This data is generated based on meteorological observation data, hydrological station data, combined with various assimilation data and remote sensing data, through the preparation of the Qinghai Tibet Plateau multi-level hydrological model system WEB-DHM (distributed hydrological model based on water and energy balance) coupling snow, glacier and frozen soil physical processes. The time resolution is monthly, the spatial resolution is 5km, and the original data format is ASCII text format, Data types include grid runoff and evaporation (if evaporation is less than 0, it means condensation; if runoff is less than 0, it means precipitation is less than evaporation in the month). If the asc cannot be opened normally in arcmap, please top the first 5 lines of the asc file.
WANG Lei, CHAI Chenhao
This data is a 5km monthly hydrological data set, including grid runoff and evaporation (if evaporation is less than 0, it means condensation; if runoff is less than 0, it means precipitation is less than evaporation), simulated and output through the WEB-DHM distributed hydrological model of the Indus River basin, with temperature, precipitation, barometric pressure, etc. as input data.
WANG Lei, LIU Hu
This product provides the data set of key variables of the water cycle of major Arctic rivers (North America: Mackenzie, Eurasia: Lena from 1971 to 2017, including 7 variables: precipitation, evapotranspiration, surface runoff, underground runoff, glacier runoff, snow water equivalent and three-layer soil humidity, which are numerically simulated by the land surface model vic-cas developed by the project team. The spatial resolution of the data set is 0.1degree and the temporal resolution is month. This data set can be used to analyze the change of water balance in the Arctic River Basin under long-term climate change, and can also be used to compare and verify remote sensing data products and the simulation results of other models.
ZHAO Qiudong, WANG Ninglian, WU Yuwei
The SZIsnow dataset was calculated based on systematic physical fields from the Global Land Data Assimilation System version 2 (GLDAS-2) with the Noah land surface model. This SZIsnow dataset considers different physical water-energy processes, especially snow processes. The evaluation shows the dataset is capable of investigating different types of droughts across different timescales. The assessment also indicates that the dataset has an adequate performance to capture droughts across different spatial scales. The consideration of snow processes improved the capability of SZIsnow, and the improvement is evident over snow-covered areas (e.g., Arctic region) and high-altitude areas (e.g., Tibet Plateau). Moreover, the analysis also implies that SZIsnow dataset is able to well capture the large-scale drought events across the world. This drought dataset has high application potential for monitoring, assessing, and supplying information of drought, and also can serve as a valuable resource for drought studies.
WU Pute, TIAN Lei, ZHANG Baoqing
The dataset was produced based on MODIS data. Parameters and algorithm were revised to be suitable for the land cover type in the Three-River-Source Regions. By using the Markov de-cloud algorithm, SSM/I snow water equivalent data was fused to the result. Finally, high accuracy daily de-cloud snow cover data was produced. The data value is 0(no snow) or 1(snow). The spatial resolution is 500m, the time period is from 2000-2-24 to 2019-12-31. Data format is geotiff, Arcmap or python+GDAL were recommended to open and process the data.
HAO Xiaohua
This data is a 5km monthly hydrological data set, including grid runoff and evaporation (if evaporation is less than 0, it means condensation; if runoff is less than 0, it means precipitation is less than evaporation). This data is a 5km monthly hydrological data set, including grid runoff and evaporation (if evaporation is less than 0, it means condensation; if runoff is less than 0, it means precipitation is less than evaporation).
WANG Lei
The basic meteorological data set of the China-Mongolia-Russia Economic Corridor meteorological station includes wind speed, wind direction, precipitation, temperature and snow depth. The time resolution is 3 hours. The site is scattered around the corridor and the number of sites is 29. The data set was extracted based on the National Oceanic and Atmospheric Administration's National Environmental Information Center (NCEI) hourly/sub-hour observation dataset. In addition to the data itself, each data includes information such as data quality assessment results and data acquisition methods. In addition, the precipitation data of each site is composed of 4 detection devices to ensure data stability. Snow depth data includes snow depth and equivalent water depth dimensions, ie the depth of water after the snow melts.
LI Shengyu, FAN Jinglong
This data is a simulated output data set of 5km monthly hydrological data obtained by establishing the WEB-DHM distributed hydrological model of the source regions of Yangtze River and Yellow River, using temperature, precipitation and pressure as input data, and GAME-TIBET data as verification data. The dataset includes grid runoff and evaporation (if the evaporation is less than 0, it means deposition; if the runoff is less than 0, it means that the precipitation in the month is less than evaporation). This data is a model based on the WEB-DHM distributed hydrological model, and established by using temperature, and precipitation (from itp-forcing and CMA) as input data, GLASS, MODIA, AVHRR as vegetation data, and SOILGRID and FAO as soil parameters. And by the calibration and verification of runoff，soil temperature and soil humidity, the 5 km monthly grid runoff and evaporation in the source regions of Yangtze River and Yellow River from 1998 to 2017 was obtained. If asc can't open normally in arcmap, please delete the blacks space of the top 5 lines of the asc file.
WANG Lei
The data include three data sets of Namcu and Muztagh Ata: an atmospheric aerosol data set of monthly average values of TSP, lithium, sodium and other elements; an atmospheric precipitation chemical data set of monthly average values of soluble sodium ions, potassium ions, magnesium ions, calcium ions and other ions; and a data set of chemical compositions of snow ice in the Zhadang Glacier of Namcu Basin of the concentrations of soluble sodium ions, potassium ions, magnesium ions, calcium ions and other ions in snow pits collected in different months. The data can be used in conducting located observations of atmospheric aerosol element content, precipitation chemistry, and glacier snow ice chemical records in the Namco and Muztagh Ata areas. The samples were processed at the Key Laboratory of Tibetan Environment Changes and Land Surface Processes of CAS using ICS2500 and ICS2000 ion-chromatographic analyzers to determine the concentration of soluble anions and cations in the samples. Data collection and processing: 1. The automatic rain gauges were erected in the typical regions of the Tibetan Plateau (the Namco Basin and the Muztagh Ata Peak area) to collect precipitation samples. The precipitation samples were collected using a SYC-2 type rainfall sampler that comprised a collector, rain sensor and gland drive. The sample collector was provided with a rain collection bucket and a dust collection bucket, and the weather condition was sensed by the rain sensor. The rain collection bucket would be opened when it started to rain, and the gland would be pressed onto the dust collection bucket. Meanwhile, the date and the rain start and end times were automatically recorded. When the rain stopped, the gland automatically flipped to the rain collection bucket to complete a rainfall record. The collected samples were placed in 20 mL clean high-density polyethylene plastic bottles and refrigerated in a -20 °C refrigerator. They were frozen during transportation and storage until right before being analyzed, when they would be taken from the refrigerator and thawed at room temperature (20 °C). They were then processed at the Key Laboratory of Tibetan Environment Changes and Land Surface Processes CAS using ICS2500 and ICS2000 ion-chromatographic analyzers to determine the concentration of soluble anions and cations in the precipitation. 2. The atmospheric aerosol sampler installed at Namco Station was 4 m above the ground and included a vacuum pump, which was powered by solar panels and batteries. The air flux was recorded by an automatic flow meter, and the instantaneous flow rate was approximately 16.7 L/min. The air flux took the meteorological parameter conversion of the Namco area as the standard volume. A Teflon filter with a diameter of 47 mm and a pore size of 0.4 & mu; m was used. The sample interval was 7 days, and the total sample flow rate of each sample was approximately 120-150 m³. Each sample was individually placed in a disposable filter cartridge and stored at low temperature in a refrigerator. Before and after sampling, the filter was placed in a constant temperature (20 ± 5 °C) and constant humidity (40 & plusmn; 2%) environment for 48 hours and weighed with a 1/10000 electronic balance (AUW220D, Shimadu); the difference between the weights before and after was the weight of the aerosol sample on the filter. The collected samples were processed at the Key Laboratory of Tibetan Environment Changes and Land Surface Processes CAS by ICP-MS to determine the concentrations of 18 elements. Strict measures were taken during indoor and outdoor operations to prevent possible contamination. 3. A precleaned plastic shovel was used to collect a sample every 5 cm from the lower part of the snow pit (samples were collected every 10 cm in some snow pits). The samples were dissolved at room temperature, placed in 20 mL clean high-density polyethylene plastic bottles and stored in a refrigerator at -20 °C. The samples were frozen during transportation and storage until they were taken out of the refrigerator before the analysis and melted at room temperature. The samples were processed at the Key Laboratory of Tibetan Environment Changes and Land Surface Processes CAS using ICS2500 and ICS2000 ion-chromatographic analyzers to determine the concentrations of soluble anions and cations in the samples. Clean clothing, disposable masks and plastic gloves should be worn during the manual collection of glacier snow ice chemical samples to prevent contamination. The data set was processed by forming a continuous sequence of monthly mean values after the raw data were quality controlled. It meets the accuracy of routine monitoring research on precipitation, aerosol, snow and ice records in China and the world and is satisfactory for comparative study with relevant climate change records.
KANG Shichang
This data set includes the observation data of 25 water net sensor network nodes in Babao River Basin in the upper reaches of Heihe River from January 2015 to December 2015. 4cm and 20cm soil moisture / temperature is the basic observation of each node; some nodes also include 10cm soil moisture / temperature, surface infrared radiation temperature, snow depth and precipitation observation. The observation frequency is 5 minutes. The data set can be used for hydrological simulation, data assimilation and remote sensing verification. For details, please refer to "2015 data document 20160501. Docx of water net of Babao River in the upper reaches of Heihe River"
KANG Jian, LI Xin, MA Mingguo
This data set includes the observation data of 40 water net sensor network nodes in Babao River Basin in the upper reaches of Heihe River since the end of June 2013. Soil moisture of 4cm, 10cm and 20cm is the basic observation of each node; 19 nodes include the observation of soil moisture and surface infrared radiation temperature; 11 nodes include the observation of soil moisture, surface infrared radiation temperature, snow depth and precipitation. The observation frequency is 5 minutes. The data set can be used for hydrological simulation, data assimilation and remote sensing verification.
KANG Jian, LI Xin, MA Mingguo
This data set includes the observation data of 40 water net sensor network nodes in Babao River Basin in the upper reaches of Heihe River since January 2014. Soil moisture of 4cm, 10cm and 20cm is the basic observation of each node; 19 nodes include the observation of soil moisture and surface infrared radiation temperature; 11 nodes include the observation of soil moisture, surface infrared radiation temperature, snow depth and precipitation. The observation frequency is 5 minutes. The data set can be used for hydrological simulation, data assimilation and remote sensing verification. Please refer to "waternet data document 20141206. Docx" for details
KANG Jian, LI Xin, MA Mingguo
The data set is the meteorological and observational data of hulugou shrub experimental area in the upper reaches of Heihe River, including meteorological data, albedo data and evapotranspiration data under shrubs. 1. Meteorological data: Qilian station longitude: 99 ° 52 ′ E; latitude: 38 ° 15 ′ n; altitude: 3232.3m, scale meteorological data from January 1, 2012 to December 31, 2013. Observation items include: temperature, humidity, vapor pressure, net radiation, four component radiation, etc. The data are daily scale data, and the calculation period is 0:00-24:00 2. Albedo: daily surface albedo data from January 1, 2012 to July 3, 2014, including snow and non snow periods. The measuring instrument is the radiation instrument on the 10m gradient tower in hulugou watershed. Among them, the data from August 4 to October 2, 2012 was missing due to instrument circuit problems, and the rest data quality was good 3. Evapotranspiration: surface evapotranspiration data of Four Typical Shrub Communities in hulugou watershed. The observation period is from July 18 to August 5, 2014, which is the daily scale data. The data include precipitation data, evaporation and infiltration data observed by lysimeter. The data set can be used to analyze the evapotranspiration data of alpine shrubs and forests. The evapotranspiration of grassland under canopy was measured by a small lysimeter with a diameter of 25 cm and a depth of 30 cm. Two lysimeters were set up in each shrub plot, and one lysimeter was set for each shrub in transplanting experiment. The undisturbed undisturbed soil column with the same height as the barrel is placed in the inner bucket, and the outer bucket is buried in the soil. During the embedding, the outer bucket shall be 0.5-1.0 cm higher than the ground, and the outer edge of the inner barrel shall be designed with a rainproof board about 2.0 cm wide to prevent surface runoff from entering the lysimeter. Lysimeter was set up in the nearby meteorological stations to measure grassland evapotranspiration, and a small lysimeter with an inner diameter of 25 cm and a depth of 30 cm was also set up in the sample plot of Picea crassifolia forest to measure the evaporation under the forest. All lysimeters are weighed at 20:00 every day (the electronic balance has a sensing capacity of 1.0 g, which is equivalent to 0.013 mm evaporation). Wind proof treatment should be taken to ensure the accuracy of measurement. Data processing method: evapotranspiration is mainly calculated by mass conservation in lysimeter method. According to the design principle of lysimeter lysimeter, evapotranspiration is mainly determined by the quality difference in two consecutive days. Since it is weighed every day, it is calculated by water balance.
SONG Yaoxuan, LIU Zhangwen
This data is 2002.07.04-2010.12.31 MODIS daily cloudless snow products in the Tibetan Plateau. Due to the snow and cloud reflection characteristics, the use of optical remote sensing to monitor snow is severely disturbed by the weather. This product is based on the most commonly used cloud removal algorithm, using the MODIS daily snow product and passive microwave data AMSR-E snow water equivalent product, and the daily cloudless snow product in the Tibetan Plateau is developed. The accuracy is relatively high. This product has important value for real-time monitoring of snow cover dynamic changes on the Tibetan Plateau. Projection method: Albers Conical Equal Area Datum: D_Krasovsky_1940 Spatial resolution: 500 m Data format: tif Naming rules: maYYMMDD.tif, where ma represents the data name; YY represents the year (01 represents 2001, 02 represents 2002 ...); MM represents the month (01 represents January, 02 represents February ...); DD represents the day (01 Means 1st, 02 means 2nd ...).
HUANG Xiaodong
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