Jalal Yarahmadi; Ali Rahimi Khoob
Abstract
Evapotranspiration is one of the most important parameters for designing irrigation systems and estimating crop water use. Joining the models of reference evapotranspiration with the data derived from satellite images provides the opportunity for studying spatial variations of this parameter in extensive ...
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Evapotranspiration is one of the most important parameters for designing irrigation systems and estimating crop water use. Joining the models of reference evapotranspiration with the data derived from satellite images provides the opportunity for studying spatial variations of this parameter in extensive levels. In this study, four empirical models were evaluated including Hargreaves-Samani, Blaney–Criddle, Turc, and Linacre, which are dependent on temperature data for estimating reference evapotranspiration. Daily LST data obtained from MOD11A1 and MYD11A1 of MODIS were used rather than temperature data in these models. The minimum and maximum daily temperature, relative humidity, daylight hours, and wind speed were collected from weather stations located in five units of sugarcane farms (Shoaybie- SH, AmirKabir-AM, Farabi-FA, Khazaie-KH, and Ghazali-GH) in order to estimate reference evapotranspiration by Fao-Penman-Monteith equation as the target output. Calibration was done by the data of Shoaybie, Amir Kabir and, Farabi stations while the data of Khazaie and Ghazali stations were used for verification. This research showed that estimation of reference evapotranspiration can accurately be performed by LST data of Modis (MOD11A1 and MYD11A1) without direct measurements. Besides, the results revealed that use of LST data of MOD11A1 can lead to more accurate result for verification than MYD11A1. This outcome was resulted by comparing the precision measures of reference evapotranspiration based on the type of used thermal product as an input. Furthermore, comparing the precision measure of the models imply that operating the Turc model based on LST data of MOD11A1 can have more accurate results than other models (RSME and R2 are 1.3 mm.d-1 and 0.86, respectively).
