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
As an important part of global semi-arid grassland, adequately understanding the spatio-temporal variability of evapotranspiration (ET) over the temperate semi-arid grassland of China (TSGC) could advance our understanding of climate, hydrological and ecological processes over global semi-arid areas. Based on the largest number of in-situ ET measurements (13 flux towers) within the TSGC, we applied the support vector regression method to develop a high-quality ET dataset at 1 km spatial resolution and 8-day timescale for the TSGC from 1982 to 2015. The model performed well in validation against flux tower‐measured data and comparison with water-balance derived ET.
LEI Huimin
Meteorological forcing dataset for Arctic River Basins includes five elements: daily maximum, minimum and average temperature, daily precipitation and daily average wind speed. The data is in NetCDF format with a horizontal spatial resolution of 0.083°, covering Yenisy, Lena, ob, Yukon and Mackenzie catchments. The data can be used to dirve hydrolodical model (VIC model) for hydrological process simulation of the Arctic River Basins. The further quality control were made for daily observation data from Global Historical Climatology Network Daily database(GHCN-D), Global Summary of the Day (GSPD),The U.S. Historical Climatology Network (USHCN),Adjusted and homogenized Canadian climate data (AHCCD) and USSR / Russia climate data set (USSR / Russia). The thin plate spline interpolating method, which similar to the method used in PNWNAmet datasets (Werner et al., 2019), was employed to interpolate daily station data to 5min spatial resolution daily gridded forcing data using WorldClim and ClimateNA monthly climate normal data as a predictor.
ZHAO Qiudong, WU Yuwei
Terrestrial actual evapotranspiration (ETa) is an important component of terrestrial ecosystems because it links the hydrological, energy, and carbon cycles. However, accurately monitoring and understanding the spatial and temporal variability of ETa over the Tibetan Plateau (TP) remains very difficult. Here, the multiyear (2000-2018) monthly ETa on the TP was estimated using the MOD16-STM model supported by datasets of soil properties, meteorological conditions, and remote sensing. The estimated ETa correlates very well with measurements from 9 flux towers, with low root mean square errors (average RMSE = 13.48 mm/month) and mean bias (average MB = 2.85 mm/month), and strong correlation coefficients (R = 0.88) and the index of agreement values (IOA = 0.92). The spatially averaged ETa of the entire TP and the eastern TP (Lon > 90°E) increased significantly, at rates of 1.34 mm/year (p < 0.05) and 2.84 mm/year (p < 0.05) from 2000 to 2018, while no pronounced trend was detected on the western TP (Lon < 90°E). The spatial distribution of ETa and its components were heterogeneous, decreasing from the southeastern to northwestern TP. ETa showed a significantly increasing trend in the eastern TP, and a significant decreasing trend throughout the year in the southwestern TP, particularly in winter and spring. Soil evaporation (Es) accounted for more than 84% of ETa and the spatial distribution of temporal trends was similar to that of ETa over the TP. The amplitudes and rates of variations in ETa were greatest in spring and summer. The multi-year averaged annual terrestrial ETa (over an area of 2444.18×103 km2) was 376.91±13.13 mm/year, equivalent to a volume of 976.52±35.7 km3/year. The average annual evapotranspirated water volume over the whole TP (including all plateau lakes, with an area of 2539.49×103 km2) was about 1028.22±37.8 km3/year. This new estimated ETa dataset is useful for investigating the hydrological impacts of land cover change and will help with better management of watershed water resources across the TP.
MA Yaoming, CHEN Xuelong,
The data set includes annual mass balance of Naimona’nyi glacier (northern branch) from 2008 to 2018, daily meteorological data at two automatic meteorological stations (AWSs) near the glacier from 2011 to 2018 and monthly air temperature and relative humidity on the glacier from 2018 to 2019. In the end of September or early October for each year , the stake heights and snow-pit features (snow layer density and stratigraphy) are manually measured to derive the annual point mass balance. Then the glacier-wide mass balance was then calculated （Please to see the reference). Two automatic weather stations (AWSs, Campbell company) were installed near the Naimona’nyi Glacier. AWS1, at 5543 m a. s.l., recorded meteorological variables from October 2011 at half hourly resolution, including air temperature (℃), relative humidity (%), and downward shortwave radiation (W m-2) . AWS2 was installed at 5950 m a.s.l. in October 2010 at hourly resolution and recorded wind speed (m/s), air pressure (hPa), precipitation (mm). Data quality: the quality of the original data is better, less missing. Firstly, the abnormal data in the original records are removed, and then the daily values of these parameters are calculated. Two probes (Hobo MX2301) which record air temperature and relative humidity was installed on the glacier at half hour resolution since October 2018. The observed meteorological data was calculated as monthly values. The data is stored in Excel file. It can be used by researchers for studying the changes in climate, hydrology, glaciers, etc.
ZHAO Huabiao
The long-time series data set of extreme precipitation index in the arid region of Central Asia contains 10 extreme precipitation index long-time series data of 49 stations. Based on the daily precipitation data of the global daily climate historical data network (ghcn-d), the data quality control and outlier elimination were used to select the stations that meet the extreme precipitation index calculation. Ten extreme precipitation indexes (prcptot, SDII, rx1day, rx5day, r95ptot, r99ptot, R10, R20) defined by the joint expert group on climate change detection and index (etccdi) were calculated 、CWD、CDD）。 Among them, there are 15 time series from 1925 to 2005. This data set can be used to detect and analyze the frequency and trend of extreme precipitation events in the arid region of Central Asia under global climate change, and can also be used as basic data to explore the impact of extreme precipitation events on agricultural production and life and property losses.
YAO Junqiang, CHEN Jing, LI Jiangang
Land surface temperature (LST) is a key variable for high temperature and drought monitoring and climate and ecological environment research. Due to the sparse distribution of ground observation stations, thermal infrared remote sensing technology has become an important means of quickly obtaining ground temperature over large areas. However, there are many missing and low-quality values in satellite-based LST data because clouds cover more than 60% of the global surface every day. This article presents a unique LST dataset with a monthly temporal resolution for China from 2003 to 2017 that makes full use of the advantages of MODIS data and meteorological station data to overcome the defects of cloud influence via a reconstruction model. We specifically describe the reconstruction model, which uses a combination of MODIS daily data, monthly data and meteorological station data to reconstruct the LST in areas with cloud coverage and for grid cells with elevated LST error, and the data performance is then further improved by establishing a regression analysis model. The validation indicates that the new LST dataset is highly consistent with in situ observations. For the six natural subregions with different climatic conditions in China, verification using ground observation data shows that the root mean square error (RMSE) ranges from 1.24 to 1.58 K, the mean absolute error (MAE) varies from 1.23 to 1.37 K and the Pearson coefficient (R2) ranges from 0.93 to 0.99. The new dataset adequately captures the spatiotemporal variations in LST at annual, seasonal and monthly scales. From 2003 to 2017, the overall annual mean LST in China showed a weak increase. Moreover, the positive trend was remarkably unevenly distributed across China. The most significant warming occurred in the central and western areas of the Inner Mongolia Plateau in the Northwest Region, and the average annual temperature change is greater than 0.1K (R>0:71, P<0:05), and a strong negative trend was observed in some parts of the Northeast Region and South China Region. Seasonally, there was significant warming in western China in winter, which was most pronounced in December. The reconstructed dataset exhibits significant improvements and can be used for the spatiotemporal evaluation of LST in high-temperature and drought-monitoring studies. More detail please refer to Zhao et al (2020). doi.org/10.5281/zenodo.3528024
MAO Kebiao
The Land Surface Temperature in China dataset contains land surface temperature data for China (about 9.6 million square kilometers of land) during the period of 2003-2017, in Celsius, in monthly temporal and 5600 m spatial resolution. It is produced by combing MODIS daily data(MOD11C1 and MYD11C1), monthly data(MOD11C3 and MYD11C3) and meteorological station data to reconstruct real LST under cloud coverage in monthly LST images, and then a regression analysis model is constructed to further improve accuracy in six natural subregions with different climatic conditions.
MAO Kebiao
This data set includes the monthly average actual evapotranspiration of the Tibet Plateau from 2001 to 2018. The data set is based on the satellite remote sensing data (MODIS) and reanalysis meteorological data (CMFD), and is calculated by the surface energy balance system model (SEBS). In the process of calculating the turbulent flux, the sub-grid scale topography drag parameterization scheme is introduced to improve the simulation of sensible and latent heat fluxes. In addition, the evapotranspiration of the model is verified by the observation data of six turbulence flux stations on the Tibetan Plateau, which shows high accuracy. The data set can be used to study the characteristics of land-atmosphere interaction and the water cycle in the Tibetan Plateau.
HAN Cunbo, MA Yaoming, WANG Binbin, ZHONG Lei, MA Weiqiang*, CHEN Xuelong, SU Zhongbo
Precipitation estimates with fine quality and spatio-temporal resolutions play significant roles in understanding the global and regional cycles of water, carbon, and energy. Satellite-based precipitation products are capable of detecting spatial patterns and temporal variations of precipitation at fine resolutions, which is particularly useful over poorly gauged regions. However, satellite-based precipitation products are the indirect estimates of precipitation, inherently containing regional and seasonal systematic biases and random errors. Focusing on the potential drawbacks in generating Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (IMERG) and its recently updated retrospective IMERG in the Tropical Rainfall Measuring Mission (TRMM) era (finished in July 2019), which were only calibrated at a monthly scale using ground observations, Global Precipitation Climatology Centre (GPCC, 1.0◦/monthly), we aim to propose a new calibration algorithm for IMERG at a daily scale and to provide a new AIMERG precipitation dataset (0.1◦/half-hourly, 2000–2015, Asia) with better quality, calibrated by Asian Precipitation – Highly Resolved Observational Data Integration Towards Evaluation of Water Resources (APHRODITE, 0.25◦/daily) at the daily scale for the Asian applications. Considering the advantages from both satellite-based precipitation estimates and the ground observations, AIMERG performs better than IMERG at different spatio-temporal scales, in terms of both systematic biases and random errors, over mainland China.
MA Ziqiang
The field observation platform of the Tibetan Plateau is the forefront of scientific observation and research on the Tibetan Plateau. The land surface processes and environmental changes based comprehensive observation of the land-boundary layer in the Tibetan Plateau provides valuable data for the study of the mechanism of the land-atmosphere interaction on the Tibetan Plateau and its effects. This dataset integrates the 2005-2016 hourly atmospheric, soil hydrothermal and turbulent fluxes observations of Qomolangma Atmospheric and Environmental Observation and Research Station, Chinese Academy of Sciences (QOMS/CAS), Southeast Tibet Observation and Research Station for the Alpine Environment, CAS (SETORS), the BJ site of Nagqu Station of Plateau Climate and Environment, CAS (NPCE-BJ), Nam Co Monitoring and Research Station for Multisphere Interactions, CAS (NAMORS), Ngari Desert Observation and Research Station, CAS (NADORS), Muztagh Ata Westerly Observation and Research Station, CAS (MAWORS). It contains gradient observation data composed of multi-layer wind speed and direction, temperature, humidity, air pressure and precipitation data, four-component radiation data, multi-layer soil temperature and humidity and soil heat flux data, and turbulence data composed of sensible heat flux, latent heat flux and carbon dioxide flux. These data can be widely used in the analysis of the characteristics of meteorological elements on the Tibetan Plaetau, the evaluation of remote sensing products and development of the remote sensing retrieval algorithms, and the evaluation and development of numerical models.
MA Yaoming
This data set describes the temporal and spatial distribution of precipitation in the Upper Brahmaputra River Basin. We integrate (CMA, GLDAS, ITP-Forcing, MERRA2, TRMM) five sets of reanalysis precipitation products and satellite precipitation products, and combine the observation precipitation of 9 national meteorological stations from China Meteorological Administration (CMA) and 166 rain gauges of the Ministry of Water Resources (MWR) in the basin. The time range is 1981-2016, the time resolution is 3 hours, the spatial resolution is 5 km, and the unit is mm/h. The data will provide better data support for the study of Upper Brahmaputra River Basin, and can be used to study the response of hydrological process to climate change. Please refer to the instruction document uploaded with the data for specific usage information.
WANG Yuanwei, WANG Lei, LI Xiuping, ZHOU Jing
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
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
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 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 data set collects the long-term monitoring data on atmosphere, hydrology and soil from the Integrated Observation and Research Station of Multisphere in Namco, the Integrated Observation and Research Station of Atmosphere and Environment in Mt. Qomolangma, and the Integrated Observation and Research Station of the Alpine Environment in Southeast Tibet. The data have three resolutions, which include 0.1 seconds, 10 minutes, 30 minutes, and 24 hours. The temperature, humidity and pressure sensors used in the field atmospheric boundary layer tower (PBL) were provided by Vaisala of Finland. The wind speed and direction sensor was provided by MetOne of the United States. The radiation sensor was provided by APPLEY of the United States and EKO of Japan. Gas analysis instrument was provided by Licor of the United States, and the soil moisture content, ultrasonic anemometer and data collector were provided by CAMPBELL of the United States. The observing system is maintained by professionals on a regular basis (2-3 times a year), the sensors are calibrated and replaced, and the collected data are downloaded and reorganized to meet the meteorological observation specifications of the National Weather Service and the World Meteorological Organization (WMO). The data set was processed by forming a time continuous sequence after the raw data were quality-controlled, and the quality control included eliminating the systematic error caused by missing data and sensor failure.
MA Yaoming
The monthly precipitation data set of China's alpine mountains includes the qilian mountains (1960-2013), tianshan mountains (1954-2013) and Yangtze river source (1957-2014). The distributed hydrological model needs high-precision spatial distribution information of precipitation as input.Because of the scarcity of stations, the precipitation interpolation at stations cannot reflect the spatial distribution of precipitation in the alpine mountainous areas.Generation method of this dataset: (1) collect precipitation data of national meteorological stations and hydrological stations in various regions, and add precipitation observation data of field stations of Chinese academy of sciences above an altitude of 4000m; (2) use the temperature data of each station to correct the collected precipitation data of different precipitation types; (3) establish the relationship between precipitation data and altitude, longitude and latitude, and fit monthly to generate monthly precipitation data set of 1km scale. The interpolation year of this data is 1954-2014. The data projection method is Albers projection. The spatial interpolation precision is 1-km, and the time precision is monthly data.The results show that the interpolation precipitation is reliable. The data is stored in ASCII files. The file names of the monthly precipitation data files of tianshan mountain and Yangtze river source are in the form yyyymm.txt. YYYY is the year and MM is the month.The monthly precipitation data of qilian mountain is named as: month_10001.txt, this file is the precipitation data of January 1960, successively month_10002.txt is the precipitation of February 1960, and month_10013.txt is the precipitation data of January 1961,......Month_10648.txt represents the precipitation data for December 2013.Each ASCII file represents the grid precipitation data of the day in mm.
CHEN Rensheng, LIU Junfeng
1. Data overview: This data set is the scale meteorological gradient data of qilian station from January 1, 2012 to December 31, 2012 (installed at the end of September 2011).VG1000 gradient observation system carries out long-term monitoring of wind speed, wind direction, air temperature, humidity, radiation and other conventional meteorological elements, and carries out data storage and processing analysis in combination with the data collector with high precision and high scanning frequency. 2. Data content: The main observation factors include four layers of air temperature, humidity and two-dimensional ultrasonic wind, rain and snow volume meter, eight layers of ground temperature, soil moisture content, etc. 3. Space and time range: Geographical coordinates: longitude: longitude: 99° 52’e;Latitude: 38°15 'N;Height: 3232.3 m
CHEN Rensheng, HAN Chuntan
The data set contains all single glacial reserves (in KM3) in the Tibetan Plateau of 1970s and 2000s. This data set comes from the result data of the paper entitled "consolidating the Randolph glacier inventory and the glacier inventory of China over the Qinghai titanium plate and investigating glacier changes since the mid-20th century". The first draft of this paper has been completed and is planned to be submitted to earth system science data. The 1970s basic glacier catalog data in the dataset is extracted from Randolph glacier Inventory data set, 2000s basic glacial catalogue is from China's second glacial catalogue data set. Based on the glacial boundary extracted from the two data sets and combined with the grid based bedrock elevation data set (https://www.ngdc.noaa.gov/mgg/global/global.html, DOI: 10.7289/v5c8276m) and the glacial table obtained by a slope dependent method Based on the surface elevation data set, the single glacier reserves in the two catalogues are calculated. In addition, the calculation results of single glacier reserves obtained in this study have been compared and verified with the calculation results of partial glacier reserves, relevant remote sensing data sets, and the global glacier thickness data set based on the average of multiple glacier model sets in multiple directions, and the errors in the calculation results have also been quantified. The establishment of the data set is expected to provide the data basis for the future regional water resources estimation and glacier ablation research, and the acquisition of the data also provides a new idea for the future glacier reserves research.
WANG Zhongjing
Near-surface atmospheric driving data prepared by ETMonitor and WRF models based on remote sensing surface evapotranspiration model were used to estimate the average surface evapotranspiration of the heihe river basin with a resolution of 250m in 8 days from may to September 2012.The coordinate system is the projection of equal latitude and longitude, and the spatial range is 96.5e -- 102.5e, 37.5n -- 43N.8 days data using synthetic way of storage, the data format for GEOTIFF, naming: 2012 ddd_evapotranspiration. Tif, including a DDD, ordinal number, for example 2012121 _evapotranspiration. Tif said 2012 day ordinal number is 121-128 days, the average surface evaporation unit is mm/d.The data type is single-precision floating point with an invalid value of -9.
JIA Li
Near-surface atmospheric driving data prepared by ETMonitor and WRF models based on remote sensing surface evapotranspiration model were used to estimate the daily surface evapotranspiration of the heihe river basin at 1km from 2009 to 2011.The coordinate system is the longitude and latitude projection, and the spatial range is 96.5e -- 102.5e, 37.5n -- 43N.Using daily data storage, data format for GEOTIFF, naming: yyyyddd_EvapoTranspiration. tif, including yyyy for years, DDD for ordinal.The data type is single-precision floating point in mm/d and the invalid value is -9.
JIA Li
Canopy interception field is located in 2700m forest in Pailugou watershed of Qilian mountain, with 60 precipitation interception barrels arranged at equal intervals on the ground. The specifications of the interception barrel are: the radius of the bottom surface is 10cm and the height is 35cm. The observation period was from June to July 2012 and from July to September 2013, and 17 precipitation events (including each precipitation) were recorded. The unit is mm.
HE Zhibin
Three artificial rainfall events were performed on the shady grassland at the altitude of 2700m in the Pailugou watershed of the Qilian Mountains. The times were July 15, 2011, July 16, and July 22, 2011, respectively. Runoff rate, data is recorded every half an hour. Two rainfall simulations were also performed on the sun-slope grassland at the same altitude. As a comparative experiment, the time was July 24 and 25, 2011.
HE Zhibin
The dataset of the drop spectrometer observations was obtained at an interval of 30 seconds in the cold region hydrology experimental area from Mar. 14 to Apr. 14, 2008. The site was chosen in A'rou (N39.06°, E100.44°, 3002m), Qilian county, Qinghai province. The data mainly included the raindrop grain size and the terminal velocity. Besides, dual polarized radar (X-band) parameters such as ZDR and KDR could be further developed based on those data. The observation was carried out within an area of 5400mm^2; the liquid grain diameter was from 0.2-5mm, and the solid grain diameter was from 0.2-25mm.
CHU Rongzhong, ZHAO Guo, HU Zeyong, ZHANG Tong, JIA Wei
The dataset of intensive rain gauges observations was obtained in the arid region hydrology experiment area, in cooperation with dual polarized doppler radar observations. There was no single dataset for the upper stream observations for the poor quality; the middle stream dataset was collected by 29 RG3-M self-recording rain gauges: the northernmost (100.36°E, 39.16°N), the southernmost (100.34°E, 38.61°N), the easternmost (100.62°E, 38.87°N), and the westernmost (100.26°E, 38.82°N). Rain gauges R02-R09 measured from May 18 to Oct. 9, 2008, and R10-R30 from May 26 to Oct. 9, 2008. The technique criterions of these rain gauges were : (1) caliber: 165mm×254mm (2) the temperature range: 0°C —+70°C (3) resolution: 0.2mm (4) the measuring range: 0—320cm (5) the measuring accuracy: 1%
CHU Rongzhong, ZHAO Guo
From June 10, 2011 to September 2, 2011, the observation instrument of 3100m grassland weather station in Tianlaochi watershed of Qilian mountain was a 20cm evaporating pan, a round metal basin with a diameter of 20 cm and a height of 10 cm, and the mouth of the basin was blade-shaped. In order to prevent birds and animals from drinking water, a trumpet-shaped wire mesh ring was set on the upper part of the mouth of the vessel. During measurement, the instrument shall be placed on the shelf with the mouth 70cm from the ground, and quantitative clear water shall be put in every day. After 24 hours, the remaining water quantity shall be measured by the dosage cup, and the reduced water quantity shall be the evaporation capacity. Data are daily evaporation from June 10, 2011 to September 2, 2011.
ZHAO Chuanyan, MA Wenying
This data comes from the Tianlaochi watershed sample plot. The vegetation types of the sample plot are grassland, shrub, Sabina przewalskii and Picea crassifolia. The self-made Lysimeter is mainly used to observe the soil evapotranspiration characteristics in Picea crassifolia forestry. To provide basic data for the development of watershed evapotranspiration model. At about 19:00 every day, an electronic scale with an accuracy of 1g is used to weigh the inner barrel. In case of rain, observe whether there is leakage in the leakage barrel. If there is leakage, measure the leakage amount in the leakage barrel as well. The observation period in 2011 is from May 30 to September 10. The observation period in 2012 is from June 11 to September 10. Observation instrument: 1) standard 20cm diameter rain tube rain gauge. 2) self-made lysimeter (diameter 30.5cm, barrel height 28.5). 3) Electronic balance (accuracy: 0.1g) used to observe the weight change of self-made lysimeter.
ZHAO Chuanyan, MA Wenying
The data are from 2011 to 2012. A 30m×30m Picea crassifolia canopy interception sample plot was set up in the Picea crassifolia sample plot at an altitude of 2800m m. A siphon raingauge model DSJ2 (Tianjin Meteorological Instrument Factory) was set up on the open land of the river about 50m from the sample plot to observe the rainfall outside the forest and its characteristics. Penetrating rain in the forest adopts a combination of manual observation and automatic observation. Automatic observation is mainly realized through a penetrating rain collection system arranged in the interception sample plot, which consists of a water collecting tank and an automatic recorder. Two 400cm×20cm water collecting tanks are connected with DSJ2 siphon rain gauge, and the change characteristics of penetrating rain under the forest are continuously recorded by an automatic recorder. Due to the spatial variability of the canopy structure of Picea crassifolia forest in the sample plot, a standard rainfall tube for manual observation is also arranged in the sample plot to observe the penetrating rain in the forest. Ninety rainfall tubes with a diameter of 20cm are arranged in the sample plot at intervals of 3m. After each precipitation event ends and the penetrating rain in the forest stops, the amount of water in the rain barrel will be emptied and the penetrating rain in the barrel will be measured with the rain cup.
ZHAO Chuanyan, MA Wenying
The project of ecological security evaluation and landscape planning in the inner flow area of hexi corridor belongs to the major research plan of "environment and ecological science in western China" of the national natural science foundation, led by researcher xiao duning of the institute of cold and dry environment and engineering, Chinese academy of sciences. The project runs from Jan. 2002 to Dec. 2004. The data of the project is the ecological data of the inner flow area of hexi corridor, including heihe basin, shiyang river basin, shule river basin and river runoff. Investigation and analysis data of ejin banner in heihe river area 1. Soil moisture TDR data The data is stored in Excel format and includes both tubular and well 2002 soil moisture survey data. Tube TDR data Tubular soil moisture survey data with 1.8m underground intervals of 0.2 m on June 1, June 11, June 21, July 1, July 11, July 21, July 31, August 11 and August 21, 2002, including erdaqiao, gobi, forest farm, qidaqiao and tseng forest. Well TDR data Data of well soil moisture survey on June 21, July 1, July 11, July 21, July 31, August 11 and August 21, 2002, which included willows, gobi, populus euphratica and weeds, with intervals of more than 5 meters and 0.2 meters underground. Groundwater GPS data In Excel format, the TDR observation points were measured by GPS, including basic information such as longitude, latitude and elevation, plus information such as water level, logging type and remarks. 2. Soil nutrient salinity data To Excel format, 42 samples containing "total oxygen N %", "total phosphorus P %", "% organic matter", "hydrolysis N N mg/kg", "organic P P mg/kg", "available K K mg/kg", "% calcium carbonate", "PH", "the % of salt" and "total potassium % K" nutrient investigation and analysis of data, such as 42 samples containing "conductance value (%) computing the salt", CO3, HCO3, CI, SO4, Ca, mg, Na + K salt investigation and analysis of data, etc. 3. Soil mechanical composition In Excel format, 42 sample points contained soil particle composition information analysis tables of depth (cm), percentage of particle content at each level (sieve analysis method) (>2mm, 2-1mm, 1-0.5mm, 0.5-0.25mm and 0.25-0.1mm) and percentage of particle content at each level (straw method) (<0.1mm, 0.1-0.05mm, 0.05-0.02mm, 0.02-0.002mm and <0.002mm). 4. Meteorological data of erqi station Is the Excel sheet, including rainfall data from 1957 to 1998, evaporation data from 1957 to 1998, temperature data from 1957 to 1991, wind speed data from 1972 to 1992, maximum temperature data from 1972 to 1992, minimum temperature data from 1972 to 1992, sunshine data from 1972 to 1992 and relative humidity data from 1972 to 1992. Scan copy of jiuquan area The scanning copy of the general map of land use status in jiuquan 1:300,000, the scanning copy of the evaluation map of the distribution of cultivated land reserve resources in jiuquan 1:300,000 and the scanning copy of the district map of jiuquan 1:300,000 Zhang ye water protection information It contains the statistics of water and soil conservation in the regions of ganzhou district, gaotai district, linze county, minle county, shandan county, sunan county and zhangye city in zhangye region (stored in Excel format) and the planning report of each region (stored in Word format). Shiyang river basin Jinchang water resources survey data It includes the scan of 1:50000 water resource distribution map of jinchang city in 1997, the average decline degree of groundwater level in qinghe and jinchuan irrigation areas in jinchang city from 81 to 2000, the statistical table of annual groundwater supply in 1986, 1995 and 2001, and the survey and evaluation report of cultivated land reserve resources in jinchang city. Survey data of water resources in minqin Includes detailed minqin county area typical Wells status per acre crops irrigation water use questionnaire, irrigation, industrial and agricultural water use questionnaire, seeded area of villages and towns questionnaire, the survey data of groundwater hardness index, minqin county of surface runoff and the runoff change situation report, irrigation water quota formulation of evaluation report, minqin county water resources development and utilization of report and opinion polls irrigation works report, etc. Zoning map of soil improvement and utilization in wuwei area For the scanning part of water and soil conservation planning map of wuwei city, the scanning part of the location map of wuwei irrigation area, the scanning part of the scanning part of the administrative map of wuwei city, the scanning part of the water source and water conservancy project construction map of wuwei city, the scanning part of the planning map of wuwei sanbei phase ii shelterbelt project and the scanning part of the administrative map of liangzhou district. Yongchang county water protection information It is the scanning copy of the soil and water conservation supervision, prevention and control plan of 1994 in yongchang county at 1:20000. Shule river basin Distribution map of water resources development and utilization in yumen city It consists of four jpeg images, a 1:250,000 general scanning map of yumen's water resources development and utilization in 2002, and three high-resolution sub-maps. River runoff This data set is stored in Excel format, mainly including the total flow of three basins from 1949 to 2002, the annual runoff of each tributary of the basin, the annual runoff of detailed investigation areas such as jiuquan and the upstream inflow of yuanyang pond reservoir. Total basin Is the annual runoff data of heihe river basin, shiyang river basin and shule river basin from 1949 to 2002. Annual runoff of black river Is the annual runoff data of heihe river, liyuan river, taolai river, hongshui river, qingshui river, fengle river and hongsha river from 1949 to 2002. Annual runoff of shiyang river Is the annual runoff data of xidahe river, dongdahe river, xiying river, jinta river, zama river, huangyang river, gulang river, dajing river and other tributaries from 1949 to 2002. Annual runoff of shule river Is the annual runoff data of dang river, shule river and harten river from 1950 to 2002. Annual river runoff in jiuquan area For the annual flow data of changma gorge of shule river, dangcheng bay of danghe river, junmiao of shule river, baiyang river, icegou of toulai river, yuanyang pond of toulai river, xindi of hongshui river, fengle river, hongsha river of maying river and suang river of yulin river in jiuquan region from 1950 to 2002. Statistics of upstream inflow of yuanyang pond reservoir The data are the upstream inflow data of yuanyang pond reservoir from 1959 to 2001.
Xiao Duning
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