Evapotranspiration

Satellite(s) e.g., Multifunctional Transport Satellite (MTSAT).	Monitoring element Land surface temperature.

Satellite(s)

e.g., Multifunctional Transport Satellite (MTSAT).

Monitoring element

Land surface temperature.

Description technique

Zhao et. al. (2019) used geostationary satellite data in combination with ground-based meteorological observations to provide model input parameters and calculate evapotranspiration (ET).

Accuracy / Resolution

R2 = 0.67,
mean bias = 0.027 mm/h,
RMSE = 0.1 mm/h
spatial resolution of 0.1°
temporal resolution: 30–min intervals.

Case study

Zhao et. al. (2019) studied ET in the Haihe River Basin (China). The Haihe River Basin is the focus of China’s industrial base and it is one of the three major grain producing regions within the country. However, this area is facing serious water resource shortages and water pollution problems.

Also fits domain

Freshwater/Land.

Benefits

Geostationary satellites have high temporal resolution and they can provide hourly and daily land surface information, offering strong potential for the calculation of land surface and water cycle data at hourly temporal resolution.

Limitations

MTSAT data can only be obtained during cloud-free weather, and clouds cause data gaps.
This research used a 0.1° forcing dataset; however, at this spatial resolution, it is difficult to accurately express the changes of terrain within a single pixel.

Applicability for Northland

Yes, possibly if another source of imagery is available, as MTSAT series only provides imagery of the Northern Hemisphere.

Publication references

Zhao J, Chen X, Zhang J, Zhao H, Song Y. 2019. Higher temporal evapotranspiration estimation with improved SEBS model from geostationary meteorological satellite data. Scientific Reports. 9(1):14981. doi:10.1038/s41598-019-50724-w.

https://www.nature.com/articles/s41598-019-50724-w

Other comments or information

ET varies with land cover type and physical and chemical properties of the underlying surface.
ET is also controlled by water availability, radiation, and other atmospheric conditions.
ET had strong correlation with the normalized difference vegetation index (NDVI).

Other references

Anderson MC, Allen RG, Morse A, Kustas WP. 2012. Use of Landsat thermal imagery in monitoring evapotranspiration and managing water resources. Remote Sensing of Environment. 122:50-65.

https://www.sciencedirect.com/science/article/pii/S0034425712000326

Zhang Y, Kong D, Gan R, Chiew FHS, McVicar TR, Zhang Q, Yang Y. 2019. Coupled estimation of 500 m and 8-day resolution global evapotranspiration and gross primary production in 2002–2017. Remote Sensing of Environment. 222:165-182.

https://doi.org/10.1016/j.rse.2018.12.031

Ma, W., Hafeez, M., Ishikawa, H. & Ma, Y. Evaluation of SEBS for estimation of actual ET using ASTER satellite data for irrigation areas of Australia. Theor. Appl. Climatol. 112, 609–616 (2013).
https://link.springer.com/article/10.1007/s00704-012-0754-3

Moletto-Lobos I, Mattar C, Barichivich J. 2020. Performance of Satellite-Based Evapotranspiration Models in Temperate Pastures of Southern Chile. Water. 12(12):3587.

https://www.mdpi.com/2073-4441/12/12/3587