Based on the Sentinel-2 and Landsat 5/7/8 multispectral instrument imageries combined with in-situ measured hydrological data, bankfull river geometry of six major exorheic river basins of the Qinghai-Tibet Plateau (the upper Yellow River, upper Jinsha River, Yalong River, Lantsang River, Nu River and Yalung Zangbo River) are presented. River surface of six mainstreams and major tributaries are included. For each river basin, two types of rivers are included: connected and disconnected rivers. Format of the dataset is .shp exported from the ArcGIS 10.5. Three products are included in the dataset: one original product (bankfull river surface dataset) and two derived products (bankfull river width dataset and bankfull river surface area dataset with a 1 km river length interval). These three products are in three folders. The first folder, “1-Bankfull River Surface”, contains river surface vectors for six river basins in the .shp file. The second folder, “2-Bankfull River Width”, contains bankfull river widths and corresponding coordinates with a 1 km-step river length for six mainstreams and some connected tributaries in .xlsx format. The river width vectors in the .shp files are also provided in the second folder. The third folder, “3-Bankfull River Surface Area”, contains bankfull river surface areas and corresponding coordinates with a 1 km-step river length for six mainstreams and some connected tributaries in .xlsx format. Three Supplementary Files are included: Supplementary File 1, tables and figures related to the dataset; Supplementary File 2, used for river surface extraction based on GEE platform; Supplementary File 3, used for river width extraction based on Matlab. The provided planform river hydromorphology data can supplement global hydrography datasets and effectively represent the combined fluvial geomorphology and geological background in the study area.
LI Dan , XUE Yuan , QIN Chao , WU Baosheng , CHEN Bowei , WANG Ge
The data set of bacterial post-treatment products and conventional water quality parameters of some lakes in the third pole in 2015 collected the bacterial analysis results and conventional water quality parameters of some lakes in the Qinghai Tibet Plateau during 2015. Through sorting, summarizing and summarizing, the bacterial post-treatment products of some lakes in the third pole in 2015 are obtained. The data format is excel, which is convenient for users to view. The samples were collected by Mr. Ji mukan from July 1 to July 15, 2015, including 28 Lakes (bamuco, baimanamuco, bangoso (Salt Lake), Bangong Cuo, bengcuo, bieruozhao, cuo'e (Shenza), cuo'e (Naqu), dawaco, dangqiong Cuo, dangjayong Cuo, Dongcuo, eyaco, gongzhucuo, guogencuo, jiarehbu Cuo, mabongyong Cuo, Namuco, Nier CuO (Salt Lake), Norma Cuo, Peng yancuo (Salt Lake), Peng Cuo, gun Yong Cuo, Se lincuo, Wu rucuo, Wu Ma Cuo, Zha RI Nan Mu Cuo, Zha Xi CuO), a total of 138 samples. The extraction method of bacterial DNA in lake water is as follows: the lake water is filtered onto a 0.45 membrane, and then DNA is extracted by Mo bio powerOil DNA kit. The 16S rRNA gene fragment amplification primers were 515f (5'-gtgccagcmgcgcggtaa-3') and 909r (5'-ggactachvggtwtctaat-3'). The sequencing method was Illumina miseq PE250. The original data were analyzed by mothur software, including quality filtering and chimera removal. The sequence classification was based on the silva109 database. The archaeal, eukaryotic and unknown source sequences had been removed. OTU classifies with 97% similarity and then removes sequences that appear only once in the database. Conventional water quality detection parameters include dissolved oxygen, conductivity, total dissolved solids, salinity, redox potential, nonvolatile organic carbon, total nitrogen, etc. The dissolved oxygen is determined by electrode polarography; Conductivity meter is used for conductivity; Salinity is measured by a salinity meter; TDS tester is used for total dissolved solids; ORP online analyzer was used for redox potential; TOC analyzer is used for non-volatile organic carbon; The water quality parameters of total nitrogen were obtained by Spectrophotometry for reference.
YE Aizhong
Normalized Difference Vegetation Index (NDVI) has been widely used for monitoring vegetation. This dataset employed all available Landsat 5/7/8 data on the Qinghai-Tibetan Plateau (QTP) (> 100,000 scenes), and reconstructed high spatiotemporal NDVI time-series data (30-m and 8-d) during 2000-2020 on the TP (QTP-NDVI30) by using the MODIS-Landsat fusion algorithm (gap filling and Savitzky–Golay filtering；GF-SG). For the details of GF-SG, please refer to Chen et al. (2021). This dataset has been evaluated carefully. The quantitative assessments show that the reconstructed NDVI images have an average MAE value of 0.02, correlation coefficient of 0.96, and SSIM value of 0.94. We compared the reconstructed images in some typical areas with the PlanetScope 3-m images and found that the spatial details were well preserved by QTP-NDVI30. The geographic coordinate system of this dataset is GCS_WGS_84. The spatial range covers the vegetation area of the QTP, which is defined as the areas with average NDVI during July- September larger than 0.15.
CAO Ruyin , XU Zichao , CHEN Yang , SHEN Miaogen , CHEN Jin
This dataset include major, trace, neodymium and strontium isotope geochemical data of 72 riverine sand samples from the Yarlung Tsangpo-Brahmaputra-Ganges river system, including 48 samples from the Yarlung Tsangpo River and its tributaries, 19 samples from the Brahmaputra River and its tributaries, and 5 samples from the Ganges River. The major elements include SiO2, Al2O3, Fe2O3 and other 7 elements from all 72 samples, expressed as percentage of oxides; trace elements include Li, Be, Sc and other 41 elements from 30 samples, expressed as parts per million (ppm); neodymium isotope data includes 143Nd/144Nd ratios and their error values from 26 samples; while strontium isotope data includes 87Sr/86Sr ratios and their error values for 26 samples. The main elements were analyzed using a PANalytical Axios X-ray fluorescence analyzer (XRF), with testing errors <3%; trace elements were tested using a Thermo Fisher VG-X7 inductively coupled plasma mass spectrometer (ICP-MS), with testing errors <5%; Nd and Sr isotopes were tested using a Thermo Fisher NEPTUNE plus multi-collector inductively coupled plasma mass spectrometer (MC-ICP-MS), with deviations of <0.005% for Sr and <0.004% for Nd isotopes relative to the reference values of the international standards. All the above laboratory tests were performed at the State Key Laboratory of Marine Geology, Tongji University. The data are of both scientific and social importance for understanding the tectonic activity, chemical weathering, and source-to-sink transport of riverine sediments in large drainage basins from the Tibetan Plateau, as well as for assessing the inter-relationship between natural processes and human activities.
LIU Zhifei , ZHAO Yulong , YU Mingyang , LIN Baozhi , ZAKIR HOSSAIN H.M, TARAL Suchana , CHAKRABORTY Tapan
The data are the detrital zircon ages of the late Cretaceous early Cenozoic strata in Sichuan Basin, Xichang Basin, Huili basin and Chuxiong Basin on the eastern margin of the Qinghai Tibet Plateau; All detrital zircon samples collected in this study are sandstone. The crushing and zircon selection of samples were completed in Langfang Chengxin Geological Service Co., Ltd; Zircon U-Pb dating was done at the State Key Laboratory of Earthquake Dynamics, Institute of Geology, China Earthquake Administration using laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS). At least 200 zircon grains were randomly selected to adhere to double-sided adhesive, and were poured into the laser sample target with epoxy resin. All samples were ablated by using a laser beam with a diameter of 28μm, a frequency of 10 Hz and laser energy density of 4.0J/cm 2 .
ZHANG Huiping
Lakes collect runoff, sediment and nutrients from upstream watersheds and are an important "destination" of material migration at the watershed scale. Therefore, the attributes of lake water and sediment are affected by catchment attributes (e.g. climate, terrain and vegetation conditions) to a large degree. This dataset delineates the watershed boundaries of 1525 Lakes (with an area from 0.2 to 4503 square kilometers) on the Tibetan Plateau, and calculates 721 catchment-scale attributes on the aspects of lake body, terrain, climate, vegetation, soil/geology and anthropogenic activities. This is the first dataset of lake-catchment characteristics on the Tibetan Plateau, which can provide foundamental data for the study of lakes in the Tibetan Plateau.
LIU Junzhi
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