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Evapotranspiration estimation and validation at 16 m resolution based on ETMonitor model driven by GF-1 satellite remote sensing datasets

  • role： First author第一作者
  • Affiliation：

    State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China

  • Email：zhengcl@aircas.ac.cn
  • Introduction：郑超磊，研究方向为蒸散发遥感理论和应用。E-mail： zhengcl@aircas.ac.cn
ZHENG Chaolei,  
  • Affiliation：

    State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China

JIA Li,  
  • Affiliation：

    State Key Laboratory of Remote Sensing Science, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100101, China

HU Guangcheng

Resümee

Evapotranspiration (ET) is one of the core variables for studying the surface water cycle and management of the field-scale water resources. Satellite remote sensing are widely adopted to obtain the variation of evapotranspiration at large spatial scale, but the resolution of existing ET products is mainly limited at low or medium resolution (1—25 km), which cannot satisfy the field-scale water management application. The Chinese GF-1 Wide Field of View (WFV) camera has the characteristics of high spatial and temporal resolution, with a spatial resolution of 16m, and it can support to generate ET products with high spatial and temporal resolution, which has not yet been well presented. The objective of this study is to present the capacity of using the remote sensing data from the GF-1 satellite as the driving force to produce high resolution (16 m) ET. The ETMonitor model was adopted to estimate ET at 16 m resolution in this study. ETMonitor is a combined model with multi-process parameterizations, and it has been proven to be able to generate accurate regional and global ET estimation at relative coarse resolution (e.g., 1 km) mainly using the biophysical and hydrological parameters/variables retrieved from satellite observations. During the ET estimation procedure, the adopted GF-1 remote sensing datasets include the Leaf Area Index (LAI), Fraction of Vegetation Cover (FVC), Albedo, and NDVI datasets, which are retrieved from previous studies. Ground observation data from 16 sites in China was collected to validate the estimated ET, including 6 grassland sites, 4 cropland sites, 1 mixed forest site, 2 shrubland sites, and 3 desert or Gobi sites. The validation results show that the overall Root Mean Square Error (RMSE) of estimated daily evapotranspiration based on GF-1 satellite remote sensing datasets is 0.85 mm d-1, the correlation coefficient (R) is 0.79, and the Bias is 0.16 mm d-1, which can demonstrate the high accuracy of estimated ET. The GF-1 based ET at 16 m resolution also presented better performance in terms of spatial variation of ET comparing with the low-resolution (e.g., 1 km) ET, especially in the regions with high surface heterogeneity. These highlight the ability of Chinese GF-1 satellite remote sensing dataset could produce accurate ET at high spatial variation, and it has potential to meet the application of field-scale agricultural water resources management, irrigation management, ecological environment monitoring and government decision-making in China. However, due to the impact of the revisit cycle of the GF-1 satellite and the impact of clouds, there are some gaps or missing values in GF-1 based LAI, FVC or Albedo, and these further cause gaps in the GF-1 ET data. In order to improve the availability of high-resolution ET products, it is necessary to produce spatially and temporally continuous high-resolution ET products, which will be the focus of follow-up research.

Schlüsselwort

evapotranspiration;ETMonitor;remote sensing;GF-1;validation;16 m resolution;China

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