This data set contains the eddy correlativity observation data of huachaizi desert station in the middle reaches of heihe hydrological meteorological observation network from January 1, 2017 to December 31, 2017.The station is located in zhangye city, gansu province.The longitude and latitude of the observation point are 100.3201E, 38.7659N and 1731.00m above sea level.The rack height of the vortex correlator is 4.5m, the sampling frequency is 10Hz, the ultrasonic orientation is due north, and the distance between the ultrasonic wind speed and temperature meter (CSAT3) and CO2/H2O analyzer (Li7500A) is 15cm. The original observation data of the vortex correlativity instrument is 10Hz, and the published data is the 30-minute data processed by Eddypro software. The main processing steps include: outliers, delay time correction, coordinate rotation (quadratic coordinate rotation), frequency response correction, ultrasonic virtual temperature correction and density (WPL) correction.Quality assessment for each intercompared to at the same time, mainly is the atmospheric stability (Δ st) and turbulent characteristics of similarity (ITC) test.The 30min pass value output by Eddypro software was also screened :(1) data when instrument error was eliminated;(2) data of 1h before and after precipitation are excluded;(3) remove the data with a missing rate of more than 10% in the original 10Hz data within every 30 minutes;(4) the observation data of weak turbulence at night (u* less than 0.1m/s) were excluded.The average observation period was 30 minutes, 48 data per day, and the missing data was marked as -6999.Suspicious data caused by instrument drift, etc., shall be marked in red font.April 3 solstice on April 4, due to the calibration of vortex correlator Li7500A, data was missing.When the 10Hz data of the vortex correlator is missing (1.1-1.22), the data will be filled by the 30-minute data output of 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).
0 2020-03-04
The data is the railway distribution map of the chaidamu river basin, with a scale of 25,000 and coordinates of longitude and latitude. The data includes spatial data and attribute data. The attribute field is code.
0 2020-04-06
Input output table of 11 districts and counties in Heihe River Basin in 2012
0 2020-07-28
This data set contains meteorological observation data of the downstream desert station of heihe hydrometeorological observation network from May 2, 2015 to December 31, 2015. The station is located at the ejin banner desert beach in Inner Mongolia, and the underlying surface is desert.The longitude and latitude of the observation point are 100.9872e, 42.1135n and 1054m above sea level.Air temperature and relative humidity sensors are set at 5m and 10m, facing due north;The barometer is installed at 2m;The tilting bucket rain gauge is installed at 10m;The wind speed sensor is set at 5m and 10m, and the wind direction sensor is set at 10m, facing due north;The four-component radiometer is installed at 6m, facing due south;Two infrared thermometers are installed at 6m, facing due south, and the probe facing vertically downward;The soil temperature probe is buried at 0cm of the surface and 2cm, 4cm, 10cm, 20cm, 40cm, 60cm and 100cm underground, 2m to the south of the meteorological tower.The soil water sensor is buried 2cm, 4cm, 10cm, 20cm, 40cm, 60cm and 100cm underground, 2m to the south of the meteorological tower.The soil hot plates (3 pieces) are buried 6cm underground. Observation projects are: air temperature and humidity (Ta_5m RH_5m Ta_10m, RH_10m) (unit: c, percentage), pressure (Press) (unit: hundred mpa), precipitation (Rain) (unit: mm), wind speed (WS_5m, WS_10m) (unit: m/s), wind (WD_10m) (unit: degrees), the radiation of four component (DR, UR, DLR_Cor, ULR_Cor, Rn) (unit: watts per square meter), the surface radiation temperature (IRT_1, IRT_2) (unit:C), soil heat flux (Gs_1, Gs_2, Gs_3) (in watts/m2), soil moisture (Ms_2cm, Ms_4cm, Ms_10cm, Ms_20cm, Ms_40cm, Ms_60cm, Ms_100cm) (unit: volumetric water content, percentage), and soil temperature (Ts_0cm, Ts_2cm, Ts_4cm, Ts_10cm, Ts_40cm, Ts_60cm, Ts_100cm) (unit: Celsius). Processing and quality control of observed data :(1) ensure 144 pieces of data every day (every 10min), and mark by -6999 in case of data missing;Soil heat flux 1 data was missing between May 11, 2015 and 6.6 due to sensor problems;(2) excluding the time with duplicate records;(3) data that obviously exceeds the physical significance or the range of the instrument is deleted;(4) the part marked with red letter in the data is the data in question;(5) date and time have the same format, and date and time are in the same column.For example, the time is: June 10, 2015, 10:30;(6) the naming rule is: AWS+ site name. 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).
0 2020-03-04
The glacial bacterial resource database of the Tibetan Plateau provides the bacterial 16S ribosomal RNA gene sequences of several glaciers, which are seven glaciers of the Tibetan Plateau separated by an experimental group led by Yongqin Liu during 2010 to 2018 (East Rongbuk Glacier of Mt. Qomolangma, Tianshan Glacier No.1, Guliya Glacier, Laohugou Glacier, Muztagh Ata Glacier, Qiyi Glacier and Yuzhufeng Glacier), the Malan Glacier separated by Shurong Xiang and the Puruogangri Glacier separated by Xinfang Zhang. After the glacier samples were collected, they were taken to the Ecological Laboratory of the Institute of Tibetan Plateau Research of the Chinese Academy of Sciences in Beijing and the National Cryosphere Laboratory in Lanzhou. After applying the spread plate method, the samples were cultured at different temperatures (4-25 °C) for 20 days to 90 days, and single colonies were picked out for purification. After the DNA was extracted from the isolated bacteria, the 16S ribosomal RNA gene fragment was amplified with 27F/1492R primer and sequenced using the Sanger method. The 16S ribosomal RNA gene sequence was compared with the RDP database using the "Classifier" software and identified as level one when the reliability exceeded 80%. These data contain the 16S ribosomal RNA gene fragment sequence and glacier sources of each sequence. Compared with sequences based on high-throughput sequencing, these data have a longer sequence and more accurate classification and can better serve in glacier microbiology research.
0 2020-04-29
I. Overview This data set contains socio-economic statistics of counties (cities) in the upper reaches of the Yellow River from 2000 to 2005. The data set is divided into basic conditions, comprehensive economics, agriculture, industry and infrastructure, education, health and social security, 4 There are 30 basic categories, including all the socio-economic statistical indicators. Ⅱ. Data processing description The data is stored in excel format, classified by province, with basic socio-economic statistics for each county. Ⅲ. Data content description This data set contains four basic classifications, namely basic situation, comprehensive economy, agriculture, industry and infrastructure, education, health and social security. The basic information includes the administrative area, the number of townships (towns), the number of villagers' committees, the total number of households at the end of the year, the number of rural households, the rural population, the number of employees at the end of the year, the number of rural employees, and the number of agricultural, forestry, animal husbandry and sideline fishermen The total power of agricultural machinery and local telephone users; the total economic categories include: the value added of the primary industry, value added of the secondary industry, revenue within the local fiscal budget, fiscal expenditure, the balance of savings deposits of urban and rural residents, and loans of financial institutions at the end of the year Balance; major categories of agriculture, industry and capital construction include: grain output, cotton output, oil output, total meat output, number of industrial enterprises above designated size, total industrial output value above designated size, and capital investment completed; education, health and social security The major categories include the number of students in ordinary middle schools, the number of students in primary schools, the number of beds in hospitals and health centers, the number of beds in social welfare homes, and the number of beds in social welfare homes. In some remote areas, some data are missing. Ⅳ. Data usage description Through this data set, the socio-economic problems of counties (cities) in the upper reaches of the Yellow River can be analyzed, and the socio-economic driving forces of certain natural processes can be analyzed and researched through this data set.
0 2020-04-07
This dataset includes data recorded by the Heihe integrated observatory network obtained from the automatic weather station (AWS) at the desert station from January 1 to December 31, 2018. The site (100.9872°E, 42.1135°N) was located on a desert surface in the desert, which is near Ejin Banner, Inner Mongolia Autonomous Region. The elevation is 1054 m. The installation heights and orientations of different sensors and measured quantities were as follows: air temperature and humidity profile (HMP45AC; 5 and 10 m, north), wind speed profile (010C; 5 and 10 m, north), wind direction (020C, 10m), air pressure (CS100; 2 m), rain gauge (TE525M; 10 m), four-component radiometer (CNR1; 6 m, south), two infrared temperature sensors (SI-111; 6 m, south, vertically downward), soil heat flux (HFP01; 3 duplicates, -0.06 m), soil temperature profile (109ss-L; 0, -0.02, -0.04, -0.1, -0.2, -0.4, -0.6, -1.0 m), soil moisture profile (ML3; -0.02, -0.04, -0.1, -0.2, -0.4, -0.6, -1.0 m). The observations included the following: air temperature and humidity (Ta_5 m and Ta_10 m; RH_5 m and RH_10 m) (℃ and %, respectively), wind speed (Ws_5 m and Ws_10 m) (m/s), wind direction (WD_10 m) (°), air pressure (press) (hpa), precipitation (rain) (mm), four-component radiation (DR, incoming shortwave radiation; UR, outgoing shortwave radiation; DLR_Cor, incoming longwave radiation; ULR_Cor, outgoing longwave radiation; Rn, net radiation) (W/m^2), infrared temperature (IRT_1 and IRT_2) (℃), soil heat flux (Gs_1, Gs_2, and Gs_3) (W/m^2), soil temperature (Ts_0 cm, Ts_2 cm, Ts_4 cm, Ts_10 cm, Ts_20 cm, Ts_40 cm, Ts_60 cm, Ts_100 cm) (℃), soil moisture (Ms_2 cm, Ms_4 cm, Ms_10 cm, Ms_20 cm, Ms_40 cm, Ms_60 cm, Ms_100 cm) (%). The data processing and quality control steps were as follows: (1) The AWS data were averaged over intervals of 10 min for a total of 144 records per day. The missing data were denoted by -6999. (2) Data in duplicate records were rejected. (3) Unphysical data were rejected. (4) The data marked in red are problematic data. (5) The format of the date and time was unified, and the date and time were collected in the same column, for example, date and time: 2018-6-10 10:30. (6) Finally, the naming convention was AWS+ site no. Moreover, suspicious data were marked in red. For more information, please refer to Liu et al. (2018) (for sites information), Liu et al. (2011) for data processing) in the Citation section.
0 2020-07-25
The permafrost stability map was created based on the classification system proposed by Guodong Cheng (1984), which mainly depended on the inter-annual variation of deep soil temperature. By using the geographical weighted regression method, many auxiliary data was fusion in the map, such as average soil temperature, snow cover days, GLASS LAI, soil texture and organic from SoilGrids250, soil moisture products from CLDAS of CMA, and FY2/EMSIP precipitation products. The permafrost stability data spatial resolution is 1km and represents the status around 2010. The following table is the permafrost stability classification system. The data format is Arcgis Raster.
0 2020-10-13
Forest canopy interception refers to the hydrological process in which part of water is intercepted and received by forest canopy and redistributed to precipitation in the process of precipitation. The data include precipitation, throughfall, canopy interception and interception rate, which are mainly used to provide data support for understanding the eco hydrological process of Picea crassifolia forest.
0 2020-03-10
This dataset contains the flux measurements from the Shenshawo desert station eddy covariance system (EC) in the middle reaches of the Heihe hydrometeorological observation network from 15 September, 2012, to 31 December, 2013. The site (100.493° E, 38.789° N) was located in the desert surface, near Zhangye city in Gansu Province. The elevation is 1594 m. The EC was installed at a height of 4.6 m, and the sampling rate was 10 Hz. The sonic anemometer faced north, and the separation distance between the sonic anemometer and the CO2/H2O gas analyzer (CSAT3&Li7500) was 0.15 m. The raw data acquired at 10 Hz were processed using the Edire post-processing software (University of Edinburgh, http://www.geos.ed.ac.uk/abs/research/micromet/EdiRe/), including the spike detection, lag correction of H2O/CO2 relative to the vertical wind component, sonic virtual temperature correction, coordinate rotation (2-D rotation), corrections for density fluctuation (Webb-Pearman-Leuning correction), and frequency response correction. The EC data were subsequently averaged over 30 min periods. The observation data quality was divided into three classes according to the quality assessment method of stationarity (Δst) and the integral turbulent characteristics test (ITC), as proposed by Foken and Wichura [1996]: class 1 (level 0: Δst<30 and ITC<30), class 2 (level 1: Δst<100 and ITC<100), and class 3 (level 2: Δst>100 and ITC>100), which represent high-, medium-, and low-quality data, respectively. In addition to the above processing steps, the half-hourly flux data were screened using a four-step procedure: (1) data from periods of sensor malfunction were rejected; (2) data collected before or after 1 h of precipitation were rejected; (3) incomplete 30 min data were rejected when the missing data constituted more than 3% of the 30 min raw record; and (4) data were rejected at night when the friction velocity (u*) was less than 0.1 m/s. There were 48 records per day, and the missing data were replaced with -6999. Suspicious data were marked in red. The 10 Hz data were missing during 8 December to 22 December, 2012, and data in this period were replaced with 30 min flux output by data logger. Data during 25 May to 29 May, 2013 were missing due to calibration of CO2/H2O gas analyzer. The released data contained the following variables: data/time, wind direction (Wdir, °), wind speed (Wnd, m/s), the standard deviation of the lateral wind (Std_Uy, m/s), virtual temperature (Tv, ℃), H2O mass density (H2O, g/m^3), CO2 mass density (CO2, mg/m^3), friction velocity (ustar, m/s), stability (z/L), sensible heat flux (Hs, W/m^2), latent heat flux (LE, W/m^2), carbon dioxide flux (Fc, mg/ (m^2s)), quality assessment of the sensible heat flux (QA_Hs), quality assessment of the latent heat flux (QA_LE), and quality assessment of the carbon flux (QA_Fc). In this dataset, the time of 0:30 corresponds to the average data for the period between 0:00 and 0:30; the data were stored in *.xls format. For more information, please refer to Li et al. (2013) (for hydrometeorological observation network or sites information), Liu et al. (2011) (for data processing) in the Citation section.
0 2019-09-15
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