Shule River Basin is one of the three inland river basins in Hexi corridor. In recent years, with the obvious change of climate and the aggravation of human activities, the shortage of water resources and the problem of ecological environment in Shule River Basin have become increasingly prominent. It is of great significance to study the runoff change of Shule River Basin in the future climate situation for making rational water resources planning and ecological environment protection The data is river data set of Shule River Basin, revised according to topographic map and TM remote sensing image, with a scale of 250000. The data includes spatial data and attribute data, and attribute data fields: HYD CODE (River code), Name (river name) and SHAPE Leng (river length). Collect and sort out the basic, meteorological, topographical and geomorphic data of Shule River Basin, and provide data support for the management of Shule River Basin.
National Basic Geographic Information Center
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
ZHENG Chunmiao
The data set mainly includes the ice observation frequency (ICO) of north temperate lakes in four periods from 1985 to 2020, as well as the location, area and elevation of the lakes. Among them, the four time periods are 1985-1998 (P1), 1999-2006 (P2), 2007-2014 (P3) and 2015-2020 (P4) respectively, in order to improve the "valid observation" times in the calculation period and improve the accuracy. The ICO of the four periods is calculated by the ratio of "icing" times and "valid observation" times counted by all Landsat images in each period. Other lake information corresponds to the HydroLAKEs data set through the "hylak_id" column in the table. In addition, the data only retains about 30000 lakes with an area of more than 1 square kilometer, which are valid for P1-P4 observation. The data set can reflect the response of Lake icing to climate change in recent decades.
WANG Xinchi
The 1:1 million wetland data of Guangdong Province (2000) is cut from the "1:1 million wetland data of China". "China 1:100,000 wetland data" mainly reflects the information of marshes and wetlands throughout the country in the 2000s, and is represented by geographical coordinates in decimal scale. The main contents include: types of marshes and wetlands, types of water supply, types of soil, types of main vegetation, and geographical regions.The information classification and coding standard of China sustainable development information sharing system was implemented.Data source of this database: 1:20 swamp map (internal version), 1:500 000 swamp map (internal version) of qinghai-tibet plateau, 1:100 000 swamp survey data and 1:400 000 swamp map of China;The processing steps are as follows: data source selection, preprocessing, marshland element digitization and coding, data editing and processing, establishment of topological relationship, edge-to-edge processing, projection transformation, connection with attribute database such as geographical name and acquisition of attribute data.
ZHANG Shuqing
The distribution of lakes in space and its change over time are closely related to agricultural, environmental and ecological issues, and are critical factors for human socio-economic development. In the past decades, satellite based remote sensing has been developed rapidly to provide essential data sources for monitoring temporal lakes dynamics with its advantage of rapidness, wide coverage, and lower cost. This dataset was produced from Landsat images using the automated water detection method (Feng et al, 2015). We collected 96,278 Landsat images (about 25 terabytes) that acquired since 2000 with less than 80% cloud contamination in the arid region of central Asia and Tibetan Plateau. Water is detected in each of the image and then aggregated to monthly temporal resolution by taking advantage of the high-performance processing capability and large data storage provided by Global Land Cover Facility (GLCF) at University of Maryland. The results are validated systematically and quantitatively using manually interpreted dataset, which consists of a set of locations collected by a stratified random sampling strategy to effectively represent different spatial-temporal distributions in the region. The validation suggests high accuracy of the results (overall accuracy: 99.45(±0.59); user accuracy: 85.37%±(3.74); produce accuracy: 98.17(±1.05)).
FENG Min, CHE Xianghong
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.
MA Rui , CHANG Qixin
The data of this study is mainly based on Google Earth Engine big data cloud processing platform. Sentinel-2 of The Three River Headwater region, Pul and Yukon River Basins in 2017 is selected as the basic data, STRM-DEM and Global Surface Water are used as auxiliary data. AWEIn，AWEIs，WI2015，MNDWI，NDWI and other index threshold extraction are selected to obtain seasonal water body and permanent water body according to annual water frequency(spatial resolution 10m). This water data product provides effective basic data for high spatial-temporal resolution water body change and permafrost hydrological analysis.
RAN Youhua
Glacier is the supply water source of rivers in the western mountainous area, and it is one of the most basic elements for people to survive and develop industry, agriculture and animal husbandry in the western region. Glaciers are not only valuable fresh water resources, but also the source of serious natural disasters in mountainous areas, such as sudden ice lake outburst flood, glacier debris flow and ice avalanche. Glacier hydrological monitoring is the basis for studying the characteristics of glacier melt water, the replenishment of glacier melt water to rivers, the relationship between glacier surface ablation and runoff, the process of ice runoff and confluence, and the calculation and prediction of floods and debris flows induced by glacier and seasonal snow melt water. Glacial hydrology refers to the water and heat conditions of glacial covered basins (i.e. glacial action areas), that is, the water and heat exchange between glaciers and their surrounding environment, the physical process of water accumulation and flow on the surface, inside and bottom of glaciers, the water balance of glaciers, the replenishment of glacial melt water to rivers, and the impact of water bodies in cold regions on climate change. At present, hydrological monitoring stations are mainly established at the outlet of the river basin to carry out field monitoring《 Glacial water resources of China (1991), hydrology of cold regions of China (2000) and glacial Hydrology (2001) summarize the early studies on glacial hydrology. China has carried out glacier hydrological monitoring on more than 20 glaciers in Tianshan, Karakorum, West Kunlun, Qilian, Tanggula, Nianqing Tanggula, gangrigab, Hengduan and Himalayas. This data set is the monthly runoff data of representative glaciers.
YANG Wei, LI Zhongqin, WANG Ninglian, QIN Xiang
The dataset includes vector map of the lakes larger than 1k㎡ on Tibetan Plateau in 1970s, 1990, 2000, 2010. The lake boundry data was extracted from remote sensing image like Landsat MSS, TM, ETM+, by means of visual interpretation. The data type is vector data, and it's attribute class includes Area (km²). The Projected Coordinate System is Albers Conical Equal Area. It is mainly used in the study of changes in lakes, hydrological and meteorological on the Tibetan Plateau.
ZHANG Guoqing
Shule River Basin is one of the three inland river basins in Hexi corridor. In recent years, with the obvious change of climate and the aggravation of human activities, the shortage of water resources and the problem of ecological environment in Shule River Basin have become increasingly prominent. It is of great significance to study the runoff change of Shule River Basin in the future climate situation for making rational water resources planning and ecological environment protection. The data is the reservoir distribution data set of Shule River Basin, which is comprehensively prepared by topographic map and remote sensing image, scale 250000, projection: longitude and latitude, data including spatial data and attribute data, attribute field: name (reservoir name), reflecting the current distribution of water reservoirs in Shule River Basin in 2000. Collect and sort out the basic, meteorological, topographical and geomorphic data of Shule River Basin, and provide data support for the management of Shule River Basin.
Based on the data of Keyhole satellite in 1960s, using object-oriented supervised classification and manual visual interpretation and correction, water data products are produced. The total interpretation area is 645,000 km2, accounting for 96.28% of the study area, of which 18,844 km2 is missing in The Three River Headwater region, 4,220 km2 is missing in the Yukon River basin study area in Alaska, and 1,954 km2 is missing in the Pul River basin in West Siberia. The width of the minimum linear figure is more than 8 meters, the area of the minimum surface figure is more than 100 square meters, the trace accuracy is 2 pixels, and the first-class interpretation accuracy is more than 95%. The obtained high spatial resolution surface water data products provide effective data for the study of water changes in the 1960s and reliable basis for the study of frozen soil changes.
RAN Youhua
The third pole 1:100,000 Water data set includes：Different grades of river lines（Tibet_River）、Polygonal drainage pattern（Tibet_Water_poly）vector space data set and its attribute name：Name（name）、Type（Type）、water leng（leng）、water area（Area）. The data comes from the 1:100,000 ADC_WorldMap global data set，The data through topology, warehousing and other data quality inspection，Data through the topology, into the library，It's comprehensive, up-to-date and seamless geodigital data. The world map coordinate system is latitude and longitude, D_WGS_1984 datum surface
ADC WorldMap
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.
ZHU Liping
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
ZHU Liping,
The Qinghai Tibet Plateau is known as the "Asian water tower", and its runoff, as an important and easily accessible water resource, supports the production and life of billions of people around, and supports the diversity of ecosystems. Accurately estimating the runoff of the Qinghai Tibet Plateau and revealing the variation law of runoff are conducive to water resources management and disaster risk avoidance in the plateau and its surrounding areas. The glacier runoff segmentation data set covers the five river source areas of the Qinghai Tibet Plateau from 1971 to 2015, with a time resolution of year by year, covering the five river source areas of the Qinghai Tibet Plateau (the source of the Yellow River, the source of the Yangtze River, the source of the Lancang River, the source of the Nujiang River, and the source of the Yarlung Zangbo River), and the spatial resolution is the watershed. Based on multi-source remote sensing and measured data, it is simulated using the distributed hydrological model vic-cas coupled with the glacier module, The simulation results are verified with the measured data of the station, and all the data are subject to quality control.
WANG Shijin
The data is the river dataset of the north slope of Tianshan River Basin. It is revised according to the topographic map and TM remote sensing image. The scale is 250,000, and the projection is latitude and longitude. The data includes spatial data and attribute data, attribute data fields: HYD_CODE (river code), Name (river name), SHAPE_ leng (river length).The data includes spatial data and attribute data. , SHAPE_leng (river length).
National Basic Geographic Information Center
This dataset includes inland water data of five countries in the Great Lakes region of Central Asia (Kazakhstan, Kyrgyzstan, Tajikistan, Turkmenistan and Uzbekistan), including the distribution of rivers, canals and lakes. The line and area features of each country are stored in different files. The dataset comes from the Digital Map of the World (DCW), and its main source is the Operational Navigation Map (ONC) 1:1,000,000 scale paper map series of the US Defense Survey and Mapping Agency (DMA) produced by the United States, Australia, Canada and the UK. The DCW database is the most comprehensive global geographic information system database available free of charge since 2006, although it has not been updated since 1992.
XU Xiaofan, TAN Minghong
This dataset includes inland water data of five countries in the Great Lakes region of Central Asia (Kazakhstan, Kyrgyzstan, Tajikistan, Turkmenistan and Uzbekistan), including the distribution of rivers, canals and lakes. The line and area features of each country are stored in different files. The dataset comes from the Digital Map of the World (DCW), and its main source is the Operational Navigation Map (ONC) 1:1,000,000 scale paper map series of the US Defense Survey and Mapping Agency (DMA) produced by the United States, Australia, Canada and the UK. The DCW database is the most comprehensive global geographic information system database available free of charge since 2006, although it has not been updated since 1992.
XU Xiaofan, TAN Minghong
This dataset includes inland water data of five countries in the Great Lakes region of Central Asia (Kazakhstan, Kyrgyzstan, Tajikistan, Turkmenistan and Uzbekistan), including the distribution of rivers, canals and lakes. The line and area features of each country are stored in different files. The dataset comes from the Digital Map of the World (DCW), and its main source is the Operational Navigation Map (ONC) 1:1,000,000 scale paper map series of the US Defense Survey and Mapping Agency (DMA) produced by the United States, Australia, Canada and the UK. The DCW database is the most comprehensive global geographic information system database available free of charge since 2006, although it has not been updated since 1992.
XU Xiaofan, TAN Minghong
The data is clipped from "1: 1 million wetland data of China". "1: 1 million wetland data of China" mainly reflects the national marsh wetland information in the 2000s. It is expressed in geographic coordinates using the decimal degree. The main contents include: marsh wetland types, wetland water supply types, soil types, main vegetation types, geographical area, etc. Implemented the "Standard for Information Classification and Coding of Sustainable Development Information Sharing System of China". Data source of this database: 1:20 swamp map (internal version), Tibetan Plateau 1: 500,000 swamp map (internal version), swamp survey data 1: 1 million and national 1: 4 million swamp map; processing steps are: data source selection, preprocessing, digitization and encoding of marsh wetland elements, data editing processing, establishing topological relationships, edge processing, projection conversion, linking with attribute databases such as place names and obtaining attribute data.
ZHANG Shuqing
Contact Support
Northwest Institute of Eco-Environment and Resources, CAS
0931-4967287
poles@itpcas.ac.cn
Links
National Tibetan Plateau Data CenterFollow Us
A Big Earth Data Platform for Three Poles © 2018-2020 No.05000491 | All Rights Reserved
｜ 
No.11010502040845
Tech Support: westdc.cn
