HiWATER: The MUlti-Scale Observation EXperiment on Evapotranspiration over heterogeneous land surfaces 2012 (MUSOEXE-12)-dataset of flux observation matrix (No.13 eddy covariance system)

This dataset contains the flux measurements from the No.13 site eddy covariance system (EC) in the flux observation matrix from 27 May to 20 September, 2012. The site (100.37852° E, 38.86074° N) was located in a cropland (maize surface) in Daman irrigation district, which is near Zhangye, Gansu Province. The elevation is 1550.73 m. The EC was installed at a height of 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 0.18 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.

WATER: Dataset of airborne LiDAR mission in the Dayekou watershed flight zone on Jun. 23, 2008

The dataset of airborne LiDAR mission in the Dayekou watershed flight zone on Jun. 23, 2008 included peak pulse data (*.LAS), full waveform data (.lgc), CCD photos, DEM, DSM and DOM. The flight routes were as follows: {| ! flight route ! startpoint lat ! startpoint lon ! endpoint lat ! endpoint lon ! altitude (m) ! length (km) ! photos |- | 8 || 38°32′52.25″ || 100°12′35.26″ || 38°30′25.65″ || 100°18′31.76″ || 3650 || 9.7 || 34 |- | 9 || 38°32′57.99″ || 100°12′39.09″ || 38°30′31.59″ || 100°18′35.14″ || 3650 || 9.7 || 34 |- | 10 || 38°33′03.74″ || 100°12′42.91″ || 38°30′40.25″ || 100°18′31.88″ || 3650 || 9.5 || 34 |- | 11 || 38°33′12.80″ || 100°12′38.68″ || 38°30′46.10″ || 100°18′35.47″ || 3650 || 9.8 || 35 |- | 12 || 38°33′18.55″ || 100°12′42.51″ || 38°30′54.86″ || 100°18′31.99″ || 3650 || 9.6 || 35 |- | 13 || 38°33′24.30″ || 100°12′46.34″ || 38°31′00.95″ || 100°18′34.98″ || 3650 || 9.5 || 36 |- | 14 || 38°33′30.05″ || 100°12′50.16″ || 38°31′09.54″ || 100°18′31.92″ || 3650 || 9.3 || 35 |- | 15 || 38°33′35.80″ || 100°12′53.99″ || 38°31′15.47″ || 100°18′35.29″ || 3750 || 9.3 || 35 |- | 16 || 38°33′41.55″ || 100°12′57.82″ || 38°31′21.66″ || 100°18′38.05″ || 3750 || 9.3 || 35 |- | 17 || 38°33′47.30″ || 100°13′01.65″ || 38°31′27.25″ || 100°18′42.27″ || 3750 || 9.3 || 35 |- | 19 || 38°34′02.11″ || 100°13′01.25″ || 38°31′45.61″ || 100°18′33.27″ || 3750 || 9.1 || 45 |- | 20 || 38°34′07.86″ || 100°13′05.07″ || 38°31′51.54″ || 100°18′36.64″ || 3750 || 9.1 || 45 |- | 21 || 38°34′13.61″ || 100°13′08.90″ || 38°32′00.12″ || 100°18′33.60″ || 3750 || 8.9 || 45 |- | 22 || 38°34′19.36″ || 100°13′12.73″ || 38°32′05.45″ || 100°18′38.44″ || 3750 || 8.9 || 45 |- | 23 || 38°34′25.10″ || 100°13′16.56″ || 38°32′14.72″ || 100°18′33.72″ || 3750 || 8.7 || 45 |- | 24 || 38°34′30.85″ || 100°13′20.39″ || 38°32′20.48″ || 100°18′37.52″ || 3750 || 8.7 || 45 |- | 25 || 38°34′36.60″ || 100°13′24.22″ || 38°32′26.24″ || 100°18′41.32″ || 3750 || 8.7 || 45 |- | 26 || 38°34′45.66″ || 100°13′19.98″ || 38°32′31.98″ || 100°18′45.15″ || 3750 || 8.9 || 45 |}

HiWATER: Dataset of hydrometeorological observation network (eddy covariance system of Sidaoqiao superstation, 2017)

The data set contains the observation data of the eddy covariance system of Sidaoqiao superstation which is located along the lower reaches of the Heihe Hydrometeorological observation network, and the data set covers data from January 1, 2017 to December 31, 2017. The station is located in Sidao Bridge, Ejina Banner, Inner Mongolia, and the underlying surface is Tamarix. The latitude and longitude of the observation station is 101.1374E, 42.0012N, and the altitude is 873 m. The height of the eddy covariance system is 8 meters, the sampling frequency is 10Hz, the ultrasonic orientation is positive north, and the distance between the ultrasonic wind speed and temperature monitor (CSAT3) and the CO2/H2O analyzer (Li7500) is 15cm. The original observation data of the eddy covariance system is 10 Hz, and the released data is a 30-minute data processed by Eddypro software. The main steps of the processing include: outlier eliminating, delay time correction, coordinates rotation (secondary coordinates rotation), frequency response correction, ultrasonic virtual temperature correction and density (WPL) correction, etc. Meanwhile, the quality evaluation of each flux value was performed,mainly includes atmospheric stability (Δst) test and turbulence similarity (ITC) test. The 30-min flux value output of Eddypro software was also screened: (1) Data from the instrument error was eliminated; (2) Data obtained with one hour before and after precipitation was removed; (3) Data with a deletion rate greater than 10% of the 10 Hz raw data every 30 minutes was eliminated; (4) Observation data of weak turbulence at night (u* less than 0.1 m/s) was excluded. The average period of observation data is 30 minutes, 48 data per day, and the missing data is marked as -6999. The data was missing due to Li7500 calibration of the eddy system on April 7 and 8; the suspicious data caused by instrument drift and other reasons was marked by red fonts. Published observation data include: date/time Date/Time, wind direction(°), horizontal wind speed(m/s), lateral wind speed standard deviation(m/s), ultrasonic virtual temperature (°C), water vapor density (g/m3), carbon dioxide concentration(mg/m3), friction velocity (m/s), length (m), sensible heat flux(W/m2), latent heat flux (W/m2), carbon dioxide flux (mg/(m2s)), sensible heat flux quality identification QA_Hs, latent heat flux quality identification QA_LE, carbon dioxide flux quality identification QA_Fc. The quality identification of sensible heat, latent heat, and carbon dioxide flux is divided into three levels (quality mark 0: (Δst <30, ITC<30); 1: (Δst <100, ITC<100); the rest is 2). The meaning of the data time, such as 0:30 represents an average data of 0:00-0:30; the data is stored in *.xls format. For hydrometeorological network or station information, please refer to Li et al. (2013). For observation data processing, please refer to Liu et al. (2011).

HiWATER: Dataset of hydro-meteorological observation network (automatic weather station of Huazhaizi Desert Steppe Station, 2014)

The data set contains the observation data of meteorological elements from the Huazhaizi Desert Steppe Station,,which is located along the middle reaches of the Heihe Hydro-meteorological Observation Network, and the data set covers data from January 1, 2014 to December 31, 2014. The station is located in Huazhaizi of Zhangye, Gansu Province. The underlying surface is piedmont desert. The latitude and longitude of the observation point is100.3186E, 38.7652N, and the altitude is 1731m. The observation instruments in Huazhaizi are installed respectively by Beijing Normal University and Cold and Arid Regions Environmental and Engineering Research Institute, Chinese Academy of Sciences. The observation instruments of Beijing Normal University are: two infrared thermometers installed 24 meters above the ground, facing south, with the probe vertical downward; soil temperature probes buried respectively at 0cm on the ground surface, 2cm、4cm、20cm、60cm and 100cmunder the ground; soil moisture sensors buried 4cm、20cm and 100cm under the ground; soil heat flow boards (3 pieces) buried 6cm under the ground. The observation instruments of Cold and Arid Regions Environmental and Engineering Research Institute are: wind speed sensor erected 10.48m、0.98m and 2.99m above the ground(3 layers),facing North; wind direction sensor erected 4 meters above the ground; air temperature and relative humidity sensors erected 1m and 2.99m above the ground(2 layers),facing North East; four-component radiometer installed 2.5 meters above the ground, facing South; barometric pressure sensor placed in the water-proof box; tipping bucket rain gauge installed 0.7 meter above the ground; soil temperature probes buried 4cm、10cm、18cm、26cm、34cm、42cm and 50cmunder the ground; soil moisture sensors buried 2cm、10cm、18cm、26cm、34cm、42cm、50cm and 58cm under the ground, 3 sensors buried at 2cm. The specific observation elements are as follows: (1) Observation elements of Beijing Normal University : surface radiation temperature (IRT_1, IRT_2) (unit: Celsius), soil heat flux (Gs_1, Gs_2, Gs_3) (unit: watt / square meter), soil moisture (Ms_4cm, Ms_20cm, Ms_100cm) (unit: percentage) and soil temperature (Ts_0cm, Ts_2cm, Ts_4cm, Ts_20cm, Ts_60cm, Ts_100cm) (unit: Celsius). (2) Observation elements of Cold and Arid Regions Environmental and Engineering Research Institute: wind speed (WS_0.48m, WS_0.98m, WS_2.99m) (unit: m/s), wind direction (WD_4m) (unit: degree), four-component radiation (DR, UR , DLR_Cor, ULR_Cor) (unit: watt / square meter), air temperature and humidity (Ta_1m, Ta_2.99m, RH_1m, RH_2.99m) (unit: Celsius, percentage), air pressure (Press) (unit: hectopascal), precipitation (unit: mm), soil temperature (Ts_4cm, Ts_10cm, Ts_18cm, Ts_26cm, Ts_34cm, Ts_42cm, Ts_50cm) (unit: Celsius), soil moisture (Ms_2cm_1, Ms_2cm_2, Ms_2cm_3, Ms_10cm, Ms_18cm, Ms_26cm, Ms_34cm, Ms_42cm, Ms_50cm, Ms_58cm) (unit: volumetric water content, percentage). The observation elements of Beijing Normal University are 10-minute average data, and the observation elements of Cold and Arid Regions Environmental and Engineering Research Institute are 30-minute average data. Processing and quality control of observation data: (1) Ensure 144 data of Beijing Normal University per day (every 10 minutes), and 48 data of Cold and Arid Regions Environmental and Engineering Research Institute per day (every 30 minutes). If there is missing data, it is marked as -6999. Data between 12.11-12.31,2014 is missing due to storage problems. (2) Eliminate moments with duplicate records; (3) Remove data that is significantly beyond physical meaning or beyond the measuring range of the instrument; (4) Data marked by red is debatable; (5) The formats of the date and time are uniform, and the date and time are in the same column. For example, the time is: 2014-6-10 10:30; (6) The naming rule is: AWS + site name. For hydro-meteorological network or site information, please refer to Li et al. (2013). For observation data processing, please refer to Liu et al. (2011).