Current Browsing: the natural oasis eco-hydrology experimental area in the lower reaches


HiWATER: Dataset of hydro-meteorological observation network (eddy covariance system of Barren-land Station, 2015)

The data set contains eddy covariance System observation data of Barren-land Station which is located in the lower reaches of the Heihe Hydro-meteorological Observation Network from January 1, 2015 to December 31, 2015. The site is located in Sidaoqiao, Ejina Banner, Inner Mongolia, and the underlying surface is barren land. The latitude and longitude of the observation point is 101.1326E, 41.9993N, and the altitude is 878m. The mount height of the Eddy Covariance System is 3.5 m, the sampling frequency is 10 Hz, the ultrasonic orientation is north, and the distance between the ultrasonic wind speed temperature meter (CSAT3) and the CO2/H2O analyzer (Li7500) is 15 cm. 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 hydro-meteorological network or station information, please refer to Li et al. (2013). For observation data processing, please refer to Liu et al. (2011).

2019-09-15

HiWATER: PROBA CHRIS dataset

This dataset includes seven scenes; two scenes cover the Dayekou catchment on (yy-mm-dd) 2012-08-19 and 2012-08-28, one scene covers the airport desert experimental site on 2012-06-29, three scenes cover the Daman foci experimental area on 2012-06-21, 2012-07-10 and 2012-08-27, and one scene covers the natural oasis eco-hydrology experimental area in the lower reaches of the Heihe River Basin. The data were all acquired around 9:00 (BJT) of full swath mode with data product of Level 1A. PROBA CHRIS dataset was acquired through the European Space Agency (ESA)-Ministry of Science and Technology of China (MOST) Cooperative Dragon 2 (project ID: 5322) and Dragon 3 (project ID: 10649) Programme.

2019-09-15

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

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.

2019-09-15

HiWATER: Dataset of hydrometeorological observation network (an automatic weather station of desert station, 2017)

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).

2019-09-15

HiWATER: Dataset of hydrometeorological observation network (an observation system of meteorological elements gradient of Sidaoqiao superstation, 2013)

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.

2019-09-15

HiWATER: Dataset of hydrometeorological observation network (an automatic weather station of Sidaoqiao barren-land 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 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.

2019-09-15

HiWATER: Dataset of hydrometeorological observation network (eddy covariance system of Sidaoqiao superstation, 2013)

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.

2019-09-15

HiWATER: Observation dataset of spectral reflectance in the downstream of the Heihe River Basin

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.

2019-09-15

HiWATER: Dataset of hydrometeorological observation network (an automatic weather station of Sidaoqiao mixed forest 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 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.

2019-09-15

HiWATER: Dataset of hydrometeorological observation network (an observation system of Meteorological elements gradient of Sidaoqiao Superstation, 2014)

This dataset contains the data of the meteorological element gradient observation system of the Sidaoqiao superstation downstream of the Heihe Hydrometeorological Observation Network from January 1, 2014 to December 31, 2014. The site is located in Sidaoqiao, Dalaihu Town, Ejin Banner, Inner Mongolia. The underlying surface is Tamarix. The latitude and longitude of the observation point is 101.1374E, 42.0012N, and the altitude is 873m. The air temperature, relative humidity and wind speed sensors are respectively set at 5m, 7m, 10m, 15m, 20m and 28m, with 6 layers facing the north; the wind direction sensor is set at 15m, facing the north; the barometer is installed in the waterproof box. The tipping bucket rain gauge is installed at 28m; the four-component radiometer is installed at 10m, facing south; two infrared thermometers are installed at 10m, facing south, the probe orientation is vertically downward; two photosynthetically active radiometers are installed At 10m, facing south, and the probe is vertically upward and downward respectively; the soil moisture sensor is installed 2m on the south side of the tower body, and the soil heat flow plates (self-correcting type) (3 pieces) are buried in turn in the ground 6cm deep; The average soil temperature sensor TCAV is buried in the ground 2cm, 4cm; the soil temperature probe is buried in the ground surface 0cm and underground 2cm, 4cm, 10cm, 20cm, 40cm, 80cm, 120cm and 160cm; soil moisture sensors are buried in the underground 2cm, 4cm, 10cm, 20cm, 40cm, 80cm, 120cm and 160cm. Observed items include: wind speed (WS_5m, WS_7m, WS_10m, WS_15m, WS_20m, WS_28m) (unit: m/s), wind direction (WD_15m) (unit: degree), air temperature and humidity (Ta_5m, Ta_7m, Ta_10m, Ta_15m, Ta_20m, Ta_28m and RH_5m, RH_7m, RH_10m, RH_15m, RH_20m, RH_28m) (unit: centigrade, percentage), pressure (unit: hectopascal), precipitation (Rain) (unit: mm), four-component radiation (DR, UR, DLR_Cor, ULR_Cor, Rn) (unit: watts/square meter), surface radiation temperature (IRT_1, IRT_2) (unit: centigrade), up and down photosynthetically active radiation (PAR_U_up, PAR_U_down) (unit: micromol/square Msec), average soil temperature (TCAV) (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_80cm) , Ms_120cm, Ms_160cm) (unit: volumetric water content, percentage), soil temperature (Ts_0cm, Ts_2cm, Ts_4cm, Ts_10cm, Ts_20cm, Ts_40cm, Ts_80cm, Ts_120cm, Ts_160cm) (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 8, 2014 to November 8, due to the sensor problems, the data is missing; on May 9, 2014, the soil moisture probe was re-buried, and the data before and after is inconsistent; (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: 2014-9-10 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).

2019-09-15