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Updating the Estimation of Daily Reference Evapotranspiration Using Limited Meteorological Data

delete2026-08-13
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OA
AI
R
Rangjian Qiu
G
Guoqing Lei *
DOI:10.3390/agronomy16161553delete
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Abstract

Abstract

En 中文
The Penman–Monteith model is the standard method for computing reference evapotranspiration (ETo–PM), requiring full meteorological data including solar radiation (Rs), actual vapor pressure (ea), and wind speed (u2). However, not all of these data are always available. This study incorporated temperature-based methods recently developed for estimating Rs (Rs_dev) and ea (ea_dev) into the ETo–PM model (PMT) and compared them with the alternative procedures developed by Paredes and Pereira for estimating Rs (Rs_PP) and ea (ea_PP). In cases where u2 is missing, a global mean value of 2 m s−1 (u2_def) or a local long-term average (u2_ave) was employed. All models were evaluated based on the comparison with ETo–PM, calculated with complete data from 1993 to 2016 at 96 radiation stations. The results showed that using Rs_dev, ea_dev, or u2_ave (compared to Rs_PP, ea_PP, or u2_def) in ETo–PM estimation was associated with better agreement with the full-data benchmark within the evaluated dataset when one or two variables are missing, with RMSE decreasing by 7–51%, although the improvements were less pronounced in arid regions. When all three variables are unavailable, combining Rs_dev, ea_dev, and u2_ave yields comparable or better agreement with the full-data benchmark without requiring additional humidity data. Overall, the updated PMT framework provides a practical pathway for reproducing FAO-56 Penman–Monteith ETo under incomplete meteorological conditions.
Keywords:
reference evapotranspiration
limited meteorological data
dynamic temperature correction
temperature-based solar radiation model
temperature-based Penman–Monteith model
Hargreaves–Samani model

Journal

A
Agronomy-Basel
IF:
3.4
Papers:
1.7W
Citations:
5.0W

Organization

W
wuhan university
Scholars:
7.8W
Papers: 5.7W
Citations: 70
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