Uncertainty Analysis of Actual Evapotranspiration Estimations Using Satellite Data and Climate Databases (Case Study: Karkheh Basin)

Evapotranspiration is an important component of water balance and a key element in water resources management, especially in arid and semi-arid regions such as Iran. The purpose of this study is to investigate the uncertainty of actual evapotranspiration (ETa) estimates derived from a remote sensing-based model, i.e. Priestley–Taylor Model (PT-JPT), and two global climate datasets namely GLEAM and ERA-Interim in Karkheh basin southwest of Iran during  the 2013-2017 period. The three cornered hat (TCH) method was used to analyze the uncertainty for each spatial cell (0.25× 0.25) in the basin. The results of uncertainty analysis showed that ETERA-Interim, ETGLEAM, and ETPT- JPT data have the lowest relative uncertainty in 38%, 12.6% and 49.4% of cells, respectively. The highest percentage of cells with lowest uncertainty in Seimare, South Karkhe and Gamasiab sub-basins was correspond to ETPT-JPT model (54.4%, 72.3%, and 50%, respectively). In Gharehsoo and Kashkan sub-basins the ETERA-Interim estimations were found as the method with least uncertainty, (55.5% and 53.4%, respectively). The highest number of cells with lowest relative uncertainty belongs to ETERA-Interim. Considering the lowest uncertainty, variation of actual evapotranspiration with elevation in Karkhe basin showed that the two databases and PT-JPT model perform well at 1400 to 1800 m above sea level. ETPT-JPT model did a better job in warm dry climates. ETERA-Interim and ETGLEAM data estimations were selected as the best methods in semi-humid temperate and hyper-humid-cold climates, respectively. In cells with farm-garden and forest land use, ETGLEAM have the lowest uncertainty. Similarly, in rangelands, both ETPT-JPT and ETERA-Interim databases, and for drylands, ETERA-Interim data can be recommended. Further feasibility studies in other climates are required for more scrutiny.