This data set includes the observation data of 40 water net sensor network nodes in Babao River Basin in the upper reaches of Heihe River since the end of June 2013. Soil moisture of 4cm, 10cm and 20cm is the basic observation of each node; 19 nodes include the observation of soil moisture and surface infrared radiation temperature; 11 nodes include the observation of soil moisture, surface infrared radiation temperature, snow depth and precipitation. The observation frequency is 5 minutes. The data set can be used for hydrological simulation, data assimilation and remote sensing verification.
KANG Jian, LI Xin, MA Mingguo
Eo-1 (Earth Observing Mission) is a new Earth Observing satellite developed by NASA to replace Landsat7 in the 21st century. It was launched on November 21, 2000.The orbit of eo-1 satellite is basically the same as that of Landsat7, which is a solar synchronous orbit with an orbital altitude of 705km and an inclination Angle of 98.7°, which is 1min less than that of Landsat7 and crosses the equator.On board of EO 1 3 kinds of sensors, namely, the Advanced Land Imager (ALI (the Advanced Land Imager), atmospheric correction instrument AC (Atmosp heric Corrector) and compose a specular as spectrometer (Hyperion), Hyperion sensor is first spaceborne hyperspectral mapping measurement instrument, the hyperspectral data a total of 242 bands, spectral range is 400 ~ 2500 nm, spectral resolution up to 10 nm, ground resolution of 30 m. Currently, there are 6 scenes of eo-1 Hyperion data in heihe river basin.The coverage and acquisition time were: 4 scenes in the encrypted observation area of zhangye urban area + yingke oasis encrypted observation area (2007-09-10, 2008-05-12, 2008-05-20, 2008-07-15).Two scenes of the iceditch watershed observation area were encrypted, the time was 2008-03-17, 2008-03-22, respectively. Product grade is L1 without geometric correction. The eo-1 Hyperion remote sensing data set of heihe integrated remote sensing joint experiment was acquired by researcher wang jian and Beijing normal university through purchase. (note: "+" represents simultaneous coverage)
Institute of Remote Sensing and Digital earth, Chinese Academy of Sciences
This data includes the basic terrain data, soil data, meteorological data, land use / land cover data, etc. needed for SWAT model operation. All maps and relevant point coordinates (meteorological station, hydrological station) adopt the coordinate system of Gauss Kruger projection which is consistent with the basic topographic map of our country. Data content includes: a) The basic topographic data include DEM and river network. The size of DEM grid is 50 * 50m, and the drainage network is manually digitized from 1:100000 topographic map. b) Soil data: including soil physics, soil chemistry and spatial distribution of soil types. The scale of digital soil map is 1:1 million, which is converted into grid format of ESRI, with grid size of 50 * 50m. Each soil profile can be divided into up to 10 layers. The sampling index of soil texture required by the model adopts the American Standard. The parameters are from the second National Soil Census data and related literature. c) Meteorological data: (1) Temperature: the data of daily maximum temperature, daily minimum temperature, wind speed and relative humidity are from the daily observation data of Qilian, Shandan, tole, yeniugou and Zhangye meteorological stations in and around the basin, with the period from 1999 to 2001. (2) Precipitation: the rainfall data comes from five hydrological stations in and around the basin, i.e. OBO (1990-1996), Sunan (1990-2000), Qilian (1990-2000), Yingluoxia (1990-2000), zamashk (1990-2000), Shandan (1999-2001), tole (1999-2001), yeniugou (1999-2001), Zhangye (1999-2001) and Qilian County (1999-2001) Observation data. (3) Wind speed and relative humidity: wind speed and relative humidity come from the daily observation data of 5 meteorological stations in Shandan, tole, yeniugou, Zhangye and Qilian county. The period is from 1999 to 2001. (4) Solar radiation: solar radiation has no corresponding observation data and is generated by model simulation. d) Land use / land cover: 1995 land use data, scale 1:100000. Convert it to grid format of ESRI, with grid size of 50 * 50m. e) Meteorological data simulation tool (weather generator) database: the weather data simulation tool of SWAT model can simulate and calculate the daily meteorological input data required by the model operation according to the monthly statistical data for many years without the actual daily observation data, and can also carry out the interpolation of incomplete observation data. The meteorological data are from the surrounding meteorological stations.
NAN Zhuotong
The dataset contains phenological camera observation data collected at the Arou Superstation in the midstream of the Heihe integrated observatory network from June 13 to November 16, 2018. The instrument was developed with data processed by Beijing Normal University. The phenomenon camera integrates data acquisition and data transmission functions. The camera captures high-quality data with a resolution of 1280×720 by looking-downward. The calculation of the greenness index and phenology are following 3 steps: (1) calculate the relative greenness index (GCC, Green Chromatic Coordinate, calculated by GCC=G/(R+G+B)) according to the region of interest, (2) perform gap-filling for the invalid values, filtering and smoothing, and (3) determine the key phenological parameters according to the growth curve fitting (such as the growth season start date, Peak, growth season end, etc.) There are also 3 steps for coverage data processing: (1) select images with less intense illumination, (2) divide the image into vegetation and soil, and (3) calculate the proportion of vegetation pixels in each image in the calculation area. After the time series data is extracted, the original coverage data is smoothed and filtered according to the time window specified by the user, and the filtered result is the final time series coverage. This data set includes relative greenness index (Gcc). Please refer to Liu et al. (2018) for sites information in the Citation section.
Qu Yonghua, XU Ziwei, LI Xin
This data includes the general layout of the reconstruction project of the middle reaches of the Heihe River, and describes in detail the water diversion flow, irrigation area and other data of each diversion outlet in the middle reaches of the Heihe River. It is attached with the statistical table of the current situation of the diversion portal (listing the diversion form, bank type, irrigation area name, irrigation area name and diversion flow of all diversion portal), the statistical table of the relative distance of the reconstructed diversion portal in the middle reaches (including the relative distance between the reconstructed diversion portal and Zhengyi gorge, bank type and the distance from the previous one), and the general layout plan of the combined reconstruction of the diversion portal (including the combined one Water diversion type, bank type, irrigation area name, irrigation area and water diversion flow) There is no vector format for the data, we only collect JPG format, with a diversion channel table.
XU Zongxue
Based on the "western data center", the daily discharge from three field observation stations (zamashk, Yingluoxia, Qilian) since 1990-1995 is sorted out.
ZHANG Zhiqiang
The dateset of surface roughness measurements was obtained in the Biandukou foci experimental area. With the roughness grid board 110cm long and the measuring intervals of 1cm, the samples were collected along the soil surface from south to north and from east to west, respectively. The coordinates of the sample would be got with the help of ArcView; and after geometric correction, surface height standard deviation (cm) and correlation length (cm) could be acquired based on the formula listed on pages 234-236, Microwave Remote Sensing, Vol. II. The original photos of each sampling point, surface height standard deviation (cm) and correlation length (cm) were included. The roughness data files were initialized by the sample name, which was followed by the serial number, the name of the file, standard deviation and correlation length. Each .txt file is matched with one sample photo and standard deviation and correlation length represent the roughness. In addition, the length of 101 needles is also included for further checking.
CAO Yongpan, WANG Jian, Wang Weizhen, WANG Xufeng, LIANG Xingtao, ZHANG Yongpan, Zhao Tianjie
The dataset of ground truth measurements synchronizing with EO-1 Hyperion was obtained in the Yingke oasis foci experimental area from Sep. 5 to Sep. 10, 2007 during the pre-observation period. It was carried out by the 3rd and 2nd sub-projects of CAS’s West Action Plan along Zhangye city-Yingke oasis-Huazhaizi, and on the very day of 10, one scene of Hyperion was captured. sampling plot time north latitude east longitude elevation notes 1 9:58 38°53′53.2″ 100°26′09.7″ 1500 cauliflower land east to the road 2 10:51 38°52′39.8″ 100°25′33.1″ 1510 cabbage land east to the road 3 11:35 38°52′39.0″ 100°25′34.6″ 1510 east to No. 2 sampling plot, maize and intercropping wheat reaped 4 12:24 38°51′53.0″ 100°25′08.0″ 1510 maize seed 5 13:08 38°51′54.2″ 100°25′09.5″ 1520 north to No. 4 sampling plot, maize and intercropping wheat reaped 6 14:40 38°51′23.5″ 100°24′45.0″ 1510 west to the road, maize seed, serious blights (red spider) 7 15:40 38°49′26.6″ 100°23′23.7″ 1540 intercrop land of sea buckthorn and beet 8 16:18 38°49′06.9″ 100°23′30.5″ 1540 tomato land, rich of amaranth weeds 9 16:18 38°49′06.4″ 100°23′30.8″ 1540 beet land 10 16:18 38°49′06.9″ 100°23′30.5″ 1540 tomato land with less weeds 11 10:30 38°48′28.3″ 100°24′11.4″ 1540 sea buckthorn seedling land west to the road 12 11:24 38°48′09.3″ 100°24′10.1″ 1550 sun flower land east to the road, intercropping wheat reaped 13 12:38 38°46′16.3″ 100°23′14.2″ 1600 dry rice land 14 12:45 38°46′16.2″ 100°23′14.0″ 1600 rape land 15 12:54 38°46′15.6″ 100°23′13.8″ 1600 buckwheat land 16 14:52 38°45′55.5″ 100°23′00.1″ 1610 maize (without intercrop) 17 15:28 38°45′57.5″ 100°22′28.3″ 1630 maize (without intercrop) 18 16:20 38°43′17.3″ 100°22′53.4″ 1730 gobi (Bassia dasyphylla and margarite dominate) 19 17:40 38°42′31.8″ 100°22′56.8″ 1780 gobi (Bassia dasyphylla and Sympegma regelii dominate) 20 10:27 38°36′25.1″ 100°20′33.2″ 2260 wheatgrass dominates 21 11:10 38°36′24.4″ 100°20′38.1″ 2260 abandoned composite land 22 11:30 2260 near site 22, wheatgrass and composite cenosis 23 bare land 24 13:09 38°38′46.3″ 100°23′08.5″ 2030 alfalfa land 25 14:39 38°44′30.8″ 100°22′41.0″ 1660 poplar 26 9:47 38°58′11.4″ 100°26′18.3″ 1460 rice land Observation items included: (1) quadrat surveys (2) LAI by LAI-2000 (3) ground object reflectance spectra by ASD FieldSpec Pro (350-2500nm)from Gansu Meteorological Administration (4) the land surface temperature and the canopy radiative temperature by the hand-held thermal infrared sensor (5) the photosynthesis rate by LI-6400 (6) the radiative temperature by ThermaCAM SC2000 (7) Atmospheric parameters by CE318 to retrieve the total optical depth, aerosol optical depth, Rayleigh scattering coefficient, column water vapor in 936 nm, and various parameters at 550nm to obtain horizontal visibility with the help of MODTRAN or 6S codes (8) chlorophyll consistency by portable SPAD Those provide reliable ground data for developing and validating retrieval meathods of biophysical parameters from EO-1 Hyperion images.
MA Mingguo, LI Xin, SU Peixi, DING Songchuang, GAO Song, YAN Qiaodi, ZHANG Lingmei, WANG Xufeng, Qian Jinbo, BAI Yunjie, HAO Xiaohua, Liu Qiang, Wen Jianguang, XIN Xiaozhou, WANG Xiaoping, HAN Hui
This data set contains the observation data of Zhangye National Climate Observatory from 2008 to 2009. The station is located in Zhangye, Gansu Province, with longitude and latitude of 100 ° 17 ′ e, 39 ° 05 ′ N and altitude of 1456m. The observation items include: atmospheric wind temperature and humidity gradient observation (2cm, 4cm, 10cm, 20m and 30m), wind direction, air pressure, photosynthesis effective radiation, precipitation, radiation four components, surface temperature, multi-layer soil temperature (5cm, 10cm, 15cm, 20cm and 40cm), soil moisture (10cm, 20cm, 50cm, 100cm and 180cm) and soil heat flux (5cm, 10cm and 15cm). Please refer to the instruction document published with the data for specific header and other information.
Zhangye city meteorological bureau
The dataset of airborne Polarimetric L-band Multibeam Radiometers (PLMR) was acquired on 4 July, 2012, located along the riverway of Heihe River in the middle reaches of the Heihe River Basin. The aircraft took off at 10:50 am (UTC+8) from Zhangye airport and landed at 14:50 pm, with the flight time of 4 hours. The flight was performed in the altitude of about 1000 m and at the speed of about 220-250 km during the observation, corresponding to an expected ground resolution of about 300 m. The PLMR instrument flown on a small aircraft operates at 1.413 GHz (L-band), with both H- and V-polarizations at incidence angles of ±7.5°, ±21.5° and ±38.5°. PLMR ‘warm’ and ‘cold’ calibrations were performed before and after each flight. The processed PLMR data include 2 DAT files (v-pol and h-pol separately) and 1 KMZ file for each flying day. The DAT file contains all the TB values together with their corresponding beam ID, incidence angle, location, time stamp (in UTC) and other flight attitude information as per headings. The KMZ file shows the gridded 1-km TB values corrected to 38.5 degrees together with flight lines. Cautions should be taken when using these data, as the RFI contaminations are often higher than expected at v-polarization.
CHE Tao, Gao Ying, LI Xin
The No. 6 hydrological section is located at Gaoya Hydrological Station (100.433° E, 39.135° N, 1420 m a.s.l.) in the midstream of the Heihe River Basin, Zhangye city, Gansu Province. This hydrological section is for intercomparison of flow measurement between ADCP and manual method. The dataset contains recorded by the No. 6 hydrological section from 10 August, 2012 to 31 December, 2013. The width of this section is 58 meters. The water level was measured using an HOBO pressure range and the discharge was measured using cross-section reconnaissance by the StreamPro ADCP. The dataset includes the following parameters: water level (recorded every 30 minutes) and discharge. The missing and incorrect (outside the normal range) data were replaced with -6999. For more information, please refer to Li et al. (2013) (for hydrometeorological observation network or sites information), He et al. (2016) (for data processing) in the Citation section.
HE Xiaobo, LIU Shaomin, LI Xin, XU Ziwei
This dataset contains the data of the meteorological element gradient observation system of the Sidaoqiao superstation downstream of the Heihe Hydrometeorological Observation Network from January 1, 2014 to December 31, 2014. The site is located in Sidaoqiao, Dalaihu Town, Ejin Banner, Inner Mongolia. The underlying surface is Tamarix. The latitude and longitude of the observation point is 101.1374E, 42.0012N, and the altitude is 873m. The air temperature, relative humidity and wind speed sensors are respectively set at 5m, 7m, 10m, 15m, 20m and 28m, with 6 layers facing the north; the wind direction sensor is set at 15m, facing the north; the barometer is installed in the waterproof box. The tipping bucket rain gauge is installed at 28m; the four-component radiometer is installed at 10m, facing south; two infrared thermometers are installed at 10m, facing south, the probe orientation is vertically downward; two photosynthetically active radiometers are installed At 10m, facing south, and the probe is vertically upward and downward respectively; the soil moisture sensor is installed 2m on the south side of the tower body, and the soil heat flow plates (self-correcting type) (3 pieces) are buried in turn in the ground 6cm deep; The average soil temperature sensor TCAV is buried in the ground 2cm, 4cm; the soil temperature probe is buried in the ground surface 0cm and underground 2cm, 4cm, 10cm, 20cm, 40cm, 80cm, 120cm and 160cm; soil moisture sensors are buried in the underground 2cm, 4cm, 10cm, 20cm, 40cm, 80cm, 120cm and 160cm. Observed items include: wind speed (WS_5m, WS_7m, WS_10m, WS_15m, WS_20m, WS_28m) (unit: m/s), wind direction (WD_15m) (unit: degree), air temperature and humidity (Ta_5m, Ta_7m, Ta_10m, Ta_15m, Ta_20m, Ta_28m and RH_5m, RH_7m, RH_10m, RH_15m, RH_20m, RH_28m) (unit: centigrade, percentage), pressure (unit: hectopascal), precipitation (Rain) (unit: mm), four-component radiation (DR, UR, DLR_Cor, ULR_Cor, Rn) (unit: watts/square meter), surface radiation temperature (IRT_1, IRT_2) (unit: centigrade), up and down photosynthetically active radiation (PAR_U_up, PAR_U_down) (unit: micromol/square Msec), average soil temperature (TCAV) (unit: centigrade), soil heat flux (Gs_1, Gs_2, Gs_3) (unit: watts/square meter), soil moisture (Ms_2cm, Ms_4cm, Ms_10cm, Ms_20cm, Ms_40cm, Ms_80cm) , Ms_120cm, Ms_160cm) (unit: volumetric water content, percentage), soil temperature (Ts_0cm, Ts_2cm, Ts_4cm, Ts_10cm, Ts_20cm, Ts_40cm, Ts_80cm, Ts_120cm, Ts_160cm) (unit: centigrade). Processing and quality control of the observation data: (1) ensure 144 data per day (every 10 minutes), when there is missing data, it is marked by -6999; From September 8, 2014 to November 8, due to the sensor problems, the data is missing; on May 9, 2014, the soil moisture probe was re-buried, and the data before and after is inconsistent; (2) eliminate the moment with duplicate records; (3) delete the data that is obviously beyond the physical meaning or the range of the instrument; (5) the format of date and time is uniform, and the date and time are in the same column. For example, the time is: 2014-9-10 10:30; (6) the naming rules are: AWS+ site name. For hydrometeorological network or site information, please refer to Li et al. (2013). For observation data processing, please refer to Liu et al. (2011).
LIU Shaomin, LI Xin, CHE Tao, XU Ziwei, REN Zhiguo, TAN Junlei
This data mainly includes ten day runoff data of Yingluo gorge and Zhengyi gorge in Heihe River Basin, among which the time range of Yingluo gorge data is 1944-2010 and Zhengyi gorge data is 1947-2010. Source: Heihe River Basin Authority. Data unit: 100 million cubic meters / 10 days. Data format: Excel "Yingluo gorge 2" and "Yingluo gorge 2 (2)" in the data table are the ten day runoff data of Yingluo gorge, the same as "Yingluo gorge" in the data table, and Yingluo gorge 2 (2) contains the chart.
WANG Zhongjing
The dataset of ground truth measurement synchronizing with the airborne microwave radiometers (L&K bands) mission was obtained in the Linze station foci experimental area on Jul. 8, 2008. Observation items included: (1) soil moisture (0-5cm) measured by the cutting ring method (50cm^3) in P1 to P6 strips (17 sample points each). Photos were taken. The preprocessed soil volumetric moisture data were archived as Excel files. (2) surface radiative temperature measured by three handheld infrared thermometer (5# and 6# from Cold and Arid Regions Environmental and Engineering Research Institute, and one from Institute of Geographic Sciences and Natural Resources, which were all calibrated) from P1 to P6 strips. There are 34 sample points in total and each was repeated three times synchronizing with the airplane. Photos were taken. Data were archived as Excel files. See the metadata record “WATER: Dataset of setting of the sampling plots and stripes in the Linze station foci experimental area” for more information of the quadrate locations.
XIE Tingting, JIANG Hao, SONG Yi, BAI Yanfen, GAO Song, Qian Jinbo, SHU Lele, SONG Yi, XU Zhen, XIE Tingting, JIANG Hao, LI Shihua
This data is obtained by spatial interpolation and permafrost simulation through the surface temperature at 0 cm of nine stations in and outside the source area of the upper reaches of Heihe River. In the figure, 1 represents seasonal frozen soil and 2 represents permafrost. The data is in TIFF format, WGS-84 is used for projection, and the spatial range is 37.7263n-39.0976n, 98.5769e-101.1608e.
GE Shemin
This dataset includes data recorded by the Heihe integrated observatory network obtained from an observation system of Meteorological elements gradient of A’rou Superstation from January 1 to December 31, 2018. The site (100.464° E, 38.047° N) was located on a cold grassland surface in the Caodaban village, A’rou Town, Qilian County, Qinghai Province. The elevation is 3033 m. The installation heights and orientations of different sensors and measured quantities were as follows: air temperature and humidity profile (HMP45C; 1, 2, 5, 10, 15 and 25 m, towards north), wind speed profile (010C; 1, 2, 5, 10, 15 and 25 m, towards north), wind direction profile (020C; 2 m, towards north), air pressure (CS100; 2 m), rain gauge (TE525M; 5 m, towards south), four-component radiometer (CNR4; 5 m, towards south), two infrared temperature sensors (SI-111; 5 m, towards south, vertically downward), photosynthetically active radiation (PAR-LITE; 5 m, towards south, vertically upward), soil heat flux (HFP01SC; 3 duplicates, -0.06 m, 2 m in the south of tower), a TCAV averaging soil thermocouple probe (TCAV; -0.02, -0.04 m, 2 m in the south of tower), soil temperature profile (109; 0, -0.02, -0.04, -0.06, -0.1, -0.15, -0.2, -0.3, -0.4, -0.6, -0.8, -1.2, -1.6, -2, -2.4, -2.8 and -3.2 m, 3 duplicates in -0.04 m and -0.1 m), and soil moisture profile (CS616; -0.02, -0.04, -0.06, -0.1, -0.15, -0.2, -0.3, -0.4, -0.6, -0.8, -1.2, -1.6, -2, -2.4, -2.8 and -3.2 m, 3 duplicates in -0.04 m and -0.1 m). The observations included the following: air temperature and humidity (Ta_1 m, Ta_2 m, Ta_5 m, Ta_10 m, Ta_15 m and Ta_25 m; RH_1 m, RH_2 m, RH_5 m, RH_10 m, RH_15 m and RH_25 m) (℃ and %, respectively), wind speed (Ws_1 m, Ws_2 m, Ws_5 m, Ws_10 m, Ws_15 m and Ws_25 m) (m/s), wind direction (WD_2 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) (℃), photosynthetically active radiation (PAR) (μmol/(s m-2)), average soil temperature (TCAV, ℃), soil heat flux (Gs_1, Gs_2 and Gs_3) (W/m2), soil temperature (Ts_0 cm, Ts_2 cm, Ts_4 cm_1, Ts_4 cm_2, Ts_4 cm_3, Ts_6 cm, Ts_10 cm_1, Ts_10 cm_2, Ts_10 cm_3, Ts_15 cm, Ts_20 cm, Ts_30 cm, Ts_40 cm, Ts_60 cm, Ts_80 cm, Ts_120 cm, Ts_160 cm, Ts_200 cm, Ts_240 cm, Ts_280 cm and Ts_320 cm) (℃), and soil moisture (Ms_2 cm, Ms_4 cm_1, Ms_4 cm_2, Ms_4 cm_3, Ms_6 cm, Ms_10 cm_1, Ms_10 cm_2, Ms_10 cm_3, Ms_15 cm, Ms_20 cm, Ms_30 cm, Ms_40 cm, Ms_60 cm, Ms_80 cm, Ms_120 cm, Ms_160 cm, Ms_200 cm, Ms_240 cm, Ms_280 cm and Ms_320 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 average soil temperature was rejected during February 16 to March 31 and April 15 to May 20 because of broken of the sensor line; Soil heat flux were wrong occasionally during November to December. 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: 2018-9-10 10:30. (6) Finally, the naming convention was AWS+ site no. Moreover, suspicious data were marked in red. For more information, please refer to Liu et al. (2018) (for sites information), Liu et al. (2011) for data processing) in the Citation section.
LIU Shaomin, LI Xin, CHE Tao, XU Ziwei, ZHANG Yang, TAN Junlei
This data set includes the continuous observation data set of soil texture, roughness and surface temperature measured by the vehicle borne microwave radiometer and synchronous measurement from November 24-25, 2013 in the desert of Minle County, Zhangye City, Gansu Province. The surface temperature and humidity include four layers of temperature sensor at the soil depth of 1cm, 5cm, 10cm, 20cm, and the observation of soil temperature and soil moisture data at the soil depth of 0-5cm. The time frequency of routine observation of soil temperature and humidity is 5 minutes. Data details: 1. Time: November 24-25, 2013 2. data: Brightness temperature: observed by vehicle mounted multi frequency passive microwave radiometer, including 6.925, 18.7 and 36.5ghz V polarization and H polarization data (10.65ghz band damage, 18.7ghz h polarization damage) Soil temperature: use sensor installed on dt80 to measure 1cm, 5cm, 10cm, 20cm soil temperature Soil moisture: use h-probe sensor to measure 0-5cm soil moisture, the probe can measure 0-5cm soil temperature at the same time Soil texture: soil samples measured in Beijing Normal University Soil roughness: measured by roughness meter provided by northeast geography 3. Data size: 2.3m 4. Data format:. Xls
ZHAO Shaojie, KOU Xiaokang, YE Qinyu, MA Mingguo
The dataset of intensive runoff observations was obtained by the cup type current meter (made in Chongqing Hydrological Instrument Factory) in the Binggou watershed foci experimental area from Jan. 17, 2008 to Dec. 31, 2009. Data directions included: (1) the regular observation before Mar. 14, 2008, once per day; the intensive observation from Mar. 15, 2008 to Apr. 1, 2008, 7-8 times per day and even hourly for some intensive observations (2) three times (9, 14 and 19 BJT) per day from May 3, 2008 to Sep. 17, 2008; from Sep. 17, 2008 on, two times (9 and 18 BJT) per day; the water runoff by evenly spaced method, 20cm, 40cm and 80cm based on different situations The data were named after WATER_Runoff_BG_yyyymmdd-yyyymmdd.csv (WATER_Runoff_BG for Ginggou, yyyymmdd-yyyymmdd for the observation time). The missing data were marked "None".
BAI Yunjie, LI Hongyi, LI Zhe, XIN Bingjie
Agricultural irrigation, which accounts for about 80% of human water consumption, is the most important part of human water resources management and closely related to human survival and development.Irrigation is also an important part of the water cycle. Large-scale irrigation can affect the water cycle and even the local climate by affecting evapotranspiration.Excessive diversion of irrigation water will lead to unsustainable utilization of water resources, and at the same time, will reduce river flow and aquifer water reserves, thus harming the ecological environment. Therefore, determining the spatial and temporal distribution and variation of irrigation is critical to studying past human water use, the impact of irrigation on ecological and hydrological processes, the environment and climate, and the development of future irrigation plans. By integrating the irrigation amount of channel diversion water and irrigation amount of groundwater intake from different data sources, and combining the evapotranspiration data of land surface model CLM4.5 simulation and remote sensing inversion, a set of spatio-temporal continuous surface water and groundwater irrigation amount data set with spatial resolution of 30 arcseconds (0.0083 degrees) on the scale of 1981-2013 in heihe river basin was made. It has been verified that this data set has a high reliability from 2000 to 2013, and a lower reliability from 1981 to 1999 than from 2000 to 2013 due to the absence of remote sensing data and the absence of soil utilization changes. The document is described as follows: Monthly surfacewater irrigation volume file name: monthly_surfacewater_irrigation gation_1981-2013.nc Monthly groundwater_irrigation gation_1981-2013.nc The data is in netcdf format.There are three dimensions, which are month, lat, and lon. Where, month is a month, and the value is 0-395, representing each month from 1981 to 2013. Lat is grid latitude information, and lon is grid longitude information.
XIE Zhenghui
Soil survey data corresponding to the ejin delta and the ecological vegetation sample during the project implementation period. Soil profile sampling corresponding to the ecological vegetation survey in ejin delta (5), 20 cm stratified sampling.Investigation items included: soil salinity, soil organic matter, C, N, P, etc., time: August 2011.
YU Jingjie
Water demand in the middle and lower reaches of Heihe River (mainly including water demand for living, livestock, industry, agriculture, tertiary industry, artificial forest and grass ecology in the middle reaches of Heihe River in current year, 2020 and 2030; water demand for living, industry, tertiary industry and ecology in Ejina Banner in the middle reaches of Heihe River in current year, 2020 and 2030)
JIANG Xiaohui
This data set contains the eddy correlativity observation data of the euphrate poplar forest station downstream of heihe hydrometeorological observation network from January 1, 2015 to December 31, 2015.The station is located in Inner Mongolia ejin banner four bridge, under the surface is the euphorbia poplar forest.The longitude and latitude of the observation point are 101.1236e, 41.9928n and 876m above sea level.The rack height of the vortex correlativity instrument is 22m, 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 (Li7500) 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 0.2m/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 April 22, solstice and April 25, data was missing due to the calibration of the vortex system Li7500.August 17 solstice September 5, due to memory card problems, resulting in intermittent data. 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 Li et al. (2013), 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 set includes the continuous observation data set of light temperature and surface temperature and humidity measured by the vehicle borne microwave radiometer from November 10 to 14, 2013 in aroucaochang, arouxiang, Qilian County, Qinghai Province. The surface temperature and humidity include six layers of temperature sensor at the soil depth of 1cm, 3cm, 5cm, 10cm, 15cm, 20cm and six layers of humidity sensor at the soil depth of 0-5cm. The time frequency of routine observation of soil temperature and humidity is 5 minutes. Data details: 1. Time: November 10-14, 2013 2. data: Brightness temperature: observed by vehicle mounted multi frequency passive microwave radiometer, including 6.925, 10.65, 18.7 and 36.5ghz V polarization and H polarization data Soil temperature: use the sensor installed on dt80 and dt85 to measure the soil temperature of 1cm, 5cm, 10cm, 20cm, and 1cm, 3cm, 5cm, 10cm, 15cm, which is measured by the sensor connected to dt80 Soil moisture: use h-probe sensor to measure 0-5cm soil moisture, the probe can measure 0-5cm soil temperature at the same time 3. Data size: 16.7M 4. Data format:. Xls
ZHAO Shaojie, KOU Xiaokang, YE Qinyu, MA Mingguo
The dataset of ground truth measurement synchronizing with Envisat ASAR was obtained in No. 1, 2 and 3 quadrates of the A'rou foci experimental area on Jul. 5 and Jul. 6, 2008. The Envisat ASAR data were in AP mode and VV/VH polarization combinations, and the overpass time was approximately at 11:14 BJT. The quadrates were divided into 4×4 subsites, with each one spanning a 30×30 m2 plot. Observation items included: (1) the quadrate investigation in No. 2 and 3 quadrates: GPS by GARMIN GPS 76, plant species by manual cognition, the plant number by manual work, the height by the measuring tape repeated 4-5 times, phenology by manual work, the coverage by manual work (compartmentalizing 0.5m×0.5m into 100 to see the percentage the stellera takes) and the chlorophyll content by SPAD 502. (2) spectrum of stellera and pasture by ASD FieldSpec (350～2 500 nm), with 20% reference board. The preprocessed canopy spectrum was archived. (3) BRDF by ASD FieldSpec (350～2 500 nm), with 20% reference board. The processed reflectance and transmittivity were archived as .txt files. (4) photosynthesis of stellera and pasture by LI-6400. The data were archived in Excel format. (5) soil moisture by WET soil moisture tachometer. Acquisition time, soil moisture (%vol), Ecp (ms/m), Tmp Eb and Ecb (ms/m) of 25 corner points were archived. (6) the soil temperature by the handheld infrared thermometer. Acquisition time, the soil temperature measured three times and the land cover types were archived. The data included the canopy reflectance on Jul. 5 and 6, photosynthesis on Jul. 5 and 6, BRDF on Jul. 5, photos on Jul. 5, the infrared land surface temperature and soil moisture by WET on Jul. 5, biomass on Jul. 5 and the surface temperature along No. 3 flight on Jul. 6.
DING Songchuang, GE Yingchun, LI Hongyi, MA Mingguo, Qian Jinbo, WANG Yang, YU Yingjie, LIU Sihan
The dataset of ground truth measurements for snow synchronizing with Envisat ASAR was obtained in the Binggou watershed foci experimental area on Mar. 15, 2008. The Envisat ASAR data were acquired in AP mode and VV/VH polarization combinations, and the overpass time was approximately at 11:34 BJT. Observation items included: (1) Snow density, snow complex permittivity, snow volumetric moisture and snow gravimetric moisture by the snowfork in BG-B, BG-D, BG-E and BG-F; (2) Snow parameters including the snow surface temperature and the snow-soil interface temperature by the handheld infrared thermometer, the snow layer temperature by the probe thermometer, the snow grain size by the handheld microscope, snow density by the aluminum case, snow depth by the ruler, and the snow surface temperature synchronizing with ASAR in BG-H, BG-D, BG-E and BG-F; (3) The snow spectrum by the portable ASD (Xinjiang Meteorological Administration) synchronizing with ASAR in BG-H15; the major and minor axis and shape of the snow layer grain through the self-made snow sieve. Two files including raw data and the preprocessed data were archived.
BAI Yanfen, BAI Yunjie, GE Chunmei, HAO Xiaohua, LI Hongyi, LIANG Ji, SHU Lele, WANG Xufeng, XU Zhen, MA Mingguo, QU Wei, REN Jie, CHANG Cun, DOU Yan, MA Zhongguo, LIU Yan, ZHANG Pu
Data source: China l Meteorological Administration Network; Data Content: Daily Rainfall Data Series of Heihe River Basin from 1990 to 2004; Evaporation Data of Heihe River Basin from 2000 to 2012. Data Spatial Range: Rainfall Data (Yingluoxia, Shandan, Gaoya, Pingchuan, Ganzhou Pingshan Lake, Zhengyixia Gorge, Liyuan River); Evaporation Data (Zhangye, Gaotai, Dingxin, Jiuquan, Jinta, Shandan, Ejina, Hequ)
WANG Zhongjing, ZHENG Hang
The dataset of snow density measurements was obtained in the Binggou watershed foci experimental area on Dec. 6 and Dec. 10, 2007 during the pre-observation period, to survey the snow layer and acquire the snow density for retrieval and modeling from remote sensing approaches. Observation items included: (1) Snow layer density: measured by snow shovel weighing method. Each 10cm was a unit. (2) Snow density, snow depth, snow temperature, snow-soil interface temperature, and snow grain size in BG-A. Measured were carried out in BG-A on Dec. 6, 2007, and in BG-B, BG-C and BG-D on Dec. 10, 2007. The dataset includes raw data and processed data plus GPS and calibration data for the snow shovel.
HAO Xiaohua, LIANG Ji, WANG Xufeng
The dataset of ground truth measurements for snow synchronizing with EO-1 Hyperion and Landsat TM was obtained in the Binggou watershed foci experimental area on Mar. 17, 2008. Observation items included: (1) Snow parameters as snow depth by the ruler, the snow layer temperature by the probe thermometer, the snow grain size by the handheld microscope, the snow surface temperature and the snow-soil interface temperature by the handheld infrared thermometer simultaneous with the satellite in BG-A, BG-E, BG-F and BG-H. (2) Snow density, snow complex permittivity, snow volumetric moisture and snow gravimetric moisture by the Snowfork in BG-A, BG-E and BG-H. Besides, 25-hour fixed-point continuous observation was carried out at the Binggou cold region hydrometerological station. (3) The snow spectrum by ASD (Xinjiang Meteorological Administration) (4) Snow albedo by the total radiometer Two files including raw data and preprocessed data were archived.
BAI Yanfen, BAI Yunjie, GE Chunmei, HAO Xiaohua, LIANG Ji, SHU Lele, WANG Xufeng, XU Zhen, ZHU Shijie, MA Mingguo, CHANG Cun, DOU Yan, MA Zhongguo, JIANG Tenglong, XIAO Pengfeng , LIU Yan, ZHANG Pu
Data of industrial structure change and water use evolution trend of social and economic development in Heihe River Basin
DENG XiangZheng
The object of this dataset is to support the atmospheric correction data for the satellite and airborne remote-sensing. It provides the atmospheric aerosol and the column content of water vapor. The dataset is sectioned into two parts: the conventional observations data and the observations data synchronized with the airborne experiments. The instrument was on the roof of the 7# in the Wuxing Jiayuan community from 1 to 24 in June. After 25 June, it was moved to the ditch in the south of the Supperstaiton 15. The dataset provide the raw observations data and the retrieval data which contains the atmosphere aerosol optical depth (AOD) of the wavebands at the center of 1640 nm, 1020 nm, 936 nm, 870 nm, 670 nm, 500 nm, 440 nm, 380 nm and 340 nm, respectively, and the water vapor content is retrieved from the band data with a centroid wavelength of 936 nm. The continuous data was obtained from the 1 June to 20 September in 2012 with a one minute temporal resolution. The time used in this dataset is in UTC+8 Time. Instrument: The sun photometer is employed to measure the character of atmosphere. In HiWATER, the CE318-NE was used.
YU Wenping, WANG Zengyan, MA Mingguo
The dataset of the drop spectrometer (PARSIVEL) observations was obtained at an interval of 30 seconds in the arid region hydrology experiment area from May 18 to Jul. 5, 2008. The site was chosen in Xiaoman township (38.86°N, 100.41°E, 1515m), Ganzhou district, Zhangye city, Gansu province. The data mainly included the raindrop grain size and the terminal velocity. Besides, dual polarized radar (X-band) parameters such as ZDR and KDR could be further developed based on those data. The sampling area of PARSIVEL was 5400mm^2; the liquid grain diameter was from 0.2-5mm, and the solid grain diameter was from 0.2-25mm.
CHU Rongzhong, ZHAO Guo, HU Zeyong, ZHANG Tong, JIA Wei
Vegetation functional type (PFT) is the combination of large plant species according to the ecosystem function of plant species and the way of resource utilization. Each plant functional type shares similar plant properties, which simplifies the diversity of plant species to the diversity of plant function and structure.Vegetation functional types have been used in the dynamic global vegetation model (DGVM) to predict changes in ecosystem structure and function under global change scenarios.The 1km vegetation functional pattern map of heihe basin is based on the 1km land cover map of heihe basin (MICLCover subset of heihe basin), and is divided by using the vegetation functional climate rules proposed by Bonan et al. (2002).The climate data utilize the 0.1 degree atmospheric drive data of he jie and Yang kun, developing China region from 1981 to 2008.This map can be used in the land surface process model of heihe river basin.
RAN Youhua
This data set contains meteorological element observation data from January 1, 2014 to December 31, 2014 from the burg station upstream of heihe hydrometeorological observation network.The station is located in caochang, qilian county, qinghai province.The latitude and longitude of the observation point is 100.9151e, 37.9492n and 3294m 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 thermometers are installed at 6m, facing due south, and the probe facing vertically 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: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, Ts_160cm) (unit: volumetric water content, percentage). 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 temperature of 4cm soil was between May 31, 2014 and June 17, 2014. Due to sensor problems, data was 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: 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).
LI Xin, CHE Tao, XU Ziwei, ZHANG Yang, TAN Junlei
The dataset of soil moisture profile observations (5cm, 10cm, 20cm and 40cm) was obtained in the Linze grassland foci experimental area from May 24 to Jun. 30, 2008. Four points, with various underlying surface and depth in each plot of A, B, C, D and E, were measured by the cutting ring. Data were archived in Excel and Word file. See WATER: Dataset of setting of the sampling plots and stripes in the foci experimental area of Linze station for more information.
YU Fan, FENG Lei, LIANG Wenguang, ZHU Xiaohua, Wang Weizhen, HAN Xujun, WU Yueru, CHAO Zhenhua, WANG Xufeng, LI Xiaoyu, Wang Jing
The dataset of the discrimination of C3/C4 species was obtained by the handheld GPS and the digital camera in the Linze station foci experimental area on Jul. 10, 2008. Data fields included Gps, Longitude, Latitude, Photo_num and Describe (descriptions on C3/C4 vegetation and photos).
CHENG Zhanhui, Liu Liangyun
This dataset contains the flux measurements from site No.2 eddy covariance system (EC) in the flux observation matrix from 3 June to 21 September, 2012. The site (100.35406° E, 38.88695° N) was located in a cropland (maize surface) in Yingke irrigation district, which is near Zhangye, Gansu Province. The elevation is 1559.09 m. The EC was installed at a height of 3.7 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.
LIU Shaomin, LI Xin, XU Ziwei
In 2007, 2008 and 2009, ENVISAT ASAR data 179 scenes, covering the whole Heihe River Basin. Among them, there were 63 in 2007, 71 in 2008 and 45 in 2009. Imaging mode and acquisition time are respectively: app can select polarization mode from August 15, 2007 to December 23, 2007, from January 02, 2008 to December 202009-02-15, 2008 to September 06, 2009; imp imaging mode from June 19, 2009 to July 12, 2009; WSM wide mode from January 1, 2007 to December 302008-01-01, 2007 to November 28, 2008, from March 13, 2009 to May 22, 2009. The product level is L1B, which is amplitude data without geometric correction. The ENVISAT ASAR remote sensing data set of Heihe comprehensive remote sensing joint experiment is mainly obtained through the China EU "dragon plan" project (Project No.: 5322 and 5344); the WSM wide model data in 2007 and January 2008 are obtained from Professor Bob Su of ITC; the 8-view app can be purchased from the earth observation and digital earth center of Chinese Academy of Sciences.
Institute of Remote Sensing and Digital earth, Chinese Academy of Sciences
The dataset of precipitation and canopy interception observations was obtained in the Pailugou watershed foci experimental area from Jul. 4 to Sep. 28, 2007, and May 8 to Sep. 27, 2008, respectively. 18 interception slots were set in three plots and the detailed information was as follows: Plot number slot number in the Qinghai spruce forest Ⅰ 1, 2, 3, 4, 5, 6 Ⅱ 7, 8, 9, 10, 11, 12 Ⅲ A, B, C, D, E, F Observation items included controlled rainfall, the forest throughfall, the stem flow and the moss and litter interception barrel throughfall.
WANG Shunli, LUO Longfa, JING Wenmao, WANG Rongxin, ZHANG Xuelong, NIU Yun
The data is the digitization of the Heihe River basin part of the 1:1 million Vegetation Atlas of China, 1:1000, 000 Vegetation Atlas of China is edited by academician Hou Xueyu, a famous vegetation ecologist (Hou Xueyu, 2001). It is jointly compiled by more than 250 experts from 53 units such as research institutes of Chinese Academy of Sciences, relevant ministries and commissions, relevant departments of various provinces and regions, colleges and universities. It is another summative achievement of vegetation ecologists in China over 40 years after the publication of monographs such as vegetation of China Basic map of natural resources and natural conditions of the family. It is based on the rich first-hand information accumulated by vegetation surveys carried out throughout the country over the past half century, and the materials obtained by modern technologies such as aerial remote sensing and satellite images, as well as the latest research achievements in geology, soil science and climatology. It reflects in detail the distribution of vegetation units of 11 vegetation type groups, 796 formations and sub formations of 54 vegetation types, horizontal and vertical zonal distribution laws, and also reflects the actual distribution of more than 2000 dominant species of plants, major crops and cash crops in China, as well as the close relationship between dominant species and soil and ground geology. The atlas is a kind of realistic vegetation map, reflecting the recent quality of vegetation in China.
HOU Xueyu
1. The data set is the soil water content data set of the upper reaches of Heihe River Basin, and the data is the measured data of location points from 2013 to 2014. 2. The infiltration data is measured with ech2o. Including 5 layers of soil moisture content and soil temperature 3. Some instruments lack of data due to insufficient battery life, broken roads, stolen instruments and other reasons
HE Chansheng
This data set contains the surface temperature and surface emissivity products retrieved from 12 ASTER data in the middle reaches of Heihe River Basin in 2012. The 12 scenes ASTER data all cover the ecological and hydrological experimental area of the middle reaches artificial oasis. The acquisition time (Beijing time) is: 2012-05-302012-06-152012-06-242012-07-102012-08-02, 2012-08-112012-08-182012-08-272012-09-03, 2012-09-122012-09-192012-09-28. The transit time of the above data is around 12:15 (Beijing time). Firstly, the L1B data is corrected by aster L3 data, and then the L1B data is corrected by MODIS mod07 atmospheric profile product with the same transit time and the atmospheric radiation transfer model MODTRAN. In order to improve the accuracy of atmospheric correction, the water vapor scaling (WVS) atmospheric correction method is used. Finally, the aster temperature emissivity separation (TES) algorithm is used to retrieve the surface temperature and the surface emissivity of five bands. The results show that the average deviation of surface temperature products is less than 0.5K and RMSE is less than 2K. This data set can provide reliable input data for remote sensing estimation of key water and heat variables of heterogeneous surface.
LI Hua, WANG Heshun
The dataset of ground truth measurements synchronizing with MODIS was obtained in C1, W2 and B2 of the Biandukou foci experimental area from 12:00-15:00 on Mar. 14, 2008. Observation items included: (1) the frost depth from 11:37-12:11 by the chopstick and the ruler. The soil was considered frozen when it was hard and with ice crystal. The cover type photos were archived. (2) the gravimetric soil moisture (soil samples from 0-1cm, 1-3cm, 3-5cm, 5-10cm and 10-20cm) by the microwave drying method. (3) the surface radiative temperature by the handheld infrared thermometer and the physical temperature by the thermocouple thermometer. (4) the soil roughness, which can be acquired from related dataset of other period.
CHANG Sheng, Fang Qian, QU Ying, LIANG Xingtao, LIU Zhigang, PAN Jinmei, PENG Danqing, REN Huazhong, ZHANG Yongpan, ZHANG Zhiyu, ZHAO Shaojie, Zhao Tianjie, ZHENG Yue, Zhou Ji, LIU Chenzhou, YIN Xiaojun, ZHANG Zhiyu
The No. 1 hydrological section is located at 213 Heihe River Bridge (100.345° E, 38.912° N, 1546 m) in the midstream of the Heihe River Basin, Zhangye city, Gansu Province. The dataset contains observations recorded by the No.1 hydrological section from 13 June, 2012, to 6 September, 2013. This section consists of two river sections, i.e., the east section,which is denoted as No. 1 and the west section, which is denoted as No. 2. The width of this section is 330 meters and consists of a gravel bed; the cross-sectional area is unstable because of human factors. The water level was measured using an SR50 ultrasonic range and the discharge was measured using cross-section reconnaissance by the StreamPro ADCP. The dataset includes the following parameters: water level (recorded every 30 minutes) and discharge. The missing and incorrect (outside the normal range) data were replaced with -6999. For more information, please refer to Li et al. (2013) (for hydrometeorological observation network or sites information), He et al. (2016) (for data processing) in the Citation section.
HE Xiaobo, LIU Shaomin, LI Xin, XU Ziwei
The dataset of airborne Polarimetric L-band Multibeam Radiometers (PLMR) was acquired on 30 June, 2012, located in the middle reaches of the Heihe River Basin. The aircraft took off at 13:10 pm (UTC+8) from Zhangye airport and landed at 18:40 pm, with the flight time of 5.5 hours. The flight was performed in the altitude of about 2500 m and at the speed of about 220-250 km during the observation, corresponding to an expected ground resolution of about 750 m. The PLMR instrument flown on a small aircraft operates at 1.413 GHz (L-band), with both H- and V-polarizations at incidence angles of ±7.5°, ±21.5° and ±38.5°. PLMR ‘warm’ and ‘cold’ calibrations were performed before and after each flight. The processed PLMR data include 2 DAT files (v-pol and h-pol separately) and 1 KMZ file for each flying day. The DAT file contains all the TB values together with their corresponding beam ID, incidence angle, location, time stamp (in UTC) and other flight attitude information as per headings. The KMZ file shows the gridded 1-km TB values corrected to 38.5 degrees together with flight lines. Cautions should be taken when using these data, as the RFI contaminations are often higher than expected at v-polarization.
CHE Tao, Gao Ying, LI Xin
The dataset includes the saturated hydraulic conductivity data of typical soil samples in Heihe River Basin from July 2012 to August 2013. The collection method of typical soil sample points in Heihe River Basin is representative sampling, which means that the typical soil types in the landscape area can be collected, and the sample points with higher representativeness can be collected as much as possible, and the saturated hydraulic conductivity of each type of soil can be measured three times for the average value.
ZHANG Ganlin,
This data set contains meteorological element observation data of huazhaizi desert station in the middle reaches of heihe hydrological meteorological observation network from January 1, 2016 to December 31, 2016.The station is located in huazhaizi, zhangye city, gansu province.The latitude and longitude of huazhaizi station is 100.3201E, 38.7659N and 1731m above sea level.The observation items include: air temperature and relative humidity sensors at 5m and 10m, facing due north;Install the barometer inside the waterproof box;The tilting bucket rain gauge is installed at 10m;The wind speed and direction sensor is set at 5m and 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.Specific observation elements are as follows: 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 observation data :(1) ensure 144 data elements of observation data every day (every 10min), and mark by -6999 in case of data missing;Due to the problem of the wind speed and direction sensor, the observed wind speed of 10m was missing between December and January 29, 2016;The data of soil heat flux G2 was missing from July 5 to August 17 due to the probe problem.(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: 2016-6-10-10:30;(6) the naming rule is: AWS+ site name. For information of hydrometeorological network or station, please refer to Li et al. (2013), and for observation data processing, please refer to Liu et al. (2011).
LIU Shaomin, LI Xin, CHE Tao, XU Ziwei, REN Zhiguo, TAN Junlei
The annual total net primary productivity (NPP) and average productivity of different ecosystems in heihe river basin from 1998 to 2002 were estimated by using the light energy utilization model c-fix, high spatial and temporal resolution remote sensing data of SPOT/VEGETATION, global grid meteorological reanalysis data and land use map of heihe river basin. From 1998 to 2002, the 10-day 1-km resolution SPOT VEGETATATION NDVI (10-day maximum synthesis) data product in the heihe basin, provided by the image processing and archiving center (CTIV) of VITO institute, Belgium, was used to calculate the key parameters fAPAR required by the c-fix model. The daily temperature and total radiation of heihe river basin from 1998 to 2002 were obtained using a global 1.5 °× 1.5 ° grid meteorological data product from MeteoFrance. It contains the spatial distribution pattern of annual accumulation of NPP in heihe basin and the seasonal dynamic map of NPP.The spatial resolution of this data is 1km.
LU Ling
This data set is one of the results of the project "Determination of Cultivated Land Use Coefficient and Land Use Change Research in Zhangye City". It is a land use database in Zhangye City based on Landsat TM and ETM remote sensing data. The land use data adopts a hierarchical land cover classification system, which divides the land use types of Zhangye City into 6 first-class categories (cultivated land, forest land, grassland, water area, land for urban and rural industrial and mining residents and unused land) and 25 second-class categories. The data range includes Shandan, Minle, Linze, Gaotai, Sunan Yugu Autonomous County and Ganzhou District. The classification standard adopts the land use classification standard used by the Chinese Academy of Sciences since 1986. The data type is vector polygon and stored in Shape format. The data range covers Zhangye City.
HU Xiaoli, WANG Jianhua, LI Xin
1、 Data Description: from May 2013 to July 2014, the observation frequency of automatic observation data is 1 time / 15 minutes. The solinst levellogger automatic water level gauge is used to observe the river water level, and the flow data is calculated through the water level flow curve. The actual flow observation is manually observed through the self-made flow weir (see the thumbnail). Due to the limited amount of manual observation data, further supplementary observation is needed to improve the water level discharge curve. 2、 Sampling location: it is located at the outlet catchment of the alluvial delta Valley, and the south side is the shrub area. A small flow weir is built. Coordinates of observation points (99 ° 52 ′ 58 ″ e, 38 ° 14 ′ 36 ″ n)
SUN Ziyong, CHANG Qixin
This data set contains cosmic ray instrument (CRS) observations from January 1, 2014 to December 31, 2014.The station is located in gansu province zhangye city da man irrigated area farmland, under the surface is corn field.The longitude and latitude of the observation point are 100.3722e, 38.8555n, and 1556m above sea level. The bottom of the instrument probe is 0.5m from the ground, and the sampling frequency is 1 hour. The original observations of the cosmic ray instrument (CRS1000B) included: voltage Batt (V), temperature T (c), relative humidity RH (%), pressure P (hPa), fast neutron number N1C (hr), thermal neutron number N2C (hr), fast neutron sampling time N1ET (s) and thermal neutron sampling time N2ET (s).The data published are processed and calculated. The data headers include Date Time, P (pressure hPa), N1C (fast neutron number/hour), N1C_cor (fast neutron number/hour with revised pressure) and VWC (soil volume moisture content %). The main processing steps include: 1) data filtering There are four criteria for data screening :(1) data with voltage less than and equal to 11.8 volts are excluded;(2) remove the data of air relative humidity greater than and equal to 80%;(3) data whose sampling interval is not within 60±1 minute are excluded;(4) the number of fast neutrons removed changed by more than 200 in one hour compared with that before and after.In addition, the missing data was supplemented by -6999. 2) air pressure correction According to the fast neutron pressure correction formula mentioned in the instrument instruction manual, the original data were revised to obtain the revised fast neutron number N1C_cor. 3) instrument calibration In the process of calculating soil moisture, N0 in the calculation formula should be calibrated.N0 is the number of fast neutrons under the condition of soil drying. The measured soil moisture (or through relatively dense soil moisture wireless sensor) m (Zreda et al. (1) Where m is mass water content, N is the number of fast neutrons after revision, N0 is the number of fast neutrons under dry conditions, a1=0.079, a2=0.64, a3=0.37 and a4=0.91 are constant terms. Here, the instrument was calibrated according to Soilnet soil water data in the source area of the instrument, and the relationship between soil volumetric water content (v) and fast neutrons was established according to the actual situation. In formula (1), m was replaced by v.Selected dry wet condition are the obvious difference of June 26-27 June and July 16 - July 17 four days of data, including June 26-27 rate data showed that soil moisture is small, so the selection of 4 cm, 10 and 20 cm as the rate of the three values of average data, its range is 22% 30%, and July 16 - July 17 rate data showed that soil moisture is bigger, so select 4 cm and 10 cm as two value average rate data, the range of 28% - 39%,Finally, the average values of crs_a and crs_b, N0, were 3252 and 3597, respectively. 4) soil moisture calculation According to formula (1), the hourly soil water content data is calculated. Please refer to Liu et al. (2018) for information of hydrometeorological network or site, and Zhu et al. (2015) for observation data processing.
LIU Shaomin, ZHU Zhongli, LI Xin, XU Ziwei
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