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
The 30 m / month synthetic leaf area index (LAI) data set of Heihe River basin provides the monthly Lai synthetic products from 2011 to 2014. This data uses the domestic satellite HJ / CCD data with high time resolution (2 days after Networking) and spatial resolution (30 m) to construct the multi angle observation data set. Considering the impact of surface classification and terrain fluctuation, the algorithm is selected according to the characteristics of different vegetation types Choosing a suitable parameterization scheme of integrated model, inversion Lai based on look-up table method. The remote sensing data acquired every month can provide more angles and more observations than the single day sensor data, but the quality of multi-phase and multi angle observation data is uneven due to the difference of on orbit operation time and performance of the sensor. Therefore, in order to effectively use multi temporal and multi angle observation data, a data quality inspection scheme is designed. Using the Lai ground observation data of 9 forest quadrats, 20 farmland quadrats and 14 savanna quadrats from dayokou area in the upper reaches of Heihe River and Yingke and Linze areas in the middle reaches to verify the Lai in July, the inversion results are in good agreement with the measurement results, and the average error is less than 1; in addition, the Lai inversion results of the combined multi temporal and multi angle observation data are in good agreement with the ground measurement data （R2=0.9，RMSE=0.42）。 In a word, the 30 m / month synthetic leaf area index (LAI) data set of Heihe River Basin comprehensively uses multi temporal and multi angle observation data to improve the estimation accuracy and time resolution of parameter products, so as to better serve the application of remote sensing data products.
LIU Qinhuo, FAN Wenjie, ZHONG Bo
Based on the downscaling temperature result data in the historical period of CMIP5 (Coupled Model Intercomparison Project Phase 5), the future multi-year average temperature in the three periods of 2011-2040, 2041-2070, and 2071-2100 was predicted. Under the scenarios of rcp2.6, rcp4.5, and rcp8.5, the method of combining ordinary least squares regression with HASM (High Accuracy Surface Modeling Method) was used to downscaling simulate and predict, and the 1km downscaling results of the multi-year average temperature in the three scenarios of 2011-2040, 2041-2070 and 2071-2100 were obtained.
YUE Tianxiang, ZHAO Na
This dataset includes soil moisture and soil temperature observations of 75 BNUNET nodes during the period from May to September 2012 (UTC+8), which is one type of WSN nodes in the Heihe eco-hydrological wireless sensor network (WSN). The BNUNET located in the observation matrix of the HiWATER artificial oasis eco-hydrology experimental area. Each BNUNET node observes the soil temperature at 4 cm, 10 cm and 20 cm depth, and soil moisture at 4 cm depth with 10 minutes interval. This dataset can be used in the estimation of surface hydrothermal variables and their validation, eco-hydrological research, irrigation management and so on. The detail description please refers to "Data introduction.docx".
Liu Jun, KOU Xiaokang, MA Mingguo
Based on the data of downscaling results in the precipitation historical period of CMIP5 (Coupled Model Intercomparison Project Phase 5), the combined Method of geographical weighted regression and HASM (High Accuracy Surface Modeling Method) was used to analyze the annual mean precipitation in the future three periods of 2011-2040, 2041-2070 and 2071-2100 in the scenario of rcp2.6, rcp4.5 and rcp8.5. Through downscaling simulation and prediction, the 1km downscaling results of the multi-year average precipitation in the three periods of 2011-2040, 2041-2070 and 2071-2100 are obtained.
YUE Tianxiang, ZHAO Na
The vegetation phenology data set of Heihe River basin provides remote sensing phenology products from 2012 to 2015. The spatial resolution is 1km and the projection type is sinusoidal. MODIS Lai product mod15a2 is used as the phenological remote sensing monitoring data source, and MODIS land cover classification product mcd12q1 is used as the auxiliary data set for extraction. The product algorithm first uses the time series data reconstruction method (bise method) to control the data quality of the input time series; then uses the main algorithm (logistic function fitting method) and the backup algorithm (piecewise linear fitting method) to extract the vegetation phenological parameters, realizes the complementary calculation method, guarantees the accuracy and improves the inversion rate. The algorithm can extract up to three growth cycles in a year, each growth cycle contains six data sets, including the start point of vegetation growth, the start point of growth peak, the end point of growth peak, the end point of growth, the fastest growth and the fastest decline. At the same time, it records the growth cycle type, growth season length, quality identification, etc., a total of 25 data sets. The phenology product reduces the missing rate of inversion, improves the stability of the product, and the data set is relatively reliable with rich information.
LI Jing
This data set includes 26 bnunet nodes in the 0.5 °× 0.5 ° observation matrix around Zhangye City in the middle reaches of Heihe River from September 2013 to March 2014. The configuration of 26 nodes is the same, including 3 layers of soil temperature probe with depth of 1cm, 5cm and 10cm and 1 layer of soil moisture probe with depth of 5cm. The observation frequency is 2 hours. This data set can provide spatiotemporal continuous observation data set for remote sensing authenticity test of surface heterogeneity and ecological hydrology research. The time is UTC + 8. Please refer to "bnunet data document. Docx" for details
ZHAO Shaojie, WANG Qi, LU Zheng, MA Mingguo, CHAI Linna
This data set is typical specific emissivity data set of Heihe River Basin. Data observation is from March 25, 2014 to June 30, 2015. Instrument: Portable Fourier transform infrared spectrometer (102f), hand-held infrared thermometer Measurement method: 102f was used to measure the radiation values of cold blackbody, warm blackbody, observation target and gold plate. Using the radiation value of the cold and warm blackbody, the 102f is calibrated to eliminate the influence of the instrument's own emission. By using the iterative inversion algorithm based on smoothness, the specific emissivity and the object temperature are inversed. The specific emissivity range is 8-14 μ m, and the resolution is 4cm-1. This data set contains the original radiation curves (in ASCII format) and recording files of cold blackbody, warm blackbody, measured target and gold plate obtained by 102f.
YU Wenping, REN Zhiguo, TAN Junlei, Li Yimeng, WANG Haibo, MA Mingguo
The data set contains soil observation data of typical sample points in Heihe River Basin: pH value and soil texture 1. Soil pH value: longitude, latitude and pH value of typical soil sample points. 2. Soil texture: including soil texture data of typical soil samples in Heihe River Basin from July 2012 to August 2013. The typical soil sampling method in Heihe River Basin is representative sampling, which means that the typical soil types in the landscape area can be collected, and the representative sample points should be collected as far as possible. According to the Chinese soil taxonomy, soil samples from each profile were taken based on the diagnostic layers and diagnostic characteristics.
ZHANG Ganlin,
The data set contains the location information and soil systematic type data of typical soil samples from the Heihe River Basin from July 2012 to August 2014. The typical soil sample collection method in the Heihe River Basin is representative sampling, which refers to the typical soil types that can be collected in the landscape area, and collects highly representative samples as much as possible. According to the Chinese soil systematic classification, the soil type of each section is divided based on the diagnostic layer and diagnostic characteristics. The sample points are divided into 8 soil orders: organic soil, anthropogenic soil, Aridisol, halomorphic soil, Gleysol, isohumicsoill , Cambisol, Entisol, and 39 sub-categories.
ZHANG Ganlin,
The output data of the distributed eco-hydrological model (GBEHM) of the upper reaches of the black river include the spatial distribution data series of 1-km grid. Region: upper reaches of heihe river (yingxiaoxia), time resolution: month scale, spatial resolution: 1km, time period: 2000-2012. The data include evapotranspiration, runoff depth and soil volumetric water content (0-100cm). All data is in ASCII format. See basan.asc file in the reference directory for the basin space range. The projection parameter of the model result is Sphere_ARC_INFO_Lambert_Azimuthal_Equal_Area.
YANG Dawen
The output data of the distributed eco-hydrological model (GBEHM) of the upper reaches of the black river include the spatial distribution data series of 1-km grid. Region: upper reaches of heihe river (yingxiaoxia), time resolution: month scale, spatial resolution: 1km, time period: 1980-2010. The data included precipitation, evapotranspiration, runoff depth, and soil volumetric water content (0-100cm). All data is in ASCII format. See basan.asc file in the reference directory for the basin space range. The projection parameter of the model result is Sphere_ARC_INFO_Lambert_Azimuthal_Equal_Area.
YANG Dawen
Agricultural irrigation, which accounts for about 80% of human water consumption, is the most important part of human water resources management and closely related to human survival and development.Irrigation is also an important part of the water cycle. Large-scale irrigation can affect the water cycle and even the local climate by affecting evapotranspiration.Excessive diversion of irrigation water will lead to unsustainable utilization of water resources, and at the same time, will reduce river flow and aquifer water reserves, thus harming the ecological environment. Therefore, determining the spatial and temporal distribution and variation of irrigation is critical to studying past human water use, the impact of irrigation on ecological and hydrological processes, the environment and climate, and the development of future irrigation plans. By integrating the irrigation amount of channel diversion water and irrigation amount of groundwater intake from different data sources, and combining the evapotranspiration data of land surface model CLM4.5 simulation and remote sensing inversion, a set of spatio-temporal continuous surface water and groundwater irrigation amount data set with spatial resolution of 30 arcseconds (0.0083 degrees) on the scale of 1981-2013 in heihe river basin was made. It has been verified that this data set has a high reliability from 2000 to 2013, and a lower reliability from 1981 to 1999 than from 2000 to 2013 due to the absence of remote sensing data and the absence of soil utilization changes. The document is described as follows: Monthly surfacewater irrigation volume file name: monthly_surfacewater_irrigation gation_1981-2013.nc Monthly groundwater_irrigation gation_1981-2013.nc The data is in netcdf format.There are three dimensions, which are month, lat, and lon. Where, month is a month, and the value is 0-395, representing each month from 1981 to 2013. Lat is grid latitude information, and lon is grid longitude information.
XIE Zhenghui
1. Data Overview: This data includes groundwater buried depth observation datal from 4 observation points in Ganzhou District of Zhangye Basin in the middle reaches of the Heihe River (The nursery garden of Xindun Town, Suijia temple of Xindun Town, the Wuzhi management house of Dangzhai Town, Shangqin Station of Shangqin Town). The data was obtained from July 12, 2012 to July 5,2014. 2. Data Content: The HOBO water level sensor is installed in the underground well, which is mainly used to monitor the dynamic change of groundwater level in Ganzhou District of Zhangye. The data contents are absolute air pressure (kPa), temperature (°C), and groundwater depth (m). The data was recorded hourly. 3. Time and Space Range: The geographical coordinates of the nursery garden well of Xindun Town (1559 m) : Longitude 100°20.8′E; Latitude: 38°54′N; The geographical coordinates of Suijia temple well of Xindun Town(1518 m) : Longitude: 100°23.9′E; Latitude: 38°54.1′N; The geographical coordinates of Wuzhi management house well of Dangzhai Town (1675 m): Longitude: 100°30.7′E; Latitude: 38°52.8′N; The geographical coordinates of Shangqin Station well of Shangqin Town(1480 m): Longitude: 100°31.7′E; Latitude: 38°54.5′N. Note: The number in brackets is elevation.
XIE Zhenghui
This data is the ASTER fractional vegetation cover in a growth cycle observed in the Yingke Oasis Crop land. Data observations began on May 30, 2012 and ended on September 12. Original data: 1.15m resolution L1B reflectivity product of ASTER 2.Vegetation coverage data set of the artificial oasis experimental area in the middle reaches Data processing: 1.Preprocessing of ASTER reflectance products to obtain ASTER NDVI; 2.Through the NDVI-FVC nonlinear transformation form, the ASTER NDVI and the ground measured FVC are used to obtain the conversion coefficients of NDVI to FVC at different ASTER scales. 3.Apply this coefficient to the ASTER image to obtain a vegetation coverage of 15m resolution; 4.Aggregate 15m resolution ASTER FVC to get 1km ASTER FVC product
HUANG Shuai, MA Mingguo
This data set consists of three parts: the first part is the monthly flow data of Yingluo gorge and caotanzhuang water conservancy project from 1979 to 2014; the second part is the S213 bridge (N38 ° 54'43.55 ", E100 ° 20'41.05") on the main stream of Heihe River from 1979 to 2014, G312 bridge (N38 ° 59'51.71 ", E100 ° 24'38.76"), railway bridge (n39 ° 2'33.08 ", E100 ° 25'49.42"), Gaoya bridge (n39 ° 08'06.35 ", E100 ° 25'58.23") and Pingchuan bridge (n39 ° The third part is the daily discharge and water level data of S213 bridge, G312 bridge, railway bridge, Gaoya bridge and Pingchuan bridge in the main stream of Heihe River from 1979 to 2014. Among them, the flow data refers to the section flow of Heihe River, and the water level data refers to the water level at the runoff densification observation point in the middle reaches of hiwater. The reliability of monthly data is higher than that of daily data, and the reliability of flow is higher than that of water level.
XIE Zhenghui
Based on the study of the terrace formation age in the upper reaches of heihe river, photoluminescence samples were collected from the sediments of grade 6 river terrace near the upper reaches of qilian river.The quartz particles (38-63 microns) in the sample were isolated in the laboratory, the equivalent dose and dose rate in the quartz particles were measured, and the photoluminescence age of the sample was finally obtained.The obtained ages range from 5ka to 82ka, corresponding to the years of cutting down the terraces of all levels.
PAN Baotian, HU Xiaofei
The data set contains data of three stations in the middle reaches: (1) the eddy related flux observation data of point 4 in the flux observation matrix from May 31 to September 17, 2012. The station is located in the Yingke irrigation area of Zhangye City, Gansu Province, and the underlying surface is the village. The longitude and latitude of the observation point are 100.35753e, 38.87752n and 1561.87m above sea level. The height of the eddy correlator is 4.2m (after August 19, the height of the eddy correlator is adjusted to 6.2m), the sampling frequency is 10Hz, the ultrasonic direction is due north, and the distance between the ultrasonic anemometer and the CO2 / H2O analyzer is 17cm. (2) Eddy related flux data of point 12 in the flux observation matrix from May 28 to September 21, 2012. The site is located in the farmland of Daman irrigation area, Zhangye City, Gansu Province, with corn as the underlying surface. The longitude and latitude of the observation point are 100.36631e, 38.86515n and 1559.25m above sea level. The height of the eddy correlator is 3.5m, the sampling frequency is 10Hz, the ultrasonic direction is north, and the distance between the ultrasonic anemometer and the CO2 / H2O analyzer is 15cm. (3) Eddy related flux data of point 14 in the flux observation matrix from May 30 to September 21, 2012. The site is located in the farmland of Yingke Irrigation District, Zhangye City, Gansu Province, with corn as the underlying surface. The longitude and latitude of the observation point are 100.35310e, 38.85867n and 1570.23m above sea level. The height of the eddy correlator is 4.6m, the sampling frequency is 10Hz, the ultrasonic direction is north, and the distance between the ultrasonic anemometer and the CO2 / H2O analyzer is 15cm. The original observation data of the eddy correlator is 10Hz. The published data is the 30 minute data processed by the edire software. The main processing steps include: outliers elimination, delay time correction, coordinate rotation (secondary coordinate rotation), frequency response correction, ultrasonic virtual temperature correction and density (WPL) correction, etc. At the same time, the quality evaluation of each flux value is mainly the test of atmospheric stability (Δ st) and turbulence similarity (ITC). The 30min flux value output by edire software was also screened: (1) data in case of instrument error; (2) data in 1H before and after precipitation; (3) data with loss rate greater than 3% in every 30min of 10Hz original data; (4) observation data with weak turbulence at night (U * less than 0.1M / s). The average period of observation data is 30 minutes, 48 data in a day, and the missing data is marked as - 6999. Suspicious data caused by instrument drift and other reasons shall be identified with red font. The published observation data include: date / time, wind direction WDIR (?), horizontal wind speed wnd (M / s), standard deviation of lateral wind speed STD uuy (M / s), ultrasonic virtual temperature TV (℃), water vapor density H2O (g / m3), carbon dioxide concentration CO2 (mg / m3), friction velocity ustar (M / s), stability Z / L (dimensionless), sensible heat flux HS (w / m2), latent heat flux Le (w / m2), two Carbon dioxide flux FC (mg / (M2S)), quality mark of sensible heat flux QA ﹤ HS, quality mark of latent heat flux QA ﹐ Le, quality mark of carbon dioxide flux QA ﹐ FC. The quality identification of sensible heat, latent heat and carbon dioxide flux is divided into three levels (quality identification 0: (Δ st < 30, ITC < 30); 1: (Δ st < 100, ITC < 100); the rest is 2). The meaning of data time, for example, 0:30 represents the average of 0:00-0:30; data is stored in *. XLS format. For station information, please refer to Liu et al. (2015), and for observation data processing, please refer to Liu et al. (2011) and Xu et al. (2013).
XIE Zhenghui, LIU Shaomin, XU Ziwei, LI Xin
The evapotranspiration and soil evapotranspiration of lycium rubra and red sand of small shrubs in typical desert weather were observed by using infrared gas analyzer to measure water vapor flux. The measurement system consists of li-8100 closed-circuit automatic measurement of soil carbon flux (li-cor, USA) and an assimilation box designed and manufactured by Beijing ligotai technology co., LTD. Li-8100 is an instrument produced by li-cor for soil carbon flux measurement. It USES an infrared gas analyzer to measure the concentration of CO2 and H2O.The length, width and height of the assimilation box are all 50cm.The assimilation box is controlled by li-8100. After setting up the measurement parameters, the instrument can run automatically.
SU Peixi
Industrial transformation refers to the state or process of significant changes in industrial structure, industrial scale, industrial organization, industrial technology and equipment in the main composition of a country or region's national economy. From this point of view, industrial transformation is a comprehensive process, including industrial transformation in structure, organization and technology. Another explanation refers to the reallocation of resource stock among industries in an industry, that is, the process of transferring capital, labor and other production factors from declining industries to emerging industries Data include industrial output impact data of water resources industrial structure adjustment (primary industry technology, secondary industry technology, tertiary industry technology)
DENG XiangZheng
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