ET（Evapotranspiration）monitoring is essential for agricultural water management, regional water resources utilization planning, and socio-economic sustainable development.The limitations of the traditional monitoring ET method are mainly that large-area simultaneous observations cannot be made and can only be limited to observation points. Therefore, the cost of personnel and equipment is relatively high, and it is unable to provide ET data on the surface, nor to provide the ET data of different land use types and crop types. Quantitative monitoring of ET can be achieved by remote sensing. The characteristics of remote sensing information are that it can reflect both the macroscopic structural characteristics of the Earth's surface and the microscopic local differences. Monthly evapotranspiration datasets (2000-2013) with 30m spatial resolution over oasis in the Middle Reaches of Heihe River Basin Version 1.0 are based on multi-source remote sensing data. The latest ET Watch model is used to estimate the raster image data. Its temporal resolution is monthly and spatial resolution is 30 meters. The data cover the middle reaches of Zhangye oasis area in millimeters. The data types include month, quarter, and year data. The projection information of the data is as follows: Albers equivalent conical projection, Central meridian: 110 degrees, First secant: 25 degrees, Second secant: 47 degrees, Coordinate west deviation: 4000000 meters. The file naming rules are as follows: Monthly cumulative ET value file name: heihe-midoasis-30m_2013m01_eta.tif Among them, heihe indicates the Heihe River Basin, midoasis indicates the middle oasis area, 30m indicates the resolution is 30 meters, 2013 indicates 2013, m01 indicates January, eta indicates actual evapotranspiration data, and tif indicates that the data is in tif format; The ET value file for each season is named: heihe-midoasis-30m_2013s01_eta.tif Among them, heihe indicates the Heihe River Basin, midoasis indicates the middle oasis area, 30m indicates the resolution is 30 meters, 2013 indicates 2013, s01 indicates 1-3 months, for the first quarter, eta indicates actual evapotranspiration data, and tif indicates that the data is in tif format; The annual cumulative value file name: heihe-midoasis-30m_2013y_eta.tif Among them, heihe indicates the Heihe River Basin, midoasis indicates the middle oasis area, 30m indicates the resolution is 30 meters, 2013 indicates 2013, y indicates the year, eta indicates the actual evapotranspiration data, and tif indicates that the data is in tif format.
2019-09-14
This dataset includes data recorded by the Hydrometeorological observation network obtained from the automatic weather station (AWS) at the observation system of Meteorological elements gradient of Huangcaogou station between 7 June, 2013, and 31 December, 2013. The site (100.731° E, 38.003° N) was located on a cold grassland surface in the Huangcaogou village, E’bao town, Qilian County, Qinghai Province. The elevation is 3137 m. The installation heights and orientations of different sensors and measured quantities were as follows: air temperature and humidity profile (HMP45D; 5 m, north), wind speed and direction profile (03001; 10 m, north), air pressure (CS100; in the tamper box on the ground), rain gauge (TE525M; 10 m), four-component radiometer (CNR1; 6 m, south), two infrared temperature sensors (IRTC3; 6 m, south, vertically downward), soil heat flux (HFT3; 3 duplicates, -0.06 m), soil temperature profile (AV-10T; 0, -0.04, -0.1, -0.2, -0.4, -0.8, -1.2, and -1.6 m), and soil moisture profile (ECh2o-5; -0.04, -0.1, -0.2, -0.4, -0.8, -1.2, and -1.6 m). The observations included the following: air temperature and humidity (Ta_5 m; RH_5 m) (℃ and %, respectively), wind speed (Ws_10 m) (m/s), wind direction (WD_10 m) (°), air pressure (press) (hpa), precipitation (rain) (mm), four-component radiation (DR, incoming shortwave radiation; UR, outgoing shortwave radiation; DLR_Cor, incoming longwave radiation; ULR_Cor, outgoing longwave radiation; Rn, net radiation) (W/m2), infrared temperature (IRT_1 and IRT_2) (℃), soil heat flux (Gs_1, Gs_2 and Gs_3) (W/m2), soil temperature (Ts_0 cm, Ts_4 cm, Ts_10 cm, Ts_20 cm, Ts_40 cm, Ts_80 cm, Ts_120 cm, and Ts_160 cm) (℃), and soil moisture (Ms_4 cm, Ms_10 cm, Ms_20 cm, Ms_40 cm, Ms_80 cm, Ms_120 cm, and Ms_160 cm) (%, volumetric water content). The data processing and quality control steps were as follows: (1) The AWS data were averaged over intervals of 10 min for a total of 144 records per day. The data of wind direction were missing during 12 June, 2013 and 24 September, 2013. The missing data were denoted by -6999. (2) Data in duplicate records were rejected. (3) Unphysical data were rejected. (4) The data marked in red are problematic data. (5) The format of the date and time was unified, and the date and time were collected in the same column, for example, date and time: 2013-9-10 10:30. (6) Finally, the naming convention was AWS+ site no. Moreover, suspicious data were marked in red. For more information, please refer to Li et al. (2013) (for hydrometeorological observation network or sites information), Liu et al. (2011) (for data processing) in the Citation section.
2019-09-14
This dataset contains the automatic weather station (AWS) measurements from site No.9 in the flux observation matrix from 4 June to 17 September, 2012. The site (100.38546° E, 38.87239° N) was located in a cropland (maize surface) in Yingke irrigation district, which is near Zhangye, Gansu Province. The elevation is 1543.34 m. The installation heights and orientations of different sensors and measured quantities were as follows: air temperature and humidity (HMP45AC; 5 m, towards north), rain gauge (TE525M; 10 m), wind speed (010C; 10 m, towards north), a four-component radiometer (CNR1; 6 m, towards south), two infrared temperature sensors (SI-111; 6 m, vertically downward), soil temperature profile (AV-10T; 0, -0.02, -0.04 m), soil moisture profile (CS616; -0.02, -0.04 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), precipitation (rain, mm), wind speed (Ws_10 m, m/s), four-component radiation (DR, incoming shortwave radiation; UR, outgoing shortwave radiation; DLR_Cor, incoming longwave radiation; ULR_Cor, outgoing longwave radiation; Rn, net radiation; W/m2), infrared temperature (IRT_1 and 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, and Ts_4 cm, ℃), and soil moisture profile (Ms_2 cm and Ms_4 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
This dataset contains the flux measurements from site No.3 eddy covariance system (EC) in the flux observation matrix from 3 June to 18 September, 2012. The site (100.37634° E, 38.89053° N) was located in a cropland (maize surface) in Yingke irrigation district, which is near Zhangye, Gansu Province. The elevation is 1543.05 m. The EC was installed at 3.8 m high, and sampled at 10 Hz. The EC was installed at a height of 3.8 m; the sampling rate was 10 Hz. The sonic anemometer faced north, and the separation distance between the sonic anemometer and the CO2/H2O gas analyzer (Gill&Li7500A) was 0.2 m. Raw data acquired at 10 Hz were processed using the Eddypro post-processing software (Li-Cor Company, http://www.licor.com/env/products/ eddy_covariance/software.html), including spike detection, lag correction of H2O/CO2 relative to the vertical wind component, sonic virtual temperature correction, angle of attack correction, coordinate rotation (2-D rotation), corrections for density fluctuation (Webb-Pearman-Leuning correction), and frequency response correction. The EC data were subsequently averaged over 30 min periods. Moreover, the observation data quality was divided into three classes according to the quality assessment method of stationarity (Δst) and the integral turbulent characteristics test (ITC), which was proposed by Foken and Wichura [1996]: class 1 (level 0: Δst<30 and ITC<30), class 2 (level 1: Δst<100 and ITC<100), and class 3 (level 2: Δst>100 and ITC>100), representing high-, medium-, and low-quality data, respectively. In addition to the above processing steps, the half-hourly flux data were screened in a four-step procedure: (1) data from periods of sensor malfunction were rejected; (2) data before or after 1 h of precipitation were rejected; (3) incomplete 30 min data were rejected when the missing data constituted more than 3% of the 30 min raw record; and (4) data were rejected at night when the friction velocity (u*) was less than 0.1 m/s. There were 48 records per day; the missing data were replaced with -6999. Moreover, suspicious data were marked in red. The released data contained the following variables: data/time, wind direction (Wdir, °), wind speed (Wnd, m/s), the standard deviation of the lateral wind (Std_Uy, m/s), virtual temperature (Tv, ℃), H2O mass density (H2O, g/m^3), CO2 mass density (CO2, mg/m^3), friction velocity (ustar, m/s), stability (z/L), sensible heat flux (Hs, W/m^2), latent heat flux (LE, W/m^2), carbon dioxide flux (Fc, mg/ (m^2s)), quality assessment of the sensible heat flux (QA_Hs), quality assessment of the latent heat flux (QA_LE), and quality assessment of the carbon flux (QA_Fc). In this dataset, the time of 0:30 corresponds to the average data for the period between 0:00 and 0:30; the data were stored in *.xlsx format. For more information, please refer to Liu et al. (2016) (for multi-scale observation experiment or sites information), Xu et al. (2013) (for data processing) in the Citation section.
2019-09-14
The dataset of TIR spectral emissivity was obtained in the arid region hydrology experiment area and A'rou foci experiment area. Observations were by: (1) Spectral emissivity obtained from 102F at 2-25um in cooperation with the handheld infrared thermometer (BNU) for the surface radiative temperature and one au-plating board for downward atmospheric radiation. The radiative transfer equation and TES methods were applied to retrieve emissivity. The grassland and the concrete floor were measured on May, 27, 2008, the wheat field and the maize field at ICBC resort on May, 29, 2008, the concrete floor (multiangle measurements) at ICBC resort on Jun. 3, 2008, the bare soil and the maize leaf in Yingke oasis maize field on Jun. 22, 2008, the maize and wheat canopy in Yingke oasis maize field on Jun. 23, 2008, the rape field in Biandukou experimental area on Jun. 24, 2008, the alfalfa, the saline land, the grassland and the barley land on Jun. 26, 2008, the wheat field and the maize field in Yingke oasis maize field on Jun. 29, 2008, the desert bare land and vegetation (Reaumuria soongorica) in No. 2 Huazhaiai desert plot on Jun. 30, 2008, the rape field and the grassland in Biandukou experimental area on Jul. 6, 2008, and the grassland and the bare land (multiangle) in A'rou experimental area on Jul. 14, 2008. The cold blackbody calibration (*.CBX/*.CBB), the warm blackbody calibration (*.WBX/*.WBB), the ground objects measurements (*.SAX), au-plating board measurements, and the downward atmospheric radiation (*.DWX) were all needed during observation. Moreover, the spectral radiance and emissivity were also archived. The response function of various bands could be acquired by 102F. And then emissivity of 2-25um could be retrieved. Two results of emissivity were developed: one was direct from 102F and the other was retrieved by ISSTES (Iterative spectrally smooth temperature-emissivity separation). Spectral resolution for raw data and proprecessed data was 4cm-1. (2) Spectral emissivity obtained from BOMAN at 2 -13μm in cooperation with the blackbody barrel and the blackbody from Institute of Remote Sensing Applications and the blackbody (BNU). The desert was measured on Jun. 30 and Jul. 1, 2008, A'rou foci experimental area on Jul. 14, 2008, indoor observations on the deep and shallow layer soil, vegetation, small stones, two maize plants from Yingke No.2 (YKYZYMD02) field and one maize plant and bare land from No. 3 (YKYZYMD03)field on on Jul. 16, 2008, Linze experimental area on Jul. 17, 2008, and gobi on Jul. 18, 2008. The sample site, coordinates, time and photos were all archived. During each observation, BOMAN was preheated and the blackbody was set at the predicted target temperature, which would be changed after the infrared radiation of the blackbody was measured by BOMAN. And then the target infrared radiation, the downward atmospheric radiation (reflected by the au-plating board) and the infrared radiation of the blackbody would be measured one by one. Raw data were archived in Igm, and after processed by FTSW500, the result was Rad (radiation). Finally, Rad would be changed into txt files by Matlab programs.
2019-09-14
This dataset contains the flux measurements from the Shenshawo sandy desert station eddy covariance system (EC) in the flux observation matrix from 1 June to 15 September, 2012. The site (100.49330° E, 38.78917° N) was located in a sandy desert surface, which is near Zhangye, Gansu Province. The elevation is 1594.00 m. The EC was installed at a height of 4.6 m; the sampling rate was 10 Hz. The sonic anemometer faced north, and the separation distance between the sonic anemometer and the CO2/H2O gas analyzer (CSAT3&Li7500) was 0.15 m. Raw data acquired at 10 Hz were processed using the Edire post-processing software (University of Edinburgh, http://www.geos.ed.ac.uk/abs/research/micromet/EdiRe/), including spike detection, lag correction of H2O/CO2 relative to the vertical wind component, sonic virtual temperature correction, coordinate rotation (2-D rotation), corrections for density fluctuation (Webb-Pearman-Leuning correction), and frequency response correction. The EC data were subsequently averaged over 30 min periods. Moreover, the observation data quality was divided into three classes according to the quality assessment method of stationarity (Δst) and the integral turbulent characteristics test (ITC), which was proposed by Foken and Wichura [1996]: class 1 (level 0: Δst<30 and ITC<30), class 2 (level 1: Δst<100 and ITC<100), and class 3 (level 2: Δst>100 and ITC>100), representing high-, medium-, and low-quality data, respectively. In addition to the above processing steps, the half-hourly flux data were screened in a four-step procedure: (1) data from periods of sensor malfunction were rejected; (2) data before or after 1 h of precipitation were rejected; (3) incomplete 30 min data were rejected when the missing data constituted more than 3% of the 30 min raw record; and (4) data were rejected at night when the friction velocity (u*) was less than 0.1 m/s. There were 48 records per day; the missing data were replaced with -6999. Moreover, suspicious data were marked in red. The released data contained the following variables: data/time, wind direction (Wdir, °), wind speed (Wnd, m/s), the standard deviation of the lateral wind (Std_Uy, m/s), virtual temperature (Tv, ℃), H2O mass density (H2O, g/m^3), CO2 mass density (CO2, mg/m^3), friction velocity (ustar, m/s), stability (z/L), sensible heat flux (Hs, W/m^2), latent heat flux (LE, W/m^2), carbon dioxide flux (Fc, mg/ (m^2s)), quality assessment of the sensible heat flux (QA_Hs), quality assessment of the latent heat flux (QA_LE), and quality assessment of the carbon flux (QA_Fc). In this dataset, the time of 0:30 corresponds to the average data for the period between 0:00 and 0:30; the data were stored in *.xlsx format. For more information, please refer to Liu et al. (2016) (for multi-scale observation experiment or sites information), Xu et al. (2013) (for data processing) in the Citation section.
2019-09-14
This dataset contains the flux measurements from the large aperture scintillometer (LAS) at Sidaoqiao Superstation (two sites) in the hydrometeorological observation network of Heihe River Basin. There were two types of LASs at site 1: German BLS900 and Netherlands Kipp&zonen. The north tower was set up with the BLS900/Kipp&zonen receiver, and the south tower was equipped with the BLS900/Kipp&zonen transmitter. The observation period of BLS900_1 and Kipp&zonen were from 11 July to 13 November, 2013, and 11 July to 12 September, 2013, respectively. There was one type of LAS at site 2: German BLS900. The north tower was set up with the BLS900 receiver, and the south tower was equipped with the BLS900 transmitter. BLS900_2 has been in use since 16 September, 2013. The Sidaoqiao Superstation (site1, north: 101.147° E, 42.005° N, south: 101.131° E, 41.987° N; site 2, north: 101.137° E, 42.008° N, south: 101.121° E, 41.990° N) was located in Ejinaqi, Inner Mongolia. The underlying surfaces between the two towers were tamarisk, populus, bare land and farmland. The elevation is 873 m. The effective height of the LASs was 25.5 m, and the path length of site 1 and site 2 were 2390 m and 2380 m, respectively. The data were sampled at 5 Hz and 1 Hz intervals for BLS900 and zzlas, respectively, and then averaged over 1 min. The raw data acquired at 1 min intervals were processed and quality controlled. The data were subsequently averaged over 30 min periods, in which sensible heat flux was iteratively calculated by combining Cn2 with meteorological data according to the Monin-Obukhov similarity theory. The main quality control steps were as follows: (1) The data were rejected when Cn2 exceeded the saturated criterion (BLS900_1: Cn2>7.25E-14, Kipp&zonen: Cn2>7.84E-14, BLS900_2: Cn2>7.33E-14). (2) The data were rejected when the demodulation signal was small (BLS900: Average X Intensity<1000; Kipp&zonen: Demod>-20mv). (3) The data were rejected when collected during precipitation. (4) The data were rejected if collected at night when weak turbulence occurred (u* was less than 0.1 m/s). In the iteration process, the universal functions of Thiermann and Grassl, 1992 and Andreas, 1988 were selected for BLS900 and Kipp&zonen, respectively. Several instructions were included with the released data. (1) The data of site 1 were primarily obtained from BLS900_1 measurements, and missing flux measurements from the BLS900_1 instrument were substituted with measurements from the Kipp&zonen instrument. The missing data were denoted by -6999. The data of site 2 were obtained from BLS900_2 measurements, missing data were denoted by -6999. Due to the problems of BLS900_1 transmitter, the data after 13 November, 2013, were not collected. (2) The dataset contained the following variables: data/time (yyyy-m-d h:mm), the structural parameter of the air refractive index (Cn2, m-2/3), and the sensible heat flux (H_LAS, W/m^2). In this dataset, a time of 0:30 corresponds to the average data for the period between 0:00 and 0:30, and the data were stored in *.xls format. 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
This dataset contains the flux measurements from the Populus 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 (101.124° E, 41.993° N) was located in the Populus surface, Ejin Banner in Inner Mongolia. The elevation is 876 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 CF card storage problem, data during 17 September to 9 December were replaced with the 30 min output flux data in the 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 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
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
On 30 June 2012 (UTC+8), TASI sensor carried by the Harbin Y-12 aircraft was used in a visible near Infrared hyperspectral airborne remote sensing experiment, which is located in the observation experimental area (30×30 km). The relative flight altitude is 2500 meters. Land surface temperature product was obtained at a resolution of 3 m using a modified temperature/emissivity separation algorithm based on TASI surface radiance data. The product were validated with in situ ground measurements. The validation results indicated that the Land surface temperature product agreed with the ground LSTs well with RMSE lower than 1.5 K.
2019-09-14
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