蒸散量
涡度相关法
环境科学
强迫(数学)
中国大陆
中国
均方误差
焊剂(冶金)
水平衡
比例(比率)
相关系数
大气科学
遥感
气候学
气象学
地理
地质学
统计
数学
生态系统
冶金
地图学
岩土工程
材料科学
生物
考古
生态学
作者
Xinrong Shi,Dunxian She,Jun Xia,Renli Liu,Tianyue Wang
标识
DOI:10.1016/j.jhydrol.2024.130949
摘要
Terrestrial evapotranspiration (ET) is a critical variable connecting water, energy and carbon cycles. Many high spatial resolution (0.1°×0.1°) remote sensing based ET (ETRS) products have been released and provide useful information for ET-related analysis. However, the accuracy of these ET products differs largely in space and time due to the estimation method and forcing data in producing the ET data, which raises the demand for the intercomparison of the capacity and applicability of these datasets to give an integrated suggestion of how to choose the optimal dataset for a specific region. In this study, we intercompare the performance of six ETRS products (AVHRR, GLASS, GLEAM, IDAHO, MODIS, and PML-V2) in mainland China during 2001–2018. The comparison of eddy covariance (EC) between ET from flux sites (ETOBS) and the estimated ET given by the terrestrial water balance method (ETTWB) at an annual time scale demonstrated good performance of these ET products in capturing the ET changes in mainland China, although there still exist some discrepancies among different ET products. PML-V2 outperforms other products with the lowest root-mean-squared-deviation (RMSE) and the highest Nash-Sutcliffe efficiency coefficient (NSE) compared to the ground-based observations from the flux network. GLEAM has the best correlation with ETTWB. A southeast-to-northwest ET gradient can be found across the study area with the range of 350–450 mm/yr and the majority of mainland China exhibited an increasing ET trend from 0.213 mm/yr2 to 3.178 mm/yr2 during 2001–2018. We also find that PML-V2 and GLASS are the most reliable products in the humid and semi-humid areas of mainland China, while GLEAM are the most effective products in arid and semi-arid areas of China. The results of this study can provide useful information on how to choose the relative ET products for water resources management and planning.
科研通智能强力驱动
Strongly Powered by AbleSci AI