This dataset contains the flux measurements from site No.1 eddy covariance system (EC) in the flux observation matrix from 4 June to 17 September 2012. The site (100.35813° E, 38.89322° N) was located in a cropland (vegetable surface) in the Yingke irrigation district, which is near Zhangye, Gansu Province. The elevation is 1552.75 m. The EC was installed at a height of 3.8 m; the sampling rate was 10 Hz. The sonic anemometer faced north, and the separation distance between the sonic anemometer and the CO2/H2O gas analyzer (Gill&Li7500A) was 0.2 m. Raw data acquired at 10 Hz were processed using the Eddypro post-processing software (Li-Cor Company, http://www.licor.com/env/products/ eddy_covariance/software.html), including spike detection, lag correction of H2O/CO2 relative to the vertical wind component, sonic virtual temperature correction, angle of attack correction, coordinate rotation (2-D rotation), corrections for density fluctuation (Webb-Pearman-Leuning correction), and frequency response correction. The EC data were subsequently averaged over 30 min periods. Moreover, the observation data quality was divided into three classes according to the quality assessment method of stationarity (Δst) and the integral turbulent characteristics test (ITC), which was proposed by Foken and Wichura [1996]: class 1 (level 0: Δst<30 and ITC<30), class 2 (level 1: Δst<100 and ITC<100), and class 3 (level 2: Δst>100 and ITC>100), representing high-, medium-, and low-quality data, respectively. In addition to the above processing steps, the half-hourly flux data were screened in a four-step procedure: (1) data from periods of sensor malfunction were rejected; (2) data before or after 1 h of precipitation were rejected; (3) incomplete 30 min data were rejected when the missing data constituted more than 3% of the 30 min raw record; and (4) data were rejected at night when the friction velocity (u*) was less than 0.1 m/s. There were 48 records per day; the missing data were replaced with -6999. Moreover, suspicious data were marked in red. The released data contained the following variables: data/time, wind direction (Wdir, °), wind speed (Wnd, m/s), the standard deviation of the lateral wind (Std_Uy, m/s), virtual temperature (Tv, ℃), H2O mass density (H2O, g/m^3), CO2 mass density (CO2, mg/m^3), friction velocity (ustar, m/s), stability (z/L), sensible heat flux (Hs, W/m^2), latent heat flux (LE, W/m^2), carbon dioxide flux (Fc, mg/ (m^2s)), quality assessment of the sensible heat flux (QA_Hs), quality assessment of the latent heat flux (QA_LE), and quality assessment of the carbon flux (QA_Fc). 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. 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.

By applying supply-demand balance analysis, the water resource supply and demand of the whole river basin and each county or district were calculated, and the results were used to assess the vulnerability of the water resources system in the basin. The IPAT equation was used to establish a future water resource demand scenario, which involved setting various variables, such as the future population growth rate, economic growth rate, and water consumption per unit GDP. By taking 2005 as the base year and using assorted forecasting data of population size and economic scale, the future water demand scenarios of various counties and cities from 2010 to 2050 were predicted. By applying the basic structure of the HBV conceptual hydrological model of the Swedish Hydro-meteorological Institute, a model of the variation trends of the basin under a changing climate was designed. The glacial melting scenario was used as the model input to construct the runoff scenario in response to climate change. According to the national regulations of the water resource allocation in the basin, a water distribution plan was set up to calculate the water supply comprehensively. Considering the supply and demand situation, the water resource system vulnerability was evaluated by the water shortage rate. By calculating the grain production-related land pressure index of the major counties and cities in the basin, the balance of supply and demand of land resources in scenarios of climate change, glacial melting and population growth was analysed, and the vulnerability of the agricultural system was evaluated. The Miami formula and HANPP model were used to calculate the human appropriation of net primary biomass and primary biomass in the major counties and cities in the future, and the vulnerability of ecosystems from the perspective of supply and demand balance was assessed.

This dataset includes the emissivity spectrum of typical ground objects in middle researches of the Heihe river basin. This dataset was acquired in oasis, desert, Gobi and wetland of experiment area. Time range starts from 2012-05-25 to 2012-07-18 (UTC+8). Instrument: MODEL 102F PORTABLE FTIR (Fourier Transform Infrared Spectrometer), Handheld infrared thermometer. Measurement methods: at the first step, measure the thermal radiance of cold blackbody, warm blackbody, sample and gold plate (Downwelling Radiance). The radiance of cold blackbody and warm blackbody was used to calibrate the instrument, and eliminate the “noise” caused by the device itself. The retrieval of emissivity and temperature was then performed using iterative spectrally smooth temperature-emissivity separation (ISSTES) algorithm. The retrieved emissivity spectrum range from 8 to 14 μm, with spectral resolution of 4cm-1. Dataset contains the original recorded spectra (in ASCII format) and the log files (in doc format). The processed data are emissivity curves (ASCII) that ranged from 8 to 14 μm, and the temperatures of samples. Thermal photos of the sample, digital photo of the scene and the object are recorded in some cases.

The aim of the simultaneous observation of river surface temperature is obtaining the land surface temperature in different places be of different kinds of underlying surface, while the sensor of WiDAS go into the experimental areas of the upstream of Heihe river basin. All the land surface temperature data will be used for validation of the retrieved land surface temperature from WiDAS sensor and the analysis of the scale effect of the land surface temperature, and finally serve for the validation of the authenticity of the surface temperature product from remote sensing. 1. Observation sites and other details Six places be of different kinds of underlying surface were chosen to observe surface temperature simultaneous in the upstream of Heihe river basin on 1 August. Self-recording point thermometers (observed once every 6 seconds) were used one place while handheld infrared thermometers (observed continuously during the sensor of WiDAS go into the region) were used in other five places. The main underlying surface including natural grassland, river section, river rapids, gravel. 2. Instrument parameters and calibration. The field of view of the self-recording point thermometer and the handheld infrared thermometer are 10 and 1 degree, respectively. The emissivity of the latter was assumed to be 0.95. All instruments were calibrated on 5 August, 2012 using black body during observation. 3. Data storage All the observation data were stored in excel.

The fraction of absorbed photosynthetically active radiation data set of the Heihe River Basin provides the fraction of absorbed photosynthetically active radiation data products from 2013 to 2014. The fraction of absorbed photosynthetically active radiation is the the ratio of photosynthetically active radiation absorbed by the canopy that passes through the canopy and then reflected from the canopy during the passage of the canopy to total photosynthetically active radiation. It is determined by the physiological and ecological characteristics and structural characteristics of vegetation canopy. This data set algorithm is developed on the basis of the energy conservation-based FPAR inversion method, in order to reflect the different path and the absorption probability of direct radiation and scattered radiation in the canopy, a FPAR inversion model is developed, which can distinguish direct radiation from scattering radiation. The algorithm can invert the direct FPAR, scattered FPAR and total FPAR of the canopy of the vegetation. The RMSE obtained from the inversion between the instantaneous FPAR and the observed FPAR is 0.0289, and the R2 is 0.8419.

The dateset of soil texture measurements was obtained by the pipette method in the Biandukou and A'rou foci experimental area. Observation items were mainly the soil texture and the soil temperature. Data were archived as Excel files. Sampling locations were not recorded.

This dataset is the spatial distribution map of the marshes in the source area of the Yellow River near the Zaling Lake-Eling Lake, covering an area of about 21,000 square kilometers. The data set is classified by the Landsat 8 image through an expert decision tree and corrected by manual visual interpretation. The spatial resolution of the image is 30m, using the WGS 1984 UTM projected coordinate system, and the data format is grid format. The image is divided into five types of land, the land type 1 is “water body”, the land type 2 is “high-cover vegetation”, the land type 3 is “naked land”, and the land type 4 is “low-cover vegetation”, and the land type 5 is For "marsh", low-coverage vegetation and high-coverage vegetation are distinguished by vegetation coverage. The threshold is 0.1 to 0.4 for low-cover vegetation and 0.4 to 1 for high-cover vegetation.

On 19 August 2012 (UTC+8), Leica ALS70 airborne laser scanner carried by the Harbin Y-12 aircraft was used in a LiDAR airborne optical remote sensing experiment. Leica ALS70 airborne laser scanner has unlimited numbers of returns intensities measurements including the first, second, third return intensities. The wavelength of laser light is 1064 nm. The absolute flight altitude is 2900 m with the point cloud density 1 point per square meter. Airborne LiDAR-DEM and DSM data production were obtained through parameter calibration, automatic classification of point cloud density and manual editing.

The dataset of automatic meteorological observations was obtained at the Yingke oasis station from Nov. 5, 2007 to Oct. 31, 2009. The observation site is located in an irrigation farmland in Yingke (E100°24′37.2″/N38°51′25.7″, 1519.1m), Zhangye city, Gansu province. The experimental area, situated in the middle stream Heihe river basin and with windbreaks space of 500m from east to west and 300m from south to north, is an ideal choice for its flat and open terrain. Observation items were multilayer (2m and 10m) of the wind speed and direction, air temperature and humidity, air pressure, precipitation, four components of radiation; the surface infrared temperature; the multilayer soil temperature (10cm, 20cm, 40cm, 80cm, 120cm and 160cm), the soil moisture (10cm, 20cm, 40cm, 80cm, 120cm and 160cm), and soil heat flux (5cm & 15cm). The raw data were level0 and the data after basic processes were level1, in which ambiguous ones were marked; the data after strict quality control were defined as Level2. The data files were named as follows: station+datalevel+AMS+datadate. Level2 or above were strongly recommended to domestic users. As for detailed information, please refer to Meteorological and Hydrological Flux Data Guide.

The dataset of Land Surface Temperature (LST) observations was obtained in the Yingke oasis and Huazhaizi desert steppe foci experimental areas. (1) The time-continuous surface radiative temperature by the automatic thermometer (FOV: 10°; six from BNU with emissivity 0.95; two from Institute of Remote Sensing Applications with emissivity 1.00, observing at nadir at an intervals of one second. The maize canopy, the bare land and the wheat canopy in Yingke oasis maize field, the wheat canopy in Yingke oasis wheat field, the maize canopy in Huazhaizi desert maize field, vegetation and the bare land in Huazhaizi desert No. 1 and 2 plots and three intensive plots (Huazhaizi desert No. 3 plot, the barley field and the maize field near the resort) were measured on May 20, 24, 28, 30 and 31, Jun. 1, 3, 4, 16, 29 and 30, Jul. 1, 7, 9 and 11, 2008. The dataset of ground truth measurement was synchronizing with WiDAS (Wide-angle Infrared Dual-mode line/area Array Scanner), OMIS-II, TM, ASTER, MODIS, Hyperion and CHRIS. Diurnal variation in the radiative temperature was recorded as well. Raw data, blackbody calibrated data and processed data were archived in Excel format. (2) the surface radiative temperature by the handheld infrared thermometer (FOV:1°; accuracy: 0.1°C) in Yingke oasis maize field and wheat field, Huazhaizi desert maize field, No. 1 and 2 plots, and the maize field at the resort on May 20, 28, 30 and 31, Jun. 1, 4, 16 and 29, Jul. 4, 7 and 11, 2008. Besides, the four component temperature was also measured in Yingke oasis maize field and wheat field, Huazhaizi desert maize field. Raw data and processed data on the surface radiative temperature were archived.

The dataset of BRDF observations was obtained in the Yingke oasis and Huazhaizi desert steppe foci experimental areas. Reflectance could be got based on R = (DN1/DN0)×R0, DN1 indicating DN of the item, R0 and DN0 the reflectance and DN of the grey board. Synchronizing with WiDAS and OMIS-II, the ground observations on reflectance (-60°~60° at intervals of 10°) of maize and wheat were carried out with ASD (FOV: 25°) and the self-made observation platform (maximum height: 5m) on May 30, Jun. 9, 14, 20, 22, 26 and 30, and Jul. 1, 2008. Raw data, recorded data and processed BRDF were archived in Excel format.

Soil respiration rate was measured at the super station of Daman irrigation district in Zhangye city using the open circuit soil carbon flux measurement system LI-8100 (LI-COR, Lincoln, NE, USA) 1) Objective: The aim of soil respiration rate measurement is to explore the diurnal variation characteristics of soil respiration rate and to provide a scientific basis for the assessment of farmland ecosystem carbon cycle and carbon balance. 2) Measurement instruments and ways Measurement instruments: the open type of cold dry soil carbon flux measurement system LI-8100 (LI-COR, Lincoln, NE, USA). Measurement means: soil respiration chamber was placed in PVC ring (10 cm of diameter, 5 cm of height), which was inserted into the soil about 1 to 2 cm 1 d before measurement. The observation is automatic with a power supply of solar panels. 3) Measurement time Soil respiration rate was continuously measured mainly in the corn growing season. The time used in this dataset is in UTC+8 Time. 4) Data processing The data was periodically collected from the data collection instrument and saved as *.81x file, then was converted to text format file using LI-8100 (M) PC Client v2.0.0 software.