Trough the select tasking, we obtained the WorldView-2 stereo image data in Dayekou Watershed production in mid-May 2012. In the same year from July to August, 27 GPS ground control points (GCP) and checkpoints were measured based on the watershed differential GPS control network. Based on the full-field GCPs, the rational polynomial coefficients (RPC) files of WorldView-2 images were corrected in the digital photogrammetry software system. In the stereo model, 60 high-precision tie points evenly distributed were got through image matching technology, and the 1-m and 2-m resolution digital elevation model (DEM) were rapid extracted. Based on collinearity equations, images at nadir were corrected to adjust relief displacements and geometric errors, and the 0.5-m resolution digital orthorectified images DOM were obtained with the principle of digital differential rectification in Dayekou Basin.
Zhang Yanli, MA Mingguo
This dataset contains the automatic weather station (AWS) measurements from site No.16 in the flux observation matrix from 1 Jun to 17 September, 2012. The site (100.36411° E, 38.84931° N) was located in a cropland (maize surface) in Daman irrigation district, which is near Zhangye, Gansu Province. The elevation is 1564.31 m. The installation heights and orientations of different sensors and measured quantities were as follows: air temperature and humidity (HMP155; 5 m, towards north), rain gauge (TE525M; 10 m), wind speed (03001; 10 m, towards north), a radiometer (Q7; 6 m, towards south), two infrared temperature sensors (SI-111; 6 m, vertically downward), soil temperature profile (AV-10T; 0, -0.02, and -0.04 m), soil moisture profile (CS616; 0.02, 0.04 m), and soil heat flux (HFT3; 3 duplicates with one below the vegetation and the other between plants, 0.06 m). The observations included the following: air temperature and humidity (Ta_5 m and RH_5 m) (℃ and %, respectively), precipitation (rain, mm), wind speed (Ws_10 m, m/s), 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, and Ts_4 cm, ℃), and soil moisture profile (Ms_2 cm and Ms_4 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.
LIU Shaomin, LI Xin, XU Ziwei
The data set includes observation data of meteorological elements in the downstream desert station of Heihe Hydrometeorological Observation Network from January 1, 2017 to December 31, 2017. The site is located in the desert beach of Ejin Banner, Inner Mongolia, and the underlying surface is red sand desert. The latitude and longitude of the observation point is 100.9872E, 42.1135N, and the altitude is 1054m.The air temperature and relative humidity sensors are installed at 5m and 10m, facing the north; the barometer is installed at 2m; the tipping bucket rain gauge is installed at 10m; the wind speed sensor is set at 5m, 10m, and the wind direction sensor is set at 10m, facing the north; the four-component radiometer is installed at 6m, facing south; two infrared thermometers are installed at 6m, facing south, the probe orientation is vertically downward; the soil temperature probe is buried in the ground surface 0cm and underground 2cm, 4cm, 10cm, 20cm 40cm, 60cm and 100cm, in the south of the 2m from the meteorological tower; soil moisture sensors are buried in the underground 2cm, 4cm, 10cm, 20cm, 40cm, 60cm and 100cm, in the south of the 2m from the meteorological tower; soil heat flux plates (3 pieces) are buried in the ground 6 cm in order. Observation items include: air temperature and humidity (Ta_5m, RH_5m, Ta_10m, RH_10m) (unit: centigrade, percentage), air pressure (Press) (unit: hectopascal), precipitation (Rain) (unit: mm), wind speed (WS_5m, WS_10m) (unit: m / s), wind direction (WD_10m) (unit: degree), four-component radiation (DR, UR, DLR_Cor, ULR_Cor, Rn) (unit: watts / square meter), surface radiation temperature (IRT_1, IRT_2 ) (unit: centigrade), soil heat flux (Gs_1, Gs_2, Gs_3) (unit: watts/square meter), soil moisture (Ms_2cm, Ms_4cm, Ms_10cm, Ms_20cm, Ms_40cm, Ms_60cm, Ms_100cm) (unit: volumetric water content, percentage) and soil temperature (Ts_0cm, Ts_2cm, Ts_4cm, Ts_10cm, Ts_20cm, Ts_40cm, Ts_60cm, Ts_100cm) (unit: centigrade). Processing and quality control of the observation data: (1) ensure 144 data per day (every 10 minutes), when there is missing data, it is marked by -6999; From September 17, 2017 to September 23, due to the re-enhancement of the observation tower, the data is missing (the four-component radiation missing period is from September 9 to September 23); (2) eliminate the moment with duplicate records; (3) delete the data that is obviously beyond the physical meaning or the range of the instrument; (5) the format of date and time is uniform, and the date and time are in the same column. For example, the time is: 2016-6-10 10:30; (6) the naming rules are: AWS+ site name. For hydrometeorological network or site information, please refer to Li et al. (2013). For observation data processing, please refer to Liu et al. (2011).
LIU Shaomin, LI Xin, CHE Tao, XU Ziwei, REN Zhiguo, TAN Junlei
This dataset contains the automatic weather station (AWS) measurements from site No.6 in the flux observation matrix from 9 May to 21 September, 2012. The site (100.35970° E, 38.87116° N) was located in a cropland (maize surface) in Yingke irrigation district, which is near Zhangye, Gansu Province. The elevation is 1562.97 m. The installation heights and orientations of different sensors and measured quantities were as follows: air temperature and humidity (HMP45AC; 5 m and 10 m, towards north), air pressure (CS100; 2 m), rain gauge (TE525M; 10 m), wind speed (010C; 5 m and 10 m, towards north), wind direction (020C; 10 m, towards north), a four-component radiometer (CNR4; 6 m, towards south), two infrared temperature sensors (SI-111; 6 m, vertically downward), soil temperature profile (109ss-L; 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). The observations included the following: air temperature and humidity (Ta_5 m and Ta_10 m, RH_5 m and RH_10 m) (℃ and %, respectively), air pressure (press, hpa), precipitation (rain, mm), wind speed (Ws_5 m and 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.
LIU Shaomin, LI Xin, XU Ziwei
On 26 July 2012, a Wide-angle Infrared Dual-mode line/area Array Scanner (WIDAS) carried by the Y-12 aircraft was used in a visible near Infrared thermal Dual-mode airborne remote sensing experiment, which is located in the artificial oasis eco-hydrology experimental area (5×5 km). WIDAS includes an CCD cameras with spatial resolution 0.2 m, a visible near Infrared multispectral camera with five bands scanner (an maximum observation angle 48° and spatial resolution 1 m), and a thermal image camera with spatial resolution 4.8 m. The CCD camera data are recorded in DN values processed by mosaic and orthorectification. The multispectral camera data are recorded in reflectance processed by atmospheric and geometric correction. Thermal image camera data are recorded in radiation brightness temperature processed by atmospheric and geometric correction.
XIAO Qing, Wen Jianguang
This dataset contains the flux measurements from site No.12 eddy covariance system (EC) in the flux observation matrix from 28 May to 21 September, 2012. The site (100.36631° E, 38.86515° N) was located in a cropland (maize surface) in Daman irrigation district, which is near Zhangye, Gansu Province. The elevation is 1559.25 m. The EC was installed at a height of 3.5 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 (CSAT3&Li7500) was 0.15 m. Raw data acquired at 10 Hz were processed using the Edire post-processing software (University of Edinburgh, http://www.geos.ed.ac.uk/abs/research/micromet/EdiRe/), including spike detection, lag correction of H2O/CO2 relative to the vertical wind component, sonic virtual temperature 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.
LIU Shaomin, LI Xin, XU Ziwei
The No. 3 hydrological section is located at Railway Heihe River Bridge (39°02′33.08″ N, 100° 25′49.42″ E, 1443 m a.s.l.) in the middle reaches of the Heihe River Basin, Zhangye, Gansu Province. The dataset contains observations from the No.3 hydrological section from 14 June, 2012, to 24 November, 2012. The width of this section is 50 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.
ZHANG Jian, NING Tianxiang, HUANG Xiaoming, JIANG Heng, LIU Shaomin, LI Xin
The No. 8 hydrological section is located at Gaotai Heihe River Bridge (39 ° 23′22 .93 ″ N, 99 ° 49′37 .29″ E, 1347 m a.s.l.) in the middle reaches of the Heihe River Basin, Zhangye, Gansu Province. The dataset contains observations from the No.8 hydrological section from 17 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.
HE Xiaobo, ZHANG Jian, NING Tianxiang, HUANG Xiaoming, JIANG Heng, LIU Shaomin, LI Xin
The dataset generated from the radiosonde observations in middle basin of Heihe River during 2012. The instrument type are RS92-SGP (Vaisala inc., Finland) or CF-06-A (Changfeng Micro-Electroinics, CHINA). Radiosondes were released during aerospace experiment, such as CASI/SAI, TASI, WIDAS sensors. Atmospheric parameters: pressure, temperature, relative humidity, wind speed and wind direction are measured or calculated at different altitude. This atmospheric parameter profiles can back up atmospheric correction in remote sensing. It can support meteorology research. Observation Site: 1. Wuxing Village: Latitude: 38°51′11.9″N，Longitude: 100°21′48.8″E，Altitude: 1563 m 2. Gaoya Hydrological Station Latitude: 39°8′7.2″N，Longitude: 100°23′59.0″E，Altitude: 1418 m 3. A’Rou Super Station Latitude: 38°03′17.9″N，Longitude: 100°27′28.1″E，Altitude: 2991 m Observation Instrument Type: RS92-SGP manufacture by Vaisala inc., Finland CF-06-A manufacture by Beijing Changfeng Micro-Electronics Technology Co., LTD, CHINA. Observation Time: Simultaneous observation time from 29 June, 2012 to 29 July, 2012 (UTC+8). Accessory data: Pressure, temperature, relative humidity, wind speed and wind direction profiles data.
TAN Junlei, MA Mingguo, Han Huibang, YU Wenping, Hu Ronghai, Zhao Jing, Wang Yan
The soil texture dataset of the Heihe River Basin (2011) is compiled by LIU Chao et al. (2011) by using the SOLIM model. Based on the famous Jenny equation of soil science, and according to the environmental factors such as climate, biology, topography and parent material, knowledge mining and fuzzy logic are combined on the basis of existing soil texture maps and soil profiles in Heihe River Basin. It is produced and integrated with thematic maps of glaciers and lakes. According to the different characteristics of the six ecological zones in Heihe River Basin, different mapping methods are used in the upper, middle and lower reaches. According to the different characteristics of six ecological zones in Heihe River Basin, different mapping methods are used in the upper, middle and lower reaches. The data is in grid format with 1KM spatial resolution and WGS-84 projection. Soil texture attributes and categories represent 0-30 cm topsoil texture attributes, derived from depth-weighted averages. The texname in the attribute table indicates the soil texture type name. Sandrange, siltrange, and clayrange respectively represent the sand, powder, and clay content ranges in the USDA soil triangle. Sandaverage, siltaverage and clayaverage are taken from the measured soil profiles, the average content of sand, silt and clay particles as the sand, silt and clay content of the soil type. (Note: The soil particle content of clay loam is derived from the soil quality map of Beijing Normal University). The soil texture classification standard is USDA, the sand grain size is defined as (2~0.05mm), the silt particle size is (0.05~0.002mm) and the clay size is defined as (<0.002mm).
LIU Chao
The site No. 1 EC towers were used for the intercomparison field in the Yingke irrigation district (1552.75 m, 38°59′51.71″ N, 100°24′38.76″ E). The land surface is homogeneous and dominated by vegetables in the middle reaches of the Heihe River Basin. The precipitation comparison dataset was collected between 12 June, 2012, and 22 November, 2012. The dataset includes data for five different rain gauge types, i.e., pit gauge, Chinese standard manual precipitation gauge, siphon rain gauge, tipping bucket gauge, and weighting gauge. The mountain heights for these gauges were 0.0, 0.7, 1.2, 1.5, and 1.5 m, respectively. The data were recorded every 1 hour, 1 day, 10 minutes, 10 minutes, and 10 minutes, respectively. The main objective of the data collection was to perform an intercomparison of in situ rainfall measurements. 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.
ZHANG Jian, NING Tianxiang, HUANG Xiaoming, JIANG Heng, LIU Shaomin, LI Xin
This dataset contains the flux measurements from the Daman superstation eddy covariance system (EC) at the highest layer in the flux observation matrix from 30 May to 15 September, 2012. The site (100.37223° E, 38.85551° N) was located in a cropland (maize surface) in Daman irrigation district, which is near Zhangye, Gansu Province. The elevation is 1556.06 m. The EC was installed at a height of 34 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 (CSAT3&Li7500A) was 0.17 m. Raw data acquired at 10 Hz were processed using the Edire post-processing software (University of Edinburgh, http://www.geos.ed.ac.uk/abs/research/micromet/EdiRe/), including spike detection, lag correction of H2O/CO2 relative to the vertical wind component, sonic virtual temperature 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.
LIU Shaomin, LI Xin, XU Ziwei
On 25 August 2012, a Leica ALS70 airborne laser scanner boarded on the Y-12 aircraft was used to obtain LiDAR DSM point cloud data. 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 5200 m with the point cloud density 1 point per square meter. Aerial LiDAR-DSM was obtained through parameter calibration, automatic classification of point cloud density and manual editing.
XIAO Qing, Wen Jianguang
This dataset contains the spectra of white cloth and black cloth obtained in the simultaneous time during the airborn remote sensing which supports the airboren data preprocessing as CASI, SASI and TASI , and the spetra of the typical targets in the middle reaches of the Heihe River Basin. Instruments: SVC-HR1024 from IRSA, ASD Field Spec 3 from CEODE, Reference board Measurement method: the spectra radiance of the targets are vertically measured by the SVC or ASD; before and after the target, the spectra radiance of the reference board is measured as the reference. This dataset contains the spectra recorded by the SVC-HR1024 ( in the format of .sig which can be opened by the SVC-HR1024 software or by the notepad ) and the ASD (in the format of .asd), the observation log (in the format of word or excel), and the photos of the measured targets. Observation time: 15-6-2012, the spectra of typical targets in the EC matrix using SVC 16-6-2012, the spectra of typical targets in the wetland by SVC 29-6-2012, the spectra of typical vegetation and soil in Daman site and Gobi site by ASD 29-6-2012, the spectra of white cloth and black cloth by ASD which is simultaneous with the airborne CASI data 30-6-2012, the spectra of vegetation and soil in the desert by ASD 5-7-2012, the spectra of white cloth and black cloth by ASD which is simultaneous with the airborne CASI data 7-7-2012, the spectra of corn in the Daman site for the research of daily speral variation. 8-7-2012, the spectra of white cloth and black cloth by ASD which is simultaneous with the airborne CASI data 8-7-2012, the spectra of corn in the Daman site by ASD for the research of daily speral variation 9-7-2012, the spectra of corn in the Daman site by ASD for the research of daily speral variation 10-7-2012, the spectra of corn in the Daman site by ASD for the research of daily speral variation 11-7-2012, the spectra of corn in the Daman site by ASD for the research of daily speral variation. The time used in this dataset is in UTC+8 Time.
XIAO Qing, MA Mingguo
This dataset contains the flux measurements from the large aperture scintillometer (LAS) at site No.3 in the flux observation matrix. There were two types of LASs at site No.3: German BLS900 and Netherland Kipp&zonen. The observation periods were from 6 June to 20 September, 2012, and 19 June to 20 September, 2012, for the BLS900 and the Kipp&zonen, respectively. The north tower is placed with the receiver of BLS900 and the transmitter of Kipp&zonen, and the south tower is placed with the transmitter of BLS900 and the receiver of Kipp&zonen. The site ( (north: 100.373° E, 38.883° N; south: 100.372° E, 38.856° 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 3111 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>3.36E-14). (2) Data were rejected when the demodulation signal was small (BLS900: Average X Intensity<1000; Kipp&zonen: Demod<-20 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 Kipp&zonen. 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.
LIU Shaomin, LI Xin, XU Ziwei
The dataset contains vegetation type in the middle reaches of the Heihe River Basin, which was used to validate products from remote sensing. It was generated from investigating the land cover strips of CASI during 2012. Instruments: High-precision handheld GPS (2-3 m) and digital camera were used as main tools in the survey. Measurement method: Hierarchical classification is applied based on CASI data. According to various land types, pixel classifications is used for forest, grassland, bare land and building lands; in-situ observations and investigations are used for different crops. Dataset contains: land types, including maize, leek, poplar trees, cauliflower, bell pepper, potatoes, endive sprout, orchard, watermelon, kidney bean, pear orchard, shadow, and non-vegetation, except for 14 others which are not classified. Observation site: core experimental areas with 5*5 matrix structure in the middle reaches of the Heihe river basin Date: From 25 June in 2012 (UTC+8) on.
Zhang Miao
The datasets of “Land Cover Map of Heihe River Basin” provide monthly land cover classification data in 2012-2013. The HJ-1/CCD data with both high spatial resolution (30 m) and high temporal (2 days) frequency was used to construct the time series data. The NDVI curves from the time series HJ-1/CCD data can depict the variation of typical land surface. Different land use type has different NDVI curve. Rules were set to extract every land use type information. The datasets of “Land Cover Map of Heihe River Basin” hold the traditional land use types including water bodies, urban and built-up, croplands, evergreen coniferous forests, deciduous broadleaf forests and so on. Crop type classification (including maize, spring wheat, highland barely, rape and so on), snow and ice and glaciers information updates, make the datasets more detailed. Compared with previous land cover map and other products, the classification result of the datasets is visually bette. Especially in middle stream, the accuracy of crop classification is quite high compared with the data from the ground campaign. The accuracy of land cover map of the datasets in 2012 was evaluated using very high spatial resolution remote sensing data within Google Earth and data from campaign, and the overall accuracy can be as high as 92.19%. In a word, the datasets of “Land Cover Map of Heihe River Basin” is not only high in overall accuracy, but also more detailed in crop fine classification. Furthermore, it updated some new classes like glaciers and snow. The datasets of “Land Cover Map of Heihe River Basin” are consequently the classification datasets with the highest accuracy and most detailed information up to now.
ZHONG Bo, YANG Aixia
This dataset contains the automatic weather station (AWS) measurements from site No.14 in the flux observation matrix from 6 May to 21 September, 2012. The site (100.35310° E, 38.85867° N) was located in a cropland (maize surface) in Yingke irrigation district, which is near Zhangye, Gansu Province. The elevation is 1570.23 m. The installation heights and orientations of different sensors and measured quantities were as follows: air temperature and humidity (HMP45D; 5 m, towards north), air pressure (CS100; 2 m), rain gauge (TE525M; 10 m), wind speed and direction (034B; 10 m, towards north), a four-component radiometer (CNR4; 6 m, towards south), two infrared temperature sensors (IRTC3; 6 m, vertically downward), soil temperature profile (AV-10T; 0, -0.02, -0.04, -0.1, -0.2, -0.4, -0.6, and -1.0 m), soil moisture profile (ECh2o-5; -0.02, -0.04, -0.1, -0.2, -0.4, -0.6, and -1.0 m), and soil heat flux (HFT3; 3 duplicates with one below the vegetation and the other between plants, 0.06 m). 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.
LIU Shaomin, LI Xin, XU Ziwei
On 30 June 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 the observation experimental area (30×30 km), Linze region and Heihe riverway. The relative flight altitude is 2500 meters. The wavelength of TASI is 8-11.5 μm with a spatial resolution of 3 meters. Through the ground sample points and atmospheric data, the data are recorded in surface radiance processed by geometric correction and atmospheric correction. Land surface temperature (LST) data was retrieved by temperature/emissivity separation algorithm.
XIAO Qing, Wen Jianguang
This dataset includes the BRF observations of the corn in the Daman site (100.372° E, 38.855° N) on 29-6-2012) and the desert site around the airport (100.700° E, 38.762° N) acquired on 8-7-2012. Instruments: SVC-HR1024 from IRSA, reference board from IRSA, the multi-angular auto-observing shelf developed by BNU Measurement methods: we measure the BRF in the unit of observing plane, i.e. fix the view azimuth then change the view zenith angle to measure the target spectra, including along the principle plane and cross the principle plane at different sun angle. Besides, the planes along and cross the ridge of corn are also measured, specific planes like 0° , 90° away from the north are also observed in the desert. In each observing plane, view zenith angles from -60° to 60° with a interval of 10° are observed. The fiber optic probe with a view field of 25° is fixed at the multi-angular shelf at a height of 5 meters. The spectrum measured by the SVC-HR1024 is ranged from 350 nm-2500 nm. In each plane measurement , the spectral radiance of the reference board is measured first, then the target radiance of different view zenith angle is measured, finally the reference board radiance is measured again. Dataset contains the originally recorded data like the spectra (in sig format) and the log files (in txt format), and the processed data BRDF (in txt format and jpg format). The processed data in the format of txt, contains the observing geometries and corresponding reflectance spectra from 350 nm to 2500 nm. The processed data in the format of jpg, is a quick view of the BRF at 550 nm, 650 nm and 850 nm of each observing plane.
You Dongqin, Wang Heshun, Yang Jian, Hu Ronghai, XIAO Qing, Wen Jianguang, MA Mingguo
On 25 July 2012, a Leica ALS70 airborne laser scanner boarded on the Y-12 aircraft was used to obtain the point cloud data. 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 4800 m with the point cloud density 1 points per square meter. Aerial LiDAR-DEM was obtained through parameter calibration, automatic classification of point cloud density and manual editing.
XIAO Qing, Wen Jianguang
This dataset includes data recorded by the Hydrometeorological observation network obtained from the automatic weather station (AWS) at the observation system of Meteorological elements gradient of Shenshawo sandy desert station between 1 September, 2012, and 31 December, 2013. The site (100.493° E, 38.789° N) was located on a desert surface in the Shenshawo, which is near Zhangye city, Gansu Province. The elevation is 1594 m. The installation heights and orientations of different sensors and measured quantities were as follows: air temperature and humidity profile (HMP45AC; 5 and 10 m, north), wind speed profile (010C; 5 and 10 m, north), wind direction profile (020C; 10 m, north), air pressure (PTB110; 2 m), rain gauge (52203; 10 m), four-component radiometer (CNR1; 6 m, south), two infrared temperature sensors (IRTC3; 6 m, south, vertically downward), soil heat flux (HFP01; 3 duplicates, -0.06 m), soil temperature profile (109; 0, -0.02, -0.04, -0.1, -0.2, -0.4, -0.6, and -1 m), and soil moisture profile (CS616; -0.02, -0.04, -0.1, -0.2, -0.4, -0.6 and -1 m). The observations included the following: air temperature and humidity (Ta_5 m and Ta_10 m; RH_5 m and RH_10 m) (℃ and %, respectively), wind speed (Ws_5 m and Ws_10 m) (m/s), wind direction (WD_10 m) (°), air pressure (press) (hpa), precipitation (rain) (mm), 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 IRT_2) (℃), soil heat flux (Gs_1, Gs_2 and Gs_3) (W/m^2), soil temperature (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 (Ms_2 cm, Ms_4 cm, Ms_10 cm, Ms_20 cm, Ms_40 cm, Ms_60 cm and Ms_100 cm) (%, volumetric water content). The data processing and quality control steps were as follows: (1) The AWS data were averaged over intervals of 10 min for a total of 144 records per day. The precipitation data were missing during 31 March, 2013 and 26 July, 2013 because of the malfunction of rain gauge. The missing data were denoted by -6999. (2) Data in duplicate records were rejected. (3) Unphysical data were rejected. (4) The data marked in red are problematic data. (5) The format of the date and time was unified, and the date and time were collected in the same column, for example, date and time: 2013-6-10 10:30. (6) Finally, the naming convention was AWS+ site no. Moreover, suspicious data were marked in red. For more information, please refer to Li et al. (2013) (for hydrometeorological observation network or sites information), Liu et al. (2011) (for data processing) in the Citation section.
LIU Shaomin, LI Xin, CHE Tao, XU Ziwei, REN Zhiguo, TAN Junlei
The dataset of airborne WiDAS mission was obtained in the Linze station-Linze grassland flight zone on Jul. 11, 2008. Intra-band data available for general users include Level-2C data (after geometric, radiometric and atmospheric corrections), Level-1B browse image (after intra-band matching) and Level-2B browse image (after registration). The raw data, Level-1A, and data processing parameters were filed; applications would be evaluated prior to access. Data processing started in Aug. 2008 and ended in Apr. 2009, and in Nov. 2009, CCD data were reprocessed to adjust radiometric calibration. The flying time of each route was as follows: {| ! id ! flight ! relative height ! starttime ! endtime ! data size ! data state ! data quality ! ground targets |- | 1 || 1#13 || 1500m || 1:52:06 || 11:58:02 || 90 || processed; compelete || good || Pingchuan reservoir |- | 2 || 1#11 || 1500m || 12:11:38 || 12:09:54 || 95 || processed; compelete || good || Linze grassland station |- | 3 || 1#9 || 1500m || 12:14:58 || 12:20:42 || 87 || processed; compelete || good || Pingchuan reservoir |- | 4 || 1#7 || 1500m || 12:27:14 || 12:33:18 || 92 || processed; compelete || good || desert transit zone |- | 5 || 1#5 || 1500m || 12:38:22 || 12:44:14 || 89 || processed; compelete || good || north-south desert plot |- | 6 || 1#3 || 1500m || 12:50:30 || 12:56:26 || 90 || processed; compelete || good || Pingchuan reservoir |- | 7 || 1#1 || 1500m || 13:01:46 || 13:07:46 || 91 || processed; compelete || good || Linze station |}
Liu Qiang, XIAO Qing, Wen Jianguang, FANG Li, Wang Heshun, LI Bo, LIU Zhigang, LI Xin, MA Mingguo
This dataset includes data recorded by the Hydrometeorological observation network obtained from an observation system of Meteorological elements gradient of Sidaoqiao Superstation between 11 July, 2013, and 31 December, 2013. The site (101.137° E, 42.001° N) was located on a tamarix (Tamarix chinensis Lour.) surface in the Sidaoqiao, Dalaihubu Town, Ejin Banner, Inner Mongolia Autonomous Region. The elevation is 873 m. The installation heights and orientations of different sensors and measured quantities were as follows: air temperature and humidity profile (HC2S3; 5, 7, 10, 15, 20 and 28 m, towards north), wind speed profile (010C; 5, 7, 10, 15, 20 and 28 m, towards north), wind direction profile (020C; 15 m, towards north), air pressure (CS100; in waterproof box), rain gauge (TE525M; 28 m, towards south), four-component radiometer (CNR4; 10 m, towards south), two infrared temperature sensors (SI-111; 10 m, towards south, vertically downward), two photosynthetically active radiation (PQS-1; 10 m, towards south, one vertically upward and one vertically downward), soil heat flux (HFP01SC; 3 duplicates with G1 below the tamarix; G2 and G3 between plants, -0.06 m), a TCAV averaging soil thermocouple probe (installed on 17 July, 2013, TCAV; -0.02, -0.04 m), soil temperature profile (109ss-L; 0, -0.02, -0.04, -0.1, -0.2, -0.4, -0.8, -1.2 and -1.6 m), and soil moisture profile (install on 7 December, 2013, ML2X; -0.02, -0.04, -0.1, -0.2, -0.4, -0.8, -1.2 and -1.6 m). The observations included the following: air temperature and humidity (Ta_5 m, Ta_7 m, Ta_10 m, Ta_15 m, Ta_20 m and Ta_28 m; RH_5 m, RH_7 m, RH_10 m, RH_15 m, RH_20 m and RH_28 m) (℃ and %, respectively), wind speed (Ws_5 m, Ws_7 m, Ws_10 m, Ws_15 m, Ws_20 m and Ws_28 m) (m/s), wind direction (WD_15 m) (°), air pressure (press) (hpa), precipitation (rain) (mm), 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 IRT_2) (℃), photosynthetically active radiation of upward and downward (PAR_up and PAR_down) (μmol/ (s m^-2)), average soil temperature (TCAV, ℃), soil heat flux (Gs_1, Gs_2 and Gs_3) (W/m^2), soil temperature (Ts_0 cm, Ts_2 cm, Ts_4 cm, Ts_10 cm, Ts_20 cm, Ts_40 cm, Ts_80 cm, Ts_120 cm and Ts_160 cm) (℃), and soil moisture (Ms_2 cm, Ms_4 cm, Ms_10 cm, Ms_20 cm, Ms_40 cm, Ms_80 cm, Ms_120 cm and Ms_160 cm) (%, volumetric water content). The data processing and quality control steps were as follows: (1) The AWS data were averaged over intervals of 10 min for a total of 144 records per day. The wind speed (10 m height) data were missing before 12 November, 2013 because of the sensor problem. The missing data were denoted by -6999. (2) Data in duplicate records were rejected. (3) Unphysical data were rejected. (4) The data marked in red are problematic data. (5) The format of the date and time was unified, and the date and time were collected in the same column, for example, date and time: 2013-9-10 10:30. (6) Finally, the naming convention was AWS+ site no. Moreover, suspicious data were marked in red. For more information, please refer to Li et al. (2013) (for hydrometeorological observation network or sites information), Liu et al. (2011) (for data processing) in the Citation section.
LIU Shaomin, LI Xin, CHE Tao, XU Ziwei, REN Zhiguo, TAN Junlei
This dataset includes data recorded by the Hydrometeorological observation network obtained from the automatic weather station (AWS) at the observation system of Meteorological elements gradient of Sidaoqiao barren-land station between 9 July, 2013, and 31 December, 2013. The site (101.133° E, 41.999° N) was located on a barren-land surface in the Sidaoqiao, Dalaihubu Town, Ejin Banner, Inner Mongolia Autonomous Region. The elevation is 878 m. The installation heights and orientations of different sensors and measured quantities were as follows: four-component radiometer (CNR4; 24 m, south), two infrared temperature sensors (SI-111; 24 m, south, vertically downward), soil heat flux (HFP01; 3 duplicates, -0.06 m), and soil temperature profile (AV-10T; 0, -0.02 and -0.04 m). The observations included the following: 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 IRT_2) (℃), soil heat flux (Gs_1, Gs_2 and Gs_3) (W/m^2), and soil temperature (Ts_0 cm, Ts_2 cm, Ts_4 cm) (℃). The data processing and quality control steps were as follows: (1) The AWS data were averaged over intervals of 10 min for a total of 144 records per day. Data were missing during 24 September, 2013 and 26 September, 2013 because of the malfunction of datalogger. The missing data were denoted by -6999. (2) Data in duplicate records were rejected. (3) Unphysical data were rejected. (4) The data marked in red are problematic data. (5) The format of the date and time was unified, and the date and time were collected in the same column, for example, date and time: 2013-9-10 10:30. (6) Finally, the naming convention was AWS+ site no. Moreover, suspicious data were marked in red. For more information, please refer to Li et al. (2013) (for hydrometeorological observation network or sites information), Liu et al. (2011) (for data processing) in the Citation section.
LIU Shaomin, LI Xin, CHE Tao, XU Ziwei, REN Zhiguo, TAN Junlei
In mid July 2011, the photosynthetic organs (leaf or assimilating branches) of typical desert plants were collected and determined by laboratory. The indicators include: leaf water potential, total leaf water content, relative water content, dry weight water content, leaf dry matter content, specific leaf area, specific leaf volume, free water, bound water, etc.
SU Peixi
The dataset of crop biochemical parameter measurements was obtained in the maize field (May 25-Jun. 8, 2008) and the wheat field (Jun. 18-Jul. 4, 2008) of Yingke oasis foci experimental area. Observation items included LAI by LAI-2000, the chlorophyll content by SPAD and leaf moisture by the oven and the scales. Four files were included, readme.txt, wheat sample coordinates.xls, wheat.xls for wheat biochemical parameters and Yingke oasis maize field.xls for maize biochemical parameters.
DONG Jingjing, GAO Shuai, WU Mingquan, WU Chaoyang
This dataset contains the flux measurements from the Sidaoqiao superstation eddy covariance system (EC) in the lower reaches of the Heihe hydrometeorological observation network from 6 July to 31 December, 2013. The site (101.137° E, 42.001° N) was located in the Tamarix surface, Ejin Banner in Inner Mongolia. The elevation is 873 m. The EC was installed at a height of 8 m, and 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 (CSAT3&Li7500A) was 0.15 m. The raw data acquired at 10 Hz were processed using the Edire post-processing software (University of Edinburgh, http://www.geos.ed.ac.uk/abs/research/micromet/EdiRe/), including the spike detection, lag correction of H2O/CO2 relative to the vertical wind component, sonic virtual temperature 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. 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), as 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), which represent high-, medium-, and low-quality data, respectively. In addition to the above processing steps, the half-hourly flux data were screened using a four-step procedure: (1) data from periods of sensor malfunction were rejected; (2) data collected 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 0.12 m/s. There were 48 records per day, and the missing data were replaced with -6999. 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 *.xls format. For more information, please refer to Li et al. (2013) (for hydrometeorological observation network or sites information), Liu et al. (2011) (for data processing) in the Citation section.
LIU Shaomin, LI Xin, CHE Tao, XU Ziwei, REN Zhiguo, TAN Junlei
In July 19, 2012 (UTC+8), the airborne LIDAR data is acquired in the foci area in the Heihe,middle reaches, which can provide high spatial resolution (m) and high precision (20 cm) of the surface elevation information. Based on airborne LIDAR data processing, the land surface DEM, DSM and point cloud density map were generated. By subtracting DSM and DEM directly, a Vegetation height product in the middle reaches of the Heihe River Basin was obtained. The product overall accuracy is 88%.
XIAO Qing, Wen Jianguang
This dataset contains the flux measurements from the Zhangye wetland station eddy covariance system (EC) in the flux observation matrix from 25 June to 26 September, 2012. The site (100.44640° E, 38.97514° N) was located in a wetland surface, which is near Zhangye city, Gansu Province. The elevation is 1460.00 m. The EC was installed at a height of 5.2 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 0.25 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.
LIU Shaomin, LI Xin, XU Ziwei
Spectral reflectance observation was carried out for the typical underlying surface and black and white cloth in the low reaches of the Heihe River Basin during the aviation flight experiment in 2014, which will provide basic data set for the preprocessing of the flight data. 1. Observation Instrument PRS-3500 portable spectrometer, with the spectral range is 350-2500 nm, and the reference board. 2. Samples and observation methods The samples including the black and white cloth, the cantaloupe, the Tamarix chinensis, the Populus euphratica, the reeds, the weeds, the Karelinia caspica, the sandy soil, the gobi, the Sophora alopecuroides and so on. Reflectance of the reference board was measure vertically for once and then objective reflectance were measured for five times for each observation objective. 3. Observation time The typical underlying surface vegetation observation was on days of 24 July, 27 July, 31 July, 2014. The black and white cloth simultaneous observation was on 29 July, 2014. 4. Data storage The observation recorded data were stored in excel and the original spectral data were stored in *.sed files derived from the spectrometer, which can be opened by the matched software of the spectrometer or by a txt.
GENG Liying, Li Yimeng
This dataset includes data recorded by the Hydrometeorological observation network obtained from the automatic weather station (AWS) at the observation system of Meteorological elements gradient of Sidaoqiao mixed forest station between 12 July, 2013, and 31 December, 2013. The site (101.134° E, 41.990° N) was located on a tamarix and populous forest (Tamarix chinensis Lour. and Populus euphratica Olivier.) surface in the Sidaoqiao, Dalaihubu Town, Ejin Banner, Inner Mongolia Autonomous Region. The elevation is 874 m. The installation heights and orientations of different sensors and measured quantities were as follows: air temperature and humidity profile (HMP45D; 28 m, north), wind speed and direction profile (034B; 28 m, north), air pressure (AV-410BP; in tamper box), rain gauge (52203; 28 m, south), four-component radiometer (CNR4; 24 m, south), two infrared temperature sensors (IRTC3; 24 m, south, vertically downward), two photosynthetically active radiation (PQS-1; 24 m, south, one vertically upward and one vertically downward), soil heat flux (HFP01; 3 duplicates, -0.06 m), soil temperature profile (AV-10T; 0, -0.02, -0.04, -0.1, -0.2, -0.4, -0.6 and -1.0 m), and soil moisture profile (ML2X; install on Dec. 7, 2013, -0.02, -0.04, -0.1, -0.2, -0.4, -0.6 and -1.0 m). The observations included the following: air temperature and humidity (Ta_28 m; RH_28 m) (℃ and %, respectively), wind speed (Ws_28 m) (m/s), wind direction (WD_28 m) (°), air pressure (press) (hpa), precipitation (rain) (mm), 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 IRT_2) (℃), photosynthetically active radiation of upward and downward (PAR_up and PAR_down) (μmol/ (s m^-2)), soil heat flux (Gs_1, Gs_2 and Gs_3) (W/m^2), soil temperature (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 (Ms_2 cm, Ms_4 cm, Ms_10 cm, Ms_20 cm, Ms_40 cm, Ms_60 cm and Ms_100 cm) (%, volumetric water content). The data processing and quality control steps were as follows: (1) The AWS data were averaged over intervals of 10 min for a total of 144 records per day. The missing data were denoted by -6999. (2) Data in duplicate records were rejected. (3) Unphysical data were rejected. (4) The data marked in red are problematic data. (5) The format of the date and time was unified, and the date and time were collected in the same column, for example, date and time: 2013-9-10 10:30. (6) Finally, the naming convention was AWS+ site no. Moreover, suspicious data were marked in red. For more information, please refer to Li et al. (2013) (for hydrometeorological observation network or sites information), Liu et al. (2011) (for data processing) in the Citation section.
LIU Shaomin, LI Xin, CHE Tao, XU Ziwei, REN Zhiguo, TAN Junlei
A land surface temperature observation system was set up in apple orchard near by the No.17 eddy covariance system of the MUlti-Scale Observation experiment on Evapotranspiration over heterogeneous land surfaces 2012 (MUSOEXE-12). This observation site can offer in situ calibration data of apple trees for TASI, WiDAS and L band sensor used in aerospace experiment. Observation Site: This point is located in a large and homogeneous apple orchard in Zhangye Experiment Field, Gansu Academy of Agricultural Sciences. It’s 4 meters away from southwest of No.17 eddy covariance system, and observation height is 4.55 m. Crown size of observed apple tree is 4 m × 4 m. Underlying surface of observation site is mainly apple trees. The coordinates of this site: 38°50′41.70" N，100°22′11.40" E. Observation Instrument: The observation system consists of one SI-111 infrared radiometers (Campbell, USA) installed vertically downward to apple tree. Observation Time: This site operates from 3 August, 2012 to 27 September, 2012. Observation data laagered by every 1 minute uninterrupted. Output data contained sample data of every 1 minute. Accessory data: Land surface (apple tree) infrared temperature (by SI-111) can be obtained. Dataset is stored in *.dat file, which can be read by Microsoft excel or other text processing software (UltraEdit, et. al). Table heads meaning: Target_C_Avg, apple tree temperature @ 4.55 m (℃); SBT_C_Avg, body temperature of SI-111 sensor (℃). Dataset is stored day by day, named as: data format + site name + interval time + date + time. The detailed information about data item showed in data header introduction in dataset.
MA Mingguo
This dataset contains Doppler Weather Radar data from the Zhangye National Climate Observatory during the Watershed Allied Telemetry Experimental Research from 2008-03-08 to 2008-06-30. The latitude and longitude of the observation point are 100°16.8'E, 39°05.094'N; the altitude is 1378m. The main observation items are: rainfall, cloud physics, weather radar, etc.
Zhangye National Climate Observatory
The dataset of automatic meteorological observations was obtained from Jun. 1, 2008 to Dec. 31, 2009 at the Huazhaizi desert station which is located in Anyangtan (E100°19'06.9″/N38°45'54.7″), south of Zhangye city, Gansu province,. The experimental area, situated in the middle stream of Heihe river, with a flat and open terrain and sparse vegetation cover is an ideal desert observing field. Observation items included the multi-layer (2m and 10m) wind speed and direction, the air temperature, precipitation, the four components of radiation, the surface infrared temperature, the multi-layer soil temperature (5cm, 10cm, 20cm, 40cm, 80cm and 160cm), soil moisture (5cm, 10cm, 20cm, 40cm, 80cm and 160cm) and soil heat flux (5cm & 10cm). The raw data were level0 and the data after basic processes were level1; the data after strict quality control were defined as Level2. The data files were named as follows: station+datalevel+AMS+datadate.. As for detailed information, please refer to “Meteorological and Hydrological Flux Data Guide".
LI Xin, XU Ziwei
The dataset include the planting structure and area information of major crops in 11 districts and counties of the Heihe River Basin from 2000 to 2012 (grain, wheat, corn, potato, soybean, cotton, oil, vegetables, etc.)
DENG XiangZheng
Trough the select tasking, we obtained the WorldView-2 stereo image data in Dayekou Basin production in mid-May 2012. In the same year from July to August, 27 GPS ground control points (GCP) and checkpoints were measured based on the watershed differential GPS control network. Based on the full-field GCPs, the rational polynomial coefficients (RPC) files of WorldView-2 images were corrected in the digital photogrammetry software system. In the stereo model, 60 high-precision tie points evenly distributed were got through image matching technology, and the 1-m and 2-m resolution digital elevation model (DEM) were rapid extracted. Moreover, the DEM was edited in some key areas, such as the shady forest coverage and Dayekou reservoir. The terrain feature points and line data were added to improve the accuracy of the results in large variation of terrain feature. Check points were composed of GPS points and model confidential points, which used for quantitative validation. And they root mean square errors RMSE were 1.9 meters and 1.2 meters respectively, which achieve the requirements of two degree accuracy of 2.0 m at a scale of 1:2000 in high mountains.
Zhang Yanli, MA Mingguo
The dataset of soil moisture observations was obtained by the cutting ring (50cm^3) and ML2X Soil Moisture Tachometer in the Linze station foci experimental area. Surface soil (0-5cm) was measured 2-3 times in 40 subplots of the west-east desert strip on May 24, 25, 28, Jun. 27 and Jul. 11, 2008, 2-4 times in 9 subplots of north-south strip on May 24, 25, 28, Jun. 27 and Jul. 11, 17 times from P1 to P6 strips on Jul. 4 and 8, nine times along LY06 strip on Jun. 6, 15, 29 and Jul. 11, LY07 strip on May 30, Jun. 6, 10, 15, 29 and Jul. 11 and LY08 strip on May 30, Jun. 6 and 10, and once by the cutting ring and three times by ML2X Soil Moisture Tachometer in Wulidun farmland quadrates on May 24, 25, 28, Jun. 29 and Jul. 11. Data were archived as Excel files. See the metadata record “WATER: Dataset of setting of the sampling plots and stripes in the Linze station foci experimental area” for more information of the quadrate locations.
SONG Yi, BAI Yanfen, DING Songchuang, GAO Song, HAO Xiaohua, PAN Xiaoduo, Qian Jinbo, SHU Lele, SONG Yi, WANG Yang, XU Zhen, YAN Qiaodi, ZHU Shijie, DONG Jian, YU Yingjie, JIANG Hao, LI Shihua
The dataset of automatic meteorological observations was obtained at the Dadongshu mountain snow observation station (E100°14′/N38°01′, 4101m) from Oct. 29, 2007 to Oct. 1, 2009. The experimental area with a flat and open terrain was slightly sloping from southeast to northwest. With alpine meadow and stones, and snow in autumn, winter and spring, the landscape was ideal. Observation items were multilayer (2m and 10m) of the wind speed, the air temperature and air humidity, the air pressure, rain and snow gauges, snow depth, four components of radiation, the multilayer soil temperature (5cm, 10cm, 20cm, 40cm, 80cm, and 120cm), soil moisture (5cm, 10cm, 20cm, 40cm, 80cm, and 120cm), 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.
WANG Jian, CHE Tao, LI Hongyi, HAO Xiaohua
The dataset of the survey at the sampling plots in the transit zone between oasis and desert was obtained in the Linze station foci experimental area. Observation items included: (1) soil moisture and temperature of the soil profiles (0-10cm, 10-20cm, 20-30cm and 30-40cm) measured by the cutting ring method (50cm^3, once each layer) and the probe thermometer (15cm, twice each layer) on May 25, 2008. Data were archived as Excel files. (2) biomass (green weight and dry weight, samples from 0.5m×0.5m) with photos measured by the plant harvesting in LY07 quadrate on Jun. 22, 2008. Data were archived as Excel files. (3) vegetation coverage measured by the diagonal method on Jun. 22, 2008. By estimating the coverage along the two diagonals, the total coverage of the plot can be developed. Data were archived as Excel files.
GAO Song, PAN Xiaoduo, Qian Jinbo, SONG Yi, WANG Yang, ZHU Shijie
The dateset of the ground-based RPG-8CH-DP microwave radiometer observations was obtained in the Biandukou foci experimental area from Mar. 14 to 17, 2008. Observation items included the brightness temperature by the ground-based microwave radiometer (18.7GHz and 36.5GHz), the soil temperature by the thermal resistor, the gravimetric soil moisture by the microwave drying method, and the surface roughness by the grid board. The wheat stubble land (38°15'44.13"N, 100°55'35.34"E) was chosen for continuous observations from 11:00 to 24:00 on Mar. 14, with the incidence 20°-70° and the step length 5°. The rape stubble land (38°15'23.17"N, 100°58'37.84"E) was chosen for continuous observations from 10:00 to 21:30 on Mar. 16, with the incidence 20°-70° and the step length 5°. The deep plowed land (38°18'8.28"N, 101° 3'27.22"E) was chosen for short time observations from 17:26 to 19:20 on Mar. 17, with the azimuth angle 240°-300° and the step length 10°, the incidence 40°-70° and the step length 5°. The brightness temperature was archived as .BRT and .txt files (the ASCII format). Each row in .txt was listed by year, month, date, hour, minute, second, 6.925GHz (h), 6.925GHz (v), 10.65GHz (h), 10.65GHz (v) , 18.7GHz (h), 18.7GHz (v), 36.5GHz (h), 36.5GHz (v), the elevation angle, and the azimuth angle. Values for 6.925GHz and 10.65GHz were zero due to malfunction. The roughness data were obtained by the grid board and the camera and the RMS height (cm) and correlation length (cm) were also calculated and archived, which could be opened by Notepad or Microsoft Office Word. Those provide reliable reference for the roughness of the same land cover type. The gravimetric soil moisture (soil samples from 0-1cm, 1-3cm and 3-5cm) was measured by the microwave drying method. The file can be opened by Microsoft Office Word. The shallow layer soil moisture was measured by hydra prob from 12:00 to 17:00 on 14 and by the Hydra probe (straight downward for 0-5cm) and HH2 (level into the soil surface) on 16. The surface temperature was measured by the thermal resistor. The file can be opened by Microsoft Office Word. Four data files were included, the brightness temperature, the surface temperature, the soil moisture and the surface roughness.
CHANG Sheng, LIANG Xingtao, PAN Jinmei, PENG Danqing, ZHANG Yongpan, ZHANG Zhiyu, ZHAO Shaojie, Zhao Tianjie, ZHENG Yue, YIN Xiaojun, ZHANG Zhiyu
Zhanye Airport desert observation system can offer in situ calibration data for TASI, WiDAS and L band sensor used in aerospace experiment. Observation Site: This point is located in a large, homogeneous and flatten desert near by Zhangye Airport. The main vegetation type is Sparse and low shrub. The coordinates of this site: 38°4′41.30" N, 100°41′48.10" E. Observation Instrument: The observation system consists of two SI-111 infrared radiometers (Campbell, USA), one installed vertically downward to land surface, another face to south of zenith angle 35°. SI-111 sensor installed at 4.0 m height. Observation Time: This site operates from 10 June, 2012 to today. Observation data laagered by every 5 seconds uninterrupted. Output data contained sample data of every 5 seconds and mean data of 1 minute. Accessory data: Land surface infrared temperature (by SI-111), sky infrared temperature (by SI-111) can be obtained. Dataset is stored in *.dat file, which can be read by Microsoft excel or other text processing software (UltraEdit, et. al). Table heads meaning: TarT_Atm, Sky infrared temperature @ facing south of zenith angle 35° (℃); SBT_Atm, body temperature of SI-111 sensor (℃) measured sky; TarT_Sur, land surface infrared temperature @ 4.0 m height; SBT_Sur, body temperature of SI-111 sensor (℃) measured land surface. Dataset is stored day by day, named as: data format + site name + interval time + date + time. The detailed information about data item showed in data header introduction in dataset.
MA Mingguo
This dataset contains the flux measurements from site No.9 eddy covariance system (EC) in the flux observation matrix from 4 June to 17 September, 2012. The site (100.38546° E, 38.87239° N) was located in a cropland (maize surface) in Yingke irrigation district, which is near Zhangye, Gansu Province. The elevation is 1543.34 m. The EC was installed at a height of 3.9 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.
LIU Shaomin, LI Xin, XU Ziwei
This dataset includes data recorded by the Hydrometeorological observation network obtained from the automatic weather station (AWS) at the observation system of Meteorological elements gradient of Huangzangsi station between 10 June, 2013, and 31 December, 2013. The site (100.192° E, 38.225° N) was located on a cropland (wheat) surface in the Huangzangsi village, Babao town, Qilian County, Qinghai Province. The elevation is 2612 m. The installation heights and orientations of different sensors and measured quantities were as follows: air temperature and humidity profile (HMP45AD; 5 m, north), wind speed and direction profile (03001; 10 m, north), air pressure (278; in the tamper box on the ground), rain gauge (TE525M; 10 m), four-component radiometer (CNR4; 6 m, south), two infrared temperature sensors (IRTC3; 6 m, south, vertically downward), soil heat flux (HFT3; 3 duplicates with G1 below the vegetation; G2 and G3 between plants, -0.06 m), soil temperature profile (AV-10T; 0, -0.04, -0.1, -0.2, -0.4, -0.8, -1.2, and -1.6 m), and soil moisture profile (CS616; -0.04, -0.1, -0.2, -0.4, -0.8, -1.2, and -1.6 m). The observations included the following: air temperature and humidity (Ta_5 m; RH_5 m) (℃ and %, respectively), wind speed (Ws_10 m) (m/s), wind direction (WD_10 m) (°), air pressure (press) (hpa), precipitation (rain) (mm), 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/m2), infrared temperature (IRT_1 and IRT_2) (℃), soil heat flux (Gs_1, Gs_2 and Gs_3) (W/m2), soil temperature (Ts_0 cm, Ts_4 cm, Ts_10 cm, Ts_20 cm, Ts_40 cm, Ts_80 cm, Ts_120 cm, and Ts_160 cm) (℃), and soil moisture (Ms_4 cm, Ms_10 cm, Ms_20 cm, Ms_40 cm, Ms_80 cm, Ms_120 cm, and Ms_160 cm) (%, volumetric water content). The data processing and quality control steps were as follows: (1) The AWS data were averaged over intervals of 10 min for a total of 144 records per day. The missing data were denoted by -6999. (2) Data in duplicate records were rejected. (3) Unphysical data were rejected. (4) The data marked in red are problematic data. (5) The format of the date and time was unified, and the date and time were collected in the same column, for example, date and time: 2013-9-10 10:30. (6) Finally, the naming convention was AWS+ site no. Moreover, suspicious data were marked in red. For more information, please refer to Li et al. (2013) (for hydrometeorological observation network or sites information), Liu et al. (2011) (for data processing) in the Citation section.
LIU Shaomin, LI Xin, CHE Tao, XU Ziwei, ZHANG Yang, TAN Junlei
On 7 July 2012 (UTC+8), a CASI/SASI sensor boarded on the Y-12 aircraft was used to obtain the visible/near Infrared hyperspectral image, which is located in the observation experimental area. The relative flight altitude is 2000 meters, The wavelength of CASI and SASI is 380-1050 nm and 950-2450 nm, respectively. The spatial resolution of CASI and SASI is 1 m and 2.4 m, respectively. Through the ground sample points and atmospheric data, the data product are recorded in reflectance processed by geometric correction and atmospheric correction based on 6S model.
XIAO Qing, Wen Jianguang
This data is the ASTER fractional vegetation cover in a growth cycle observed in the Yingke Oasis Crop land. Data observations began on May 30, 2012 and ended on September 12. Original data: 1.15m resolution L1B reflectivity product of ASTER 2.Vegetation coverage data set of the artificial oasis experimental area in the middle reaches Data processing: 1.Preprocessing of ASTER reflectance products to obtain ASTER NDVI; 2.Through the NDVI-FVC nonlinear transformation form, the ASTER NDVI and the ground measured FVC are used to obtain the conversion coefficients of NDVI to FVC at different ASTER scales. 3.Apply this coefficient to the ASTER image to obtain a vegetation coverage of 15m resolution; 4.Aggregate 15m resolution ASTER FVC to get 1km ASTER FVC product
HUANG Shuai, MA Mingguo
This dataset contains the flux measurements from the Huazhaizi desert steppe station eddy covariance system (EC) in the flux observation matrix from 6 June to 15 September, 2012. The site (100.31860° E, 38.76519° N) was located in a desert surface, which is near Zhangye, Gansu Province. The elevation is 1731.00 m. The EC was installed at a height of 2.85 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 (CSAT3&Li7500) was 0.15 m. Raw data acquired at 10 Hz were processed using the Edire post-processing software (University of Edinburgh, http://www.geos.ed.ac.uk/abs/research/micromet/EdiRe/), including spike detection, lag correction of H2O/CO2 relative to the vertical wind component, sonic virtual temperature 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.
LIU Shaomin, LI Xin, XU Ziwei
This dataset contains the automatic weather station (AWS) measurements from Zhangye wetland station in the flux observation matrix from 25 June to 21 September, 2012. The site (100.44640° E, 38.97514° N) was located in a wetland surface, which is near Zhangye city, Gansu Province. The elevation is 1460 m. The installation heights and orientations of different sensors and measured quantities were as follows: air temperature and humidity (HMP45AC; 5 m and 10 m, towards north), air pressure (CS100; 2 m), rain gauge (TE525M; 10 m), wind speed (03002; 5 m and 10 m, towards north), wind direction (03002; 10 m, towards north), a four-component radiometer (NR01; 6 m, towards south), two infrared temperature sensors (SI-111; 6 m, vertically downward), soil temperature profile (109ss-L; 0, -0.02, -0.04, -0.1, -0.2, and -0.4 m), and soil heat flux (HFP01; 3 duplicates, 0.06 m). The observations included the following: air temperature and humidity (Ta_5 m and Ta_10 m, RH_5 m and RH_10 m) (℃ and %, respectively), air pressure (press, hpa), precipitation (rain, mm), wind speed (Ws_5 m and 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, Gs_2 and Gs_3, W/m^2), and soil temperature profile (Ts_0 cm, Ts_2 cm, Ts_4 cm, Ts_10 cm, Ts_20 cm, Ts_40 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.
LIU Shaomin, LI Xin, XU Ziwei
This dataset contains the flux measurements from the Daman superstation eddy covariance system (EC) at the lowest layer in the flux observation matrix from 25 May to 15 September, 2012. The site (100.37223° E, 38.85551° N) was located in a cropland (maize surface) in the Daman irrigation district, which is near Zhangye, Gansu Province. The elevation is 1556.06 m. The EC was installed at a height of 4.5 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 (CSAT3&Li7500A) was 0.17 m. Raw data acquired at 10 Hz were processed using the Edire post-processing software (University of Edinburgh, http://www.geos.ed.ac.uk/abs/research/micromet/EdiRe/), including spike detection, lag correction of H2O/CO2 relative to the vertical wind component, sonic virtual temperature 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/m2), 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.
LIU Shaomin, LI Xin, XU Ziwei
This dataset contains the flux measurements from the large aperture scintillometer (LAS) at Daman Superstation in the hydrometeorological observation network of Heihe River Basin between 15 September, 2012, and 31 December, 2013. There were two types of LASs at Daman Superstation: German BLS450 (labeled as NQ and AR) and Netherlands Kipp&zonen. The north tower was set up with the Kipp&zonen/BLS450_AR receiver and the BLS450_NQ transmitter, and the south tower was equipped with the Kipp&zonen/BLS450_AR transmitter and the BLS450_NQ receiver. BLS450_NQ has been in use since 26 September, 2012, Kipp&zonen has been in use since 23 September, 2013, and the observation period of BLS450_AR was from 15 September, 2012, to 25 July, 2013. The site (north: 100.379° E, 38.861° N; south: 100.369° E, 38.847° N) was located in Daman irrigation district, which is near Zhangye, Gansu Province. The underlying surfaces between the two towers were corn, orchard, and greenhouse. The elevation is 1556 m. The effective height of the LASs was 22.45 m, and the path length was 1854 m. The data were sampled at 5 Hz and 1 Hz intervals for BLS450 and Kipp&zonen, respectively, then averaged to 1 minute. The raw data acquired at 1 min intervals were processed and quality controlled. The data were subsequently averaged over 30 min periods, in which sensible heat flux was iteratively calculated by combining Cn2 with meteorological data according to the Monin-Obukhov similarity theory. The main quality control steps were as follows: (1) The data were rejected when Cn2 exceeded the saturated criterion (BLS450: Cn2>1.43E-13, Kipp&zonen: Cn2>1.54E-13). (2) The data were rejected when the demodulation signal was small (BLS450: Average X Intensity<1000; Kipp&zonen: Demod>-20mv). (3) The data were rejected when collected during precipitation. (4) The data were rejected if collected at night when weak turbulence occurred (u* was less than 0.1 m/s). In the iteration process, the universal functions of Thiermann and Grassl, 1992 and Andreas, 1988 were selected for BLS450 and Kipp&zonen, respectively. Several instructions were included with the released data. (1) The data were primarily obtained from BLS450_NQ measurements, and missing flux measurements from the BLS450_NQ instrument were substituted with measurements from the BLS450_AR and Kipp&zonen instrument. The missing data were denoted by -6999. Due to the problems of BLS450_NQ SPU storing and wireless transmission, large amount of data from 11 August to 17 August, 18 August to 20 August, 22 August to 24 August, 27 August to 30 August, 2013, and 1 September to 3 September, 19 September to 23 September, 2013, were not collected. (2) The dataset contained the following variables: data/time (yyyy-m-d h:mm), the structural parameter of the air refractive index (Cn2, m-2/3), and the sensible heat flux (H_LAS, W/m^2). In this dataset, a time of 0:30 corresponds to the average data for the period between 0:00 and 0:30, and the data were stored in *.xls format. Moreover, suspicious data were marked in red. For more information, please refer to Li et al. (2013) (for hydrometeorological observation network or sites information), Liu et al. (2011) (for data processing) in the Citation section.
LI Xin, CHE Tao, XU Ziwei, REN Zhiguo, TAN Junlei
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