Input output table of 11 districts and counties in Heihe River Basin in 2012
Data source: survey data of Heihe River Basin Authority; Data introduction: in 2010, Sunan County, Ganzhou District, Minle County, Linze County, Gaotai County, Shandan County, Jinta County, Ejina, Suzhou District and Jiayuguan used water for living, industry, agriculture, urban and rural ecology.
Glaciers are sensitive to climate change and are important indicators and amplifiers of global change. In inland river regions, river runoff mainly comes from mountain ice and snow melt. Glaciers are very important "solid reservoirs" in these regions, and glacial melt water is an important source of supply for the tributaries of the Heihe River. The inventory of glaciers in the Heihe River Basin was completed from 1979 to 1980. For related information, please refer to "Chinese Glacier Inventory-Qilian Mountains" edited by Wang Zongtai and others. In 2004, the relevant results of the "China Glacier Inventory" were systematically digitized and a database was established. The final results were released through the "China Glacier Information System". However, in the process of coordinate restoration, the accuracy of the reference data was poor, and the glaciers in the Heihe River Basin had obvious position shifts. Therefore, we used the Landsat remote sensing image corrected by ortho-geometric correction. The processed Heihe Glacier distribution data is highly consistent with the existing basic geographic information in China in terms of geometric accuracy, and consistent with the first glacier inventory in terms of attributes.
Since the formation of Heihe River, sporopollen data samples have been collected from the drilling strata of Da'ao well in the middle reaches of Heihe River. Drilling location: 39.491 n, 99.605 E. The drilling depth is 140 meters. 128 samples of sporopollen are collected from top to bottom. At present, there are 19 data of sporopollen results, which are distributed in each sedimentary facies from top to bottom. The sporopollen samples were removed from carbonate, organic matter, silicate and other impurities in the laboratory, and the species and data of sporopollen were identified under the microscope. Sporopollen results mainly include the percentage content and number of trees, shrubs, herbs, aquatic, ferns and other families and genera.
HU Xiaofei PAN Baotian
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
Two shallow drills near Heiquan in the middle reaches of Heihe River are 140 meters and 68.2 meters deep respectively. The physical and chemical indexes of the two boreholes are analyzed, including grain size and heavy mineral analysis.
PAN Baotian HU Xiaofei
This data set contains two shallow drilling data near Heiquan in the middle reaches of Heihe River: 140 meters and 68.2 meters deep respectively. Paleomagnetic age samples were taken at 10-50 cm intervals from the two boreholes, and the magnetostratigraphic sequences of the two boreholes were obtained by testing these samples.
HU Xiaofei PAN Baotian
The landform near Qilian in the upper reaches of Heihe River includes the first level denudation surface (wide valley surface) and the Ninth level river terrace. The stage surface distribution data is mainly obtained through field investigation. GPS survey is carried out for the distribution range of all levels of geomorphic surface. The field data is analyzed in the room, and then combined with remote sensing image, topographic map, geological map and other data, the distribution map of all levels of geomorphic surface in the upper reaches of Heihe river is drawn. The age of the denudation surface is about 1.4ma, and the formation of Heihe terrace is later than this age, all of which are terraces since late Pleistocene.
HU Xiaofei PAN Baotian
Since the formation of heihe, palynology data samples were collected from the borehole formation of dasunken well in the middle reaches of heihe.Borehole location: 39.491 n, 99.605 e.The borehole has a depth of 140 meters and 18 palynological samples are collected from top to bottom. Currently, there are 3 palynological results, which are distributed in each sedimentary phase from top to bottom.Impurities such as carbonate, organic matter and silicate were removed from palynology samples in the laboratory, and the palynology types and data were identified under the microscope.Palynology results mainly included the percentage and number of trees, shrubs, herbs, aquatic and ferns.
PAN Baotian HU Xiaofei
The population data of Zhangye City from 2001 to 2012 include: annual population density and natural population growth rate, Data source: Statistical Bureau of Zhangye City. Statistical yearbook of Zhangye City. 2001-2012, Department of water resources of Gansu Province. Bulletin of water resources of Gansu Province. 2001-2012. Water Affairs Bureau of Zhangye City. Comprehensive annual report of water resources of Zhangye City, 1999-2011
1. Overview of data This data is based on the latest googleearth remote sensing image data to establish the spatial distribution database of crops in Ganzhou District of Zhangye City. 2. Data content Based on the spatial distribution of maize seed production focused by the project, the land use types in the study area are divided into 14 types (maize seed production land, spring wheat land, vegetable land, greenhouse land, intercropping land, rice land, water area, wetland, forest land, urban and rural industrial and mining residential land, roads, railways and unused land). 3. Space-time range The data range includes 19 villages and towns including Pingshanhu, Shajing, Wujiang River, Jingan, Mingyong, Sanzha, Ganjun, Xindun, Shangqin, Jiantan, Chengguan Town, Liangjiadun, Chang 'an, Dangzhai, Xiaoman, Longqu, Daman, Huazhai and Anyang. The data type is vector polygon and stored in Shape format. The data range covers Ganzhou District.
Data content: total water resources, agricultural water consumption and industrial water consumption of Heihe River Basin; social and economic data include population, GDP and farmland irrigation area.
1. Data overview Based on the collected statistical yearbooks and survey data of counties and districts in Zhangye City in the middle reaches of Heihe River, the social and economic database in the middle reaches is constructed to reflect the basic situation of regional social economy. 2. Data content The database includes two data sets: (1) statistical yearbook data; (2) survey data of human factors in river basin. The statistical yearbook data mainly includes a number of relevant statistical data such as the gross product, financial revenue, construction of villages and towns, industrial output value, grain output, etc. of Zhangye City and its towns. The survey data of human factors in Heihe River Basin mainly include the survey data of social capital, cultural theory, happiness index and sustainable consumption in Heihe River Basin. 3. Time and space The statistical yearbook data is the statistical data of Ganzhou District, Linze County, Gaotai County, Sunan County, Shandan County, Minle county and towns under the jurisdiction of each county from 1990 to 2010. The survey data of human factors in the basin is the corresponding survey data of counties in the upper, middle and lower reaches in 2005.
DEM (digital elevation model) is the abbreviation of digital elevation model, which is an important original data for watershed terrain and feature recognition. The principle of DEM is to divide the watershed into M rows and N columns of quadrilateral (cell), calculate the average elevation of each quadrilateral, and then store the elevation in a two-dimensional matrix. Because DEM data can reflect the local terrain features of a certain resolution, a large amount of surface morphology information can be extracted by DEM, which includes the slope, slope direction and the relationship between cells of watershed grid unit . At the same time, the surface water flow path, river network and watershed boundary can be determined by certain algorithm. Therefore, to extract basin features from DEM, a good basin structure model is the premise and key of the design algorithm.
XU Zongxue HU Litang XU Maosen
The distribution map of irrigation area and main and branch canals in Heihe River basin includes the main irrigation area and the distribution of all main and branch canals in Heihe River Basin. The irrigation area mainly includes Luocheng irrigation area, Youlian irrigation area, Liuba irrigation area, Pingchuan irrigation area, liaoquan irrigation area, Liyuan River irrigation area, yannuan irrigation area, Banqiao irrigation area, Shahe irrigation area, Xijun irrigation area, Yingke irrigation area, Daman irrigation area, Maying River irrigation area, shangsan irrigation area, Xinba irrigation area and Hongyazi irrigation area. The distribution map of main and branch canals includes all the main canals and branch canals of these 16 irrigation areas.
XU Maosen XU Zongxue HU Litang
Data source: China l Meteorological Administration Network; Data Content: Daily Rainfall Data Series of Heihe River Basin from 1990 to 2004; Evaporation Data of Heihe River Basin from 2000 to 2012. Data Spatial Range: Rainfall Data (Yingluoxia, Shandan, Gaoya, Pingchuan, Ganzhou Pingshan Lake, Zhengyixia Gorge, Liyuan River); Evaporation Data (Zhangye, Gaotai, Dingxin, Jiuquan, Jinta, Shandan, Ejina, Hequ)
WANG Zhongjing ZHENG Hang
"Coupling and Evolution of Hydrologic -Ecologic-Economic Processes of the Heihe River Basin Under the Framework of Water Rights" (91125018) Project data collection 1 - SWater Resources Improvement Plan of Shiyang River Basin 1. Data Overview:The improvement plan of Shiyang River Basin was implemented in 2007 for river basin comparison. 2. Data Content: The released plan.
The land use / land cover data set of Heihe River Basin in 2011 is the Remote Sensing Research Office of Institute of cold and drought of Chinese Academy of Sciences. Based on the remote sensing data of landsatm and ETM in 2011, combined with field investigation and verification, a 1:100000 land use / land cover image and vector database of Heihe River Basin is established. The data set mainly includes 1:100000 land use graph data and attribute data in the middle reaches of Heihe River Basin. The land cover data of 1:100000 (2011) in Heihe River Basin and the previous land cover are classified into six first-class categories (cultivated land, forest land, grassland, water area, urban and rural residents, industrial and mining land and unused land) and 25 second-class categories by the same hierarchical land cover classification system. The data type is vector polygon and stored in shape format. Land cover classification attributes: Level 1 type level 2 type attribute code spatial distribution location Cultivated land: plain dry land 123 is mainly distributed in basin, piedmont, river alluvial, proluvial or lacustrine plain (poor irrigation conditions due to water shortage). The upland and land 122 is mainly distributed in the hilly area, and generally, the plot is distributed on the gentle slope of the hill, as well as on the top of the ridge and the base. The dry land 121 is mainly distributed in the mountainous area, the hillside (gentle slope, hillside, steep slope platform, etc.) and the Piedmont belt below 4000 m above sea level. Woodland: there are woodland (Arbor) 21 mainly distributed in high mountains (below 4000 meters above sea level) or middle mountain slopes, valley slopes, mountain tops, plains, etc. Shrub land 22 is mainly distributed in the higher mountain area (below 4500m), most of which are hillside, valley and sandy land. Sparse forest land 23 is mainly distributed in mountainous areas, hills, plains and sandy land, Gobi (Loamy, sandy conglomerate) edge. Other forest lands 24 are mainly distributed around the oasis ridge, riverside, roadside and rural residential areas. Grassland: high cover grassland 31 is generally distributed in mountainous area (gentle slope), hilly area (steep slope), river beach, Gobi, sandy land, etc. The middle cover grassland 32 is mainly distributed in dry areas (low-lying land next door and land between Sandy Hills, etc.). Low cover grassland 33 mainly grows in dry areas (loess hills and sand edge). Water area: channel 41 is mainly distributed in plain, inter Sichuan cultivated land and inter mountain valley. Lake 42 is mainly distributed in low-lying areas. Reservoir pond 43 is mainly distributed in plain and valley between rivers, surrounded by residential land and cultivated land. Glaciers and permanent snow cover 44 are mainly distributed on the top of (over 4000) mountains. The beach land 46 is mainly distributed in the valley, piedmont, plain lowland, the edge of river lake basin and so on. Residential land: urban land 51 is mainly distributed in plain, mountain basin, slope and gully platform. Rural residential land 52 is mainly distributed in oasis, cultivated land and roadside, tableland, slope, etc. Industrial and mining land and traffic land 53 are generally distributed in the periphery of cities and towns, more developed traffic areas and industrial mining areas. Unused land: sand 61 is mostly distributed in the basin, both sides of the river, the river bay and the periphery of the mountain front Gobi. Gobi 62 is mainly distributed in the Piedmont belt with strong wind erosion and sediment transport. Salt alkali 63 is mainly distributed in relatively low and easy to accumulate water, dry lakes and lakeside. Swamp 64 is mainly distributed in relatively low and easy to accumulate water. Bare soil 65 is mainly distributed in the arid areas (mountain steep slopes, hills, Gobi), and the vegetation coverage is less than 5%. Bare rock 66 is mainly distributed in the extremely dry stone mountain area (windy, light rain). The other 67 are mainly distributed in the exposed rocks formed by freezing and thawing over 4000 meters, also known as alpine tundra. Projection parameters: Projection ALBERS Units METERS Spheroid Krasovsky Parameters: 25 00 0.000 /* 1st standard parallel 47 00 0.000 /* 2nd standard parallel 105 00 0.000 /* central meridian 0 0 0.000 /* latitude of projection's origin 0.00000 /* false easting (meters) 0.00000 /* false northing (meters)
This data set is extracted from the second Glacier Inventory Data Set of China for Three River Source area. The file is SHP format. The attribute data are as follows: Glc_Name (glacier name), Drng_Code (basin code), FCGI_ID (first glacier catalogue code), GLIMS_ID (GLIMS glacier code), Mtn_Name (mountain system name), Pref_Name (administrative division), Glc_Long (glacier longitude), Glc_Lati (glacier latitude), Glc_Area (glacier area), Abs_Accu (absolute area accuracy), Rel_Accu (relative area accuracy), Deb_Area (surface Moraine Area), Deb_A_Accu (absolute accuracy of surface moraine Area), Deb_R_Accu (relative accuracy of surface moraine area)、Glc_Vol_A (estimation of glacier volume 1)、Glc_Vol_B (estimation of glacier volume 2)、Max_Elev (maximum glacier elevation)、Min_Elev (minimum glacier elevation)、Mean_Elev (average glacier elevation)、MA_Elev (median area height of glacier)、Mean_Slp (average glacier slope)、Mean_Asp (average glacier slope direction)、Prm_Image (major remote sensing data)、Aux_Image (auxiliary remote sensing data)、Rep_Date (glacier catalogue represents date)、Elev_Src (elevation data source)、Elev_Date (elevation represents date)、Compiler (glacier cataloguing editor)、Verifier (glacier cataloguing verifier).
LIU Shiyin GUO Wanqin XU Junli
This dataset contains the flux measurements from the Subalpine shrub eddy covariance system (EC) belonging to the Qinghai Lake basin integrated observatory network from April 28 to December 31 in 2019. The site (100°6'3.62"E, 37°31'15.67" N ) was located near Dasi, Shaliuhe Town, Gangcha County, Qinghai Province. The elevation is 3495m. The EC was installed at a height of 2.5m, and the sampling rate was 10 Hz. The sonic anemometer faced north, and the separation distance between the sonic anemometer and the CO2/H2O gas analyzer (Gill&Li7500A) was about 0.17 m. The raw data acquired at 10 Hz were processed using the Eddypro post-processing software, including the spike detection, lag correction of H2O/CO2 relative to the vertical wind component, sonic virtual temperature correction, coordinate rotation (2-D rotation), corrections for density fluctuation (Webb-Pearman-Leuning correction), and frequency response correction. The EC data were subsequently averaged over 30 min periods. The observation data quality was divided into three classes according to the quality assessment method of stationarity (Δst) and the integral turbulent characteristics test (ITC): class 1-3 (high quality), class 4-6 (good), class 7-8 (poor, better than gap filling data), class9 (rejected). In addition to the above processing steps, the half-hourly flux data were screened in a four-step procedure: (1) data from periods of sensor malfunction were rejected; (2) data collected before or after 1 h of precipitation were rejected; (3) incomplete 30 min data were rejected when the missing data constituted more than 3% of the 30 min raw record; and (4) data were rejected at night when the friction velocity (u*) was less than 0.1 m/s. There were 48 records per day, and the missing data were replaced with -6999. The released data contained the following variables: DATE/TIME, wind direction (Wdir, °), wind speed (Wnd, m/s), the standard deviation of the lateral wind (Std_Uy, m/s), virtual temperature (Tv, ℃), H2O mass density (H2O, g/m3), CO2 mass density (CO2, mg/m3), friction velocity (ustar, m/s), stability (z/L), sensible heat flux (Hs, W/m2), latent heat flux (LE, W/m2), carbon dioxide flux (Fc, mg/ (m2s)), quality assessment of the sensible heat flux (QA_Hs), quality assessment of the latent heat flux (QA_LE), and quality assessment of the carbon flux (QA_Fc). The quality marks of sensible heat flux, latent heat flux and carbon flux are divided into three levels (quality marks 0 have good data quality, 1 have good data quality and 2 have poor data quality). In this dataset, the time of 0:30 corresponds to the average data for the period between 0:00 and 0:30; the data were stored in *.xls format. Detailed information can be found in the suggested references.