The dataset of LST (Land Surface Temperature) observations was obtained by three handheld infrared thermometers (5# and 6# from Cold and Arid Regions Environmental and Engineering Research Institute, and also one from Institute of Geographic Sciences and Natural Resources, which were all calibrated) in the Linze station foci experimental area. The temperature was measured 14-30 times in 40 subplots of the west-east desert strip on May 24, 25 and 28, 2008, 12-30 times in 9 subplots of north-south strip on May 24, 25 and 28, 17 times from P1 to P6 strips on Jul. 4 and 8, three times of 147 points along LY06 strip on Jun. 6, 15, 29 and Jul. 11, LY07 strip on May 30, Jun. 6, 15, 29 and Jul. 11 and LY08 strip on May 30, Jun. 6 and 10, and three times in Wulidun farmland quadrates on May 25, Jun. 29 and Jul. 11. Calibration was carried out in the desert on May 25, and in Pingchuan reservoir on May 30. 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.
BAI Yanfen, SONG Yi, DING Songchuang, GAO Song, HAO Xiaohua, PAN Xiaoduo, Qian Jinbo, SHU Lele, SONG Yi, WANG Yang, XU Zhen, YAN Qiaodi, ZHU Shijie, YU Yingjie, DONG Jian, JIANG Hao, LI Shihua
This dataset contains the flux measurements from site No.9 eddy covariance system (EC) in the flux observation matrix from 4 June to 17 September, 2012. The site (100.38546° E, 38.87239° N) was located in a cropland (maize surface) in Yingke irrigation district, which is near Zhangye, Gansu Province. The elevation is 1543.34 m. The EC was installed at a height of 3.9 m; the sampling rate was 10 Hz. The sonic anemometer faced north, and the separation distance between the sonic anemometer and the CO2/H2O gas analyzer (Gill&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
The dataset of airborne Polarimetric L-band Multibeam Radiometers (PLMR) was acquired on 10 July, 2012, located in the middle reaches of the Heihe River Basin. The aircraft took off at 10:30 am (UTC+8) from Zhangye airport and landed at 15:30 pm, with the flight time of 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
Background: this data interchange is the first data interchange of the key project of "integrated study of eco-hydrological processes in heihe basin", "genomics research on drought tolerance mechanism of typical desert plants in heihe basin".The main research targets of the key projects is a typical sand desert plants are Holly, using the current international advanced a new generation of gene sequencing technology to the whole genome sequence and gene transcription of Holly group sequence decoding, so as to explore related to drought resistance gene and gene groups, and transgenic technology in model to verify their drought resistance in plants. Process and content: as genome sequencing requires special sequencing equipment, the project is huge and the process is complex (mainly including genome library construction, sequencing, data analysis and genome assembly), so it needs to be completed by a professional sequencing company.After contacting with sequencing companies, we learned that before sequencing an unknown genome, the size and complexity of the genome should be predicted, which is a necessary prerequisite for designing sequencing schemes and strategies.Therefore, in 2013, we mainly predicted the chromosome composition, genome size and complexity of sand Holly, and successfully established the extraction and purification method of its genomic DNA.The results showed that the plant was diploid, the genome was composed of 9 staining lines (18 lines of diploid), and the genome size was 1.07G.The quality test results of the genomic DNA indicated that the requirements of the obtained DNA complex sequencing have been sent to the sequencing company for library construction and sequencing, which is now in progress.In addition, in order to obtain a large number of uniform plant materials, we have discussed the induction of callus, which has been successful.Due to these reasons, we were unable to complete the genome sequencing and submit the relevant data of sand Holly in accordance with the original plan of the project this year, mainly because we did not count the predicted contents of the genome before. Data usage: the data obtained in this year on ploidy, karyotype composition and genome size of lycopodium SPP.The success of the callus induction provides a high-quality material guarantee for the subsequent transcriptome sequencing and drought-resistance mechanism research experiments, and it is also a new contribution to the cytological and physiological research of the plant.
HE Junxian, GU Lifei
This data set contains the eddy correlation-meter observation data of the mixed forest station downstream of heihe hydrometeorological observation network from March 16, 2016 to December 31, 2016.The station is located in Inner Mongolia ejin banner four road bridge, under the surface is populus and tamarix.The longitude and latitude of the observation point are 101.1335e, 41.9903n and 874 m 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.April 21 solstice April 23 due to instrument calibration, data is missing.Suspicious data caused by instrument drift, etc., are identified in red font.When 10Hz data is missing due to a problem with the storage card (3.16-4.21), the data will be replaced by the 30min 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 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 dataset includes the emissivity spectrum of typical ground objects in middle researches of the Heihe river basin. This dataset was acquired in oasis, desert, Gobi and wetland of experiment area. Time range starts from 2012-05-25 to 2012-07-18 (UTC+8). Instrument: MODEL 102F PORTABLE FTIR (Fourier Transform Infrared Spectrometer), Handheld infrared thermometer. Measurement methods: at the first step, measure the thermal radiance of cold blackbody, warm blackbody, sample and gold plate (Downwelling Radiance). The radiance of cold blackbody and warm blackbody was used to calibrate the instrument, and eliminate the “noise” caused by the device itself. The retrieval of emissivity and temperature was then performed using iterative spectrally smooth temperature-emissivity separation (ISSTES) algorithm. The retrieved emissivity spectrum range from 8 to 14 μm, with spectral resolution of 4cm-1. Dataset contains the original recorded spectra (in ASCII format) and the log files (in doc format). The processed data are emissivity curves (ASCII) that ranged from 8 to 14 μm, and the temperatures of samples. Thermal photos of the sample, digital photo of the scene and the object are recorded in some cases.
MA Mingguo
A small lysimeter was made by ourselves, which simulated the natural conditions and selected typical desert plants as the object to study the water consumption and its law. Repeat 3 times for each plant. In 2011, the experiment of physiological water demand and water consumption of desert plants was carried out with the soil water content kept at (50 ± 10)% of the field water capacity; in 2012, the experiment of physiological water demand and water consumption was carried out with the soil water content kept at (20 ± 5)% of the field water capacity under stress.
SU Peixi
The dataset of ground truth measurement synchronizing with the airborne imaging spectrometer (OMIS-II) mission was obtained in the Linze station foci experimental area on Jun. 6, 2008. Observation items included: (1) soil moisture (0-5cm) measured by the cutting ring (50cm^3) along LY06, LY07 and LY08 strips (repeated nine times). The preprocessed soil volumetric moisture data were archived as Excel files. (2) surface radiative temperature measured by three handheld infrared thermometers (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) in LY06 and LY07 strips. There are 49 sample points in total and each was repeated three times synchronizing with the airplane. 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.
GAO Song, HAO Xiaohua, PAN Xiaoduo, Qian Jinbo, SONG Yi, WANG Yang
The 1km / 5day vegetation index (NDVI / EVI) data set of Heihe River basin provides a 5-day resolution NDVI / EVI composite product in 2015. The data uses the characteristics of China's domestic FY-3 satellite data with high time resolution (1 day) and spatial resolution (1km) to construct a multi angle observation data set. Based on the analysis of the multi-source data set and the existing composite vegetation index products and algorithms A global synthetic vegetation index product algorithm system based on multi-source data set is proposed. The vegetation index synthesis algorithm of MODIS is basically adopted, that is, the algorithm system of BRDF angle normalization method, cv-mvc method and MVC method based on the semi empirical walthal model. Using the algorithm system, the composite vegetation index is calculated for the first level data and the second level data, and the quality is identified. Multi-source data sets can provide more angles and more observations than a single sensor in a limited time. However, due to the difference of on orbit running time and performance of sensors, the observation quality of multi-source data sets is uneven. Therefore, in order to make more effective use of multi-source data sets, the algorithm system first classifies the quality of multi-source data sets, which can be divided into primary data, secondary data and tertiary data according to the observation rationality. The third level data are observations polluted by thin clouds and are not used for calculation. In the middle reaches of Heihe River, the verification results of farmland and forest areas show that the NDVI / EVI composite results of combined multi temporal and multi angle observation data are in good agreement with the ground measured data (RMSE = 0.105). Compared with the time series of MODIS mod13a2 product, it fully shows that when the time resolution is increased from 16 days to 5 days, a stable and high-precision vegetation index can describe the details of vegetation growth in detail. In a word, the NDVI / EVI data set of Heihe River Basin, which is 1km / 5day, comprehensively uses multi temporal and multi angle observation data to improve the estimation accuracy and time resolution of parameter products and better serves the application of remote sensing data products.
LI Jing, LIU Qinhuo, ZHONG Bo, YANG Aixia
Precipitation is one of the elements of meteorological monitoring and a measurement basis of regional precipitation. Precipitation is the only source of water for plants’ survival in mountain areas. Therefore, precipitation is the main link of the forest hydrological cycle. This data only provides precipitation of the Pailugou watershed during the growing season.
CHANG Xuexiang
The dataset of surface roughness measurements was obtained in No. 1 and 2 quadrates of the E’bao foci experimental area during the pre-observation period. Both the quadrates were divided into 3×3 subsites, with each one spanning a 30×30 m2 plot. With the roughness board 110cm long and the measuring points distance 1cm, the samples were collected along the strip 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 calculated 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 archived. The roughness data 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 validation.
CAO Yongpan, CHAO Zhenhua, CHE Tao, QIN Chun, WU Yueru,
The 1km / 5day vegetation index (NDVI / EVI) data set of Heihe River basin provides a 5-day resolution NDVI / EVI composite product from 2011 to 2014. The data uses the characteristics of FY-3 data, a domestic satellite, with high time resolution (1 day) and spatial resolution (1km), to construct a multi angle observation data set, which is the basis for analyzing multi-source data sets and existing composite vegetation index products and algorithms On the basis of this, an algorithm system of global composite vegetation index production based on multi-source data set is proposed. The vegetation index synthesis algorithm of MODIS is basically adopted, that is, the algorithm system of BRDF angle normalization method, cv-mvc method and MVC method based on the semi empirical walthal model. Using the algorithm system, the composite vegetation index is calculated for the first level data and the second level data, and the quality is identified. Multi-source data sets can provide more angles and more observations than a single sensor in a limited time. However, due to the difference of on orbit running time and performance of sensors, the observation quality of multi-source data sets is uneven. Therefore, in order to make more effective use of multi-source data sets, the algorithm system first classifies the quality of multi-source data sets, which can be divided into primary data, secondary data and tertiary data according to the observation rationality. The third level data are observations polluted by thin clouds and are not used for calculation. In the middle reaches of Heihe River, the verification results of farmland and forest areas show that the NDVI / EVI composite results of combined multi temporal and multi angle observation data are in good agreement with the ground measured data (RMSE = 0.105). Compared with the time series of MODIS mod13a2 product, it fully shows that when the time resolution is increased from 16 days to 5 days, a stable and high-precision vegetation index can describe the details of vegetation growth in detail. In a word, the NDVI / EVI data set of Heihe River Basin, which is 1km / 5day, comprehensively uses multi temporal and multi angle observation data to improve the estimation accuracy and time resolution of parameter products and better serves the application of remote sensing data products.
LI Jing, LIU Qinhuo, ZHONG Bo, YANG Aixia
This dataset contains soil organic matter content 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 refers to the collection of typical soil types in the landscape area and the collection of highly representative sample points as far as possible.Soil samples from each profile were taken on the basis of diagnostic layers and diagnostic characteristics, classified according to the Chinese soil system.
ZHANG Ganlin
1. Data overview The data set of the base camp integrated environmental observation system is a set of ENVIS (IMKO, Germany) which was installed at the base camp observation point by qilian station.It is stored automatically by ENVIS data mining system. 2. Data content This data set is the scale data from January 1, 2011 to December 31, 2011.It mainly includes two layers of temperature, humidity and wind, six layers of soil water content, precipitation, 5cm geothermal flux, total radiation, seven layers of soil temperature, CO2 and air pressure. 3. Space and time scope Geographical coordinates: longitude: 99° 53’e;Latitude: 38°16 'N;Height: 2980.2 m
CHEN Rensheng, HAN Chuntan
All data in this data set are original data, including meteorological and soil moisture content, stem sap flow, water potential of plant tissue, isotope characteristics of atmospheric and humidified water vapor, fluorescence tracer image, plant photosynthetic fluorescence, and basic data of five desert plants, Tamarix chinensis, Haloxylon ammodendron, Bawang, Nitraria tangutorum and red sand, which are related to field and indoor control experiments Because of the data of expression regulation. 1. Isotopic data of Tamarix chinensis. After humidifying for 1 hour, 2 hours and 3 hours, the tissue samples of indoor and outdoor plants of plexiglass were collected at the same time. The samples were put forward and processed by low-temperature vacuum distillation glass water extraction system, and then used euro The isotopic data were measured by ea3000 element analyzer and isoprime gas stability mass spectrometer. Tamarix Tamarix samples were collected from Sitan village, Jingtai County, including humidification and control samples. The variation data of isotopic composition can be used to determine the way and amount of water vapor absorbed by plant leaves. 2. Fluorescence section photo data: all the data in this data set are original data, including the structural photos under high-power microscope of Tamarix, Haloxylon ammodendron, Nitraria, Bawang, Hongsha and other desert plant leaves in Sitan village of Jingtai County and Ejin Banner. The specific method is as follows: apply fluorescent dye to the surface of desert plant leaves before humidification, collect plant leaves and stems after humidification for 1 hour, 2 hours and 3 hours, put them in liquid nitrogen, take them back to the laboratory, observe and take photos with fluorescence microscope. It can be used to analyze the tissue and organs of water absorption by desert plant leaves and the direction and path of water migration in plants. 3: Gene transcription and expression data: transcription and expression data of Tamarix chinensis, data collection time: May 25, 2014, location: Sitan village, Jingtai County, Gansu Province, data analysis platform: lllumina hisep TM 2000 platform, obtained by transcriptome analysis of baimaike company. 4. Photosynthetic and fluorescence data: photosynthetic and fluorescence parameters measured by photosynthetic apparatus in the field (Sitan village and Ejin Banner, Jingtai County). 5. Sap flow and environmental data: all data are original data. Sap flow data of desert plants measured by stem flow meter, including Tamarix chinensis, Haloxylon ammodendron, Nitraria tangutorum, red sand and other desert plants (Sitan village, Jingtai County and Ejin Banner), and environmental data monitored by automatic weather station, including temperature and humidity.
XIAO Honglang
In the middle of August 2013, photosynthesis of population was measured, and plant species: red sand. The group photosynthesis measurement system consists of li-8100 closed-circuit soil carbon flux automatic measurement system (li-cor, USA) and assimilation box designed and manufactured by Beijing ligotai science and Technology Co., Ltd. li-8100 is an instrument produced by li-cor company of USA for soil carbon flux measurement. The concentration of CO2 and H2O is measured by infrared gas analyzer. The length, width and height of assimilation boxes were all 50 cm. The assimilator is controlled by li-8100. After the measurement parameters are set, the instrument can run automatically.
SU Peixi
This data is produced using knowledge rule-based land cover classification methods. It is a set of USGS global land cover classification standards that can be used in atmospheric models and land surface process models of land cover types in the Heihe River Basin. The data covers the upper, middle, and lower reaches of the Heihe River Basin. The data uses Albers Conical Equal Area projection with a spatial resolution of 1 km. It is an ASCII file containing the land cover classification code and named: Rule_Based_Lulc_of_HRB2009.asc. You can directly use a text program (such as Notepad) to open and view the file, you can also input it in ArcGIS for other operations. The NOAH land surface process parameter table and parameter table description matched with the data are provided. Users can refer to this parameter table to apply the data to the land surface process model. The two files are USGS_LULC_NOAHVEGPARM.TBL and NOAHVEGPARM_documentation.txt, both can be opened by the text program (such as Notepad).
NAN Zhuotong
This dataset includes data recorded by the Heihe integrated observatory network obtained from the automatic weather station (AWS) at the Sidaoqiao mixed forest station from January 1 to December 31, 2018. The site (101.134° E, 41.990° N) was located on a tamarix and populous forest (Tamarix chinensis Lour. and Populus euphratica Olivier.) surface in the Sidaoqiao, Dalaihubu Town, Ejin Banner, Inner Mongolia Autonomous Region. The elevation is 874 m. The installation heights and orientations of different sensors and measured quantities were as follows: air temperature and humidity profile (28 m, north), wind speed and direction profile (28 m, north), air pressure (in tamper box), rain gauge (28 m, south), four-component radiometer (24 m, south), two infrared temperature sensors (24 m, south, vertically downward), two photosynthetically active radiation (24 m, south, one vertically upward and one vertically downward), soil heat flux (HFP01; 3 duplicates, -0.06 m), soil temperature profile (0, -0.02, -0.04, -0.1, -0.2, -0.4, -0.6, -1.0, -1.6, -2.0, -2.4 m), and soil moisture profile (-0.02, -0.04, -0.1, -0.2, -0.4, -0.6, -1.0, -1.6, -2.0, -2.4 m). The observations included the following: air temperature and humidity (Ta_28 m; RH_28 m) (℃ and %, respectively), wind speed (Ws_28 m) (m/s), wind direction (WD_28 m) (°), air pressure (press) (hpa), precipitation (rain) (mm), four-component radiation (DR, incoming shortwave radiation; UR, outgoing shortwave radiation; DLR_Cor, incoming longwave radiation; ULR_Cor, outgoing longwave radiation; Rn, net radiation) (W/m^2), infrared temperature (IRT_1 and IRT_2) (℃), photosynthetically active radiation of upward and downward (PAR_up and PAR_down) (μmol/ (s m^-2)), soil heat flux (Gs_1, Gs_2 and Gs_3) (W/m^2), soil temperature (Ts_0 cm, Ts_2 cm, Ts_4 cm, Ts_10 cm, Ts_20 cm, Ts_40 cm, Ts_60 cm, Ts_100, Ts_160, Ts_200, Ts_240 cm) (℃), and soil moisture (Ms_2 cm, Ms_4 cm, Ms_10 cm, Ms_20 cm, Ms_40 cm, Ms_60 cm, Ms_100, Ms_160, Ms_200, Ms_240 cm) (%, volumetric water content). The data processing and quality control steps were as follows: (1) The AWS data were averaged over intervals of 10 min for a total of 144 records per day. The missing data were denoted by -6999. Due to the power loss of datalogger, there were occasionally data missing during January 1 to 9, and November 10 to December 14; (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, REN Zhiguo, TAN Junlei
This data set contains meteorological element observation data from January 1, 2016 to December 31, 2016 at the downstream mixed forest station of heihe hydrometeorological observation network.The station is located at sidao bridge, dalaihubu town, ejin banner, Inner Mongolia.The longitude and latitude of the observation point are 101.1335e, 41.9903n and 874m above sea level.The air temperature and relative humidity sensors are located at 28m, facing due north.The barometer is installed in the anti-skid box on the ground;Tilting bucket rain gauge installed at 28m;The wind speed and direction sensor is located at 28m, facing due north.The four-component radiometer is installed at 24m, facing due south;Two infrared thermometers are installed at 24m, facing due south and the probe facing vertically downward.Two photosynthetically active radiators were installed at a position of 24m, facing due south, with one probe vertically upward and one probe vertically downward.The soil temperature probe is buried at 0cm of the surface and 2cm, 4cm, 10cm, 20cm, 40cm, 60cm and 100cm underground (observation at depths of 160cm,200cm and 240cm were increased on April 22), 2m to the south of the meteorological tower.The soil water probe was buried 2cm, 4cm, 10cm, 20cm, 40cm, 60cm and 100cm underground (observation at depths of 160cm,200cm and 240cm were increased on April 22), 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 items are: air temperature and humidity (Ta_28m, RH_28m) (unit: c, percentage), pressure (Press) (unit: hundred mpa), precipitation (Rain) (unit: mm), wind speed (WS_28m) (unit: m/s), wind (WD_28m) (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 temperature (Ts_0cm, Ts_2cm, Ts_4cm, Ts_10cm, Ts_20cm, Ts_40cm, Ts_60cm, Ts_100cm, Ts_160cm, Ts_200cm, Ts_240cm) (in:C), soil moisture (Ms_2cm, Ms_4cm, Ms_10cm, Ms_20cm, Ms_40cm, Ms_60cm, Ms_100cm, Ms_160cm, Ms_200cm, Ms_240cm) (unit: volumetric water content, percentage), upward and downward photosynthetically active radiation (PAR_up, PAR_down) (unit: micromole/sq.s). 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;Due to the sensor problem, the wind direction was partly missing between April and April 21, 2016;The soil heat flux G1 is between 2.21-3.15, G2 is between 1.24-3.15, 4.4-4.22 and 12.1-12.21.(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: 2016-9-1010:30;(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 data set is the contour map of the diving level in the middle reaches of heihe main stream, which contains the diving level profile of the middle reaches of heihe main stream in 2005, 2006 and 2007. It is made by arcgis as a vector map.Contains attributes such as length, elevation and thickness of equal water level line.Its scope is: Left: 604028.6599 right: 645635.1531 Above: 4333504.1090 below: 4296403.637
XU Zongxue
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