According to the global soil map. Net standard, the 0-1m soil depth is divided into 5 layers: 0-5cm, 5-15cm, 15-30cm, 30-60cm and 60-100cm. According to the principle of soil landscape model, the spatial distribution data products of soil sand content in different layers are made by using the digital soil mapping method. The American system classification is used as the standard of soil particle classification. The source data of this data set comes from the soil profile data integrated by the major research plan integration project of Heihe River Basin (soil data integration and soil information product generation of Heihe River Basin, 91325301). Scope: Heihe River Basin; Projection: WGS · 1984 · Albers; Spatial resolution: 100M; Data format: TIFF; Dataset content: hh_sand_layer1.tif: 0-5cm soil sand content; hh_sand_layer2.tif: 5-15cm soil sand content; hh_sand_layer3.tif: 15-30cm soil sand content; hh_sand_layer4.tif: 30-60cm soil sand content; hh_sand_layer5.tif: 60-100cm soil sand content;
0 2020-06-01
Ⅰ. Overview FAO (Food and Agriculture Organization of the United Nations) and IIASA (International Institute for Applied Systems Analysis) combined the soil information of all regions and countries in the world with the world soil map of FAO-UNESCO, formed a new soil database - Harmonized World Soil Database (HWSD). The data source in China is 1:1 million soil data provided by Nanjing Soil Research Institute of the second national land survey. The database will be of great significance to improve people's understanding of current and future soil productivity, soil carbon storage, land resources, water resources and soil degradation. Ⅱ. Data processing description The data comes from the Harmonized World Soil Database (HWSD) constructed by FAO and IIASA. The data in China comes from the 1:1 million soil data provided by Nanjing Soil Research Institute of the second national land survey. The main soil classification system is FAO-90. Ⅲ. Data content description The main fields of soil attribute table include: SU_SYM90 (soil name in FAO90 soil classification system): SU_SYM85 (FAO85 classification); T_TEXTURE (top soil texture); DRAINAGE (19.5); ROOTS: String (depth classification with obstacles to the bottom of soil); SWR: String (soil water content characteristics); ADD_PROP: Real (agricultural use related in soil unit) Specific soil type); T_GRAVEL: Real (gravel volume percentage); T_SAND: Real (sand content); T_SILT: Real (silt content); T_CLAY: Real (clay content); T_USDA_TEX: Real (USDA soil texture classification); T_REF_BULK: Real (soil bulk weight); T_OC: Real (organic carbon content); T_PH_H2O: Real (PH); T_CEC_CLAY: Real (cation exchange of clayey soil); T_CEC_SOIL: Real (cation exchange capacity of soil); T_BS: Real (basic saturation); T_TEB: Real (exchangeable base); T_CACO3: Real (carbonate or lime content); T_CASO4: Real (sulfate content); T_ESP: Real (exchangeable sodium salt); T_ECE: Real (conductivity). The attribute field beginning with T_ represents the upper soil attribute (0-30cm), and the attribute field beginning with S_ represents the lower soil attribute (30-100cm) (FAO 2009). Ⅳ. Data usage description Through this database, people's understanding of current and future soil productivity, soil carbon storage and global soil carbon storage will be improved. It can help people to understand the limitation of land and water resources, and correctly assess the risk of soil degradation, especially soil loss. Through understanding the physical and chemical properties of soil, it can also help people to obtain the following information, such as the filtering function of soil on waste, the impact on biological growth, etc. The potential of soil production and the response of soil to climate change were correctly judged.
0 2020-03-28
"Hydrologic - ecological - economic process coupling and evolution of heihe Basin governance under the framework of water rights" (91125018) project data exchange 4-basin-plan-mdb 1. Data overview: a watershed plan revision for the Murray darling river in Australia, adopted in 2012, for catchment comparisons 2. Data content: the public plan
0 2020-03-10
The aim of the simultaneous observation of river surface temperature is obtaining the land surface temperature in different places be of different kinds of underlying surface, while the sensor of WiDAS go into the experimental areas of the upstream of Heihe river basin. All the land surface temperature data will be used for validation of the retrieved land surface temperature from WiDAS sensor and the analysis of the scale effect of the land surface temperature, and finally serve for the validation of the authenticity of the surface temperature product from remote sensing. 1. Observation sites and other details Six places be of different kinds of underlying surface were chosen to observe surface temperature simultaneous in the upstream of Heihe river basin on 1 August. Self-recording point thermometers (observed once every 6 seconds) were used one place while handheld infrared thermometers (observed continuously during the sensor of WiDAS go into the region) were used in other five places. The main underlying surface including natural grassland, river section, river rapids, gravel. 2. Instrument parameters and calibration. The field of view of the self-recording point thermometer and the handheld infrared thermometer are 10 and 1 degree, respectively. The emissivity of the latter was assumed to be 0.95. All instruments were calibrated on 5 August, 2012 using black body during observation. 3. Data storage All the observation data were stored in excel.
0 2019-09-12
This dataset contains the flux measurements from the A’rou Superstation eddy covariance system (EC) in the upper reaches of the Heihe hydrometeorological observation network from 29 December, 2012, to 19 November, 2013. The site (100.464° E, 38.047° N) was located in the Alpine grassland, Caodaban village, A’rou Country, Qilian County in Qilian Province. The elevation is 3033 m. The EC was installed at a height of 3.5 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 & Li7500A) 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 data from 14 February to 28 February were missing due to a storage problem of CF card in the datalogger. 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/m2), 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 Liu et al. (2018) (for hydrometeorological observation network or sites information), Liu et al. (2011) (for data processing) in the Citation section.
0 2020-04-10
This data set contains the eddy correlativity observation data of the naked earth station downstream of heihe hydrometeorological observation network from January 1, 2014 to December 31, 2014.The station is located in Inner Mongolia ejin banner four bridge, the underlying surface is bare ground.The longitude and latitude of the observation point are 101.1326e, 41.9993n and 878m above sea level.The rack height of the vortex correlativity meter is 3.5m, the sampling frequency is 10Hz, the ultrasonic orientation is due north, and the distance between the ultrasonic wind speed and temperature meter (CSAT3) and CO2/H2O analyzer (Li7500) is 15cm. The original observation data of the vortex correlativity instrument is 10Hz, and the published data is the 30-minute data processed by Eddypro software. The main processing steps include: outliers, delay time correction, coordinate rotation (quadratic coordinate rotation), frequency response correction, ultrasonic virtual temperature correction and density (WPL) correction.Quality assessment for each intercompared to at the same time, mainly is the atmospheric stability (Δ st) and turbulent characteristics of similarity (ITC) test.The 30min pass value output by Eddypro software was also screened :(1) data when instrument error was eliminated;(2) data of 1h before and after precipitation are excluded;(3) remove the data with a missing rate of more than 10% in the original 10Hz data within every 30 minutes;(4) the observation data of weak turbulence at night (u* less than 0.1m/s) were excluded.The average observation period was 30 minutes, 48 data per day, and the missing data was marked as -6999.Suspicious data caused by instrument drift, etc., shall be marked in red font. The published observational data include:Date/Time for the Date/Time, wind Wdir (°), Wnd horizontal wind speed (m/s), standard deviation Std_Uy lateral wind speed (m/s), ultrasonic virtual temperature Tv (℃), the water vapor density H2O (g/m3), carbon dioxide concentration CO2 (mg/m3), friction velocity Ustar) (m/s), stability Z/L (dimensionless), sensible heat flux Hs (W/m2), latent heat flux LE (W/m2), carbon dioxide flux Fc (mg/(m2s)), the quality of the sensible heat flux identifier QA_Hs, the quality of the latent heat flux identifier QA_LE,Quality indicator for co2 flux QA_Fc.The quality of the sensible heat and latent heat, carbon dioxide flux identification is divided into three (quality id 0: (Δ st < 30, the ITC < 30);1: (Δ st < 100, ITC < 100);The rest is 2).The meaning of data time, such as 0:30 represents the average of 0:00-0:30;The data is stored in *.xls format. For information of hydrometeorological network or station, please refer to Li et al.(2013), and for observation data processing, please refer to Liu et al.(2011).
0 2020-03-04
The dataset is a 30-minute eddy covariance flux observation data from nine flux stations in the Three Poles, including the data of ecosystem Net Carbon Exchange (NEE), Gross Primary Productivity(GPP), and Ecosystem Respiration (ER) . The time coverage of the data is from 2000 to 2016. The main steps of data pre-processing include outlier removal (±3σ), coordinate axis rotation(three-dimensional wind rotation), Webb-Pearman-Leuning correction, outlier elimination, carbon flux interpolation and decomposition. And missing data is interpolated by the nonlinear empirical formula between CO2 flux value(Fc) and environmental factors.
0 2020-01-19
This dataset contains the flux measurements from the Dashalong station eddy covariance system (EC) in the upperstream reaches of the Heihe integrated observatory network from January 1 to December 31 in 2018. The site (98.9406° E, 38.8399° N) was located in the Qilian County in Qinghai Province. The elevation is 3739 m. The EC was installed at a height of 4.5 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&Li7500RS) was 0.15 m. The raw data acquired at 10 Hz were processed using the Eddypro post-processing software, 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): class 1-3 (high quality), class 4-6 (good), class 7-8 (poor, better than gap filling data), class9 (rejected). 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 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. Data during September 27 to November 14, 2018 were missing due to the sensor calibration of sonic anemometer. 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/m3), CO2 mass density (CO2, mg/m3), friction velocity (ustar, m/s), stability (z/L), sensible heat flux (Hs, W/m2), latent heat flux (LE, W/m2), carbon dioxide flux (Fc, mg/ (m2s)), 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. Detailed information can be found in the suggested references. 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
Interaction "heihe region in field observation experiment (HEIFE)", is in the heihe river basin in hexi corridor in the middle of a 70 km by 90 km range of experimental zone for the center with water and heat exchange of a very comprehensive experiment, the interaction is the current international field the longest continuous observation on the land surface process experiment, has obtained the Eurasia hinterland typical in heihe river basin, gobi desert and oasis in arid regions different underlaying surface, such as solar radiation, atmospheric boundary layer meteorological data and oasis of meteorological data, and collect the conventional meteorological and hydrological data in the region,It has laid the foundation of observation experiment for theoretical study of land surface processes in arid areas. The heihe experimental database (HDB) (tao zehong and zuo hongchao, 1994a) comprehensively collected and systematically integrated the field observation data of heihe experiment.In the database, all observation data are divided into three categories according to the nature and purpose of observation: Category 1: normal observation period (FOP) data.It includes :(1) observation data of 5 micrometeorological stations and 5 automatic meteorological stations;(2) groundwater level data observed at four well stations;(3) distribution of blowing sand and dust and ozone observation data;(4) conventional observation data of 3 upper-air weather stations, 3 surface weather stations, 4 hydrology stations, some rain measuring stations and downhole water stations. The second category: enhanced observation period (IOP) data.It includes: observations of turbulence, tethered balloons, Sodar, Lidar, soil moisture content and composition during each strengthening period (PlOP, IOP-1, lop-2, IOP-3, IOP-4). The third category is special observation period data, which includes: biological meteorological observation (BOP), precipitation mechanism observation (iop-r) in arid areas, turbulence contrast observation (iop-c), supplementary observation data of deserts far from the oasis (iop-da) and observation data of sand sample experiment.Please refer to HEIFE database user manual for more detailed information (tao zehong et al., 1994b).
0 2020-03-08
"Coupling and Evolution of Hydrologic -Ecologic-Economic Processes of the Heihe River Basin Under the Framework of Water Rights" (91125018) Project data collection 1 - SWater Resources Improvement Plan of Shiyang River Basin 1. Data Overview:The improvement plan of Shiyang River Basin was implemented in 2007 for river basin comparison. 2. Data Content: The released plan.
0 2020-07-28
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