基于多源数据的黑河流域日尺度蒸散发量模拟

植被蒸散发是地表水量平衡和热量平衡的重要参量,也是衡量植被生长状况和作物产量的重要指标,同时也是进行流域水资源优化配置的依据。遥感技术的快速发展使其成为区域尺度蒸散发模拟的重要手段。以黑河流域为例,构建遥感驱动的蒸散发模拟模型,结合多源遥感数据(MODIS、TRMM等)以及GLDAS全球陆面数据同化系统数据,对黑河流域2005、2010、2015年三个时期的潜在蒸散发和实际蒸散发进行了时间尺度为每日、空间尺度为1km的模拟。研究结果表明:潜在蒸散发月际变化明显,从5月开始增长,于7月达到峰值,然后逐渐减少;实际蒸散发在月份之间变化趋势明显,在2015年均达到了最高值;精度检验结果表明本研究采用的两个模型均达到了很好的效果,Kristensen-Jensen模型更适合用于黑河流域。本研究为黑河流域地表特征数据集提供了重要的日尺度蒸散发数据。

Simulating the daily evapotranspiration in Heihe river basin with multi-sensor remote sensing data

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.