USING REMOTE SENSING TECHNIQUES TO ESTIMATE ACTUAL EVAPOTRANSPIRATION IN THE NILE DELTA, EGYPT - Asaad DERBALA; Darwish MOHAMED; Hesham ABOELSOUD; Abdel Aziz BELAL; Abdallah ELASSAL; Mayie AMER (Scientific Papers Series : Management, Economic Engineering in Agriculture and Rural Development)
With 755 million tonnes consumed as a cereal grain in 2020, rice is the most consumed crop in the world. Estimating rice's water requirements is crucial since the crop often grows under flood conditions and water serves a number of vital purposes for it. This study uses the Penman-Monteith (FAO 56-PM) method to assess and estimate evapotranspiration, whereas the METRIC model is used to calculate surface enrage balance. The estimation and monitoring of field agricultural water use has shown to be a successful application of remote sensing technology. Using remote sensing techniques, this work aimed to develop a method for estimating crop coefficient and actual crop evapotranspiration (ETc). for rice using METRIC model within the Google Earth Engine (GEE) based on Landsat-8 satellite imagery. The average seasonal ETo (FAO56) resulted 469 mm for crop rice and the water productivity (WP) was 0.42 kg m-3. Good correlations were found between the crop coefficients (Kc) proposed by FAO and (Kc)Sat, with R2 0.92. The KcFAO used to validate KcSat. Linear relationship between KcFAO and KcSat was established and R2 was 0.96. Normalized Deference Vegetation Index (NDVI) used to estimate crop coefficient according to satellite data (KcSat). Landsat TM and Landsat ETM+ data were used to outline the growth of vegetation cover, and these data were coupled with land surface temperature (LST) taken from Landsat8 satellite data and air temperature (Tair) acquired from ground stations. The findings indicated that as cultivated area expanded during rice development, (LST) declined by around 2.3°C and (Tair) reduced by roughly 1.6°C.