Based on the long-term observation data of the field stations in the alpine network and the overseas stations in the pan third polar region, a series of data sets of meteorological, hydrological and ecological elements in the pan third polar region are established; through the intensive observation and sample plot and sample point verification in key areas, the inversion of meteorological elements, lake water and water quality, aboveground vegetation biomass, glacier and frozen soil change and other data products are completed; based on the Internet of things, the data products are retrieved Network technology, research and establish meteorological, hydrological, ecological data management platform of multi station networking, to achieve real-time data acquisition and remote control and sharing. The hydrological data set of the surface process and environment observation network in China's alpine regions in 2019 mainly collects the measured hydrological (runoff, water level, water temperature, etc.) data at six stations, including Southeast Tibet station, Zhufeng station, Yulong Snow Mountain station, Namco station, Ali station and Tianshan station. Southeast Tibet station: flow data, including 4 times of using M9 to measure flow in 2019, including average velocity, flow and maximum water depth; relative water level data is measured by hobo pressure water level meter, including daily average relative water level and water temperature data in 2019. Namco station: discharge data, including the data measured by domestic ls-1206b hand-held current meter for 4 times in 2019, including river width and flow data. The water level data is measured by hobo pressure water level meter, including the water pressure, water temperature and electricity of the original 1 hour in 2019. The relative water level can be calculated by water pressure; Everest station: rongbuhe river discharge, including river width and discharge data measured by domestic ls-1206b hand-held current meter 13 times from June to September 2019; Ali station: flow data: including 22 times of irregular measurement data by river anchor M9 in 2019, and relative water level data measured by hobo pressure water level meter, including hourly water level and water temperature data of the whole year in 2019; Tianshan station: water level data: including daily average water level of 3 points in 2019 Yulong Xueshan station: including mujiaqiao flow data from January to October in 2019
2022-04-18
This data is from the hydrological station of kafinigan River, a tributary of the upper Amu Darya River. The station is jointly built by Urumqi Institute of desert meteorology of China Meteorological Administration, Institute of water energy and ecology of Tajik National Academy of Sciences and Tajik hydrometeorological Bureau. The data can be used for scientific research such as water resources assessment and water conservancy projects in Central Asia. Data period: November 3, 2019 to December 3, 2020. Data elements: Hourly velocity (M / s), hourly water level (m) and hourly rainfall (m). Site location: 37 ° 36 ′ 01 ″ n, 68 ° 08 ′ 01 ″ e, 420m 1、 300w-qx River velocity and water level observation instrument （1） Flow rate parameters: 1 power supply voltage 12 (9 ~ 27) V (DC) The working current is 120 (110 ~ 135) MA 3 working temperature (- 40 ~ 85) ℃ 4 measurement range (0.15 ~ 20) m / S The measurement accuracy is ± 0.02m/s The resolution is less than 1 mm The detection range is less than 0.1 ~ 50 m 8 installation height 0.15 ~ 25 m 9 sampling frequency ＜ 20sps （2） Water level parameters: 1 measuring range: 0.5 ~ 20 m The measurement accuracy is ± 3 mm The resolution is less than 1 mm The repeatability was ± 1 mm 2、 SL3-1 tipping bucket rain sensor 1. Water bearing diameter Φ 200mm 2. The measured precipitation intensity is less than 4mm / min 3. Minimum precipitation of 0.1 mm 4. The maximum allowable error is ± 4% mm 3、 Flow velocity, frequency of data acquisition of the observation instrument: the sensor measures the flow velocity and water level data every 5S 4、 Calculation of hourly average velocity: the hourly average velocity and water level data are obtained from the average of all the velocity and water level data measured every 5S within one hour 5、 Description of a large number of values of 0 in water level data: the value of 0 in water level data is caused by power failure and restart of sensor due to insufficient power supply. The first data of initial start-up is 0, resulting in the hourly average value of 0. After the power supply transformation on July 26, 2020, the data returned to normal. At the end of September 2020, the power supply began to be insufficient. After the secondary power supply transformation on December 25, 2020, the data returned to normal 6、 Description of water level monitoring (such as line 7358, 2020 / 11 / 3, 16:00, maximum water level 6.7m, minimum water level 0m, how to explain? In addition, the maximum value of the highest water level is 6.7m, which appears many times in the data. It seems that 6.7m is the limit value of the monitoring data. Is this the case? ）: 6.7m is the height from the initial sensor to the bottom of the river bed. The appearance of 6.7m is the abnormal data when the sensor is just started. The sensor is restarted due to the power failure caused by the insufficient power supply of the equipment. This abnormal value appears in the initial start-up. After the power supply transformation on December 25, 2020, the data returns to normal
2022-04-18
The data is the phytoplankton data of 70 points in 26 lakes in Tibet in 2020. The sampling time is from August to September. The sampling method is the conventional phytoplankton sampling method. 1.5 liters of samples are collected, fixed by Lugo's solution, siphoned and concentrated after static precipitation, and the results are examined by inverted microscope. The data includes the density data of different phytoplankton of 77 species / genus in 10 categories, including diatom, green algae, cyanobacteria, dinoflagellate, naked algae, cryptoalgae, brown algae, brown algae and CHAROPHYTA. This data is original and unprocessed. The unit is piece / L. The data can be used to characterize the composition and abundance of phytoplankton in the open water areas of these lakes, and can also be used to calculate the diversity of phytoplankton communities in these lakes.
2022-04-15
Based on the meteorological data of 105 meteorological stations in and around the Qinghai Tibet Plateau from 1980 to 2019, the National Meteorological Science Data Center of China Meteorological Administration (CMA) was established. By calculating the oxygen content, it is found that there is a significant linear correlation between oxygen content and altitude, y = - 0.0263x + 283.8, R2 = 0.9819. Therefore, the oxygen content distribution map can be calculated based on DEM data grid. Due to the limitation of the natural environment in the Qinghai Tibet Plateau, there are few related fixed-point observation institutions. This data can reflect the distribution of oxygen content in the Qinghai Tibet Plateau to a certain extent, and has certain reference significance for the research of human living environment in the Qinghai Tibet Plateau.
2021-01-25
Lake ice is an important parameter of Cryosphere. Its change is closely related to climate parameters such as temperature and precipitation, and can directly reflect climate change. Therefore, lake ice is an important indicator of regional climate parameter change. However, due to the poor natural environment and sparsely populated area, it is difficult to carry out large-scale field observation, The spatial resolution of 10 m and the temporal resolution of better than 30 days were used to monitor the changes of different types of lake ice, which filled in the blank of observation. The hmrf algorithm is used to classify different types of lake ice. The distribution of different types of lake ice in some lakes with an area of more than 25km2 in the three polar regions is analyzed by time series to form the lake ice type data set. The distribution of different types of lake ice in these lakes can be obtained. The data includes the sequence number of the processed lake, the year and its serial number in the time series, and vector The data set includes the algorithm used, sentinel-1 satellite data, imaging time, polar region, lake ice type and other information. Users can determine the change of different types of lake ice in time series according to the vector file.
2020-08-05
The data include the collection of elements and isotopes of river water and groundwater (including spring water) in hulugou small watershed of Heihe River. Sampling location: (1) There are two river water sampling points, one of which is located at the outlet weir of hulugou small watershed in the upper reaches of Heihe River, with longitude and latitude of 99 ° 52 ′ 47.7 ″ E and 38 ° 16 ′ 11 ″ n. The second sampling point is located at the outlet of hulugou area II in the upper reaches of Heihe River, with longitude and latitude of 99 ° 52 ′ 58.40 ″ E and 38 ° 14 ′ 36.85 ″ n. (2) The sampling points of groundwater spring and well water are located at 20m to the east of the drainage basin outlet, with longitude and latitude of 99 ° 52 ′ 50.9 ″ E and 38 ° 16 ′ 11.44 ″ n. The well water sampling point is located near the intersection of East and West Branch ditches, with longitude and latitude of 99 ° 52 ′ 45.38 ″ E and 38 ° 15 ′ 21.27 ″ n. Data Description: 1. Doc and DIC values of river water and groundwater at the outlet of hulugou small watershed from July to September 2014 were analyzed. The DOC and DIC values of the samples were tested by oiaurora 1030w TOC instrument, and the detection range was 2ppb c-30000ppm C. 2. From July to September 2014, the δ D and δ 18O values of precipitation, river water and groundwater in hulugou small watershed were measured by Picaro l2130-i ultra-high precision liquid water and water vapor isotope analyzer. The results were expressed by δ values relative to the international standard material v-smow, with the measurement accuracy of 0.038 ‰ and 0.011 ‰ respectively. 3. Doc values of river water and soil water at the outlet of hulugou small watershed from May to September 2013 were determined by analytikjena multi n / C 3100 total nitrogen and total carbon tester. 4. Doc and DIC values of river water and groundwater at the outlet of hulugou small watershed from July to September 2014 were measured by oiaurora 1030w TOC instrument, and the detection range was 2ppb c-30000ppm C.
2020-07-30
Data of industrial structure change and water use evolution trend of social and economic development in Heihe River Basin
2020-07-28
This project use distributed HEIFLOW Ecological hydrology model (Hydrological - Ecological Integrated watershed - scale FLOW model) of heihe river middle and lower reaches of the eco Hydrological process simulation.The model USES the dynamic land use function, and adopts the land use data of the three phases of 2000, 2007 and 2011 provided by hu xiaoli et al. The space-time range and accuracy of simulation are as follows: Simulation period: 2000-2012, of which 2000 is the model warm-up period Analog step size: day by day Simulation space range: the middle and lower reaches of heihe river, model area 90589 square kilometers Spatial accuracy of the simulation: 1km×1km grid was used on both the surface and underground, and there were 90589 hydrological response units on the surface.Underground is divided into 5 layers, each layer 90589 mobile grid The data set of HEIFLOW model simulation results includes the following variables: (1) precipitation (unit: mm/month) (2) observed values of main outbound runoff in the upper reaches of heihe river (unit: m3 / s) (3) evapotranspiration (unit: mm/month) (4) soil infiltration amount (unit: mm/month) (5) surface yield flow (unit: mm/month) (6) shallow groundwater head (unit: m) (7) groundwater evaporation (unit: m3 / month) (8) supply of shallow groundwater (unit: m3 / month) (9) groundwater exposure (unit: m3 / month) (10) river-groundwater exchange (unit: m3 / month) (11) simulated river flow value of four hydrological stations of heihe main stream (gaoya, zhengyi gorge, senmaying, langxin mountain) (unit: cubic meter/second) The first two variables above are model-driven data, and the rest are model simulation quantities.The time range of all variables is 2001-2012, and the time scale is month.The spatial distributed data precision is 1km×1km, and the data format is tif. In the above variables, if the negative value is encountered, it represents the groundwater excretion (such as groundwater evaporation, groundwater exposure, groundwater recharge channel, etc.).If groundwater depth is required, the groundwater head data can be subtracted from the surface elevation data of the model. In some areas, the groundwater head may be higher than the surface, indicating the presence of groundwater exposure. In addition, the dataset provides: Middle and downstream model modeling scope (format:.shp) Surface elevation of the middle and downstream model (in the format of. Tif) All the above data are in the frame of WGS_1984_UTM_Zone_47N. Take heiflow_v1_et_2001m01.tif as an example to illustrate the naming rules of data files: HEIFLOW: model name V1: data set version 1.0 ET: variable name 2001M01: January 2000, where M represents month
2020-07-28
The distribution map of irrigation area and main and branch canals in Heihe River basin includes the main irrigation area and the distribution of all main and branch canals in Heihe River Basin. The irrigation area mainly includes Luocheng irrigation area, Youlian irrigation area, Liuba irrigation area, Pingchuan irrigation area, liaoquan irrigation area, Liyuan River irrigation area, yannuan irrigation area, Banqiao irrigation area, Shahe irrigation area, Xijun irrigation area, Yingke irrigation area, Daman irrigation area, Maying River irrigation area, shangsan irrigation area, Xinba irrigation area and Hongyazi irrigation area. The distribution map of main and branch canals includes all the main canals and branch canals of these 16 irrigation areas.
2020-07-28
Zhangye basin mainly includes 20 irrigation areas. Under the restriction of water diversion, the surface water consumption of the irrigation area is under control, but the groundwater exploitation is increased, resulting in the groundwater level drop in the middle reaches, resulting in potential ecological environment risks. Due to the complex and frequent exchange of surface water and groundwater in the study area, it is possible to realize the overall water resource saving by optimizing the utilization ratio of surface water and groundwater in each irrigation area. In this project, on the premise of not changing the water demand of the middle reaches irrigation area, the two problems of maximizing the outflow of Zhengyi Gorge (given groundwater reserve constraint) and maximizing the outflow of Zhengyi Gorge (given groundwater reserve constraint) are studied.
2020-06-11
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