation aims to deepen the understanding of ET variability for rice cropping systems to promote improved water resources management and sustainable agriculture practices. As areas for future work suggest the application of vegetation indices incorporating high-resolution multispectral imagery to accurately estimate ET and appropriately differentiate between evaporation and transpiration in these complex agricultural systems.
Keywords: evapotranspiration, Direct ET estimation, SEBAL, Metric, machine learning
Received: 31 Dec 2024; Accepted: 05 Feb 2025.
Copyright: © 2025 Behura, Raul, Paul, Mohanty, Jena, Dwibedi, Ghosh, Singh, Devi, Singha and Mohanty. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence:
Laishram Kanta Singh, The ICAR Research Complex for North Eastern Hill Region (ICAR RC NEH), Umiam, India
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