Simulating the daily evapotranspiration in Heihe river basin with multi-sensor remote sensing data
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Abstract:
Vegetation evapotranspirat ion is an import ant parameter involving gr ound surface w ater and heat balance. It is also an import ant index to measur e veg etation g rowth and cr op yield and the basis fo r o ptimized allocation of w atershed w ater re2 sour ces. T he remote sensing technolog y has become an impo rtant metho d for simulat ion of reg ional scale evapotr anspir ation. With t he Heihe Riv er Basin as a case study , w e constructed a r emote sensing2driven evapotr anspir atio n simulatio n model, combi2 ning multi2source remo te sensing data ( M ODIS, TRMM, etc. ) and GLDAS data, we simulated the pot ential ev apo transpiratio n and actual ev apo transpiratio n of H eihe Riv er basin in 2005, 2010 and 2015 on daily sca le at a 12km spatial r eso lutio n. The r esults show ed that: the po tent ial ev apo transpiratio n v aried sig nificantly betw een differ ent mo nths, starting to gr ow in May, peaking in July, and then g radually decreasing . The actual eva pot ranspiratio n varied sig nificantly betw een the months and r eached the high2 est value in 2015. The results of pr ecision test show ed t hat t he tw o mo dels used in this study bo th had g ood effects. The Kris2 tensen2Jensen model w as mo re suitable fo r the H eihe river basin. T his r esear ch can prov ide im po rtant diurnal ev apo transpiratio n data fo r the Heihe riv er basin surface feature dat aset.
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