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HiWATER: Dataset of hydrometeorological observation network (automatic weather station of Shenshawo sandy desert station, 2015)

This data set includes observation data of meteorological elements in the Shenshawo Desert Station in the middle of the Heihe Hydrometeorological Observation Network from January 1, 2015 to April 12, 2015. The site is located in Shenshawo, Zhangye City, Gansu Province, and the underlying surface is desert. The latitude and longitude of the observation point is 100.4933E, 38.7892N, and the altitude is 1594m. 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, and among them a repetitive soil moisture sensor (Ms_40cm_2) was embedded in the underground 40cm on May 6, 2014.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 March 19, 2015 to March 26, due to the collector problem, the data is missing; (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: 2015-6-10 10:30; (6) the naming rules are: AWS+ site name. The station was dismantled after April 12. For hydrometeorological network or site information, please refer to Li et al. (2013). For observation data processing, please refer to Liu et al. (2011).

2019-09-14

HiWATER: Dataset of hydrometeorological observation network (No.1 runoff observation system of 213 bridge on the Heihe River, 2013)

The No. 1 hydrological section is located at 213 Heihe River Bridge (100.345° E, 38.912° N, 1546 m) in the midstream of the Heihe River Basin, Zhangye city, Gansu Province. The dataset contains observations recorded by the No.1 hydrological section from 13 June, 2012, to 6 September, 2013. This section consists of two river sections, i.e., the east section,which is denoted as No. 1 and the west section, which is denoted as No. 2. The width of this section is 330 meters and consists of a gravel bed; the cross-sectional area is unstable because of human factors. 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 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.

2019-09-14

HiWATER: The multi-scale observation experiment on evapotranspiration over heterogeneous land surfaces 2012 (MUSOEXE-12)-Dataset of flux observation matrix (No.11 eddy covariance system)

This dataset contains the flux measurements from site No.11 eddy covariance system (EC) in the flux observation matrix from May 29 to September 18, 2012. The site (100.34197° E, 38.86991° N) was located in a cropland (maize surface) in Yingke irrigation district, which is near Zhangye, Gansu Province. The elevation is 1575.65 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.

2019-09-14

HiWATER: The multi-scale observation experiment on evapotranspiration over heterogeneous land surfaces 2012 (MUSOEXE-12)-Dataset of flux observation matrix(automatic meteorological station of No.5)

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.

2019-09-14

HiWATER: Dataset of hydrometeorological observation network (automatic weather station of Jingyangling station, 2013)

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 Jingyangling station between 15 August, 2013, and 31 December, 2013. The site (101.116° E, 37.838° N) was located on a cold meadow surface in the Jingyangling, Qilian County, Qinghai Province. The elevation is 3750 m. The installation heights and orientations of different sensors and measured quantities were as follows: air temperature and humidity profile (HMP45AC; 5 m, north), wind speed and direction profile (034B; 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 (SI-111; 6 m, south, vertically downward), soil heat flux (HFP01; 3 duplicates, -0.06 m), soil temperature profile (109-L; 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/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_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 radiation data were missing because of wiring 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.

2019-09-14

HiWATER: Dataset of hydrometeorological observation network (eddy covariance system of mixed forest station, 2013)

This dataset contains the flux measurements from the mixed forest station eddy covariance system (EC) in the lower reaches of the Heihe hydrometeorological observation network from 12 July to 31 December, 2013. The site (101.134° E, 41.990° N) was located in the Populus and Tamarix surface, Ejin Banner in Inner Mongolia. The elevation is 874 m. The EC was installed at a height of 22 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&Li7500) was 0.17 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 malfunction of sonic anemometer, data during 16 August to 17 September 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.

2019-09-14

HiWATER: Dataset of hydrometeorological observation network (automatic weather station of Zhangye wetland station, 2013)

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 Daman Superstation between 22 September, 2012, and 31 December, 2013. The site (100.4464° E, 38.9751° N) was located on a wetland (reed surface) in Zhangye National Wetland Park, 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 profile (HMP45AC; 5 and 10 m, north), wind speed profile (03002; 5 and 10 m, north), wind direction profile (03002; 10 m, north), air pressure (CS100; 2 m), rain gauge (TE525M; 10 m), four-component radiometer (CNR1; 6 m, south), two infrared temperature sensors (SI-111; 6 m, south, vertically downward), soil heat flux (HFP01; 3 duplicates, -0.06 m), soil temperature profile (109ss-L; 0, -0.02, -0.04, -0.1, -0.2 and -0.4 m), and four photosynthetically active radiation (PQS-1; install on 28 July, 2013, two above the plants, 6 m, south, one vertically downward and one vertically upward; two below the plants, 0.25 m, south, one vertically downward and one vertically upward). 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 and Ts_40 cm) (℃), on the plants photosynthetically active radiation of upward and downward (PAR_U_up and PAR_U_down) (μmol/ (s m^-2)), and below the plants photosynthetically active radiation of upward and downward (PAR_D_up and PAR_D_down) (μmol/ (s m^-2)). 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 10 May, 2013 and 30 May, 2013 because of datalogger malfunction; the wind speed data were missing during 1 September, 2013 and 5 September, 2013 because of sensor malfunction. 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.

2019-09-14

HiWATER: Dataset of leaf area index by LAI2200 in the lower reaches of the Heihe River Basin

LAI observation was carried out for the typical underlying surface in the lower reaches of Heihe River Basin during the aviation flight experiment in 2014. The observation started on 24 July, 2014 and finished on 1 August, 2014. 1. Observation time On days of 24 July, 27 July, 30 July, 31 July and 1 August, 2014 2. Samples and observation methods Large areas with homogeneous vegetation (greater than 100 m * 100 m) were chosen as the observation samples. And forty field samples were selected according to the characteristics of vegetation distribution in the downstream. The land-use types including the cantaloupe, the Tamarix chinensis, the reeds, the weeds, the Karelinia caspica, the Sophora alopecuroides and so on. LAI data were calculated according to the transmittance derived from an A value (above-canopy readings) and four B values (below readings). More than two LAI values were obtained for each sample. At the same time, the heights of the vegetation in each sample were measured. 3. Observation instrument LAI 2200 4. Data storage The observation recorded data were stored in excel and the original LAI data were stored in txt files.

2019-09-13

HiWATER: Dataset of hydrometeorological observation network (No.4 runoff observation system of Wujing bridge on the Heihe River, 2013)

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.

2019-09-13

HiWATER: Dataset of hydrometeorological observation network (No.3 runoff observation system of Railway bridge on the Heihe River, 2014)

This dataset contains data on river water level and flow velocity at No.3 in the intensive runoff observation in the middle reaches of Heihe River runoff from July 28, 2014 to December 31, 2014. The observation point is located at Heihe Bridge, Lan-Xin Railway, Zhangye City, Gansu Province. The riverbed is gravel and the section is stable. The latitude and longitude of the observation point is N39°2'33.08", E100°25'49.42", the altitude is 1443 meters, and the river channel width is 50 meters. The water level observation is measured by SR50 ultrasonic range finder with a frequency of 60 minutes. The flow profile observation is conducted by StreamPro micro ADCP. The data declaration includes the following two parts: Water level observation, the observation frequency is 60 minutes, unit (cm); data covering time period from July 28, 2014 to December 31, 2014; Flow observation, unit (m3); monitoring flow and obtaining water level flow curve according to different water levels. The process of the runoff changing is obtained by observing the water level process. The missing data is uniformly represented by the string -6999. For hydrometeorological network or site information, please refer to Li et al. (2013). For observation data processing, please refer to He et al. (2016).

2019-09-13