文献类型：期刊文献

英文题名：Estimation of Evapotranspiration in Sparse Vegetation Areas by Applying an Optimized Two-Source Model

作者：Li, Changlong[1,2,3] Li, Zengyuan[1,2] Gao, Zhihai[1,2] Sun, Bin[1,2]

第一作者：Li, Changlong

通信作者：Sun, B[1];Sun, B[2]

机构：[1]Chinese Acad Forestry, Inst Forest Resource Informat Tech, Beijing 100091, Peoples R China;[2]NFGA, Key Lab Forestry Remote Sensing & Informat Syst, Beijing 100091, Peoples R China;[3]Natl Acad Forestry & Grassland Adm, Beijing 102600, Peoples R China

年份：2021

卷号：13

期号：7

外文期刊名：REMOTE SENSING

收录：;EI(收录号：20211610214950);Scopus(收录号：2-s2.0-85104010526);WOS:【SCI-EXPANDED(收录号:WOS:000638792000001)】；

基金：This research was funded by the Fundamental Research Funds for the Central Non-profit Research Institution of CAF (No. CAFYBB2019ZB004) and Commissioned project by State Forestry and Grassland Administration.

语种：英文

外文关键词：Shuttleworth– Wallace two-layer model; Beijing– Tianjin sandstorm source region; vegetation transpiration; soil water evaporation; evapotranspiration

摘要：Evapotranspiration (ET) is an important part of the water, carbon, and energy cycles in ecosystems, especially in the drylands. However, due to the particularity of sparse vegetation, the estimation accuracy of ET has been relatively low in the drylands. Therefore, based on the dry climate and sparse vegetation distribution characteristics of the drylands, this study optimized the core algorithms (canopy boundary resistance, aerodynamic resistance, and sparse vegetation coverage) and explored an ET estimation method in the Shuttleworth-Wallace two-layer model (SW model). Then, the Beijing-Tianjin sandstorm source region (BTSSR) was used as the study area to evaluate the applicability of the improved model in the drylands. Results show that: (1) The R-2 value of the improved model results was increased by 1.4 and the RMSE was reduced by 1.9 mm, especially in extreme value regions of ET (maximum or minimum). (2) Regardless of the spatial distribution and seasonal changes of the ET (63-790 mm), the improved ET estimation model could accurately capture the differences. Furtherly, the different vegetation regions could stand for the different climate regions to a certain extent. The accuracy of the optimized model was higher in the semi-arid region (R-2 = 0.92 and 0.93), while the improved model had the best improvement effect in the arid region, with R-2 increasing by 0.12. (3) Precipitation was the decisive factor affecting vegetation transpiration and ET, with R-2 value for both exceeding 0.9. The effect of vegetation coverage (VC) was less. This method is expected to provide a more accurate and adaptable model for the estimation of ET in the drylands.