The aerosol optical thickness data of the Arctic Alaska station is based on the observation data products of the atmospheric radiation observation plan of the U.S. Department of energy at the Arctic Alaska station. The data coverage time is updated from 2017 to 2019, with the time resolution of hour by hour. The coverage site is the northern Alaska station, with the longitude and latitude coordinates of (71 ° 19 ′ 22.8 ″ n, 156 ° 36 ′ 32.4 ″ w). The source of the observed data is retrieved from the radiation data observed by mfrsr instrument. The characteristic variable is aerosol optical thickness, and the error range of the observed inversion is about 15%. The data format is NC format. The aerosol optical thickness data of Qomolangma station and Namuco station in the Qinghai Tibet Plateau is based on the observation data products of Qomolangma station and Namuco station from the atmospheric radiation view of the Institute of Qinghai Tibet Plateau of the Chinese Academy of Sciences. The data coverage time is from 2017 to 2019, the time resolution is hour by hour, the coverage sites are Qomolangma station and Namuco station, the longitude and latitude coordinates are (Qomolangma station: 28.365n, 86.948e, Namuco station Mucuo station: 30.7725n, 90.9626e). The source of the observed data is retrieved from the radiation data observed by mfrsr instrument. The characteristic variable is aerosol optical thickness, and the error range of the observed inversion is about 15%. The data format is TXT.

The dataset of surface roughness measurements was obtained in No. 1 and 2 quadrates of the E’bao foci experimental area during the pre-observation period. Both the quadrates were divided into 3×3 subsites, with each one spanning a 30×30 m2 plot. With the roughness board 110cm long and the measuring points distance 1cm, the samples were collected along the strip from south to north and from east to west, respectively. The coordinates of the sample would be got with the help of ArcView; and after geometric correction, surface height standard deviation (cm) and correlation length (cm) could be calculated based on the formula listed on pages 234-236, Microwave Remote Sensing, Vol. II. The original photos of each sampling point, surface height standard deviation (cm) and correlation length (cm) were archived. The roughness data were initialized by the sample name, which was followed by the serial number, the name of the file, standard deviation and correlation length. Each .txt file is matched with one sample photo and standard deviation and correlation length represent the roughness. In addition, the length of 101 needles is also included for further validation.

This dataset contains the flux measurements from the large aperture scintillometer (LAS) at site No.1 in the flux observation matrix. There were two types of LASs at site No.1: German BLS900 and China zzlas. The observation periods were from 7 June to 19 September, 2012, and 16 June to 19 September, 2012, for the BLS900 and the zzlas, respectively. The north tower is placed with the receiver of BLS900 and the transmitter of zzlas, and the south tower is placed with the transmitter of BLS900 and the receiver of zzlas. The site (north: 100.352° E, 38.884° N; south: 100.351° E, 38.855° N) was located in the Yingke irrigation district, which is near Zhangye, Gansu Province. The elevation is 1552.75 m. The underlying surface between the two towers contains corn, greenhouse, and village. The effective height of the LASs was 33.45 m; the path length was 3256 m. Data were sampled at 1 min intervals. Raw data acquired at 1 min intervals were processed and quality-controlled. The data were subsequently averaged over 30 min periods. The main quality control steps were as follows. (1) The data were rejected when Cn2 was beyond the saturated criterion (Cn2>3.05E-14). (2) Data were rejected when the demodulation signal was small (BLS900: Average X Intensity<1000; zzlas: Demod<-40 mv). (3) Data were rejected within 1 h of precipitation. (4) Data were rejected at night when weak turbulence occurred (u* was less than 0.1 m/s). The sensible heat flux was iteratively calculated by combining with meteorological data and based on Monin-Obukhov similarity theory. There were several instructions for the released data. (1) The data were primarily obtained from BLS900 measurements; missing flux measurements from the BLS900 were filled with measurements from the zzlas. Missing data were denoted by -6999. (2) The dataset contained the following variables: data/time (yyyy-mm-dd hh:mm:ss), the structural parameter of the air refractive index (Cn2, m-2/3), and the sensible heat flux (H_LAS, W/m^2). (3) In this dataset, the time of 0:30 corresponds to the average data for the period between 0:00 and 0:30; the data were stored in *.xlsx format. Moreover, suspicious data were marked in red. For more information, please refer to Liu et al. (2016) (for multi-scale observation experiment or sites information), Xu et al. (2013) (for data processing) in the Citation section.

The data set contains eddy covariance System observation data of Barren-land Station which is located in the lower reaches of the Heihe Hydro-meteorological Observation Network from January 1, 2015 to December 31, 2015. The site is located in Sidaoqiao, Ejina Banner, Inner Mongolia, and the underlying surface is barren land. The latitude and longitude of the observation point is 101.1326E, 41.9993N, and the altitude is 878m. The mount height of the Eddy Covariance System is 3.5 m, the sampling frequency is 10 Hz, the ultrasonic orientation is north, and the distance between the ultrasonic wind speed temperature meter (CSAT3) and the CO2/H2O analyzer (Li7500) is 15 cm. The original observation data of the Eddy Covariance System is 10 Hz, and the released data is a 30-minute data processed by Eddypro software. The main steps of the processing include: outlier eliminating, delay time correction, coordinates rotation (secondary coordinates rotation), frequency response correction, ultrasonic virtual temperature correction and density (WPL) correction, etc. Meanwhile, the quality evaluation of each flux value was performed,mainly includes atmospheric stability (Δst) test and turbulence similarity (ITC) test. The 30-min flux value output of Eddypro software was also screened: (1) Data from the instrument error was eliminated; (2) Data obtained with one hour before and after precipitation was removed; (3) Data with a deletion rate greater than 10% of the 10 Hz raw data every 30 minutes was eliminated; (4) Observation data of weak turbulence at night (u* less than 0.1 m/s) was excluded. The average period of observation data is 30 minutes, 48 data per day, and the missing data is marked as -6999. The data was missing due to Li7500 calibration of the eddy system on April 7 and 8; the suspicious data caused by instrument drift and other reasons was marked by red fonts. Published observation data include: date/time Date/Time, wind direction(°), horizontal wind speed(m/s), lateral wind speed standard deviation(m/s), ultrasonic virtual temperature (°C), water vapor density (g/m3), carbon dioxide concentration(mg/m3), friction velocity (m/s), length (m), sensible heat flux(W/m2), latent heat flux (W/m2), carbon dioxide flux (mg/(m2s)), sensible heat flux quality identification QA_Hs, latent heat flux quality identification QA_LE, carbon dioxide flux quality identification QA_Fc. The quality identification of sensible heat, latent heat, and carbon dioxide flux is divided into three levels (quality mark 0: (Δst <30, ITC<30); 1: (Δst <100, ITC<100); the rest is 2). The meaning of the data time, such as 0:30 represents an average data of 0:00-0:30; the data is stored in *.xls format. For hydro-meteorological network or station information, please refer to Li et al. (2013). For observation data processing, please refer to Liu et al. (2011).

This dataset include soil moisture and soil temperature observations of 50 SoilNET Nodes during June 2012~March 2013 (UTC+8), which located in a MODIS pixel in the observation matrix of the HiWATER artificial oasis eco-hydrology experimental area, and aim to capture the spatial-temporal variance at the ~100 m scale. Each SoilNET node observe the soil moisture and soil temperature at 4 cm, 10 cm, 20 cm and 40 cm depth using the SPADE sensor with 10 minutes interval. This dataset can be used in the estimation of surface hydrothermal variables and their validation, eco-hydrological research, irrigation management and so on. The detail description please refers to "SoilNET_data_document.docx".

The first dataset of ground truth measurements synchronizing with airborne Polarimetric L-band Multibeam Radiometer (PLMR) mission was obtained in the Yingke oasis and Huazhaizi desert steppe on 28-29 June, 7, 10, 26 July, 2 August, 2012 (UTC+8). The dataset of ground truth measurements synchronizing with airborne Polarimetric L-band Multibeam Radiometer (PLMR) mission was obtained in the Linze Inland River Basin Comprehensive Research Station on 3 July, 2012. PLMR is a dual-polarization (H/V) airborne microwave radiometer with a frequency of 1.413 GHz, which can provide multi-angular observations with 6 beams at ±7º, ±21.5º and ±38.5º. The PLMR spatial resolution (beam spot size) is approximately 0.3 times the altitude, and the swath width is about twice the altitude. The measurements were conducted in the southwest part of the Zhangye Oasis, which included two sampling plots. One was located in Gobi desert with an area of 1 km × 1 km. Due to its homogeneous landscape, around 10 points were sampled to acquire the situation of soil water content. The other sampling plot was designed in farmlands with a dominant plant type of maize. Ground measurements took place along 16 transects, which were arranged parallelly with an interval of 160 m between each other in the east-west direction. In each 2.4 km long transect, soil moisture was sampled at every 80 m in the north-south direction. Steven Hydro probes were used to collect soil moisture and other measurements. For each sampling point in farmland, two measurements were acquired within an area of 1 m2, with one for the soil covered by plastic film (point name was tagged as LXPXXA) and the other for exposed soil (point name was tagged as LXPXXB). The field campaign started from 11:00 AM, but stopped at 4:00 PM on 28 June because of rain. The rest of measurements were completed from 10:30 AM to 5:30 PM on 29 June. Concurrently with soil moisture sampling, vegetation properties were measured at around 10 locations within the farmland sampling plot. Observation items included: Soil parameters: volumetric soil moisture (inherently converted from measured soil dielectric constant), soil temperature, soil dielectric constant, soil electric conductivity. Vegetation parameters: biomass, vegetation water content, canopy height. Data and data format: This dataset includes two parts of measurements, i.e. soil and vegetation parameters. The former is as shapefile, with measured items stored in its attribute table. The measured vegetation parameters are recorded in an Excel file.

The No. 6 hydrological section is located at Gaoya Hydrological Station (100.433° E, 39.135° N, 1420 m a.s.l.) in the midstream of the Heihe River Basin, Zhangye city, Gansu Province. This hydrological section is for intercomparison of flow measurement between ADCP and manual method. The dataset contains recorded by the No. 6 hydrological section from 10 August, 2012 to 31 December, 2013. The width of this section is 58 meters. The water level was measured using an HOBO pressure range and the discharge was measured using cross-section reconnaissance by the StreamPro ADCP. The dataset includes the following parameters: water level (recorded every 30 minutes) and discharge. The missing and incorrect (outside the normal range) data were replaced with -6999. For more information, please refer to Li et al. (2013) (for hydrometeorological observation network or sites information), He et al. (2016) (for data processing) in the Citation section.

The Landuse/Landcover data of the Heihe River Basin in 2000 ( newly compiled in 2012), was finished by the Remote Sensing Laboratory of Cold and Arid Regions Environmental and Engineering Research Institute, Chinese Academy of Sciences, using satellite remote sensing, based on the LandsaTM and ETM remote sensing data around 2000, combing field investigation and verification, thus leading to the establishment of the Heihe River Basin 1:10. 10,000 land use/land cover imagery and vector database. The main contents are: 1:100,000 land use graphic data and attribute data in the Heihe River Basin. The Heihe River Basin 1:100,000 (2011) land cover data and the previous land cover data use the same layered land cover classification system, the whole basin is divided into six first-class categories (cultivated land, woodland, grassland, waters, urban and rural residents, industrial and mining land and unused land), 25 secondary classes; data types are vector polygons, stored as Shape format. Land cover classification attributes: Primary type, secondary type, attribute coding, spatial distribution position Cultivated land: Plain dry land, 123, is mainly distributed in basin, Piedmont zone, river alluvial, diluvial plain or lacustrine plain (lack of water, irrigation condition is poor). Hilly dry land, 122, is mainly distributed in Hilly areas. Generally speaking, land blocks distribute on gentle slopes, ridges and mats of hills. Mountainous dry land, 121, is mainly distributed in mountainous areas, with the elevation below 4000 meters (gentle slope, mountainside, steep slope platform, etc.) and the Piedmont zones. Woodland: There is woodland (arbor), 21, is mainly distributed in the mountains (below 4000 meters ) or on the slopes of the mountains, valleys, hills, plains and so on. Shrub land, 22, is mainly distributed in higher mountain areas (below 4500 meters), most of which distribute in hillsides, valleys and sandy land. Sparse forest land, 23, is mainly distributed in the mountains, hills, plains and sandy land, and on the edge of the Gobi (loam, gravel). Other woodlands, 24, are mainly distributed in the oasis field, around rivers, roadsides and rural settlements. Grassland: Highly covered grassland, 31, is mainly distributed in mountainous areas (slow slopes), hills (steep slopes) and inter-river beaches, Gobi, sand dunes, etc.  Mid-covered grassland, 32, is mainly distributed in relatively dry areas (Gobi, low-lying land and sandy land,sand dunes, etc.). The low-cover grassland, 33, grows mainly in drier areas (on the loess hills and on the edge of the sand). Waters: Channel, 41 is mainly distributed in plains, inter-river cultivated land and inter-mountain valleys. Lake, 42, is mainly distributed in low-lying areas. Reservoir pit, 43, is mainly distributed in plains and valleys between rivers, surrounded by residential areas and cultivated land. Glacier and permanent snow cover, 44, mainly distribute at the top of (over 4000) alpine regions. Flood land, 46, is mainly distributed in the high and low hillside gullies, the piedmont, the plain lowlands, and the edge of the river and lake basins. Residents land: Urban land, 51, is mainly distributed in plains, mountain basins, slopes and valleys. Rural residential land, 52, are mainly distributed in oases, cultivated land and roadsides, on the tablelands and the slopes. Industrial land and traffic land, 53, are generally distributed in the periphery of towns, areas with fairly developed transportation and industrial mining areas. Unutilized land: Sandy land, 61, is mostly distributed in the basin, on both sides of the river, in the river bay and on the periphery of the Piedmont and Gobi. Gobi, 62, is mainly distributed in the Piedmont belt with strong wind erosion and sediment transport. Saline and alkaline land, 63, is mainly distributed in dry lakes, lakeside and areas relatively low with easy water accumulation. Swamp, 64, is mainly distributed in relatively low areas with easy water accumulation. Bare soil, 65, is mainly distributed in arid areas (steep hillsides, hills and gobi), with vegetation coverage less than 5%. Bare rock, 66, is mainly distributed in extremely arid rocky mountainous areas (windy and rainless). The other, 67 mainly distributes in bare rocks formed by freezing and thawing above 4000 meters, also known as alpine tundra.

The No. 7 hydrological section is located at Pingchuan Heihe River Bridge (39 ° 20′2.03 ″ N, 100° 5′49.63″ E, 1375 m a.s.l.) in the middle reaches of the Heihe River Basin, Zhangye, Gansu Province. The dataset contains observations from the No.7 hydrological section from 13 June, 2012, to 24 November, 2012. The width of this section is 130 meters. The water level was measured using SR50 ultrasonic range and the discharge was measured using cross-section reconnaissance by the StreamPro ADCP. The dataset includes the following sections: Water level (recorded every 30 minutes) and Discharge. The data processing and quality control steps were as follows: 1) The water level data which collected from the hydrological station were averaged over intervals of 10 min for a total of 144 records per day. The missing data were denoted by -6999. 2) Data out the normal range records were rejected. 3) Unphysical data were rejected. For more information, please refer to Liu et al. (2016) (for multi-scale observation experiment or sites information), He et al. (2016) (for data processing) in the Citation section.

On 4 July 2012 (UTC+8), TASI sensor carried by the Harbin Y-12 aircraft was used in a visible near Infrared hyperspectral airborne remote sensing experiment, which is located in Linze region and Heihe riverway. The relative flight altitude is 2500 meters. Land surface temperature product was obtained at a resolution of 3 m using a modified temperature/emissivity separation algorithm based on TASI surface radiance data. The product were validated with in situ ground measurements. The validation results indicated that the Land surface temperature product agreed with the ground LSTs well with RMSE lower than 1.5 K.

This dataset contains the automatic weather station (AWS) measurements from site No.17 in the flux observation matrix from 12 May to 17 September, 2012. The site (100.36972° E, 38.84510° N) was located in an orchard in Daman irrigation district, which is near Zhangye, Gansu Province. The elevation is 1559.63 m. The installation heights and orientations of different sensors and measured quantities were as follows: air temperature and humidity (HMP45C; 5 m, towards north), air pressure (PTB110; 2 m), rain gauge (52203; 10 m), wind speed and direction (034B; 10 m, towards north), a four-component radiometer (CNR1; 6 m, towards south), two infrared temperature sensors (SI-111; 6 m, vertically downward), soil temperature profile (109; 0, -0.02, -0.04, -0.1, -0.2, -0.4, -0.6, and -1.0 m), soil moisture profile (CS616; -0.02, -0.04, -0.1, -0.2, -0.4, -0.6, and -1.0 m), and soil heat flux (HFP01; 3 duplicates with one below the vegetation and the other between plants, 0.06 m). One of the infrared temperature sensors (IRT_2) was adjusted to a zenith angle of 50° after 6 August. The observations included the following: air temperature and humidity (Ta_5 m and RH_5 m) (℃ and %, respectively), air pressure (press, hpa), precipitation (rain, mm), wind speed (Ws_10 m, m/s), wind direction (WD_10 m, °), four-component radiation (DR, incoming shortwave radiation; UR, outgoing shortwave radiation; DLR_Cor, incoming longwave radiation; ULR_Cor, outgoing longwave radiation; Rn, net radiation; W/m^2), infrared temperature (IRT_1 and IR_2, ℃), soil heat flux (Gs_1, below the vegetation; Gs_2 and Gs_3, W/m^2), soil temperature profile (Ts_0 cm, Ts_2 cm, Ts_4 cm, Ts_10 cm, Ts_20 cm, Ts_40 cm, Ts_60 cm, and Ts_100 cm, ℃), and soil moisture profile (Ms_2 cm, Ms_4 cm, Ms_10 cm, Ms_20 cm, Ms_40 cm, Ms_60 cm, and Ms_100 cm, %). The data processing and quality control steps were as follows. (1) The AWS data were averaged over intervals of 10 min; therefore, there were 144 records per day. The missing data were filled with -6999. (2) Data in duplicate records were rejected. (3) Unphysical data were rejected. (4) In this dataset, the time of 0:10 corresponds to the average data for the period between 0:00 and 0:10; the data were stored in *.xlsx format. (5) Finally, the naming convention was AWS+ site no. Moreover, suspicious data were marked in red. For more information, please refer to Liu et al. (2016) (for multi-scale observation experiment or sites information), Xu et al. (2013) (for data processing) in the Citation section.

The data set include crop height observed at four sample regions, that is the soil moisture control experimental field at Daman county, and the EC plots, the super station, and Shiqiao sample plots at Wuxing village in Zhangye city. 1) Objective Crop height, a key biophysical parameter, was observed for evapotranspiration estimation in regional scale and the retrieval of other biophysical parameters as well as the application in eco-hydrological models. 2) Measurement instrument: Steel tape. 3) Measurement site a. the soil moisture control experimental field at Daman county, Twelve soil water treatments are set. The wheat height are measured on 17, 23 and 29 May, and 3, 9, 14 and 24 June, and 5 and 12 July. b. the EC site Maize height at 14 EC site (EC-2,EC-3,EC-5,EC-6,EC-7,EC-8,EC-9, EC-10, EC-11, EC-12, EC-13, EC-14, EC-15, EC-16) are measured on 14, 21, 25 and 31 May, 7, 13, 23 and 28 June, 3, 13, 18 and 23 July, 3, 12 and 28 August. c. the super station Maize height at the super station is measured on 22 and 28 May, 5, 11, 18, and 25 June, and 1, 8, 15, 22 and 31 July, 9, 15 and 22 August, and 3 and 11 September. d. the Shiqiao sample site Maize height at the Shiqiao village is measured on 17, 22 and 28 May, 4, 11, 17 and 25 June, 1, 8, 15, 22, and 30 July, 8, 16 and 27 August, and 9 September. 4) Data processing The observational data was recorded in the sheets and reorganized in the EXCEL sheets. The time used in this dataset is in UTC+8 Time.