Temperature analysis of reference evapotranspiration models

Abstract

Evapotranspiration has a significant role in agricultural and forest meteorology research, the hydrological cycle, irrigation scheduling and water resources management. Several models are available to estimate evapotranspiration, including mass transfer-based, radiation-based, temperature-based and pan evaporation-based models. This study aims to assess temperature-based models versus the Food and Agriculture Organization of the United Nations (FAO) Penman–Monteith model to detect the best one using linear regression under different weather conditions. For this purpose, weather data were gathered from 181 synoptic stations in 31 provinces of Iran. Evapotranspiration was estimated using 11 temperature-based models and was compared with the FAO Penman–Monteith model. The results showed that the modified Hargreaves–Samani 1 estimates the evapotranspiration better than other models in most provinces of Iran. However, the R2 values were <0.9930 for 20 provinces of Iran. The best precise method was the modified Hargreaves–Samani 4 for Alborz province (AL). Finally, a list of the best performances of each model was presented to use in other regions according to mean, maximum and minimum temperature elevation, minimum and mean relative humidity, sunshine, precipitation and wind speed. The best weather conditions for use in temperature-based equations (based on the performance of all methods) are 12–18 °C, 18.0–22.5 °C, 5–13 °C, 40–55%, 2.00–3.25 m s−1 and 230–260 h month−1 for mean, maximum and minimum temperatures, relative humidity, wind speed and sunshine respectively. Results are also useful for selecting the best model when researchers must apply temperature-based models on the basis of available data.