Current Browsing: the artificial oasis experimental area in the middle reaches


HiWATER: The multi-scale Observation experiment on evapotranspiration over heterogeneous land surfaces (MUSOEXE-12)-Dataset of flux observation matrix (No.16 eddy covariance system) (2012)

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.

2020-06-29

HiWATER: The multi-scale observation experiment on evapotranspiration over heterogeneous land surfaces 2012 (MUSOEXE-12)-dataset of flux observation matrix (No.7 eddy covariance system )

This dataset contains the flux measurements from site No.7 eddy covariance system (EC) in the flux observation matrix from 29 May to 18 September, 2012. The site (100.36521° E, 38.87676° N) was located in a cropland (maize surface) in Yingke irrigation district, which is near Zhangye, Gansu Province. The elevation is 1556.39 m. 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 (CSAT3&Li7500A) 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.

2020-06-29

HiWATER: Dataset of fractional vegetation cover over the midstream of Heihe River Basin (2012.05.25-09.14)

This dataset is the Fractional Vegetation Cover observation in the artificial oasis experimental region of the middle stream of the Heihe River Basin. The observations lasted for a vegetation growth cycle from May 2012 to September 2012 (UTC+8). Instruments and measurement method: Digital photography measurement is implemented to measure the FVC. Plot positions, photographic method and data processing method are dedicatedly designed. Details are described in the following: 0. 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. 1. For row crop like corn, the plot is set to be 10×10 m2, and for the orchard, plot scale is 30×30 m2. Shoot 9 times along two perpendicularly crossed rectangular-belt transects. The picture generated of each time is used to calculate a FVC value. “True FVC” of the plot is then acquired as the average of these 9 FVC values. 2. The photographic method used depends on the species of vegetation and planting pattern: Low crops (<2 m) in rows in a situation with a small field of view (<30 ), rows of more than two cycles should be included in the field of view, 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. 3. High vegetation in rows (>2 m) Through the top-down photography of the low vegetation underneath the crown and the bottom-up photography beneath the tree crown, the FVC within the crown projection area can be obtained by weighting the FVC obtained from the two images. Next, the low vegetation between the trees is photographed, and the FVC that does not lie within the crown projection area is calculated. Finally, the average area of the tree crown is obtained using the tree crown projection method. The ratio of the crown projection area to the area outside the projection is calculated based on row spacing, and the FVC of the quadrat is obtained by weighting. 4. FVC extraction from the classification of digital images. 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.

2020-06-19

HiWATER:Landsat ETM+ dataset (2012)

This dataset includes five scenes, covering the artificial oasis eco-hydrology experimental area of the Heihe River Basin, which were acquired on (yy-mm-dd) 2012-04-05, 2012-04-21, 2012-05-07, 2012-06-24, 2012-07-10. The data were all acquired around 11:50 (BJT) with data product of Level 2. Landsat ETM+ dataset was downloaded from http://glovis.usgs.gov/.

2020-05-28

HiWATER: Radarsat-2 dataset on July. 06, 2012

This dataset includes one scene acquired on (yy-mm-dd hh:mm, BJT) 2012-07-06 06:30, covering the artificial oasis eco-hydrology experimental area of the Heihe River Basin. This datum was acquired at Stripmap-Quad mode with product level of SLC, and this image includes VV, VH, HH and HV polarization with a spatial resolution of 8 m. Radarsat-2 dataset was acquired from the Institute of Remote Sensing and Digital Earth of Chinese Academy of Sciences (Courtesy: Dr. Chen Quan).

2020-05-28

HiWATER: Dataset of hydrometeorological observation network (eddy covariance system of Bajitan Gobi desert station, 2013)

This dataset contains the flux measurements from the Bajitan Gobi station eddy covariance system (EC) in the middle reaches of the Heihe hydrometeorological observation network from 18 September, 2012, to 31 December, 2013. The site (100.304° E, 38.915° N) was located in the Gobi surface, near Zhangye city in Gansu Province. The elevation is 1562 m. The EC was installed at a height of 4.6 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 0.1 m/s. There were 48 records per day, and the missing data were replaced with -6999. Suspicious data were marked in red. Data during 22 May to 13 June, 2013 were missing due to malfunction of data logger. 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 Liu et al. (2018) (for hydrometeorological observation network or sites information), Liu et al. (2011) (for data processing) in the Citation section.

2020-04-10

HiWATER: Dataset of hydrometeorological observation network (eddy covariance system of Bajitan Gobi desert station, 2014)

This data set contains eddy correlativity observation data from January 1, 2014 to December 31, 2014 at the gobi station in baji tan, middle reaches of the heihe hydrometeorological observation network.The station is located in zhangye city, gansu province.The longitude and latitude of the observation point are 100.30420E, 38.91496N and 1562.00m above sea level.The rack height of the vortex correlative is 4.6m, the sampling frequency is 10Hz, the ultrasonic orientation is due north, and the distance between the ultrasonic anemometer (CSAT3) and the CO2/H2O analyzer (Li7500) is 15cm. The original observation data of the vortex correlativity instrument is 10Hz, and the published data is the 30-minute data processed by Eddypro software. The main processing steps include: outliers, delay time correction, coordinate rotation (quadratic coordinate rotation), frequency response correction, ultrasonic virtual temperature correction and density (WPL) correction.Quality assessment for each intercompared to at the same time, mainly is the atmospheric stability (Δ st) and turbulent characteristics of similarity (ITC) test.The 30min pass value output by Eddypro software was also screened :(1) data when instrument error was eliminated;(2) data of 1h before and after precipitation are excluded;(3) remove the data with a missing rate of more than 10% in the original 10Hz data within every 30 minutes;(4) the observation data of weak turbulence at night (u* less than 0.1m/s) were excluded.The average observation period was 30 minutes, 48 data per day, and the missing data was marked as -6999.Suspicious data caused by instrument drift, etc., shall be marked in red font.On March 2, solstice, March 31, October 13, solstice, November 14, and December 12, solstice, December 31, 10Hz data was missing due to the memory card storage data problems, which were replaced by the 30-min flux data output by the collector. The published observational data include:Date/Time for the Date/Time, wind Wdir (°), Wnd horizontal wind speed (m/s), standard deviation Std_Uy lateral wind speed (m/s), ultrasonic virtual temperature Tv (℃), the 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)), the quality of the sensible heat flux identifier QA_Hs, the quality of the latent heat flux identifier QA_LE,Quality indicator for co2 flux QA_Fc.The quality of the sensible heat and latent heat, carbon dioxide flux identification is divided into three (quality id 0: (Δ st < 30, the ITC < 30);1: (Δ st < 100, ITC < 100);The rest is 2).The meaning of data time, such as 0:30 represents the average of 0:00-0:30;The data is stored in *.xls format. For information of hydrometeorological network or station, please refer to Liu et al.(2018), and for observation data processing, please refer to Liu et al.(2011).

2020-04-10

HiWATER: Dataset of hydrometeorological observation network (automatic weather station of Bajitan Gobi desert station, 2013)

This dataset includes data recorded by the Hydrometeorological observation network obtained from the automatic weather station (AWS) at the Bajitan Gobi desert station between 21 September, 2012, and 31 December, 2013. The site (100.304° E, 38.915° N) was located on a Gobi desert surface in the Bajitan, which is near Zhangye city, Gansu Province. The elevation is 1562 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 (010C; 5 and 10 m, north), wind direction profile (020C; 10 m, north), air pressure (PTB110; 2 m), 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, 2 m in the south), soil temperature profile (AV-10T; 0, -0.02, -0.04, -0.1, -0.2, -0.4, -0.6, and -1 m), and soil moisture profile (ECh2o-5; -0.02, -0.04, -0.1, -0.2, -0.4, -0.6 and -1 m). 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, 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: 2013-6-10 10:30. (6) Finally, the naming convention was AWS+ site no. Moreover, suspicious data were marked in red. For more information, please refer to Liu et al. (2018) (for hydrometeorological observation network or sites information), Liu et al. (2011) (for data processing) in the Citation section.

2020-04-10

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

The data set contains the observation data of meteorological elements from the Bajitan Gobi Desert Station, which is located along the middle reaches of the Heihe Hydro-meteorological Observation Network, and the data set covers data from January 1, 2014 to December 31, 2014. The station is located in Bajitan, West Zhangye City, Gansu Province, the underlying surface is Gobi. The latitude and longitude of the observation point is 100.3042E, 38.9150N, and the altitude is 1562m. The air temperature and relative humidity sensors are erected 5 and 10 meters above the ground, facing North; the barometer is installed 2 meters above the ground; tipping bucket rain gauge is installed 10 meters above the ground; the wind speed sensors are set 5 and 10 meters above the ground, facing North; 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, 4cm, 10cm, 20cm, 40cm, 60cm and 100cm under the ground, they are located 2 meters from the meteorological tower in the North. The soil moisture sensors are buried 2cm, 4cm, 10cm, 20cm, 40cm, 60cm and 100cm 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. Observed items include: air temperature and humidity (Ta_5m、RH_5m、Ta_10m、RH_10m) (unit: Celsius, percentage), pressure(Press) (unit:hectopascal), precipitation (Rain) (unit: mm), wind speed (WS_5m、WS_10m) (unit: meter / sec), wind direction (WD_10m) (unit: degree), 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、Ms_10cm、Ms_20cm、Ms_40cm、Ms_60cm、Ms_100cm) (unit: volumetric water content, percentage), soil temperature (Ts_0cm、Ts_2cm、Ts_4cm、Ts_10cm、Ts_20cm、Ts_40cm、Ts_60cm、Ts_100cm) (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. Due to sensor problem, Ms_40cm data between January 1 and March 2 had a large fluctuation, it can only be used as reference. (2) Eliminate moments with duplicate records; (3) Remove data that is significantly beyond physical meaning or beyond the measuring range of the instrument; (4) Data marked by red is debatable; (5) The formats of the date and time are uniform, and the date and time are in the same column. For example, the time is: 2014-6-10 10:30; (6) The naming rule is: AWS + site name. For hydro-meteorological network or site information, please refer to Liu et al. (2018). For observation data processing, please refer to Liu et al. (2011).

2020-04-10

HiWATER: Dataset of hydrometeorological observation network (automatic weather station of Bajitan Gobi desert station, 2015)

This data set contains meteorological element observation data of baji tan gobi station in the middle reaches of heihe hydrological meteorological observation network from January 1, 2015 to April 13, 2015. The station is located at baji beach, chengxiye city, zhangye city, gansu province, and the underlying surface is gobi.The longitude and latitude of the observation point are 100.3042e, 38.9150n and 1562m above sea level.Air temperature and relative humidity sensors are set at 5m and 10m, facing due north;The barometer is installed at 2m;The tilting bucket rain gauge is installed at 10m;The wind speed sensor is set at 5m and 10m, and the wind direction sensor is set at 10m, facing due north;The four-component radiometer is installed at 6m, facing due south;Two infrared thermometers are installed at 6m, facing due south, and the probe facing vertically downward;The soil temperature probe is buried at 0cm of the surface and 2cm, 4cm, 10cm, 20cm, 40cm, 60cm and 100cm underground, 2m to the south of the meteorological tower.The soil water sensor is buried 2cm, 4cm, 10cm, 20cm, 40cm, 60cm and 100cm underground, 2m to the south of the meteorological tower.The soil hot plates (3 pieces) are buried 6cm underground. Observation projects are: air temperature and humidity (Ta_5m RH_5m Ta_10m, RH_10m) (unit: c, percentage), pressure (Press) (unit: hundred mpa), precipitation (Rain) (unit: mm), wind speed (WS_5m, WS_10m) (unit: m/s), wind (WD_10m) (unit: degrees), the radiation of four component (DR, UR, DLR_Cor, ULR_Cor, Rn) (unit: watts per square meter), the surface radiation temperature (IRT_1, IRT_2) (unit:C), soil heat flux (Gs_1, Gs_2, Gs_3) (in watts/m2), 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_40cm, Ts_60cm, Ts_100cm) (unit: Celsius). Processing and quality control of observed data :(1) ensure 144 pieces of data every day (every 10min), and mark by -6999 in case of data missing;(2) excluding the time with duplicate records;(3) data that obviously exceeds the physical significance or the range of the instrument is deleted;(4) the part marked with red letter in the data is the data in question;(5) date and time have the same format, and date and time are in the same column.For example, the time is: June 10, 2015, 10:30;(6) the naming rule is: AWS+ site name.The station will be demolished after April 13. For information of hydrometeorological network or station, please refer to Liu et al. (2018), and for observation data processing, please refer to Liu et al. (2011).

2020-04-10