11 groundwater level observation logs are arranged in the transition zone from Heihe River to desert oasis in Pingchuan oasis, Linze. From May to July 2012-2013, the groundwater level is monitored three times a month, and the NO3-N content, Cl, SO42 - change are analyzed by sampling once a month.
30m month compositing Fraction Vegetation Cover (FVC) data set of Heihe River Basin provides the results of monthly FVC synthesis in 2011-2014. The data constructs multi-angle observation data sets by using China's domestic satellite HJ/CCD data with high temporal resolution (2 days after networking) and spatial resolution (30m) , and divides the country into different vegetation divisions and land types. The conversion coefficients of NDVI and FVC are calculated respectively, and use the calculated conversion coefficient lookup table and monthly compositing NDVI to produce the regional monthly compositing FVC products. The 30m month compositing FVC product in the Heihe River Basin can directly obtain the vegetation coverage ratio through high-resolution data, and mitigate the influence of low-resolution data heterogeneity; in addition, selecting the typical period of vegetation growth change, by fitting the vegetation index of each pixel time series to obtain the growth curve parameters that correspond to each pixel; then the land use map and the vegetation classification map are combined to find the representative uniform pixels of the region for training the conversion coefficients of the vegetation index. Compared with the ASTER reference FVC results, the 30m/month compositing FVC product in the Heihe River Basin is slightly higher than the ASTER reference result, but the overall deviation is not large, and the maximum value of the root mean square error (RMSE) of the product and the reference value is less than 0.175. In addition, compared with the ground survey data of Huailai experimental site in Hebei Province, the 30 m/month compositing FVC products generally reflect the seasonal variation of vegetation growth, and the deviation from the ground survey data is less than 0.1. At the same time, compared with the ground measurements of vegetation coverage in many watersheds in Northeast, North China and Southeast China, the overall error between the compositing FVC products and the ground measurements is less than 0.2. In all, the 30m/month compositing FVC data set of Heihe River Basin comprehensively utilizes multi-temporal and multi-angle remote sensing data to improve the estimation accuracy and time resolution of FVC parameter products, so as to better serve the application of remote sensing data products.
MU Xihan, RUAN Gaiyan, ZHONG Bo, WU Junjun, WU Shanlong, LIU Qinhuo
The data set contains the data of meteorological gradient observation system of sidaqiao superstation downstream of heihe hydrometeorological observation network from January 1, 2015 to December 31, 2015.The station is located in the four Bridges of dalaihubu town, ejin banner, Inner Mongolia.The latitude and longitude of the observation point are 101.1374e, 42.0012n, and 873m above sea level.Air temperature, relative humidity and wind speed sensors are installed at 5m, 7m, 10m, 15m, 20m and 28m, with a total of 6 layers, facing due north.The wind sensor is installed at 15m, facing due north;The barometer is installed in the waterproof box;Dump-type rain gauge installed at 28m;The four-component radiometer is installed at 10m, facing due south;The two infrared thermometers are installed at 10m, facing due south, and the probe is facing vertically down.The two photosynthetic effective radiometers are installed at a location of 10m, facing due south, with the probes pointing vertically up and down, respectively.Part of the soil sensor is installed at 2m to the south of the tower body, in which the soil heat flow plate (self-calibration formal) (3 pieces) is successively buried at 6cm underground;The average soil temperature sensor TCAV is buried 2cm and 4cm underground.The soil temperature probe is buried at 0cm on the surface and 2cm, 4cm, 10cm, 20cm, 40cm, 80cm, 120cm and 160cm underground.The soil moisture sensors were embedded in the ground at 2cm, 4cm, 10cm, 20cm, 40cm, 80cm, 120cm and 160cm. The observation items are: 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: Celsius, percentage), air pressure (Press) (unit:Hundred mpa), precipitation (Rain) (unit: mm), 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), up and down the photosynthetic active radiation (PAR_U_up, PAR_U_down) (unit: second micromoles/m2), the average soil temperature (TCAV) (unit: c), soil heat flux (Gs_1, Gs_2, Gs_3) (unit:W/m2), soil moisture (Ms_2cm, Ms_4cm, Ms_10cm, Ms_20cm, Ms_40cm, Ms_80cm, Ms_120cm, Ms_160cm) (unit: volume water content, percentage), soil temperature (Ts_0cm, Ts_2cm, Ts_4cm, Ts_10cm, Ts_20cm, Ts_40cm, Ts_80cm, Ts_120cm, Ts_160cm) (unit: Celsius). Processing and quality control of observation data :(1) ensure 144 data per day (every 10min). If data is missing, it will be marked by -6999;Infrared temperature 1 between February 11, 2015 and April 25, 2015 due to sensor problems, data is missing;The soil temperature of 4cm was between October 8, 2015 and October 29, 2015. Due to sensor problems, the data was missing.(2) eliminate the moments with duplicate records;(3) data that is obviously beyond the physical meaning or the range of the instrument is deleted;(4) the part marked by red letter in the data is the data in question;(5) the format of date and time is uniform, and the date and time are in the same column.For example, the time is: 2015-9-10-10:30;(6) the naming rule is: AWS+ site name. Please refer to Li et al. (2013) for hydrometeorological network or site information, and Liu et al. (2011) for observation data processing.
LIU Shaomin, LI Xin, CHE Tao, XU Ziwei, REN Zhiguo, TAN Junlei
This data set contains meteorological element observation data from January 1, 2014 to December 31, 2014 at the aruyinpo station, upstream of heihe hydrometeorological observation network.The station is located in the south of ahrou township, qilian county, qinghai province.The longitude and latitude of the observation point are 100.4108E, 37.9841N and 3536m above sea level.The air temperature and relative humidity sensors are located at 5m, facing due north.The barometer is installed in the anti-skid box on the ground;The tilting bucket rain gauge is installed at 10m;The wind speed and direction sensor is set at 10m, facing due north;The four-component radiometer is installed at 6m, facing due south;Two infrared surface thermometers were installed at 6m, facing due south, and the probe facing vertically downward;Two photosynthetically active radiators were installed at 6m, facing due south, and one probe was vertically upward and downward.The soil temperature probe is buried at 0cm on the surface and 4cm underground, 10cm, 20cm, 40cm, 80cm, 120cm, 160cm, 2m to the south of the meteorological tower.The soil water probe is buried at 4cm, 10cm, 20cm, 40cm, 80cm, 120cm and 160cm underground, 2m to the south of the meteorological tower.The soil heat flow plates (3 pieces) are buried in the ground 6cm underground, 2m to the south of the meteorological tower. Observation projects are: air temperature and humidity (Ta_5m, RH_5m) (unit: c, percentage), pressure (Press) (unit: hundred mpa), precipitation (Rain) (unit: mm), wind speed (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:(unit: Ts_0cm, Ts_4cm, Ts_10cm, Ts_20cm, Ts_40cm, Ts_80cm, Ts_120cm, Ts_160cm) (unit: Celsius), soil moisture (Ms_4cm, Ms_10cm, Ms_20cm, Ms_40cm, Ms_80cm, Ms_120cm, Ms_160cm) (unit:Volumetric water content, percentage), upward and downward photosynthetically active radiation (PAR_up, PAR_down) (in micromol/m2 seconds). 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;The air temperature was between June 24, 2014 to June 28, 2014 and July 7, 2014 to August 24, 2014.Surface radiation temperature was between June 24, 2014 and July 4, 2014. Due to sensor problems, data was missing.The soil temperature was between June 24, 2014 and July 1, 2014. Due to the problem of the extension board of collector, data was missing.Due to problems in the power supply system, data was missing between December 3, 2014 and December 31, 2014.(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: September 10, 2014, 10:30;(6) the naming rule is: AWS+ site name. 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).
LIU Shaomin, LI Xin, CHE Tao, XU Ziwei, ZHANG Yang, TAN Junlei
Advanced along orbit scanning radiometer (AATSR) is an advanced tracking scanning radiometer sensor mounted on the European Space Agency ENVISAT satellite. It is one of many high-precision and stable infrared radiometers for retrieving sea surface temperature (SST). Its accuracy can reach 0.3k, and it can also be used to record meteorological data. AATSR is a multi-channel imaging radiometer. Its main goal is to provide global ocean surface temperature with high accuracy and stability for monitoring the earth's climate change. At present, there are 38 ENVISAT AATSR images in Heihe River Basin. The acquisition time is 2008-05-17 (2 scenes), 2008-05-27 (2 scenes), 2008-05-30 (2 scenes), 2008-06-02 (2 scenes), 2008-06-12 (2 scenes), 2008-06-15 (2 scenes), 2008-06-18 (2 scenes), 2008-06-21 (2 scenes), 2008-07-04 (2 scenes), 2008-07-072008-07-102008-07-172008-07-202008-07-232008-07-262008-08-022008-08-052008-08-082008 -08-11，2008-08-14，2008-08-21，2008-08-24，2008-08-27，2008-08-30，2008-09-06，2008-09-12，2008-09-15，2008-09-18，2008-09-25。 The product level is L1B, which has been corrected by radiation but not by geometry. The ENVISAT AATSR remote sensing data set of Heihe comprehensive remote sensing joint test was obtained through the China EU "dragon plan" project (Project No.: 5322) (see the data use statement for details).
LI Xin
The dataset of snow properties measured by the Snowfork was obtained in the Binggou watershed foci experimental area from Mar. 10 to 30, 2008, in cooperation with simultaneous airborne, satellite-borne and ground-based remote sensing experiments and other control experiments. Observation items included (1) physical quantities by direct observations: resonant frequency, the rate of attenuation and 3db bandwidth; (2) physical quantities by indirect observations: snow density, snow complex permittivity (the real part and the imaginary part), snow volumetric moisture and snow gravimetric moisture. 13 files are archived, and the user guide of the sampling plot and observation background is included too.
HAO Xiaohua, LIANG Ji, LI Zhe
The data comes from the Harmonized World Soil Database (HWSD) constructed by the Food and Agriculture Organization of the United Nations (FAO) and International Institute for Applied System Analysis in Vienna (IIASA), which released version 1.1 on March 26, 2009. The data resolution is 1 km. The data source in China is 1: 1 million soil data. The soil classification system used is mainly FAO-90. The main fields of the soil property sheet include: SU_SYM90 (name of soil in FAO90 soil classification system) SU_SYM85 (FAO85 classification) T_TEXTURE (top soil texture) DRAINAGE (19.5); ROOTS: String (depth classification to the bottom of the soil with obstacles); SWR: String (characteristics of soil water content); ADD_PROP: Real (specific soil type in the soil unit related to agricultural use); T_GRAVEL: Real (gravel volume percentage); T_SAND: Real (sand content); T_SILT: Real (silt content); T_CLAY: Real (clay content); T_USDA_TEX: Real (USDA Soil Texture Classification); T_REF_BULK: Real (soil bulk density); T_OC: Real (organic carbon content); T_PH_H2O: Real (pH) T_CEC_CLAY: Real (cation exchange capacity of the sticky layer soil); T_CEC_SOIL: Real (soil cation exchange capacity) T_BS: Real (basic saturation); T_TEB: Real (exchangeable base); T_CACO3: Real (carbonate or lime content) T_CASO4: Real (sulfate content); T_ESP: Real (exchangeable sodium salt); T_ECE: Real (conductivity). The attribute field at the beginning of T_ indicates the upper soil attribute (0-30 cm), and the attribute field at the beginning of S_ indicates the lower layer soil attribute (30-100 cm) (FAO 2009). This data provides model input parameters for Earth system modelers, and in agricultural perspective, it can be used to study eco-agricultural divisions, food security, and climate change.
Food and Agriculture Organization of the United Nations（FAO）
halong Beach area on the west side of Qilian County, Qinghai Province. The underlying surface is swamp meadow. The latitude and longitude of the observation point is 98.9406E, 38.8399N, and the altitude is 3739m. The air temperature and relative humidity sensors are erected 5 meters above the ground, facing North; the barometer is installed in the pick-proof box on the ground; the tipping bucket rain gauge is erected 10 meters above the ground; the wind speed and direction sensor is set 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, 4cm、10cm、20cm、40cm、80cm、120cm and 160cm under the ground, they are located 2 meters from the meteorological tower in the South; the soil moisture sensors are buried 4cm、10cm、20cm、40cm、80cm、120cm and 160cm 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_5m, RH_5m) (unit: Celsius, percentage), air pressure (Press) (unit: hectopascal), precipitation (Rain) (unit: mm), wind speed (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 temperature (Ts_0cm, Ts_4cm, Ts_10cm, Ts_20cm, Ts_40cm, Ts_80cm, Ts_120cm, Ts_160cm) (unit: Celsius), soil moisture (Ms_4cm , Ms_10cm, Ms_20cm, Ms_40cm, Ms_80cm, Ms_120cm, Ms_160cm) (unit: volumetric water content, percentage). 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. (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: 2016-9-10 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).
LI Xin, CHE Tao, XU Ziwei, ZHANG Yang, TAN Junlei
The data set contains soil observation data of typical sample points in Heihe River Basin: pH value and soil texture 1. Soil pH value: longitude, latitude and pH value of typical soil sample points. 2. Soil texture: including soil texture data of typical soil samples in Heihe River Basin from July 2012 to August 2013. The typical soil sampling method in Heihe River Basin is representative sampling, which means that the typical soil types in the landscape area can be collected, and the representative sample points should be collected as far as possible. According to the Chinese soil taxonomy, soil samples from each profile were taken based on the diagnostic layers and diagnostic characteristics.
ZHANG Ganlin,
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).
LIU Shaomin, LI Xin, CHE Tao, XU Ziwei, REN Zhiguo, TAN Junlei
This data includes experimental data of grassland interception control and observation data of maximum water holding capacity of grassland. The maximum water holding capacity experiment was carried out in 2011. The main vegetation types selected are Carex, Polygonum viviparum, Plantago asiatica and Potentilla chinensis. The maximum water holding capacity experiment was carried out on each type of samples and the samples were photographed. The specific data obtained are shown in the document. The grassland canopy interception was carried out in the growing season of 2012, and was completed by artificial rainfall control experiment. At the end of the growing season, the main types of grassland in the basin were sampled according to grazing and grazing ban. During artificial rainfall, rainfall and penetrating rainfall are recorded every 1min. Finally, the grassland canopy interception is calculated by the difference between rainfall and penetrating rainfall.
ZHAO Chuanyan, MA Wenying
The leaf epidermis micromorphological structure of the constructive species in the arid area of the middle and lower reaches of Heihe River Basin. The plant material number is consistent with the number in the sampling table. Refer to the sampling table number to determine the material and its distribution position.
LIU Yubing
The dataset of ground-based microwave scatterometer and snow parameter observations was obtained in the Binggou watershed experimental area on Mar. 16, 2008. Observation items included: (1) Snow backscattering coefficient by the scatterometer (2) Snow parameters as the snow surface temperature by the probe thermometer, snow grain size by the handheld microscope, snow density by the snow shovel, the snow surface temperature and the snow-soil interface temperature by the handheld infrared thermometer in BG-I. (3) The snow spectrum by the portable ASD (Xinjiang Meteorological Administration) at the Dadongshu mountain pass; the major and minor axis and shape of the snow layer grain through the snow sieve. (4) Snow albedo by the total radiometer from 10:29 to 15:00 (5) Snow density, snow complex permittivity, snow volumetric moisture and snow gravimetric moisture by the Snowfork at the Dadongshu mountain pass Two subfolders including raw data and preprocessed data were archived.
LIU Zengcan, LIU Zengcan, QIN Wei, SHU Lele, WANG Xufeng, XU Zhen, ZHU Shijie, MA Mingguo, CHANG Cun, DOU Yan, MA Zhongguo, ZHANG Pu, JIANG Tenglong
This data set contains the eddy correlograph observation data from January 1, 2015 to December 31, 2015 at the alou superstation, upstream of the heihe hydrometeorological observation network.The station is located in caoban village, aru township, qilian county, qinghai province.The longitude and latitude of the observation point are 100.4643e, 38.0473n and 3033m above sea level.The rack height of the vortex correlativity meter is 3.5m, the sampling frequency is 10Hz, the ultrasonic orientation is due north, and the distance between the ultrasonic wind speed and temperature meter (CSAT3) and CO2/H2O analyzer (Li7500A) 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 and other reasons are marked with red font, in which the calibration data of Li7500A of the eddy current system on April 16-17 is missing;When 10Hz data is missing due to a problem with the memory card storage data (9.20-10.21,11.3-11.18), the data is 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), Mr. Hoff length L (m), 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).
LI Xin, CHE Tao, XU Ziwei, ZHANG Yang, TAN Junlei
The algorithm firstly adopts the canopy BRDF model and represents the canopy reflectivity as a function of a series of parameters such as LAI/FAPAR, wavelength, reflectivity of soil and leaves, aggregation index, incidence and observation Angle.The parameter table is established for several key parameters as the input of inversion.Then input the pre-processed surface reflectance data and land cover data, and invert LAI products by look-up table (LUT) method.See references for detailed algorithms. Image format: tif Image size: about 1M per scene Time range: 2000-2012 Temporal resolution: 8 days Spatial resolution: 1km
FAN Wenjie
This data set contains the observation data of vortex-correlograph in the middle reaches of heihe hydrometeorological observation network from January 1, 2016 to December 31, 2016.The station is located in the daman irrigation district of zhangye city, gansu province.The latitude and longitude of the observation point is 100.37223E, 38.85551N, and the altitude is 1556.06m.The rack height of the vortex correlativity meter is 4.5m, the sampling frequency is 10Hz, the ultrasonic orientation is due north, and the distance between the ultrasonic wind speed and temperature meter (CSAT3) and CO2/H2O analyzer (Li7500A) is 17cm. 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.Due to the power failure from March 3 to 23, the Li7500A of the vortex system was calibrated from April 17 to 25, and the collector problems from October 10 to 24 and December 19 to 31 led to data loss. 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), Mr. Hoff length L (m), 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).
LIU Shaomin, LI Xin, CHE Tao, XU Ziwei, REN Zhiguo, TAN Junlei
On 25 July 2012, Leica ALS70 airborne laser scanner carried by the Harbin Y-12 aircraft was used in a LiDAR airborne optical remote sensing experiment. Leica ALS70 airborne laser scanner has unlimited numbers of returns intensities measurements including the first, second ,third return intensities. The wavelength of laser light is 1064 nm. The absolute flight altitude is 4800 m with the point cloud density 1 points per square meter. Airborne LiDAR-DEM and DSM data production were obtained through parameter calibration, automatic classification of point cloud density and manual editing.
XIAO Qing, Wen Jianguang
From 2012 to 2013, the geomorphic surface near the Zhengyi gorge in the middle reaches of the Heihe River was investigated, mainly including the 4-level river terrace. The data are mainly obtained through field investigation, and analyzed and mapped indoors to obtain the distribution map of geomorphic surface at all levels near the middle reaches of Zhengyi gorge.
HU Xiaofei, PAN Baotian
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.
MU Xihan, HUANG Shuai, MA Mingguo
This dataset contains the flux measurements from site No.1 eddy covariance system (EC) in the flux observation matrix from 4 June to 17 September 2012. The site (100.35813° E, 38.89322° N) was located in a cropland (vegetable surface) in the Yingke irrigation district, which is near Zhangye, Gansu Province. The elevation is 1552.75 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 (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.
LIU Shaomin, LI Xin, XU Ziwei
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