Based on the long-term observation data of each field station in the alpine network and 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; the inversion of data products such as meteorological elements, lake water quantity and quality, aboveground vegetation biomass, glacial and frozen soil changes are completed through enhanced observation and sample site verification in key regions; based on the IOT Network technology, the development and establishment of multi station network meteorological, hydrological, ecological data management platform, to achieve real-time access to network data and remote control and sharing. In 2018, the hydrological data set of surface process and environmental observation network in China's alpine region mainly collects the daily measured hydrological (runoff, water level, water temperature, etc.) data of Qilianshan station, Southeast Tibet station, Zhufeng station, Yulong Xueshan station, Namucuo station, Ali station, mostag and other seven stations.
The study of chemical weathering is of great significance to understand how the plateau uplift regulates the mechanism of climate change and the circulation of elements and materials in the sphere. The data set is the seasonal major element concentration and stable isotope data of the river water at the hydrological station of the Yellow River Basin originating from the Qinghai Tibet Plateau. There are two hydrological stations in total: 1. Longmen hydrological station in the middle reaches of the Yellow River is the high-resolution (weekly) sample data collected in 2013, and the element concentrations include K, CA, Na, Mg, SO4, HCO3, Cl, etc. The cation data of collected water samples are tested on ICP-AES of Institute of earth environment, Chinese Academy of Sciences, and the anion data are tested on ion chromatograph (ics1200) of Nanjing Institute of geography and lakes, Chinese Academy of Sciences. The uncertainty is within 5%, and HCO3 is tested by titration. The high-resolution (weekly) Li isotope data of river water was tested in MC-ICP-MS of Institute of earth environment, Chinese Academy of Sciences in 2017, and the test accuracy 2sd is better than 5 ‰; 2. Tangnaihai hydrological station on the Yellow River is the river water (month by month) data set collected from July 2012 to June 2014. The major element concentrations include K, CA, Na, Mg, SO4, HCO3, Cl, etc., and the stable isotope data include s, O and H. The data set can be used to study the modern weathering process under the background of the uplift of the Qinghai Tibet Plateau, and provides the first-hand reliable data for the study of physical erosion and chemical weathering in the basin.
China's high-quality natural gauge-based streamflow dataset (CNRD_gauge) was developed from a well-trained and tested land surface model (VIC) that coupled to a routing model with flow direction correction. The dataset currently covers multiple hydrological stations for the period 1961–2018 , and will continue to update. The land surface model was trained by a comprehensive parameter uncertainty framework, including parameter sensitivity, optimization, and regionalization. The rooting model was corrected based on high-resolution river flowlines, as well the ascertained gauge locations and catchment areas. Supported by a well-trained model system, about 83% of the catchments across China exhibited NSE > 0.7, and about 56% of the catchments exhibited KGE > 0.7. The systematic bias of estimated natural streamflow from a calibrated land surface model was reduced by the statistical post-processing technique with the Pbias metric decreased from 17.13% to 2.27%. The reconstructed gauge-based streamflow dataset provides a reliable representation of natural hydrological processes in regions affected by intensive human activity.
This dataset provides the in-situ lake water parameters of 124 closed lakes with a total lake area of 24,570 km2, occupying 53% of the total lake area of the TP.These in-situ water quality parameters include water temperature, salinity, pH,chlorophyll-a concentration, blue-green algae (BGA) concentration, turbidity, dissolved oxygen (DO), fluorescent dissolved organic matter (fDOM), and water clarity of Secchi Depth (SD).
The data set contains the data of rivers and lakes in Sichuan Tibet transportation corridor. The river is divided into 1-4 grades. The rivers are numbered and geocoded. The data can be used not only as the basic elements of regional geographic base map, but also as the basic conditions of hydrological regional division. The data source is not the national 1:1 million basic geographic data, covering the national land area and the main islands including Taiwan Island, Hainan Island, Diaoyu Island, South China Sea Islands and their adjacent waters, with a total of 77 1:1 million maps. The overall current situation of the data is 2015. 2000 national geodetic coordinate system, 1985 National elevation datum, longitude and latitude coordinates are used.
This dataset contains the physicochemical properties and water environment indicators of typical alpine wetlands in the Selincuo and Lhasa River basins of the Tibetan Plateau. Wetland water samples were obtained through field sampling, and data on the physicochemical indicators of the water bodies were obtained through chemical analysis in the laboratory. Some indicators were measured in the field using instruments. The data analysis method meets the requirements of relevant national standards and the results are reliable. The data can be used as background data for the water environment of wetlands on the Tibetan Plateau, to assess the ecological and environmental quality of wetlands, and to study the impact of climate change on alpine wetlands.
Lake salinity is an important parameter of lake water environment, an important embodiment of water resources, and an important part of climate change research. This data is based on the measured salinity data of lakes in the Qinghai Tibet Plateau. The salinity is characterized by the practical salinity unit (PSU), which is converted from the specific conductivity (SPC) measured by the conductivity sensor. ArcGIS software was used to convert the measured data into space vector format. SHP format, and the measured salinity spatial distribution data file was obtained. The data can be used as the basic data of lake environment, hydrology, water ecology, water resources and other related research reference.
The data set consists of four sub tables, which are remote sensing monitoring of Lake area from 2000 to 2019, total lake water storage based on underwater 3D simulation model, Lake area volume equation based on underwater 3D simulation model, and key parameters and results of water storage measurement and Simulation of 24 typical lakes in Qinghai Province. The first sub table is the time series Lake area data from 2000 to 2019 from remote sensing image data monitoring. The third sub table stores the area storage capacity equation of the lake based on the underwater three-dimensional simulation model of the lake. The second sub table is the estimation result by combining the time series Lake area data and the area storage capacity equation, Finally, the key parameters and results of water storage measurement and Simulation of 24 typical lakes in Qinghai Province from 2000 to 2019 are obtained, including simulated water depth, maximum water depth, simulated reference water level and corresponding Lake area of each lake, which are stored in the fourth sub table.
In 2017, 27 surface sediments were collected in Qinghai Lake by gravity sampler, and the top 1cm was taken as the surface layer, which was freeze-dried and ground into powder after being taken back to the laboratory. Before testing the content of organic carbon and nitrogen, 1mol / L hydrochloric acid should be used to stir the reaction for more than 10 hours, so that the carbonate is completely removed, then dried and ground, and the organic carbon and nitrogen are tested on the element analyzer. The total inorganic carbon content is the carbonate content of the whole rock powder sample measured by infrared spectrum, which is then calculated as the total inorganic carbon content. The contents of organic carbon and inorganic carbon constitute the total carbon content of the lake, and they are close to each other, indicating that the inorganic carbon burial flux and organic carbon burial flux of Qinghai Lake are similar.
This dataset includes data recorded by the Qinghai Lake integrated observatory network obtained from an observation system of Meteorological elements gradient of Yulei station on Qinghai lake from Janurary 1 to December 31, 2020. The site (100° 29' 59.726'' E, 36° 35' 27.337'' N) was located on the Yulei Platform in Erlangjian scenic area, Qinghai Province. The elevation is 3209m. The installation heights and orientations of different sensors and measured quantities were as follows: air temperature and humidity profile (HMP155; 12 and 12.5 m above the water surface, towards north), wind speed and direction profile (windsonic; 14 m above the water surface, towards north) , rain gauge (TE525M; 10m above the water surface in the eastern part of the Yulei platform ), four-component radiometer (NR01; 10 m above the water surface, towards south), one infrared temperature sensors (SI-111; 10 m above the water surface, towards south, vertically downward), photosynthetically active radiation (LI190SB; 10 m above the water surface, towards south), water temperature profile (109, -0.2, -0.5, -1.0, -2.0, and -3.0 m). The observations included the following: air temperature and humidity (Ta_12 m, Ta_12.5 m; RH_12 m, RH_12.5 m) (℃ and %, respectively), wind speed (Ws_14 m) (m/s), wind direction (WD_14 m) (°) , 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) (℃), photosynthetically active radiation (PAR) (μmol/ (s m-2)), water temperature (Tw_20cm、Tw_50cm、Tw_100cm、Tw_200cm、Tw_300cm) (℃). 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. As the lake water freezes in winter, the water temperature probe is withdrawn, so there is no water temperature data record during October 19, 2020 to December 31, 2020. 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: 2018-1-1 10:30. Moreover, suspicious data were marked in red.