The modern sporopollen identification results of five different geomorphic types in the middle reaches of Heihe River show that there are 39 sporopollen types, 22 main types, belonging to 6 different vegetation types in 45 topsoil samples distributed in the desert vegetation belt. The SPOROPOLLEN ASSEMBLAGES with high percentage of sporopollen in the sporopollen map were selected to represent different geomorphic types. It was found that five geomorphic types (dune, alluvial proluvial fan, flood plain, riverbed and wetland) could be expressed by different combinations of nine sporopollen.
0 2020-07-30
The dataset is the vector map of the administrative boundary of the Tarim River Basin, with a scale of 250,000 and projection: latitude and longitude. The data includes spatial data and attribute data, mainly the name and administrative code of the county boundary of the Tarim River Basin.
0 2020-06-04
This data includes three parts of data, namely shrub water holding experiment, shrub interception experiment and shrub transpiration experiment data. Shrub water holding experiment: select the two shrub types of Caragana jubata and Potentilla fruticosa, respectively pick the branches and leaves of the two vegetation types, weigh their fresh weight, carry out water holding experiment, measure the saturated weight of branches and leaves, dry weight of branches and leaves, dry weight of branches and leaves after completion, and finally obtain the data of branches, leaves and total water holding capacity. Shrub interception experiment: two shrubs, Caragana jubata and Potentilla fruticosa, were also selected and investigated. 30 rain-bearing cups were respectively arranged under the two shrubs. after each rainfall, penetration rainfall was measured and observed from June 1, 2012 to September 10, 2012. Shrub Transpiration Experiment: Potentilla fruticosa on July 14, Caragana jubata on August 5, Salix gilashanica on August 15, 2012. The measurement is made every hour according to the daily weather conditions.
0 2020-07-30
This glacial lake inventory is supported by the International Centre for Integrated Mountain Development (ICIMOD) and the United Nation Environment Programme/Regional Resources Centre, Asia and The Pacific (UNEP/RRC-AP). 1. The glacial lake inventory uses the remote sensing data of Landsat，reflecting the current status of glacial lakes larger than 0.01 square kilometers in Nepal in 2000. 2. The spatial coverage of the glacial lake inventory： Nepal 3. Contents of the glacial lake inventory: glacial lake code, glacial lake types, glacial lake area, distance between glacial lakes and the glaciers, related glaciers, etc. 4. Data Projection: Grid Zone IIA Projection: Lambert conformal conic Ellipsoid: Everest (India 1956) Datum: India (India, Nepal) False easting: 2743196.40 False northing: 914398.80 Central meridian: 90°00'00"E Central parallel: 26°00'00"N Scale factor: 0.998786 Standard parallel 1: 23°09'28.17"N Standard parallel 2: 28°49'8.18"N Minimum X Value: 1920240 Maximum X Value: 2651760 Minimum Y Value: 914398 Maximum Y Value: 1188720 Grid Zone IIB Projection: Lambert conformal conic Ellipsoid: Everest (India 1956) Datum: India (India, Nepal) False easting: 2743196.40 False northing: 914398.80 Central meridian: 90°00'00"E Central parallel: 26°00'00"N Scale factor: 0.998786 Standard parallel 1: 21°30'00"N Standard parallel 2: 30°00'00"N Minimum X Value: 1823188 Maximum X Value: 2000644 Minimum Y Value: 1306643 Maximum Y Value: 1433476 For a detailed data description, please refer to the data file and report.
0 2020-06-09
This dataset includes data recorded by the Hydrometeorological observation network obtained from the automatic weather station (AWS) at the observation system of Meteorological elements gradient of Sidaoqiao mixed forest station between 12 July, 2013, and 31 December, 2013. 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 (HMP45D; 28 m, north), wind speed and direction profile (034B; 28 m, north), air pressure (AV-410BP; in tamper box), rain gauge (52203; 28 m, south), four-component radiometer (CNR4; 24 m, south), two infrared temperature sensors (IRTC3; 24 m, south, vertically downward), two photosynthetically active radiation (PQS-1; 24 m, south, one vertically upward and one vertically downward), soil heat flux (HFP01; 3 duplicates, -0.06 m), soil temperature profile (AV-10T; 0, -0.02, -0.04, -0.1, -0.2, -0.4, -0.6 and -1.0 m), and soil moisture profile (ML2X; install on Dec. 7, 2013, -0.02, -0.04, -0.1, -0.2, -0.4, -0.6 and -1.0 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 and Ts_100 cm) (℃), and soil moisture (Ms_2 cm, Ms_4 cm, Ms_10 cm, Ms_20 cm, Ms_40 cm, Ms_60 cm and Ms_100 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. (2) Data in duplicate records were rejected. (3) Unphysical data were rejected. (4) The data marked in red are problematic data. (5) The format of the date and time was unified, and the date and time were collected in the same column, for example, date and time: 2013-9-10 10:30. (6) Finally, the naming convention was AWS+ site no. Moreover, suspicious data were marked in red. For more information, please refer to Li et al. (2013) (for hydrometeorological observation network or sites information), Liu et al. (2011) (for data processing) in the Citation section.
0 2019-09-15
The data set includes observation data of meteorological elements in the downstream desert station of Heihe Hydrometeorological Observation Network from January 1, 2017 to December 31, 2017. The site is located in the desert beach of Ejin Banner, Inner Mongolia, and the underlying surface is red sand desert. The latitude and longitude of the observation point is 100.9872E, 42.1135N, and the altitude is 1054m.The air temperature and relative humidity sensors are installed at 5m and 10m, facing the north; the barometer is installed at 2m; the tipping bucket rain gauge is installed at 10m; the wind speed sensor is set at 5m, 10m, and the wind direction sensor is set at 10m, facing the north; the four-component radiometer is installed at 6m, facing south; two infrared thermometers are installed at 6m, facing south, the probe orientation is vertically downward; the soil temperature probe is buried in the ground surface 0cm and underground 2cm, 4cm, 10cm, 20cm 40cm, 60cm and 100cm, in the south of the 2m from the meteorological tower; soil moisture sensors are buried in the underground 2cm, 4cm, 10cm, 20cm, 40cm, 60cm and 100cm, in the south of the 2m from the meteorological tower; soil heat flux plates (3 pieces) are buried in the ground 6 cm in order. Observation items include: air temperature and humidity (Ta_5m, RH_5m, Ta_10m, RH_10m) (unit: centigrade, percentage), air pressure (Press) (unit: hectopascal), precipitation (Rain) (unit: mm), wind speed (WS_5m, WS_10m) (unit: m / s), wind direction (WD_10m) (unit: degree), four-component radiation (DR, UR, DLR_Cor, ULR_Cor, Rn) (unit: watts / square meter), surface radiation temperature (IRT_1, IRT_2 ) (unit: centigrade), soil heat flux (Gs_1, Gs_2, Gs_3) (unit: watts/square meter), soil moisture (Ms_2cm, Ms_4cm, Ms_10cm, Ms_20cm, Ms_40cm, Ms_60cm, Ms_100cm) (unit: volumetric water content, percentage) and soil temperature (Ts_0cm, Ts_2cm, Ts_4cm, Ts_10cm, Ts_20cm, Ts_40cm, Ts_60cm, Ts_100cm) (unit: centigrade). Processing and quality control of the observation data: (1) ensure 144 data per day (every 10 minutes), when there is missing data, it is marked by -6999; From September 17, 2017 to September 23, due to the re-enhancement of the observation tower, the data is missing (the four-component radiation missing period is from September 9 to September 23); (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: 2016-6-10 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).
0 2019-09-15
Dataset of airborne imaging spectrometer (OMIS-II) mission was obtained in the Zhangye-Yingke-Huazhaizi flight zone on Jun. 4, 2008. Data after radiometric correction and calibration and geometric approximate correction were released. The flying time of each route was as follows: {| ! id ! flight ! file ! starttime ! lat ! long ! alt ! image linage ! endtime ! lat ! long ! alt |- | 1 || 3-15 || 2008-06-04_10-09-09_DATA.BSQ || 10:09:16 || 38.964 || 100.512 || 3315.0 || 6764 || 10:16:47 || 38.713 || 100.351 || 3351.0 |- | 2 || 3-14 || 2008-06-04_10-20-29_DATA.BSQ || 10:21:20 || 38.713 || 100.344 || 3319.1 || 6865 || 10:28:57 || 38.961 || 100.504 || 3311.7 |- | 3 || 3-13 || 2008-06-04_10-33-05_DATA.BSQ || 10:34:27 || 38.974 || 100.505 || 3340.1 || 6934 || 10:42:09 || 38.718 || 100.341 || 3370.7 |- | 4 || 3-12 || 2008-06-04_10-45-51_DATA.BSQ || 10:47:00 || 38.711 || 100.30 || 3331.2 || 6999 || 10:54:47 || 38.966 || 100.494 || 3315.8 |- | 5 || 3-11 || 2008-06-04_10-58-29_DATA.BSQ || 11:00:26 || 38.978 || 100.495 || 3332.3 || 6914 || 11:08:07 || 38.723 || 100.331 || 3356.2 |- | 6 || 3-10 || 2008-06-04_11-11-48_DATA.BSQ || 11:12:43 || 38.716 || 100.320 || 3326.8 || 6969 || 11:20:28 || 38.970 || 100.484 || 3318.1 |- | 7 || 3-9 || 2008-06-04_11-24-09_DATA.BSQ || 11:25:54 || 38.978 || 100.483 || 3337.7 || 6755 || 11:33:25 || 38.727 || 100.321 || 3339.4 |- | 8 || 3-8 || 2008-06-04_11-37-06_DATA.BSQ || 11:38:31 || 38.721 || 100.310 || 3327.3 || 6930 || 11:46:13 || 38.976 || 100.474 || 3326.6 |- | 9 || 3-7 || 2008-06-04_11-49-54_DATA.BSQ || 11:51:37 || 38.984 || 100.473 || 3333.0 || 6730 || 11:59:05 || 38.732 || 100.311 || 3351.4 |- | 10 || 3-6 || 2008-06-04_12-02-47_DATA.BSQ || 12:03:48 || 38.725 || 100.300 || -1.0 || 6790 || 12:11:21 || 38.978 || 100.462 || 3325.8 |- | 11 || 3-5 || 2008-06-04_12-15-02_DATA.BSQ || 12:16:41 || 38.991 || 100.465 || 3357.9 || 6893 || 12:24:21 || 38.734 || 100.300 || 3386.0 |- | 12 || 3-4 || 2008-06-04_12-28-02_DATA.BSQ || 12:28:52 || 38.729 || 100.290 || 3331.3 || 6820 || 12:36:27 || 38.983 || 100.453 || 3327.5 |- | 13 || 3-3 || 2008-06-04_12-40-09_DATA.BSQ || 12:41:59 || 38.994 || 100.454 || 3347.3 || 6934 || 12:49:41 || 38.741 || 100.291 || 3360.4 |- | 14 || 3-2 || 2008-06-04_12-53-23_DATA.BSQ || 12:54:31 || 38.734 || 100.280 || 3328.1 || 7110 || 13:02:25 || 38.990 || 100.445 || 3338.6 |- | 15 || 3-1 || 2008-06-04_13-06-07_DATA.BSQ || 13:07:35 || 39.000 || 100.444 || 3325.9 || 6979 || 13:15:20 || 38.746 || 100.281 || 3334.4 |}
0 2019-05-23
This data set contains meteorological element observation data from January 1, 2014 to December 31, 2014 from the grand salon station upstream of heihe hydrometeorological observation network.The station is located in shalantan, west of qilian county, qinghai province.The latitude and longitude of the observation point is 98.9406e, 38.8399n and 3739m 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 hot plates (3 pieces) are buried in the ground 6cm underground and 2m to the south of the weather 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;Due to insufficient power supply, data was missing between January 1, 2014 and January 19, 2014.(2) excluding the time with duplicate records;(3) data that obviously exceeds the physical significance or the range of the instrument is deleted;(4) the part marked with red letter in the data is the data in question;(5) date and time have the same format, and date and time are in the same column.For example, the time is: September 10, 2014, 10:30;(6) the naming rule is: AWS+ site name. For information of hydrometeorological network or station, please refer to Liu et al.(2018), and for observation data processing, please refer to Liu et al.(2011).
0 2020-04-10
The data is clipped from "1: 1 million wetland data of China". "1: 1 million wetland data of China" mainly reflects the national marsh wetland information in the 2000s. It is expressed in geographic coordinates using the decimal degree. The main contents include: marsh wetland types, wetland water supply types, soil types, main vegetation types, geographical area, etc. Implemented the "Standard for Information Classification and Coding of Sustainable Development Information Sharing System of China". Data source of this database: 1:20 swamp map (internal version), Tibetan Plateau 1: 500,000 swamp map (internal version), swamp survey data 1: 1 million and national 1: 4 million swamp map; processing steps are: data source selection, preprocessing, digitization and encoding of marsh wetland elements, data editing processing, establishing topological relationships, edge processing, projection conversion, linking with attribute databases such as place names and obtaining attribute data.
0 2020-10-09
This data set contains the vortex correlator observation data of zhangye wetland station in the middle reaches of heihe hydrometeorological observation network from March 18, 2016 to December 31, 2016.The site is located in zhangye city, gansu province.The latitude and longitude of the observation point is 100.44640E, 38.97514N, and the altitude is 1460.00m.The height of the vortex correlation instrument is 5.2m, the sampling frequency is 10Hz, the ultrasonic direction is due to the north, and the distance between the ultrasonic wind speed and temperature instrument (Gill) and the CO2/H2O analyzer (Li7500A) is 25cm. The original observation data of vorticity correlativity is 10Hz, and the released data is the data of 30 minutes processed by Eddypro software. The main steps of its processing include: outfield value elimination, delay time correction, Angle correction, coordinate rotation (secondary 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.(2) data of 1h before and after precipitation were excluded;(3) the missing rate of 10Hz original data is more than 10% every 30min;(4) the observed data of weak turbulence at night were excluded (u* less than 0.1m/s).The average period of observation data was 30 minutes, 48 data a day, and the missing data was marked as -6999.The suspicious data caused by instrument drift and other reasons are marked in red. Among them, the three-dimensional ultrasonic discontinuity of the vortex system from April to June 2016 has some problems, and some data are missing. Observations published 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,Carbon dioxide flux mass identification 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 are 2).The meaning of data time, such as 0:30 represents the average between 0:00 and 0:30;The data is stored in *.xls format. Please refer to Li et al. (2013) for hydrometeorological network or site information, and Liu et al. (2011) for observation data processing.
0 2020-03-05
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