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A review of evapotranspiration estimation methods for climate-smart agriculture tools under a changing climate: vulnerabilities, consequences, and implications

Climate change (CC) seriously threatens global water resources, exacerbating extreme water scarcity issues, especially in agriculture. Evapotranspiration (ET) is one of the essential components of the water cycle and is particularly sensitive to CC. Thus, this study presents an overview of the impor...

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Bibliographic Details
Published in:Journal of water and climate change 2024-12
Main Authors: Lakhiar, Imran Ali, Yan, Haofang, Zhang, Chuan, Zhang, Jianyun, Wang, Guoqing, Deng, Shuaishuai, Syed, Tabinda Naz, Wang, Biyu, Zhou, Rui
Format: Article
Language:English
Online Access:Get full text
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Summary:Climate change (CC) seriously threatens global water resources, exacerbating extreme water scarcity issues, especially in agriculture. Evapotranspiration (ET) is one of the essential components of the water cycle and is particularly sensitive to CC. Thus, this study presents an overview of the importance of ET estimation as climate-smart agriculture (C-SA) and its relevance in addressing CC's challenges. We adopted a systematic review methodology to select the relevant literature based on predefined inclusion and exclusion criteria. Based on the analysis, we found that CC has significantly affected the yield of various crops and changed the ET over time. Besides, C-SA tools are vital for addressing the challenges of CC. Its adoption in traditional agriculture can build strong resilience against threats posed by CC. In addition, significant development has been attained in the precision monitoring of the ET from agriculture fields, ranging from direct and indirect to more sophisticated energy balance and modern techniques. However, the accuracy of each method mainly depended on the specific regional climate conditions. In the absence of actual field measurements, empirical or modern models are helpful to estimate ET using routine meteorological variables. Yet, these models require local calibration for the best accuracy.
ISSN:2040-2244
2408-9354
DOI:10.2166/wcc.2024.048