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.
The data includes ten typical hydropower stations in Datong River Basin of Qinghai-Tibet Plateau in July 2020, including Duolong Hydropower Station, Gousikou Hydropower Station, Jinxing Hydropower Station, Kasuoxia Hydropower Station, Liancheng Hydropower Station, Nazixia Hydropower Station, Stone Gorge Hydropower Station, Tianwanggou Hydropower Station, Tiemai Hydropower Station and Xueyitan Hydropower Station. Data are helpful to study the distribution and use of hydropower stations in Datong River Basin. The data were taken by the expedition team through aerial photography using DJI UAV RTK and Royal Series, and spliced by DJI mapping software. The aerial image data has high definition, which can obviously observe the water level difference between upstream and downstream of the hydropower station and the topographic distribution around the hydropower station. The data can be applied to the research field of hydropower stations in Qinghai-Tibet Plateau, providing relevant analysis data.
This dataset contains the LAI measurements from the Daman superstation in the middle reaches of the Heihe integrated observatory network from June 1 to September 20 in 2020. The site (100.376° E, 38.853°N) was located in the maize surface, near Zhangye city in Gansu Province. The elevation is 1556 m. There are 6 observation samples, each of which is about 30m×30m in size, and the latitude and longitude are (100.376°E, 38.853°N), (100.377° E, 38.858°N), (100.374°E, 38.855°N), (100.374°E, 38.858°N), (100.371°E, 38.854°N), (100.369°E, 38.854°N). Five sub-canopy nodes and one above-canopy node are arranged in each sample. The data is obtained from LAINet measurements; the four-steps are performed to obtain LAI: the raw data is light quantum (level 0); the daily LAI can be obtained using the software LAInet (level 1); further the invalid and null values are screened and using the 7 days moving averaged method to obtain the processed LAI (level 2); for the multi LAINet nodes observation, the averaged LAI of the nodes area is the final LAI (level 3). The released data are the post processed LAI products and stored using *.xls format. For more information, please refer to Liu et al. (2018) (for sites information), Qu et al. (2014) for data processing) in the Citation section.
The dataset of water quality investigation in the urbanized area of Tibetan Plateau mainly includes the investigation data of water quality in the Huangshui River Basin and other key urban areas of Tibetan Plateau. The data were collected during July-August, 2020, by Hash DR900 water quality monitor. The datasets include the measured water quality of each reach of the Huangshui River, and the upstream and downstream of rivers that flow through major towns on the Tibetan Plateau. The main parameters include: total nitrogen, total phosphorus, ammonia nitrogen, chemical oxygen demand, dissolved oxygen content, pH, hardness, turbidity and chroma. To note, the chemical indexes (total nitrogen, total phosphorus, ammonia nitrogen, chemical oxygen demand) were determined in the laboratory after the scientific expedition, and the time interval between sample collection and water quality determination is too long to sustain the original content of ammonia nitrogen, thus the ammonia nitrogen of some water samples were not measured. In addition, due to the budget restriction, only water samples from the river outlet of towns on the plateau were allowed to measure the chemical indexes. Our dataset will support the study of optimizing the ecological security barrier system and validating ecohydrological models in the key urbanized areas of the Tibetan Plateau.
This data set is the summary of the survey results of rural small hydropower in Tibet in 2018. The main contents include the name, installed capacity, start-up time and completion time of small hydropower stations in different districts and counties of each prefecture and city in Tibet Autonomous Region, as well as the operation status of each hydropower station. The hydropower development in Tibet Autonomous Region has an early history. There are not many large and medium-sized hydropower stations, mainly in rural areas. With the development of social economy, most of the small hydropower stations in Tibet Autonomous Region have been shut down. At present, the development of large and medium-sized hydropower projects is the main one. In plateau areas where Hydropower Survey data are scarce, this data set reflects the history and current situation of small hydropower in Tibet Autonomous Region, and can provide a certain data basis for hydropower development survey and evaluation in Tibet Autonomous Region.
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.