This data mainly includes ten day runoff data of Yingluo gorge and Zhengyi gorge in Heihe River Basin, among which the time range of Yingluo gorge data is 1944-2010 and Zhengyi gorge data is 1947-2010. Source: Heihe River Basin Authority. Data unit: 100 million cubic meters / 10 days. Data format: Excel "Yingluo gorge 2" and "Yingluo gorge 2 (2)" in the data table are the ten day runoff data of Yingluo gorge, the same as "Yingluo gorge" in the data table, and Yingluo gorge 2 (2) contains the chart.
WANG Zhongjing
The observation frequency is 1 time / 30 minutes with hobo automatic temperature recorder. No. 01: the observation point is located at the exit of zone III divided by Cold and Arid Regions Environmental and Engineering Research Institute, Chinese Academy of Sciences, and the boundary point between the cold desert zone and the cold meadow zone. The coordinates of the observation point (99 ° 53 ′ 37 ″ e, 38 ° 13 ′ 34 ″ n) are 100cm from the surface of the air temperature recorder. The observation period is from July 28 to September 2, 2012. No. 02: the observation point is located at the exit of No. 2 area divided by Cold and Arid Regions Environmental and Engineering Research Institute, Chinese Academy of Sciences, where the terrain is gentle, at the outlet of the alluvial delta valley where there is no other tributary flowing in. The observation point coordinates (99 ° 52 ′ 58 ″ e, 38 ° 14 ′ 36 ″ n) the temperature recorder in the air is 120cm from the ground surface. The observation period is from July 4, 2012 to September 6, 2012
SUN Ziyong, CHANG Qixin
The data includes the discharge data of the outlet river of No.2 catchment area of hulugou small watershed from July 24 to September 11, 2014 / 2015. Sampling location: the coordinates of river flow monitoring section are located at the outlet of No. 2 catchment area, near the red wall, with coordinates of 99 ° 52 ′ 58.40 ″ E and 38 ° 14 ′ 36.85 ″ n. The soil temperature monitoring depth in hulugou is 20cm, 50cm, 100cm, 200cm and 300cm. The monitoring depth of groundwater temperature is 10m. The observation frequency is 1 time / 1 hour. The time range of observation data is from May 13, 2015 to September 5, 2015. Sampling location: the soil temperature monitoring point in hulugou small watershed is located in the middle of the Delta, with the geographic coordinates of 99 ° 52 ′ 45.38 ″ E and 38 ° 15 ′ 21.27 ″ n.
MA Rui
This data provides the annual lake area of 582 lakes with an area greater than 1 km2 in the enorheic basin of the Qinghai-Tibet Plateau from 1986 to 2019. First, based on JRC and SRTM DEM data, 582 lakes are identified in the area that are larger than 1 km2. All Landsat 5/7/8 remote sensing images covering a lake are used to make annual composite images. NDWI index and Ostu algorithm were used to dynamically segment lakes, and the size of each lake from 1986 to 2019 is then calculated. This study is based on the Landsat satellite remote sensing images, and using Google Earth Engine allowed us to process all Landsat images available to create the most complete annual lake area data set of more than 1 km2 in the Qinghai-Tibet Plateau area; A set of lake area automatic extraction algorithms were developed to calculate of the area of a lake for many years; This data is of great significance for the analysis of lake area dynamics and water balance in the Qinghai-Tibet Plateau region, as well as the study of the climate change of the Qinghai-Tibet Plateau lake.
ZHU Liping,
This data is from the central station of environmental monitoring in gansu province. The data includes three observation elements that are disclosed on the network, namely PH, permanganate index and ammonia nitrogen. The data format is a text file. The first column is the city name, the second column is PH, the third column is permanganate index, the fourth column is ammonia nitrogen, and the fifth column is the observation date. The data include 6 sections of gushuizi, niubei village, wufo temple, shichuan bridge, xincheng bridge and bikou. Gansu section of the Yellow River: xincheng bridge (lanzhou upstream section), shichuan bridge (lanzhou - baiyin junction section), wufo temple (gansu-ningxia junction section), niubei village (gansu-shaanxi junction section).Bailong river wudu section :(section of gushuizi village). Lanzhou city bridge automatic water quality monitoring station is located in xigu district, lanzhou city, gansu province.Point coordinates 103 degrees 35 minutes 02 seconds east longitude, 36 degrees 07 minutes 20 seconds north latitude.Yellow River system (Yellow River main stream), state - controlled provincial boundary section.By lanzhou city environmental monitoring station custody.It's 35 kilometers away.Built in March 2001. PH: the index that characterizes the acidity and alkalinity of water. When the pH value is 7, it is neutral, less than 7 is acidic, and greater than 7 is alkaline.The pH value of natural surface water is generally between 6 and 9. When algae grow in the water, they absorb carbon dioxide due to photosynthesis, resulting in an increase in surface pH value. Permanganate index (CODMn) : the amount consumed when treating surface water samples with potassium permanganate as the oxidant, expressed as mg/L of oxygen.Under these conditions, reductive inorganic substances (ferrous salts, sulphides, etc.) and organic pollutants in water can consume potassium permanganate, which is often used as a comprehensive indicator of the degree of surface water pollution by organic pollutants.Also known as the chemical oxygen demand potassium permanganate method, as distinct from the chemical oxygen demand (COD) of the potassium dichromate method, which is often used to monitor wastewater discharge. Ammonia nitrogen (nh3-n) : ammonia nitrogen exists in water in the form of dissolved ammonia (also known as free ammonia, NH3) and ammonium salt (NH4+). The ratio of the two depends on the pH value and water temperature of the water, and the content of ammonia nitrogen is expressed by the amount of N element.The main sources of ammonia nitrogen in the water are domestic sewage and some industrial wastewater (such as coking and ammonia synthesis industry) and surface runoff (mainly refers to the fertilizer used in farmland entering rivers, lakes, etc.). This data will be updated automatically and continuously according to the data source.
Gansu environmental monitoring center station
This data set includes a monthly composite of 30 m × 30 m surface vegetation coverage products in the Qilian Mountain Area in 2019. In this paper, the maximum value composition (MVC) method is used to synthesize monthly NDVI products and calculate FVC by using the reflectance data of Landsat 8 and sentinel 2 red and near infrared channels. The data is monthly synthesized by Google Earth engine cloud platform, and the index is calculated by the model. The missing pixels are interpolated with good quality, which can be used in environmental change monitoring and other fields.
SUN Ziyong, CHANG Qixin
River and lake resources are important components for studying the Earth ecological environment, affecting global ecosystems, heat, material exchange and balance and serving as an important basis for studying changes in the global environmental mechanism. At present, the lack of global lake vector data with large-scale, high-precision, and large-range has hindered hydrological research on rivers and lakes. Taking the data collection of global rivers and lakes of Jun Chen as the source data and combining the domestic high-resolution image GF data of 2 to 3 years before and after 2010, a data set of global rivers and lakes was generated. This data set makes up for the shortcomings of low precision in some areas and is an editable lake and river vector data set with high accuracy.
QIU Yubao
The runoff record of Pailugou watershed in the upper reaches of Heihe River, dated from January 2011 to September 2012. The data measuring device is the measuring weir at the exit of the small watershed, the unit of the data is m³/day.
HE Zhibin
The data is the river dataset of Qinghai Lake Basin. It is revised according to the topographic map and TM remote sensing image. The scale is 250,000. The projected latitude and longitude. The data includes spatial data and attribute data. The attribute data fields are: HYD_CODE (river code), Name (river name), SHAPE_leng ( River length).
National Basic Geographic Information Center
1、 Data overview: use solinst leveloger automatic water level gauge to observe river water level, calculate flow data through water level flow curve, and manually observe the flow through self-made flow weir (see thumbnail). Due to the limited amount of manual observation data, further supplementary observation is needed to improve the water level discharge curve. 2、 Data content: we manually observe the water level and flow data of the two sections. The first section: the exit of area III divided by Cold and Arid Regions Environmental and Engineering Research Institute, Chinese Academy of Sciences, the boundary point between cold desert zone and cold meadow zone, where the valley is deep and the bedrock is exposed. Coordinates of observation points (99 ° 53 ′ 37 ″ e, 38 ° 13 ′ 34 ″ n). The observation period is from July 21, 2012 to May 6, 2013. The observation frequency of automatic observation data is 1 time / 30 minutes from July 21 to July 25, 2012. 1 time / 15 minutes from July 25, 2012 to May 6, 2013. After September 15, 2012, there was an error in the automatic monitoring data of the observation point. The reason may be that the flow of the river channel became smaller, the probe was exposed to the air, and the water level gauge could not correctly reflect the change of the flow of the river channel. At the same time, the temperature decreased after September, and the river channel froze in winter. There was no automatic monitoring flow data during this period. The second section: the exit of No.2 area divided by Cold and Arid Regions Environmental and Engineering Research Institute, Chinese Academy of Sciences, with flat terrain, is located at the catchment of the outlet of the alluvial delta Valley, and the south side is the shrub area. A small flow weir is built. The observation point coordinates (99 ° 52 ′ 58 ″ e, 38 ° 14 ′ 36 ″ n), and the observation frequency of automatic observation data is 1 time / 15 minutes. The observation period is from July 21, 2012 to May 6, 2013. After the observation point entered September, the river flow gradually decreased and there was no water in the river. At this time, the reading of water level gauge can not correctly reflect the change of river discharge. At the same time, our field experience shows that from September to May of the next year, the observation point is basically in a state of no water.
SUN Ziyong, YU Linan
The near surface atmospheric forcing and surface state dataset of the Tibetan Plateau was yielded by WRF model, time range: 2000-2010, space range: 25-40 °N, 75-105 °E, time resolution: hourly, space resolution: 10 km, grid number: 150 * 300. There are 33 variables in total, including 11 near surface atmospheric variables: temperature at 2m height on the ground, specific humidity at 2m height on the ground, surface pressure, latitudinal component of 10m wind field on the ground, longitudinal component of 10m wind field on the ground, proportion of solid precipitation, cumulative cumulus convective precipitation, cumulative grid precipitation, downward shortwave radiation flux at the surface, downward length at the surface Wave radiation flux, cumulative potential evaporation. There are 19 surface state variables: soil temperature in each layer, soil moisture in each layer, liquid water content in each layer, heat flux of snow phase change, soil bottom temperature, surface runoff, underground runoff, vegetation proportion, surface heat flux, snow water equivalent, actual snow thickness, snow density, water in the canopy, surface temperature, albedo, background albedo, lower boundary Soil temperature, upward heat flux (sensible heat flux) at the surface and upward water flux (sensible heat flux) at the surface. There are three other variables: longitude, latitude and planetary boundary layer height.
PAN Xiaoduo
The matching data of water and soil resources in the Qinghai Tibet Plateau, the potential evapotranspiration data calculated by Penman formula from the site meteorological data (2008-2016, national meteorological data sharing network), the evapotranspiration under the existing land use according to the influence coefficient of underlying surface, and the rainfall data obtained by interpolation from the site rainfall data in the meteorological data, are used to calculate the evapotranspiration under the existing land use according to the different land types of land use According to the difference, the matching coefficient of water and soil resources is obtained. The difference between the actual rainfall and the water demand under the existing land use conditions reflects the matching of water and soil resources. The larger the value is, the better the matching is. The spatial distribution of the matching of soil and water resources can pave the way for further understanding of the agricultural and animal husbandry resources in the Qinghai Tibet Plateau.
DONG Lingxiao
The dataset is the distribution map of lakes in Qinghai Lake Basin. The projection is latitude and longitude. The data includes the spatial distribution data and attribute data of the lake. The attribute fields of the lake are: NAME (lake name), CODE (lake code).
WU Lizong
The water level observation data set of lakes on the Tibetan Plateau contains the daily variations of water levels for three lakes: Zhari Namco, Bamco and Dawaco. The lake water level was obtained by a HOBO water level gauge (U20-001-01) installed on the lakeshore, then corrected using the barometer installed on the shore or pressure data of nearby weather stations, and then the real water level changes were obtained. The accuracy was less than 0.5 cm. The items of this data set are as follows: Daily variation data of water level in Zhari Namco from 2009 to 2014; Daily variation data of water level in Bamco from 2013 to 2014; Daily variation data of water level in Dawaco from 2013 to 2014. Water level, unit: m.
LEI Yanbin
The data is a dataset of rivers in the Tarim River Basin. It is revised according to topographic maps and TM remote sensing images. The scale is 250,000. The data includes spatial data and attribute data. The attribute data fields are: HYD_CODE (river code), Name (river name), SHAPE_leng ( River length).
National Basic Geographic Information Center
The dataset is a lake distribution map of Tarim River Basin, with a scale of 250000, projection: latitude and longitude, data including spatial data and attribute data, and lake attribute fields: NAME (name of lake) and CODE (lake code)
National Basic Geographic Information Center
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.
Tian Bangsen, QIU Yubao
GLObal WAter BOdies database（GLOWABO）were obtained based on the GeoCoverTM Water bodies Extraction Method, Charles verpoorer et al， by Landsat 7 ETM + image in 2000 ± 3 years. The water extraction method combines the principal component analysis, threshold extraction, texture feature extraction and other methods, with a spatial resolution of 15 m and an overall accuracy of 91%. The data also includes water area, perimeter, shape index, elevation and other information. In this data set, The Three River Headwater region, Pul River Basin and Yukon River Basin, are selected to provide data support for polar hydrological research in the northern hemisphere.
Charles Verpoorter
Based on 11 well-acknowledged global-scale microwave remote sensing-based surface soil moisture products, and with 9 main quality impact factors of microwave-based soil moisture retrieval incorporated, we developed the Remote Sensing-based global Surface Soil Moisture dataset (RSSSM, 2003~2020) through a complicated neural network approach. The spatial resolution of RSSSM is 0.1°, while the temporal resolution is approximately 10 days. The original dataset covered 2003~2018, but now it has been updated to 2020. RSSSM dataset is outstanding in terms of temporal continuity, and has full spatial coverage except for snow, ice and water bodies. The comparison against the global-scale in-situ soil moisture measurements indicates that RSSSM has a higher spatial and temporal accuracy than most of the frequently-used global/regional long-term surface soil moisture datasets. In addition, although RSSSM is remote sensing based, without the incorporation of any precipitation data or records, its interannual variation generally conforms with that of precipitation (e.g., the GPM IMERG precipitation data) and Standardized Precipitation Evapotranspiration Index (SPEI). Moreover, RSSSM can also reflect the impact of human activities, e.g., urbanization, cropland irrigation and afforestation on soil moisture changes to some degree. The data is in ‘Tiff’ format, and the size after compression is 2.48 GB. The relevant data describing paper has been published in the Journal ‘Earth System Science Data’ in 2021.
CHEN Yongzhe, FENG Xiaoming, FU Bojie
There are three types of glacial lakes: supraglacial lakes, lakes attached to the end of the glacier and lakes not attached to the end of the glacier. Based on this classification, the following properties are studied: the variation in the number and area of glacial lakes in different basins in the Third Pole region, the changes in extent in terms of size and area, distance from glaciers, the differences in area changes between lakes with and without the supply of glacial melt water runoff, the characteristics of changes in the glacial lake area with respect to elevation, etc. Data source: Landsat TM/ETM+ 1990, 2000, 2010. The data were visually interpreted, which included checking and editing by comparing the original image with Google Earth images when the area was greater than 0.003 square kilometres. The data were applied to glacial lake changes and glacial lake outburst flood assessments in the Third Pole region. Data type: Vector data. Projected Coordinate System: Albers Conical Equal Area.
ZHANG Guoqing
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