Abstract
The Food and Agricultural Organization of the United Nations (FAO) Penman–Monteith (PM) method is widely regarded as the most effective reference evapotranspiration (ETo) estimator; however, it requires a wide range of data that may be scarce in some rural regions. When feasible relative humidity, solar radiation and wind speed data are unavailable, a temperature-based method may be useful to estimate ETo and provide suitable data to support irrigation management. This study has evaluated the accuracy of two ETo estimations methods: (1) a locally and monthly adjusted Hargreaves–Samani (HS) equation; (2) a simple procedure that only uses maximum temperature and a temperature adjustment coefficient (MaxTET). Results show that, if a monthly adjusted radiation adjustment coefficient (kRs) is calibrated for each site, acceptable ETo estimations (RMSE and R2 equal to 0.79 for the entire region) can be achieved. Results also show that a procedure to estimate ETo based only on maximum temperature performs acceptably, when compared with ETo estimation using PM equation (RMSE = 0.83 mm day−1 and R2 = 0.77 for Alentejo). When comparing these results with the ones attained when adopting a monthly adjusted HS method, the MaxTET procedure proves to be an accurate ETo estimator. Results also show that both methods can be used to estimate ETo when weather data are scarce.
Highlights
Accepted: 29 December 2020The Food and Agricultural Organization of the United Nations (FAO) Penman–Monteith (PM) reference evapotranspiration (ETo) equation [1], despite being regarded as the most accurate method to estimate ETo, is not always viable since data quality needs to be assured and representative of well-watered conditions [2]
While maximum (Tmax ) and minimum (Tmin ) temperature data are commonly observed at most weather stations, windspeed (u2 ), relative humidity (RH) and solar radiation (Rs ) are not frequently available, and, if recorded, the data quality may not be adequate
In order to improve the accuracy of ETo estimations, these indicators were used to determine both kRs and kTmax. The calibration of these coefficients was performed using a trial and error procedure for each month and location, was calibrated using 50% of the years, randomly chosen from the dataset, and validated for the remainder of the years. Results for both HS and maximum temperature-based evapotranspiration (MaxTET) approaches were compared with the PM method to test its accuracy
Summary
Accepted: 29 December 2020The Food and Agricultural Organization of the United Nations (FAO) Penman–Monteith (PM) reference evapotranspiration (ETo) equation [1], despite being regarded as the most accurate method to estimate ETo, is not always viable since data quality needs to be assured and representative of well-watered conditions [2]. The PM calculation requires air temperature, windspeed, relative humidity and solar radiation. While maximum (Tmax ) and minimum (Tmin ) temperature data are commonly observed at most weather stations, windspeed (u2 ), relative humidity (RH) and solar radiation (Rs ) are not frequently available, and, if recorded, the data quality may not be adequate. To overcome this constraint, [1] proposed a set of methods that allow for the estimation of theses missing variables. For estimation of Rs , [1] proposed the adoption of the Hargreaves–Samani method [5], which expresses Rs as a linear function expressed as: Published: 2 January 2021
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