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


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 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 (eddy covariance system of Populus forest station, 2014)

This dataset contains eddy correlation instrument observation data from the Huyanglin station downstream of the Heihe Hydrological and Meteorological Observation Network from January 1, 2014 to December 31, 2014. The site is located in Sidaoqiao, Ejin Banner, Inner Mongolia, and the underlying surface is Populus euphratica. The latitude and longitude of the observation point is 101.1236E, 41.9928N, and the altitude is 876m. The vortex correlator has a height of 22 m and a sampling frequency of 10 Hz. The ultrasonic orientation is in the north direction, and the distance between the ultrasonic wind speed temperature meter (CSAT3) and the CO2/H2O analyzer (Li7500) is 17 cm. The original observation data of the eddy correlation meter is 10 Hz, and the released data is 30 minutes of data processed by Eddypro software. The main steps of the processing include: outlier removal, time-lag correction, coordinate rotation (secondary coordinate rotation), frequency response correction, ultrasonic virtual temperature correction and density (WPL) correction, etc. At the same time, the quality evaluation of each flux value is conducted, it mainly contains atmosphere state stability test(Δst) and integrated turbulence characteristic test(ITC). The 30-min flux value output by Eddypro software was also screened: (1) data from the instrument error was eliminated; (2) data 1 h before and after precipitation was removed; (3) data from the deletion rate greater than 10% within every 30 min of the 10 Hz raw data. (4) eliminating observation data of weak turbulence at night (u* less than 0.1 m/s). The average time period of observation data is 30 minutes, 48 data per day, and the missing data is labeled -6999. Abnormal data caused by instrument drift and other reasons are marked in red. From February 21 to March 13, the data is missing due to problems in memory card and wireless transmission module. Published observations include: date/time Date/Time, wind direction Wdir(°), horizontal wind speed Wnd(m/s), lateral wind speed standard deviation Std_Uy(m/s), ultrasonic virtual temperature Tv(°C), water vapor density H2O (g/m3), carbon dioxide concentration CO2 (mg/m3), friction velocity Ustar (m/s), stability Z/L (dimensionless), sensible heat flux Hs (W/m2), latent heat flux LE (W/m2), carbon dioxide flux Fc (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 of 0:00-0:30; the data is stored in *.xls format. For hydrometeorological network or site information, please refer to Li et al. (2013). For observation data processing, please refer to Liu et al. (2011).

2019-09-12

HiWATER: Observation dataset of fractional vegetation cover by digital camera in the downstream of the Heihe River Basin (2014)

The fractional vegetation cover observation was carried out for the typical underlying surface in the lower reaches of the 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 method 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 low reaches. The land-use types including the cantaloupe, the Tamarix chinensis, the reeds, the weeds, the Karelinia caspica, the Sophora alopecuroides and so on. 3. Observation methods 3.1 Instruments and measurement method Digital photography measurement is implemented to measure the FVC. Plot positions, photographic method and data processing method are dedicatedly designed. In field measurements, a long stick with the camera mounted on one end is beneficial to conveniently measure various species of vegetation, enabling a larger area to be photographed with a smaller field of view. The stick can be used to change the camera height; a fixed-focus camera can be placed at the end of the instrument platform at the front end of the support bar, and the camera can be operated by remote control. 3.2 Photographic method The photographic method used depends on the species of vegetation and planting pattern. A long stick with the camera mounted on one end is used for the Tamarix chinensisi and reeds. For the Tamarix chinensisi and reeds, rows of more than two cycles should be included in the field of view (<30), and the side length of the image should be parallel to the row. If there are no more than two complete cycles, then information regarding row spacing and plant spacing are required. The FVC of the entire cycle, that is, the FVC of the quadrat, can be obtained from the number of rows included in the field of view. For other vegetation , the photos of FVC were obtained by directly photographing for the lower heights of the vegetation. 3.3 Method for calculating the FVC The detail method of the FVC calculation can be found in the reference below. Many methods are available to extract the FVC from digital images, and the degree of automation and the precision of identification are important factors that affect the efficiency of field measurements. This method, which is proposed by the authors, has the advantages of a simple algorithm, a high degree of automation and high precision, as well as ease of operation (see the reference). 4 Data storage The observation recorded data were stored in excel and the original FVC data were stored in photos.

2019-09-12

HiWATER: Dataset of Hydro-meteorological observation network (an automatic weather station of Sidaoqiao populus forest station, 2015)

The data set contains the observation data of meteorological elements from the Huyanglin Station, which is located along the lower reaches of the Heihe Hydro-meteorological Observation Network, and the data set covers data from January 1, 2015 to December 31, 2015. The station is located in Sidaoqiao, Dalaihubu Town, Ejina Banner, Inner Mongolia, the underlying surface is Populus euphratica forest and Tamarisk. The latitude and longitude of the observation point is 101.1239E, 41.9932N, and the altitude is 876m. The air temperature and relative humidity sensor s are erected 28 meters above the ground, facing North; the wind speed sensor is set at 28m, facing north; the four-component radiometer is installed 24 meters above the ground, facing South; two infrared thermometers are installed 24 meters above the ground, facing South, and the probe orientation is vertical downward; two photosynthetically active radiometers are installed 24 meters above the ground, facing South, and the two probes are vertically upward and downward respectively; the soil temperature probes are buried respectively at 0cm on the ground surface, 2cm and 4cm under the ground, they are located 2 meters from the meteorological tower in the North. The soil moisture sensors are buried 2cm and 4cm under the ground, 2 meters from the meteorological tower in the South. The soil heat flow boards (3 pieces) are buried 6cm under the ground, 2 meters from the meteorological tower in the South. Observed items include: air temperature and humidity (Ta_28m, RH_28m) (unit: Celsius, percentage), wind speed (WS_28m) (unit: m/s), four-component radiation (DR, UR, DLR_Cor, ULR_Cor, Rn) (unit: watt / square meter), surface radiation temperature (IRT_1, IRT_2) (unit: Celsius), soil heat flux (Gs_1, Gs_2, Gs_3) (unit: watts / square meter), soil temperature (Ts_0cm, Ts_2cm, Ts_4cm) (unit : Celsius), soil moisture (Ms_2cm, Ms_4cm) (unit: volumetric water content, percentage), up and down photosynthetically active radiation (PAR_up, PAR_down) (unit: micromoles / square meter second). Processing and quality control of observation data: (1) Ensure 144 data per day (every 10 minutes), if there is missing data, it is marked as -6999. Due to instrument adjustment, data between April 22 to April 27 of 2015 is missing. Soil heat flux data between June 19 to September 5 is missing due to sensor failure. (2) Eliminate moments with duplicate records; (3) Remove data that is significantly beyond physical meaning or beyond the measuring range of the instrument; (4) Data marked by red is debatable; (5) The formats of the date and time are uniform, and the date and time are in the same column. For example, the time is: 2015-9-10 10:30; (6) The naming rule is: AWS + site name. For hydro-meteorological network or site information, please refer to Li et al. (2013). For observation data processing, please refer to Liu et al. (2011).

2019-09-11

HiWATER: Dataset of Hydrometeorological observation network (an automatic weather station of Sidaoqiao populus 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 populus forest station between 10 July, 2013, and 31 December, 2013. The site (101.124° E, 41.993° N) was located on a populous and tamarix forest (Populus euphratica Olivier. and Tamarix chinensis Lour.) surface in the Sidaoqiao, Dalaihubu Town, Ejin Banner, Inner Mongolia Autonomous Region. The elevation is 876 m. The installation heights and orientations of different sensors and measured quantities were as follows: air temperature and humidity profile (HMP45AC; 28 m, north), wind speed profile (010C; 28 m, north), two four-component radiometer (CNR4; 6 m and 24 m, south), two infrared temperature sensors (SI-111; 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), and soil temperature profile (109ss-L; 0, -0.02 and -0.04 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), 24 m four-component radiation (DR_1, incoming shortwave radiation; UR_1, outgoing shortwave radiation; DLR_Cor_1, incoming longwave radiation; ULR_Cor_1, outgoing longwave radiation; Rn_2, net radiation) (W/m^2), 6 m four-component radiation (DR_2, incoming shortwave radiation; UR_2, outgoing shortwave radiation; DLR_Cor_2, incoming longwave radiation; ULR_Cor_2, outgoing longwave radiation; Rn_2, 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), and 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) (℃). 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 during 16 July, 2013 and 17 July, 2013 were missing during the malfunction of datalogger. The soil heat flux (G3) was missing during 20 November, 2013 and 8 December, 2013 because the wire was break by the sheep. 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.

2019-09-11

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

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

2019-09-11

HiWATER:Dataset of hydrometeorological observation network (eddy covariance system of barren-land station, 2013)

This dataset contains the flux measurements from the barren-land station eddy covariance system (EC) in the lower reaches of the Heihe hydrometeorological observation network from 10 July to 31 December, 2013. The site (101.133° E, 41.999° N) was located in the barren-land surface, Ejin Banner in Inner Mongolia. The elevation is 878 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&Li7500) 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 0.2 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 CO2/H2O gas analyzer and CF card storage problem, data during 17 July to 13 September and 6 December to 11 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.

2019-09-11

HiWATER:Dataset of Hydrometeorological observation network (an automatic weather station of desert station, 2016)

This data set includes observation data of meteorological elements in the downstream desert station of Heihe Hydrometeorological Observation Network from January 1, 2016 to December 31, 2016. The site is located in the desert beach of Ejina Banner, Inner Mongolia, and the underlying surface is 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; (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).

2019-07-18

HiWATER:Dataset of Hydro-meteorological Observation Network (An Automatic Weather Station of Sidaoqiao Barren-land Station, 2014)

The data set contains the observation data of meteorological elements from the Barren-land Station,which is located along the lower reaches of the Heihe Hydro-meteorological Observation Network, and the data set covers data from January 1, 2014 to December 31, 2014. The station is located in Sidaoqiao,Dalaihubu Town, Ejina Banner, Inner Mongolia. 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 four-component radiometer is installed 6 meters above the ground, facing South; two infrared thermometers are installed 6 meters above the ground, facing South, and the probe orientation is vertical downward; the soil temperature probes are buried respectively at 0cm on the ground surface, 2cm and 4cm under the ground, they are located 2 meters from the meteorological tower in the South; the soil moisture sensors (installed on March 15,2014) are buried 2cm and 4cm under the ground, 2 meters from the meteorological tower in the South; the soil heat flow boards (3 pieces) are buried 6cm under the ground, 2 meters from the meteorological tower in the South. Observed items include: four-component radiation (DR, UR, DLR_Cor, ULR_Cor, Rn) (unit: watt / square meter), surface radiation temperature (IRT_1, IRT_2) (unit: Celsius) , soil heat flux (Gs_1, Gs_2, Gs_3) (unit: watt / square meter), soil moisture (Ms_2cm , Ms_4cm) (unit: volumetric water content, percentage), soil temperature (Ts_0cm, Ts_2cm, Ts_4cm) (unit: Celsius). Processing and quality control of observation data: (1) Ensure 144 data per day (every 10 minutes), if there is missing data, it is marked as -6999. The surface radiation temperature IRT2 data during October 12,2014 to November 8,2014 is missing because of sensor problem; Some 2cm soil moisture data during March21 to March 29 and October 12 to November 8 is missing due to probe problem. (2) Eliminate moments with duplicate records; (3) Remove data that is significantly beyond physical meaning or beyond the measuring range of the instrument; (4) Data marked by red is debatable; (5) The formats of the date and time are uniform, and the date and time are in the same column. For example, the time is: 2014-9-10 10:30; (6) The naming rule is: AWS + site name. For hydro-meteorological network or site information, please refer to Li et al. (2013). For observation data processing, please refer to Liu et al. (2011).

2019-07-12