Development and Validation of Satellite-based water and energy balance Model “SMARET” for Arid Regions to Detect and Map Evapotranspiration of Date Crops in Oman

Actual Evapotranspiration (ETa) is considered an important step in the water cycle. ETa is a phase transition of water, on soil and plant surfaces spontaneously becoming vapors. Traditionally, the estimation of ETa was approximated using different in-situ techniques. But these techniques have high initial and maintenance costs with a low spatial resolution and can only be applied to small areas. On other hand, ETa is considered an important component of the surface water budget that can be monitored by satellite imagery. This study developed a Satellite-based water and energy balance Model for Arid Region to determine Evapotranspiration (SMARET) model to monitor, detect and map evapotranspiration for the hot and hyper-arid regions including Oman. Firstly, Three different satellite imagery-based evapotranspiration models including two surface energy balance models named; Surface Energy Balance Algorithm for Land (SEBAL) and Mapping Evapotranspiration at High-Resolution Internalized Calibration (METRIC), and an agro-hydrological model named; Soil, Water, Atmosphere and Plant (SWAP) were investigated to estimate actual evapotranspiration (ETa) on both local and regional scales in a hyper-arid condition of Oman. The model's investigations were validated against sap flow field measurements as well as the common Penman-Monteith (PM) model. This study showed that all three models worked differently in estimating ETa. Although PM showed a higher correlation with sap flow measurement, with R2 = 0.87, METRIC, among the three examined models showed a high value of correlation with an R2 value of 0.83. SEBAL and METRIC models overestimated ETa especially in summer times in comparison with the field measured sap flow rates. On the contrary, SWAP underestimated ETa against SFM. These models have their advantages, disadvantages, and limitations over each other in the study area. Hence, this study developed and tested a surface energy-balance satellite imagery model (SMARET) to estimate ETa for hot a hyper-arid region. The newly developed model coupled the satellite imagery with in-situ measurements from the field and validated against in-situ devices the sap flow meter and lysimeter. The developed model was also evaluated against other existing models including SEBAL, METRIC, and PM. The SMARET model provided a great variety of energy fluxes within the study area. Results have shown that the value of net radiations (Rn) and soil heat flux (G) decreased in August as compared with May due to the decrease in Land surface temperature values. SMARET model was validated against SEBAL, METRIC, PM, and Lysimeter. The overall trend has shown that the ETa values estimated by the SMARET model were high but closer to the PM and Lysimeter readings in the summer as compared to SEBAL and METRIC models. The study resulted in a good correlation between SMARET (R2 = 0.73) as well as PM model (R2 = 0.72) and ETa values calculated from Lysimeter. The SMARET model was in a good correlation (R2 = 0.66) with the ETa values recorded using the Sap flow meter. The strong relationship between SMARET, Sap flow measurement, and Lysimeter observation suggests that the model has the application capability in hot and hyper-arid regions. This study recommends that there is still room for further research in the application of the SMARET model using high-resolution satellite imagery. This study also recommends policy makers and decision-makers apply the SMARET model for water requirement estimation and water resources management in hot and hyper-arid regions including Oman.