Brief Introduction:The high-cold regions in China include the Qinghai Tibetan Plateau, and the alpine regions of Gansu, Inner Mongolia and Xinjiang, with a total area of about 2.9 million square kilometers. Due to the complexity of topography and geomorphology, the worldwide researches more and more focus on the surface processes of the Qinghai Tibetan Plateau and its adjacent areas. The High-cold Region Observation and Research Network for Land Surface Processes & Environment of China (HORN) has gradually formed. It integrates 17 stations of Chinese Academy of Sciences, for long term observations and researches of land surface processes, including glaciers, permafrost, lades, alpine ecosystem in the high-cold regions of China. It provides a platform support for integrated researches of earth system, through condensation of scientific problems, integration of monitoring resources, improvement of observation capability and level, long-term continuous monitoring of surface processes and environmental changes in cold regions. It also provides data support for revealing the law of climate change and water resources formation and transformation in the headwaters of big rivers, exploring the changes of ecosystem structure and service function, grasping the mechanism of natural disasters such as ice and snow freezing and thawing, and promoting the sustainable development of regional economy and society, etc. A network integrated center is set up to organize research and carry out the specific implementation of network construction. It consists of an office, an observation technology service group and a data integration management group. The participating units of HORN should sign construction/research contracts in order to implement contract-based management, perform all tasks in the contracts and accept the examination and acceptance of the network organization. The network construction should give priority to scientific research, coordinated development, relatively balanced allocation of infrastructure and observation instruments, and free sharing of data within the network. For the principle of sharing and opening, the observatories of the network are open to the whole country. The network cooperates with relevant units through consultation, agreement or contract according to specific tasks and costs; the original observation data are gradually shared based on the principle of first the network, then the department and then the society. The network carries out planned and coordinated cooperation with foreign scientific research institutions and universities, which can improve the level of network observation and expand the content of observation through the cooperation. The HORN is managed by the Chinese Academy of Sciences in the allocation of funds and resources.

Number of Datasets:465

  • δD、δ18O of Rainfall,River Water and Ground Water from the Hulugou Outlet(July to September, 2014)

    Ⅰ Data description The data includes δD, δ18O of rainfall, river water and ground water from the Hulugou Outlet during July to September ,2014. The sampling frequency is once every two weeks. ⅡLocations of the sampling points. (1) The rainfall sampling point is located in the eco-hydrological station of Cold and Arid Regions Environmental and Engineering Research Institute, Chinese Academy of Sciences. The coordinates are 99°53′06.66′′E, 38°16′18.35′′N; (2) The first sampling point of the river water is the Hulugou outlet along the upper reaches of the Heihe River. The latitude and longitude is 99°52′47.7′′E, 38°16′11′′N. The second sampling point of the river water is the exit of the Hulugou No. II area in the upper reaches of the Heihe River, and the latitude and longitude is 99°52′58.40′′E, 38°14′36.85′′N. (3) The sampling points of ground water include spring water and well water sampling points. The sampling point of the spring water is 20m on the east side of the basin exit, with a latitude and longitude of 99°52′50.9′′E, 38°16′11.44′′N; the well water sampling point is located near the junction of the east and west branch, with a latitude and longitude of 99°52′45.38′′E, 38°15′21.27′′N. Ⅲ Testing method The δD and δ18O values of the samples were determined by the PICARRO L2130-i ultra-high precision liquid water and water vapor isotope analyzer. The results were expressed by the δ value of the test precision relative to the international standard material V-SMOW, and the determination precision was 0.038 ‰ and 0.011 ‰ .

    2019-07-10 0 0 View Details

  • HiWATER:Dataset of Hydro-meteorological Observation Network (Eddy Covariance System of Barren-land Station, 2015)

    The data set contains eddy covariance System observation data of Barren-land Station which is located in the lower reaches of the Heihe Hydro-meteorological Observation Network from January 1, 2015 to December 31, 2015. The site is located in Sidaoqiao, Ejina Banner, Inner Mongolia, and the underlying surface is barren land. The latitude and longitude of the observation point is 101.1326E, 41.9993N, and the altitude is 878m. The mount height of the Eddy Covariance System is 3.5 m, the sampling frequency is 10 Hz, the ultrasonic orientation is north, and the distance between the ultrasonic wind speed temperature meter (CSAT3) and the CO2/H2O analyzer (Li7500) is 15 cm. The original observation data of the Eddy Covariance System is 10 Hz, and the released data is a 30-minute data processed by Eddypro software. The main steps of the processing include: outlier eliminating, delay time correction, coordinates rotation (secondary coordinates rotation), frequency response correction, ultrasonic virtual temperature correction and density (WPL) correction, etc. Meanwhile, the quality evaluation of each flux value was performed,mainly includes atmospheric stability (Δst) test and turbulence similarity (ITC) test. The 30-min flux value output of Eddypro software was also screened: (1) Data from the instrument error was eliminated; (2) Data obtained with one hour before and after precipitation was removed; (3) Data with a deletion rate greater than 10% of the 10 Hz raw data every 30 minutes was eliminated; (4) Observation data of weak turbulence at night (u* less than 0.1 m/s) was excluded. The average period of observation data is 30 minutes, 48 data per day, and the missing data is marked as -6999. The data was missing due to Li7500 calibration of the eddy system on April 7 and 8; the suspicious data caused by instrument drift and other reasons was marked by red fonts. Published observation data include: date/time Date/Time, wind direction(°), horizontal wind speed(m/s), lateral wind speed standard deviation(m/s), ultrasonic virtual temperature (°C), water vapor density (g/m3), carbon dioxide concentration(mg/m3), friction velocity (m/s), length (m), sensible heat flux(W/m2), latent heat flux (W/m2), carbon dioxide flux (mg/(m2s)), sensible heat flux quality identification QA_Hs, latent heat flux quality identification QA_LE, carbon dioxide flux quality identification QA_Fc. The quality identification of sensible heat, latent heat, and carbon dioxide flux is divided into three levels (quality mark 0: (Δst <30, ITC<30); 1: (Δst <100, ITC<100); the rest is 2). The meaning of the data time, such as 0:30 represents an average data of 0:00-0:30; the data is stored in *.xls format. For hydro-meteorological network or station information, please refer to Li et al. (2013). For observation data processing, please refer to Liu et al. (2011).

    2019-07-10 0 1 View Details

  • HiWATER:Dataset of Hydro-meteorological Observation Network (Automatic Weather Station of Huazhaizi Desert Steppe Station, 2014)

    The data set contains the observation data of meteorological elements from the Huazhaizi Desert Steppe Station,,which is located along the middle reaches of the Heihe Hydro-meteorological Observation Network, and the data set covers data from January 1, 2014 to December 31, 2014. The station is located in Huazhaizi of Zhangye, Gansu Province. The underlying surface is piedmont desert. The latitude and longitude of the observation point is100.3186E, 38.7652N, and the altitude is 1731m. The observation instruments in Huazhaizi are installed respectively by Beijing Normal University and Cold and Arid Regions Environmental and Engineering Research Institute, Chinese Academy of Sciences. The observation instruments of Beijing Normal University are: two infrared thermometers installed 24 meters above the ground, facing south, with the probe vertical downward; soil temperature probes buried respectively at 0cm on the ground surface, 2cm、4cm、20cm、60cm and 100cmunder the ground; soil moisture sensors buried 4cm、20cm and 100cm under the ground; soil heat flow boards (3 pieces) buried 6cm under the ground. The observation instruments of Cold and Arid Regions Environmental and Engineering Research Institute are: wind speed sensor erected 10.48m、0.98m and 2.99m above the ground(3 layers),facing North; wind direction sensor erected 4 meters above the ground; air temperature and relative humidity sensors erected 1m and 2.99m above the ground(2 layers),facing North East; four-component radiometer installed 2.5 meters above the ground, facing South; barometric pressure sensor placed in the water-proof box; tipping bucket rain gauge installed 0.7 meter above the ground; soil temperature probes buried 4cm、10cm、18cm、26cm、34cm、42cm and 50cmunder the ground; soil moisture sensors buried 2cm、10cm、18cm、26cm、34cm、42cm、50cm and 58cm under the ground, 3 sensors buried at 2cm. The specific observation elements are as follows: (1) Observation elements of Beijing Normal University : surface radiation temperature (IRT_1, IRT_2) (unit: Celsius), soil heat flux (Gs_1, Gs_2, Gs_3) (unit: watt / square meter), soil moisture (Ms_4cm, Ms_20cm, Ms_100cm) (unit: percentage) and soil temperature (Ts_0cm, Ts_2cm, Ts_4cm, Ts_20cm, Ts_60cm, Ts_100cm) (unit: Celsius). (2) Observation elements of Cold and Arid Regions Environmental and Engineering Research Institute: wind speed (WS_0.48m, WS_0.98m, WS_2.99m) (unit: m/s), wind direction (WD_4m) (unit: degree), four-component radiation (DR, UR , DLR_Cor, ULR_Cor) (unit: watt / square meter), air temperature and humidity (Ta_1m, Ta_2.99m, RH_1m, RH_2.99m) (unit: Celsius, percentage), air pressure (Press) (unit: hectopascal), precipitation (unit: mm), soil temperature (Ts_4cm, Ts_10cm, Ts_18cm, Ts_26cm, Ts_34cm, Ts_42cm, Ts_50cm) (unit: Celsius), soil moisture (Ms_2cm_1, Ms_2cm_2, Ms_2cm_3, Ms_10cm, Ms_18cm, Ms_26cm, Ms_34cm, Ms_42cm, Ms_50cm, Ms_58cm) (unit: volumetric water content, percentage). The observation elements of Beijing Normal University are 10-minute average data, and the observation elements of Cold and Arid Regions Environmental and Engineering Research Institute are 30-minute average data. Processing and quality control of observation data: (1) Ensure 144 data of Beijing Normal University per day (every 10 minutes), and 48 data of Cold and Arid Regions Environmental and Engineering Research Institute per day (every 30 minutes). If there is missing data, it is marked as -6999. Data between 12.11-12.31,2014 is missing due to storage problems. (2) Eliminate moments with duplicate records; (3) Remove data that is significantly beyond physical meaning or beyond the measuring range of the instrument; (4) Data marked by red is debatable; (5) The formats of the date and time are uniform, and the date and time are in the same column. For example, the time is: 2014-6-10 10:30; (6) The naming rule is: AWS + site name. For hydro-meteorological network or site information, please refer to Li et al. (2013). For observation data processing, please refer to Liu et al. (2011).

    2019-07-09 0 2 View Details

  • HiWATER:Dataset of Hydro-meteorological Observation Network (an Automatic Weather Station of Sidaoqiao Populus Forest Station, 2015)

    The data set contains the observation data of meteorological elements from the Huyanglin Station, which is located along the lower reaches of the Heihe Hydro-meteorological Observation Network, and the data set covers data from January 1, 2015 to December 31, 2015. The station is located in Sidaoqiao, Dalaihubu Town, Ejina Banner, Inner Mongolia, the underlying surface is Populus euphratica forest and Tamarisk. The latitude and longitude of the observation point is 101.1239E, 41.9932N, and the altitude is 876m. The air temperature and relative humidity sensor s are erected 28 meters above the ground, facing North; the wind speed sensor is set at 28m, facing north; the four-component radiometer is installed 24 meters above the ground, facing South; two infrared thermometers are installed 24 meters above the ground, facing South, and the probe orientation is vertical downward; two photosynthetically active radiometers are installed 24 meters above the ground, facing South, and the two probes are vertically upward and downward respectively; the soil temperature probes are buried respectively at 0cm on the ground surface, 2cm and 4cm under the ground, they are located 2 meters from the meteorological tower in the North. The soil moisture sensors are buried 2cm and 4cm under the ground, 2 meters from the meteorological tower in the South. The soil heat flow boards (3 pieces) are buried 6cm under the ground, 2 meters from the meteorological tower in the South. Observed items include: air temperature and humidity (Ta_28m, RH_28m) (unit: Celsius, percentage), wind speed (WS_28m) (unit: m/s), four-component radiation (DR, UR, DLR_Cor, ULR_Cor, Rn) (unit: watt / square meter), surface radiation temperature (IRT_1, IRT_2) (unit: Celsius), soil heat flux (Gs_1, Gs_2, Gs_3) (unit: watts / square meter), soil temperature (Ts_0cm, Ts_2cm, Ts_4cm) (unit : Celsius), soil moisture (Ms_2cm, Ms_4cm) (unit: volumetric water content, percentage), up and down photosynthetically active radiation (PAR_up, PAR_down) (unit: micromoles / square meter second). Processing and quality control of observation data: (1) Ensure 144 data per day (every 10 minutes), if there is missing data, it is marked as -6999. Due to instrument adjustment, data between April 22 to April 27 of 2015 is missing. Soil heat flux data between June 19 to September 5 is missing due to sensor failure. (2) Eliminate moments with duplicate records; (3) Remove data that is significantly beyond physical meaning or beyond the measuring range of the instrument; (4) Data marked by red is debatable; (5) The formats of the date and time are uniform, and the date and time are in the same column. For example, the time is: 2015-9-10 10:30; (6) The naming rule is: AWS + site name. For hydro-meteorological network or site information, please refer to Li et al. (2013). For observation data processing, please refer to Liu et al. (2011).

    2019-07-09 0 2 View Details

  • Hydrological data set of China alpine region surface process and environmental observation network (2018)

    "1)Data content (including elements and meanings): hydrological data set of 7 rivers of HORN in Pan-Third pole 2)Data source and processing method: 7 rivers of HORN, field observation Excel format 3)Data quality description: site day resolution 4)Data application results and prospects: Based on the long-term observation data of the 17 stations of HORN, establish a series of data series of meteorological, hydrological and ecological elements in the Pan-Earth region; Strengthen observation and sample and sample verification, and complete the inversion of meteorological elements, lake water quantity and water quality, aboveground vegetation biomass, glacier and frozen soil changes; based on Internet of Things technology, develop multi-station networked meteorological, hydrological, The ecological data management platform realizes real-time acquisition and remote control and sharing of networked data.

    2019-07-08 0 9 View Details

  • Sentine-1 SAR data were used to monitor the permafrost of Biuniugou in Heihe River Basin of Qinghai-Tibet Plateau. Based on the Sentine-1 SAR image of Bison Valley from 2014 to 2018, the active layer thickness in the study area was estimated by using the small baseline set time series InSAR (DSs-SBAS) frozen soil deformation monitoring method based on distributed radar target, combined with SAR backscattering coefficient, MODIS surface temperature and Stefan model. The results show that the thickness of active layer is between 0.8 m and 6.6 m, with an average of about 3.3 M. It is of great significance to carry out large-scale and high-resolution monitoring.

    2019-07-08 0 0 View Details

  • WATER: Dataset of Forest Structure Parameter Survey at the Super Site around the Dayekou Guantan Forest Station

    The data set mainly includes observation data of each tree in the super site, and the observation time is from June 2, 2008 to June 10, 2008. The super site is set around the Dayekou Guantan Forest Station. Since the size of the super site is 100m×100m, in order to facilitate the forest structure parameter survey, the super site is divided into 16 sub-sample sites, and tally forest measurement is performed in units of sub-samples. The tally forest measurement factors include: diameter, tree height, height under branch, crown width in transversal slope direction, crown width in up and down slope direction, and tindividual tree growth status. The measuring instruments are mainly: tape, diameter scale, laser altimeter, ultrasonic altimeter, range pole and compass. The data set also records the center point latitude and longitude coordinates of 16 sub-samples (measured by Z-MAX DGPS). The data set can be used for verification of remote sensing forest structure parameter extraction algorithm. The data set, together with other observation data of the super site, can be used for reconstruction of forest 3D scenes, establishment of active and passive remote sensing mechanism models, and simulation of remote sensing images,etc. At the same time, the leaf area index was measured adopting the following three methods: LAI-2000, TRAC and HemiVeiw fish-eye lens.

    2019-06-24 0 0 View Details

  • Ground Water Level Dataset in the Middle Reaches of the Heihe River Basin

    1. Data Overview: This data includes groundwater buried depth observation datal from 4 observation points in Ganzhou District of Zhangye Basin in the middle reaches of the Heihe River (The nursery garden of Xindun Town, Suijia temple of Xindun Town, the Wuzhi management house of Dangzhai Town, Shangqin Station of Shangqin Town). The data was obtained from July 12, 2012 to July 5,2014. 2. Data Content: The HOBO water level sensor is installed in the underground well, which is mainly used to monitor the dynamic change of groundwater level in Ganzhou District of Zhangye. The data contents are absolute air pressure (kPa), temperature (°C), and groundwater depth (m). The data was recorded hourly. 3. Time and Space Range: The geographical coordinates of the nursery garden well of Xindun Town (1559 m) : Longitude 100°20.8′E; Latitude: 38°54′N; The geographical coordinates of Suijia temple well of Xindun Town(1518 m) : Longitude: 100°23.9′E; Latitude: 38°54.1′N; The geographical coordinates of Wuzhi management house well of Dangzhai Town (1675 m): Longitude: 100°30.7′E; Latitude: 38°52.8′N; The geographical coordinates of Shangqin Station well of Shangqin Town(1480 m): Longitude: 100°31.7′E; Latitude: 38°54.5′N. Note: The number in brackets is elevation.

    2019-06-22 0 0 View Details

  • Observation Data of Temperature and Rainfall in Permafrost Regions of Qinghai-Tibet Engineering Corridor (1956-2012)

    The data set includes the trends of annual average temperature and rainfall changes at the three meteorological stations in the permafrost section of the Qinghai-Tibet Engineering Corridor over the past 50 years. According to the recorded data, the annual average temperature is experiencing a gradually rising process. The annual average temperature change over the past 56 years in Wudaoliang and Tuotuohe has a good correlation (r2=0.83). In 1957, the average annual temperatures of Wudaoliang and Tuotuohe were -6.6 °C and -5.1 °C, respectively. By 2012, the temperatures of the two stations were -4.6 and -3.1 °C, and the total temperature has risen by approximately 2 °C. The annual average temperature rises by 0.03-0.04 °C. The annual average temperature changes over the past 47 years in Wudaoliang and Anduo also have a good correlation (r2=0.84). In 1966, the average annual temperature in Anduo was -3.0 °C. By 2012, the temperature has risen to -1.8 °C, corresponding to a total temperature rise of approximately 1.2 °C and an annual average temperature rise of 0.02-0.03 °C. The annual average temperature in Wudaoliang and Tuotuohe rose slightly faster than that in Anduo. However, the change in rainfall was more volatile than that of temperature. The correlation between the rainfall change in Wudaoliang and Tuotuohe over the past 56 years is relatively poor (r2=0.60). In 1957, the annual rainfall amounts in Wudaoliang and Tuotuohe were 302 and 309 mm, respectively. By 2012, the annual rainfall amounts at the two stations were 426 and 332 mm. Thus, the rainfall in Wudaoliang had increased by 124 mm, with an annual rainfall increase of approximately 2 mm. In contrast, the annual rainfall in Tuotuohe only increased by 0.4 mm. The correlation between the rainfall change in Wudaoliang and Anduo over the past 47 years is also poor (r2=0.35). In 1966, and 2012, the annual average rainfall amounts in Anduo were 354 and 404 mm. The total increase was approximately 50 mm, and the annual average increase was 1 mm. The annual rainfall in Wudaoliang increased the fastest. The observation data from the three meteorological stations reveal climate changes in the permafrost sections of the Qinghai-Tibet Engineering Corridor. Judging from the overall trend of temperature and rainfall changes, the temperature in the northern and central parts of the corridor has increased rapidly over the past 50 years, exceeding the global average of 0.02 °C/a (IPCC). The rainfall increase in the northern part of the corridor is also obvious, especially the rate of rainfall increase at the Wudaoliang meteorological station. Increases in both temperature and rainfall have a great impact on accelerating the spatial variation in permafrost, and they are the leading cause of permafrost degradation on the Tibetan Plateau.

    2019-05-31 0 5 View Details