ET (evapotranspiration) monitoring is very important for agricultural water resources management, regional water resources utilization planning and socio-economic sustainable development. The limitation of traditional et monitoring method is that it can not be observed in large area at the same time, and it can only be limited to observation points. Therefore, the cost of personnel and equipment is relatively high. It can not provide the ET data on the surface, nor can it provide the ET data of different land use types and crop types.
The 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 macro structural characteristics of the earth surface, but also reflect the micro local differences. Due to the differences in groundwater depth, irrigation and management, even if it is adjacent plots, the real agricultural water consumption will be very different. Remote sensing monitoring based on pixel can monitor the spatial differences of crop evapotranspiration, and can provide better field level agricultural water consumption information.
The objective of this project is to take the remote sensing estimation of land surface evapotranspiration in arid areas as the research object. Aiming at the bottleneck problem in the parameterization of evapotranspiration model, the etwatch method and the existing ground observation basis of Heihe River are fully used. The quantitative description method of thermal heterogeneity of underlying surface, the closure correction of surface energy, advection error compensation, surface water stress, and determination of atmospheric reference height are discussed In order to improve the reliability, stability and spatiotemporal continuity of evapotranspiration estimation at basin scale, a long-term evapotranspiration remote sensing data set of Heihe River Basin is constructed by optimizing the parameters of land surface with multi-scale and multi-source data fusion.
This data is the first edition of ET data with resolution of 1 km in Heihe River Basin from 2000 to 2010.
(1) Remote sensing image data
MODIS data with medium and low resolution
Low resolution remote sensing data were collected by purchasing and downloading online free of charge to form MODIS data set from 2000 to 2010. MODIS data covering the whole Heihe River Basin for one day is composed of four groups of files, each group of files is divided into two files according to the regional scope.
FY-2 data
The cloud classification product data of FY-2C and FY-2D from 2005 to 2011 were obtained through the Fengyun satellite remote sensing data service website of National Satellite Meteorological Center of China Meteorological Administration. The cloud classification products are in nominal format, covering the whole FY-2D disk range. The resolution is consistent with the nominal map, and the resolution of sub star point is 5km.
FY-2C / D cloud classification products can accurately complete the cloud classification of FY-2 in the whole observation area. On the basis of cloud detection, the high cloud part is mainly classified. For the medium and low cloud, due to the limitation of the current detection ability, the cloud classification product of FY-2C / D can accurately complete the cloud classification of FY-2. For high clouds, it can be accurately divided into cumulonimbus, cirrus, cirrus, high-level cloud or rain layer cloud.
(2) Meteorological data
The daily meteorological data covering the whole Heihe River Basin for 1 km resolution et monitoring in 2010 were obtained, including six elements: wind speed, maximum temperature, minimum temperature, humidity, air pressure and sunshine hours.
Etwatch, SEBAL model, SEBS model, penman Montes formula
See the documentation for details
According to the verification and analysis of EC data of Yingke station in 2008, it is found that the calculated value is smaller in winter and larger in summer, with an annual error of 2.9%.
This work is licensed under
CC BY 4.0 (Creative Commons Attribution 4.0 International License).
CSTR:11738.11.ncdc.Westdc.2020.700
10.12072/ncdc.Westdc.db0021.2020
