The No. 2 hydrological section is located at 312 Heihe River Bridge (38°59′51.71″ N, 100° 24′38.76″ E, 1485 m a.s.l.) in the middle reaches of the Heihe River Basin, Zhangye, Gansu Province. The dataset contains observations from the No.2 hydrological section from 19 June, 2012, to 24 November, 2012. This section consists of two river sections, i.e., the east section is marked as No. 1 and the west section is marked as No. 2. The width of this section is 90 meters. This section consists of a gravel bed; the cross-sectional area is unstable because of human factors. 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. 1 hydrological section is located at 213 Heihe River Bridge (38°54′43.55″ N, 100° 20′41.05″ E, 1546 m a.s.l.) in the middle reaches of the Heihe River Basin, Zhangye, Gansu Province. The dataset contains observations from the No.1 hydrological section from 13 June, 2012, to 24 November, 2012. This section consists of two river sections, i.e., the east section is marked as No. 1 and the west section is marked as No. 2. The width of this section is 330 meters. This section consists of a gravel bed; the cross-sectional area is unstable because of human factors. 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
This dataset contains the flux measurements from the Bajitan Gobi station eddy covariance system (EC) in the flux observation matrix from 31 May to 15 September, 2012. The site (100.30420° E, 38.91496° N) was located in Gobi surface, which is near Zhangye, Gansu Province. The elevation is 1562.00 m. The EC was installed at a height of 4.6 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.
LI Xin, XU Ziwei
This dataset contains the flux measurements from site No.4 eddy covariance system (EC) in the flux observation matrix from 31 May to 17 September, 2012. The site (100.35753° E, 38.87752° N) was located in a residential area in Yingke irrigation district, which is near Zhangye, Gansu Province. The elevation is 1561.87 m. The EC was installed at a height of 4.2 m (6.2 m after 19 August); 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
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
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 Huangcaogou station between 7 June, 2013, and 31 December, 2013. The site (100.731° E, 38.003° N) was located on a cold grassland surface in the Huangcaogou village, E’bao town, Qilian County, Qinghai Province. The elevation is 3137 m. The installation heights and orientations of different sensors and measured quantities were as follows: air temperature and humidity profile (HMP45D; 5 m, north), wind speed and direction profile (03001; 10 m, north), air pressure (CS100; in the tamper box on the ground), rain gauge (TE525M; 10 m), four-component radiometer (CNR1; 6 m, south), two infrared temperature sensors (IRTC3; 6 m, south, vertically downward), soil heat flux (HFT3; 3 duplicates, -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 (ECh2o-5; -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 data of wind direction were missing during 12 June, 2013 and 24 September, 2013. 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
This dataset contains the automatic weather station (AWS) measurements from site No.13 in the flux observation matrix from 6 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 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 (EC20-5; -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
The data set includes the observation data of river water level and velocity at NO.5 point in the dense runoff observation of the middle reaches of Heihe River from January 1 to April 30, 2014 and from July 18 to July 26, 2014,. The observation point is located in Heihe bridge, Banqiao Township, Linze County, Zhangye City, Gansu Province. The riverbed is sandy gravel with unstable section. The longitude and latitude of the observation point are n39 ° 15'32.41 ", E100 ° 16'33.95", with an altitude of 1398 meters and a channel width of 270 meters. In 2014, the water level was observed by sr50 ultrasonic distance meter with acquisition frequency of 30 minutes. During the observation period, the instrument failure was returned to the factory for maintenance, and the failure was not eliminated after later installation.
HE Xiaobo, LIU Shaomin, LI Xin, XU Ziwei
This dataset contains the flux measurements from the Zhangye wetland station eddy covariance system (EC) in the middle reaches of the Heihe hydrometeorological observation network from 15 September, 2012, to 21 November, 2013. The site (100.446° E, 38.975° N) was located in the desert steppe surface, near Zhangye city in Gansu Province. The elevation is 1460 m. The EC was installed at a height of 5.2 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 (Gill&Li7500A) was 0.25 m. The 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 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 0.1 m/s. There were 48 records per day, and the missing data were replaced with -6999. Suspicious data were marked in red. Due to the calibration of CO2/H2O gas analyzer and CF card storage problem, data during 28 May to 30 May, and 21 November to 31 December, 2013 were missing. 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
This dataset contains the flux measurements from the cropland eddy covariance system (EC) in the lower reaches of the Heihe hydrometeorological observation network from 14 July to 11 December, 2013. The site (101.134° E, 42.005° N) was located in the muskmelon surface, Ejin Banner in Inner Mongolia. The elevation is 875 m. The EC was installed at a height of 3.5 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&EC150) was 0 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 0.2 m/s. There were 48 records per day, and the missing data were replaced with -6999. Suspicious data were marked in red. Due to the CF card storage problem and calibration of CO2/H2O gas analyzer, data during 29 July to 19 August and 11 December to 31 December were missing. 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
This dataset contains the automatic weather station (AWS) measurements from site No.5 in the flux observation matrix from 4 June to 18 September, 2012. The site (100.35068° E, 38.87574° N) was located in a cropland (maize surface) in Yingke irrigation district, which is near Zhangye, Gansu Province. The elevation is 1567.65 m. The installation heights and orientations of different sensors and measured quantities were as follows: air temperature and humidity (HMP45C; 5 m, towards north), air pressure (CS100; 2 m), rain gauge (TE525M; 10 m), wind speed and direction (010C/020C; 10 m, towards north), a four-component radiometer (CNR1; 4 m, towards south), two infrared temperature sensors (SI-111; 4 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 (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 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
The No. 4 hydrological section is located at Wujin Heihe River Bridge (100.433° E, 39.065° N, 1431 m) in the midstream of the Heihe River Basin, Zhangye city, Gansu Province. The dataset contains recorded by the No.4 hydrological section from 10 June, 2012 to 10 August, 2012, and from 6 September, 2013 to 31 December, 2013. The width of this section is 58 meters and the cross-sectional area is unstable because of human factors. The water level was measured using an HOBO pressure range and the discharge was measured using cross-section reconnaissance by the StreamPro ADCP. The dataset includes the following parameters: water level (recorded every 30 minutes) and discharge. The missing and incorrect (outside the normal range) data were replaced with -6999. For more information, please refer to Li et al. (2013) (for hydrometeorological observation network or sites information), He et al. (2016) (for data processing) in the Citation section.
HE Xiaobo, LIU Shaomin, LI Xin, XU Ziwei
The No. 3 hydrological section is located at Railway Heihe River Bridge (100.430° E, 39.043° N, 1443 m) in the midstream of the Heihe River Basin, Zhangye city, Gansu Province. The dataset contains observations recorded by the No.3 hydrological section from 14 June, 2012, to 31 December, 2013. The width of this section is 50 meters. The water level was measured using an SR50 ultrasonic range and the discharge was measured using cross-section reconnaissance by the StreamPro ADCP. The dataset includes the following parameter: water level (recorded every 30 minutes) and discharge. The missing and incorrect (outside the normal range) data were replaced with -6999. For more information, please refer to Li et al. (2013) (for hydrometeorological observation network or sites information), He et al. (2016) (for data processing) in the Citation section.
HE Xiaobo, LIU Shaomin, LI Xin, XU Ziwei
Input and output table of Heihe River Basin in Gansu Province in 2002 and 2007, including 144 departments
DENG XiangZheng
The No. 5 hydrological section is located at Gaoya Hydrological Station (39°08′06.35″ N，100°25′58.23″ E, 1420 m a.s.l.) in the middle reaches of the Heihe River Basin, Zhangye, Gansu Province. This hydrological section is for intercomparison of flow measurement between ADCP and manual method. The dataset contains observations from the No.5 hydrological section from 10 August, 2012, to 24 November, 2012. The width of this section is 58 meters. The water level was measured using HOBO pressure 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
This dataset contains the flux measurements from site No.5 eddy covariance system (EC) in the flux observation matrix from 3 June to 18 September, 2012. The site (100.35068° E, 38.87574° N) was located in a cropland (maize surface) in Yingke irrigation district, which is near Zhangye, Gansu Province. The elevation is 1567.65 m. The EC was installed at a height of 3 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 0.17 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
This dataset contains the flux measurements from site No.16 eddy covariance system (EC) in the flux observation matrix from 6 June 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 EC was installed at a height of 4.9 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&Li7500) 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 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 the observational data that were collected by two sets of Cosmic-ray Soil Moisture Observation System (COSMOS), named crs_a and crs_b, which were installed near the Daman Superstation in the flux observation matrix from 1 June through 20 September 2012. The land cover in the footprint was maize crop, and the site was located with the cropland of the Daman Irrigation District, Zhangye, Gansu Province. Crs_a was located at 100.36975° E, 38.85385° N and 1557.16 m above sea level; Crs_b was located at 100.37225° E, 38.85557° N and 1557.16 m above sea level. The bottom of the probe was 0.5 m above the ground; the sampling interval was 1 hour. The raw COSMOS data include the following: battery (Batt, V), temperature (T, ℃), relative humidity (RH, %), air pressure (P, hPa), fast neutron counts (N1C, counts per hour), thermal neutron counts (N2C, counts per hour), sample time of fast neutrons (N1ET, s), and sample time of thermal neutrons (N2ET, s). The distributed data include the following variables: Date, Time, P, N1C, N1C_cor (corrected fast neutron counts) and VWC (volume soil moisture, %), which were processed as follows: 1) Quality control Data were removed and replaced by -6999 when (a) the battery voltage was less than 11.8 V, (b) the relative humidity was greater than 80% inside the probe box, (c) the counting data were not of one-hour duration and (d) then neutron count differed from the previous value by more than 20%. 2) Air pressure correction An air pressure correction was applied to the quality-controlled raw data according to the equation contained in the equipment manual. The procedure was previously described by Jiao et al. (2013) and Zreda et al. (2012). 3) Calibration After the quality control and corrections were applied, soil moisture was calculated using the equation in Desilets et al. (2010), where N0 is the neutron counts above dry soil and the other variables are fitted constants that define the shape of the calibration function. Here, the parameter N0 must be calibrated using the in situ observed soil moisture within the footprint. This procedure was previously described by Jiao et al. (2013) and Zreda et al. (2012) 4) Computing the soil moisture Based on the calibrated N0 and corrected N1C, the hourly soil moisture was computed using the equation from the equipment manual. This procedure was previously described by Jiao et al, (2013) and Zreda et al. (2012) For more information, please refer to Liu et al. (2016) (for multi-scale observation experiment or sites information), Zhu et al. (2015) (for data processing) in the Citation section.
LIU Shaomin, ZHU Zhongli, XU Ziwei, LI Xin
This dataset contains the flux measurements from site No.3 eddy covariance system (EC) in the flux observation matrix from 3 June to 18 September, 2012. The site (100.37634° E, 38.89053° N) was located in a cropland (maize surface) in Yingke irrigation district, which is near Zhangye, Gansu Province. The elevation is 1543.05 m. The EC was installed at 3.8 m high, and sampled at 10 Hz. The EC was installed at a height of 3.8 m; the sampling rate was 10 Hz. The sonic anemometer faced north, and the separation distance between the sonic anemometer and the CO2/H2O gas analyzer (Gill&Li7500A) was 0.2 m. Raw data acquired at 10 Hz were processed using the Eddypro post-processing software (Li-Cor Company, http://www.licor.com/env/products/ eddy_covariance/software.html), including spike detection, lag correction of H2O/CO2 relative to the vertical wind component, sonic virtual temperature correction, angle of attack correction, coordinate rotation (2-D rotation), corrections for density fluctuation (Webb-Pearman-Leuning correction), and frequency response correction. The EC data were subsequently averaged over 30 min periods. Moreover, the observation data quality was divided into three classes according to the quality assessment method of stationarity (Δst) and the integral turbulent characteristics test (ITC), which was proposed by Foken and Wichura [1996]: class 1 (level 0: Δst<30 and ITC<30), class 2 (level 1: Δst<100 and ITC<100), and class 3 (level 2: Δst>100 and ITC>100), representing high-, medium-, and low-quality data, respectively. In addition to the above processing steps, the half-hourly flux data were screened in a four-step procedure: (1) data from periods of sensor malfunction were rejected; (2) data before or after 1 h of precipitation were rejected; (3) incomplete 30 min data were rejected when the missing data constituted more than 3% of the 30 min raw record; and (4) data were rejected at night when the friction velocity (u*) was less than 0.1 m/s. There were 48 records per day; the missing data were replaced with -6999. Moreover, suspicious data were marked in red. The released data contained the following variables: data/time, wind direction (Wdir, °), wind speed (Wnd, m/s), the standard deviation of the lateral wind (Std_Uy, m/s), virtual temperature (Tv, ℃), H2O mass density (H2O, g/m^3), CO2 mass density (CO2, mg/m^3), friction velocity (ustar, m/s), stability (z/L), sensible heat flux (Hs, W/m^2), latent heat flux (LE, W/m^2), carbon dioxide flux (Fc, mg/ (m^2s)), quality assessment of the sensible heat flux (QA_Hs), quality assessment of the latent heat flux (QA_LE), and quality assessment of the carbon flux (QA_Fc). In this dataset, the time of 0:30 corresponds to the average data for the period between 0:00 and 0:30; the data were stored in *.xlsx format. For more information, please refer to Liu et al. (2016) (for multi-scale observation experiment or sites information), Xu et al. (2013) (for data processing) in the Citation section.
LIU Shaomin, LI Xin, XU Ziwei
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