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ET (ET) monitoring is crucial to agricultural water resource management, regional water resource utilization planning and socio-economic sustainable development.The limitations of traditional ET monitoring methods mainly lie in that they cannot observe a large area at the same time and can only be limited to observation points. Therefore, the cost of personnel and equipment is relatively high, and they can neither provide surface ET data, nor provide ET data of different land use types and crop types.

Quantitative monitoring of ET can be achieved by using remote sensing. The characteristics of remote sensing information are that it can not only reflect the macroscopic structure characteristics of the earth surface, but also reflect the microscopic local differences.

Version 2.0 (second edition) of the surface evapotranspiration data set of the heihe river basin from 2000 to 2013 is based on multi-source remote sensing data and the latest ETWatch model is adopted to estimate the raster image data. Its temporal resolution is monthly scale and the spatial resolution is 1km scale. The data covers the whole basin in millimeters.Data types include monthly, quarterly, and annual data.

The projection information of the data is as follows:

Albers equal-area cone projection,

Central longitude: 110 degrees,

First secant: 25 degrees,

Second secant: 47 degrees,

Coordinates by west: 4000000 meter.

File naming rules are as follows:

Monthly cumulative ET value file name: heihe-1km_2013m01_eta.tif

Heihe represents the heihe river basin, 1km represents the resolution of 1km, 2013 represents the year of 2013, m01 represents the month of January, eta represents the actual evapotranspiration data, and tif represents the data in tif format.

Name of quarterly cumulative ET value file: heihe-1km_2013s01_eta.tif

Heihe refers to heihe river basin, 1km refers to the resolution of 1km, 2013 refers to 2013, s01 refers to january-march, is the first quarter, eta refers to the actual evapotranspiration data, and tif refers to the data in tif format.

Annual cumulative value file name: heihe-1km_2013y_eta.tif

Among them, heihe represents heihe river basin, 1km represents the resolution of 1km, 2013 represents the year of 2013, y represents the year, eta represents the actual evapotranspiration data, and tif represents the data in tif format.

File naming and required software

The data is stored in raster tif format, File naming rules are as follows:
Monthly cumulative ET value file name: heihe-1km_2013m01_eta.tif
Heihe represents the heihe river basin, 1km represents the resolution of 1km, 2013 represents the year of 2013, m01 represents the month of January, eta represents the actual evapotranspiration data, and tif represents the data in tif format.
Name of quarterly cumulative ET value file: heihe-1km_2013s01_eta.tif
Heihe refers to heihe river basin, 1km refers to the resolution of 1km, 2013 refers to 2013, s01 refers to january-march, is the first quarter, eta refers to the actual evapotranspiration data, and tif refers to the data in tif format.
Annual cumulative value file name: heihe-1km_2013y_eta.tif
Among them, heihe represents heihe river basin, 1km represents the resolution of 1km, 2013 represents the year of 2013, y represents the year, eta represents the actual evapotranspiration data, and tif represents the data in tif format.

Data reading: Envi, Arcgis and other remote sensing software can be used to open and read

Data Citations Data citation guideline What's data citation?

Wu, B. (2015). Monthly evapotranspiration dataset with 1 km spatial resolution over the Heihe River Basin Version 2.0 (2000-2013). A Big Earth Data Platform for Three Poles, DOI: 10.11888/Hydro.tpdc.270884. CSTR: 18406.11.Hydro.tpdc.270884. (Download the reference： RIS | Bibtex )

1. Wu,B.F, Zhu,W.W, Yan,N.N, Xing,Q, Liu,S.F, Chang,S, Qi,F. Integration of parameterization based on mult-source remote sensing data for estimation evapotranspiration: A case study on Heihe River Basin. Manuscript under preparation.( View Details | Bibtex)

Using this data, the data citation is required to be referenced and the related literatures are suggested to be cited.

References literature

1.Wu, B. , Xing, Q. , Yan, N. , Zhu, W. , & Zhuang, Q. . (2015). A linear relationship between temporal multiband modis brdf and aerodynamic roughness in hiwater wind gradient data. Geoscience and Remote Sensing Letters, IEEE, 12(3), 507-511. (View Details )

2.Feng,X.L, Wu,B.F,Yan,N.N, Zhu,W.W. Method to derived mixed boundary layer height from MODIS atmospheric profile data product at Heihe river basin. Boundary-layer Meteorology. Under Review. (View Details | Download )

3.Wu, B. , Yan, N. , Xiong, J. , Bastiaanssen, W. G. M. , Zhu, W. , & Stein, A. . (2012). Validation of etwatch using field measurements at diverse landscapes: a case study in hai basin of china. Journal of Hydrology, 436-437(none), 67-80. (View Details )

4.Xiong, J. , Wu, B. F. , Yan, N. , Zeng, Y. , & Liu, S. . (2010). Estimation and validation of land surface evaporation using remote sensing and meteorological data in north china. Selected Topics in Applied Earth Observations and Remote Sensing, IEEE Journal of, 3(3), P.337-344. (View Details )

5.Zhang, H. , Wu, B. , Yan, N. , Zhu, W. , & Feng, X. . (2014). An improved satellite-based approach for estimating vapor pressure deficit from modis data. Journal of Geophysical Research: Atmospheres, 119(21), 12,256-12,271. (View Details )

6.Zhu, W. , Wu, B. , Yan, N. , Feng, X. , & Xing, Q. . (2014). A method to estimate diurnal surface soil heat flux from modis data for a sparse vegetation and bare soil. Journal of Hydrology, 511, 139-150. (View Details )

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License： This work is licensed under an Attribution 4.0 International (CC BY 4.0)

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