This project is based on the gsflow model of USGS to simulate the surface groundwater coupling in Zhangye basin in the middle reaches of Heihe River. The space-time range and accuracy of the simulation are as follows: Simulation period: 1990-2012; Simulation step: day by day; The spatial scope of simulation: Zhangye basin; The spatial accuracy of simulation: the underground part is 1km × 1km grid (5 layers, the total number of grids in each layer is 150 × 172 = 25800, among which the active grid 9106); the surface part is based on the hydrological response unit (HRU) (588 in total, each HRU covers an area of several square kilometers to dozens of square kilometers). The data include: surface infiltration, actual evapotranspiration, average soil moisture content, surface groundwater exchange, shallow groundwater level, simulated daily flow of Zhengyi gorge, simulated monthly flow of Zhengyi gorge, groundwater extraction and river diversion
ZHENG Yi
This data includes animal products and labor prices; economic income structure, level and per capita net income; economic expenditure structure, productive and living expenditure structure; population composition, labor and household head age and education level; pasture area, grade, suitable stocking capacity; , livestock sheds, human and animal drinking water, pastoral roads, fence construction scale; maintenance scale, and livestock structure.
ZHAO Chengzhang
These processes include the biosphere - atmosphere transmission solutions, using FC80 closed Grell cumulus parameterization scheme, MRF planetary boundary condition and modify the CCM3 radiation, such as the heihe river basin observation and remote sensing data of important parameters in the model for second rate, and USES the heihe river basin vegetation data list data of land use in 2000 and the heihe river basin in 30 SEC DEM data, building up suitable for the study of heihe river basin ecological - hydrological processes of the regional climate model. Spatial scope: the grid center of the simulation area is located at (40.30n, 99.50e), the horizontal resolution is 3 km, and the number of simulated grid points in the model is 161 (meridional) X 201 (zonal). Projection: LAMBERT conformal projection, two standard latitudes of 30N and 60N. Time range: from January 1, 1980 to December 31, 2010, with an interval of 6 hours Description of file contents: monthly storage by grads without format.Except the maximum and minimum temperature as the daily scale, the other variables are all 6-hour data. MATLAB can be used to read, visible tmax_erain_xiong_heihe.m file description. Data description of heihe river basin: 1) Anemometer west wind (m/s) abbreviation usurf 2) Anemometer south wind(m/s), abbreviation vsurf College 3) Anemometer temperature (degK) abbreviation tsurf College 4) maximal temperature (degK) abbreviation tmax 5) minimal temperature (deg K) abbreviated tmin 6) college Anemom specific humidity (g/kg) abbreviation qsurf 7) value (mm/hr) abbreviation precip 8) Accumulated evaporation (mm/hr) abbreviation evap 9) Accumulated sensible heat (watts/m**2/hr) abbreviation sensible 10) Accumulated net infrared radiation (watts/m * * 2 / hr) abbreviation netrad Definition file name: Abbreviation-erain-xiong. YTD
XIONG Zhe
1) Initial data of community characteristics and main plant biological characteristics of the grass-animal equilibrium stage of the test grassland in 1983; 2) Livestock management data of 4-5 grazing grasslands; 3) Observation data of diversity, productivity and functional group of different grazing grassland communities; 4) Observation data on the height, coverage, biomass, and flower morphology, tillering, and leaf characteristics of main plants in different grazing gradient grasslands 5) Observation data of soil nutrients and litter in different grazing grasslands.
ZHAO Chengzhang
1. The grassland animal husbandry production and management policies in the study area from 1954 to 2012 mainly include: 1) the time series of the formation and evolution of various policies; 2) the key policies related to herdsman's livestock activities and grassland management and utilization. 2. Residents' perception and response to pastoral socio-economic development policies, grassland management systems, ecological compensation policies, ecological restoration projects, and ecological environment status quo.
ZHAO Chengzhang
Spectral reflectance observation was carried out for the typical underlying surface and black and white cloth in the low reaches of the Heihe River Basin during the aviation flight experiment in 2014, which will provide basic data set for the preprocessing of the flight data. 1. Observation Instrument PRS-3500 portable spectrometer, with the spectral range is 350-2500 nm, and the reference board. 2. Samples and observation methods The samples including the black and white cloth, the cantaloupe, the Tamarix chinensis, the Populus euphratica, the reeds, the weeds, the Karelinia caspica, the sandy soil, the gobi, the Sophora alopecuroides and so on. Reflectance of the reference board was measure vertically for once and then objective reflectance were measured for five times for each observation objective. 3. Observation time The typical underlying surface vegetation observation was on days of 24 July, 27 July, 31 July, 2014. The black and white cloth simultaneous observation was on 29 July, 2014. 4. Data storage The observation recorded data were stored in excel and the original spectral data were stored in *.sed files derived from the spectrometer, which can be opened by the matched software of the spectrometer or by a txt.
GENG Liying, Li Yimeng
Soil respiration observation was carried out for the typical vegetation ground in the lower reaches of the Heihe River Basin during the aviation flight experiment in 2014. The observation started on 23 July, 2014 and finished on 2 August, 2014. 1. Observation time Days from 23 July to 2 August, 2014 (25 July, 2014 excepted) 2. Samples and observation methods Large areas with relatively homogeneous vegetation (greater than 100 m * 100 m) were chosen as the observation samples. And combined the flux tower sites distribution of the lower reaches, five field samples closed to the sites were selected The observation sites sampled including Populus and Tamarix mixed forest, Populus, Tamarix group, bare ground and melon quadrats. 3-5 plots were observed for each samples. The PVC soil rings were installed one day before observation and kept about 5 cm out of the ground (the inner diameter of the PVC is 19.5 cm, the outer diameter is 20.0 cm, and the height is 12.0 cm). Minimal the effects to the surface of vegetation and withered matter when install the rings. In order to avoid fluctuations of the soil respiration value by the PVC rings, soil respiration rate was obtained when it returned to its original state (about 24h after the rings install). The observation time for each day was from 8:00 to 12:00 when soil respiration is relatively stable and can represent the whole day in this time. The Li-8100 Open Path soil carbon flux automatic analyzer was used (Model 8100-103) once for each plot. Cycles of observation for all plots of the five samples were completed for every morning. The soil respiration values of the samples were obtain by averaging the values of plots of the samples. 3. Observation instrument Li 8100 4. Data storage The observation recorded data were stored in excel and the original Soil respiration data were stored in 81x files.
REN Zhiguo
The aim of the simultaneous observation of land surface temperature is obtaining the land surface temperature for different kinds of underlying surface, including the lager areas of homogeneous vegetation with high coverage, water, and concrete floor, while the thermal imager go into the experimental areas of the low reaches. All the land surface temperature data will be used for validation of the retrieved land surface temperature from thermal imager and the analysis of the scale effect of the land surface temperature, and finally serve for the validation of the plausibility checks of the surface temperature product from remote sensing. 1. Observation time On 1 August, 2014 2. Observation samples Three field samples were chosen in the fly zone, which were large areas of homogeneous vegetation (with high coverage), water, and concrete floor. 3. Observation method Surface temperature values were observed continuously for each sample using handheld infrared thermometers during the imager went into the flying area. 4. Instrument parameters and calibration The field of view of the handheld infrared thermometer is one degree and the emissivity was assumed to be 0.95. All instruments were calibrated on 31 July, 2014 using a black body. 5. Data storage All the observation data were stored in an excel.
Li Yimeng, REN Zhiguo, Zhou Shengnan, MA Mingguo
The dataset of photosynthesis was observed by LI-6400XT Portable Photosynthesis System in the natural oasis eco-hydrology experimental area of the Heihe River Basin. Observation items included the main vegetation type in the lower reaches of Heihe river: Populus forest, which located in the Populus forest station and the mixed forest station of Ejinaqi. Observation periods lasted from 2014-07-24 to 2014-07-31. This dataset included the raw observation data of the Populus forest observed by LI-6400 during the observation periods. 1） Objectives of observation The photosynthetic datasets can be used in the study of plant physiological ecology characteristic and the simulation and validation for the eco-hydrological models. 2） Instrument and theory of the observation Measuring instrument: LI-6400XT Portable Photosynthesis System. Measuring theory: Using the infrared gas analyzer to measure the change of CO2 concentration, and then measuring the differences of CO2 concentration between the sample chamber and the referenced chamber so as to acquire the net productivity of the leaf. 3） Time and site of observation Observation site in the Populus forest station. Observation time: 2014-07-24 Observation site in the mixed forest station. Observation time: From 2014-07-25 to 2014-07-31. 4） Data processing The raw data of LI-6400 were archived in text format and can be opened by text editor or excel, the preprocessed data were in Excel format. Every time period of observation was archived in a single document, named as “date + type”.
WANG Haibo
The fractional vegetation cover observation was carried out for the typical underlying surface in the lower reaches of the Heihe River Basin during the aviation flight experiment in 2014. The observation started on 24 July, 2014 and finished on 1 August, 2014. 1. Observation time On days of 24 July, 27 July, 30 July, 31 July and 1 August, 2014 2. Samples method Large areas with homogeneous vegetation (greater than 100 m * 100 m) were chosen as the observation samples. And forty field samples were selected according to the characteristics of vegetation distribution in the low reaches. The land-use types including the cantaloupe, the Tamarix chinensis, the reeds, the weeds, the Karelinia caspica, the Sophora alopecuroides and so on. 3. Observation methods 3.1 Instruments and measurement method Digital photography measurement is implemented to measure the FVC. Plot positions, photographic method and data processing method are dedicatedly designed. In field measurements, a long stick with the camera mounted on one end is beneficial to conveniently measure various species of vegetation, enabling a larger area to be photographed with a smaller field of view. The stick can be used to change the camera height; a fixed-focus camera can be placed at the end of the instrument platform at the front end of the support bar, and the camera can be operated by remote control. 3.2 Photographic method The photographic method used depends on the species of vegetation and planting pattern. A long stick with the camera mounted on one end is used for the Tamarix chinensisi and reeds. For the Tamarix chinensisi and reeds, rows of more than two cycles should be included in the field of view (<30), and the side length of the image should be parallel to the row. If there are no more than two complete cycles, then information regarding row spacing and plant spacing are required. The FVC of the entire cycle, that is, the FVC of the quadrat, can be obtained from the number of rows included in the field of view. For other vegetation , the photos of FVC were obtained by directly photographing for the lower heights of the vegetation. 3.3 Method for calculating the FVC The detail method of the FVC calculation can be found in the reference below. Many methods are available to extract the FVC from digital images, and the degree of automation and the precision of identification are important factors that affect the efficiency of field measurements. This method, which is proposed by the authors, has the advantages of a simple algorithm, a high degree of automation and high precision, as well as ease of operation (see the reference). 4 Data storage The observation recorded data were stored in excel and the original FVC data were stored in photos.
Guo Dong, WANG Haibo, Zhou Shengnan
LAI observation was carried out for the typical underlying surface in the lower reaches of Heihe River Basin during the aviation flight experiment in 2014. The observation started on 24 July, 2014 and finished on 1 August, 2014. 1. Observation time On days of 24 July, 27 July, 30 July, 31 July and 1 August, 2014 2. Samples and observation methods Large areas with homogeneous vegetation (greater than 100 m * 100 m) were chosen as the observation samples. And forty field samples were selected according to the characteristics of vegetation distribution in the downstream. The land-use types including the cantaloupe, the Tamarix chinensis, the reeds, the weeds, the Karelinia caspica, the Sophora alopecuroides and so on. LAI data were calculated according to the transmittance derived from an A value (above-canopy readings) and four B values (below readings). More than two LAI values were obtained for each sample. At the same time, the heights of the vegetation in each sample were measured. 3. Observation instrument LAI 2200 4. Data storage The observation recorded data were stored in excel and the original LAI data were stored in txt files.
SONG Yi, Li Yimeng
The data includes earthquakes at various levels across the country from 2300 BC to 2005 AD. There are a total of more than 330,000 catalogs, each of which includes earthquake time, epicenter longitude, epicenter latitude, focal depth, positioning accuracy, and magnitude. This data was first released by the National Seismological Bureau. The China Earthquake Catalog contains a Mapinfo layer (Total_0510Time) and files with the extensions .TAB, .MAP, .DAT, .ID. Their functions are as follows: TAB: the main file, including the table data structure and entity data format fields; MAP: a geographic data file containing map objects; ID: the index file of the graphic object file (MAP); DAT: Form data file.
MA Jin
This data is based on the DEM data generated by 1:250,000 digital contour lines and elevation points in China released by national basic geographic information center, and the DEM data set of heihe river basin is generated by the nearest neighbor method resampling method of ARCGIS spatial analysis module with a spatial resolution of 30 SEC.
National Basic Geographic Information Center
I. Overview The Yellow River is the second longest river in our country. The problem of the Yellow River's sediment has attracted the attention of people all over the world. Based on the vector map of the 14 million rivers in China as a base map, the upper reaches of the Yellow River basin were cut out. The vector map of the river is a key element for extracting the boundary of the basin by using the topographic map, and it is also a key element for flood evolution and sediment evolution. Ⅱ. Data processing description Using the national vector map of the 14 million rivers as the data source, it is cut out by using the boundary of the upper reaches of the Yellow River. Ⅲ. Data content description The map is stored in ArcGIS, .shp files, including vector diagrams of the main and tributaries from the source area of the Yellow River to Toudaoguai. Ⅳ. Data usage description The vector map of the river is a key element for extracting the boundary of the watershed by using the topographic map, and it is also a key element for flood evolution and sediment evolution.
XUE Xian, DU Heqiang
I. Overview This data set contains daily meteorological data from the Inner Mongolia section of the Yellow River from Wuhai to Dalat Banner from 1952 to 2006. Non-standard station data includes two elements, namely: temperature and precipitation. Ⅱ. Data processing description The data is stored as integers, the temperature unit is (0.1 ° C) value, the precipitation unit is (0.1 mm), and it is stored as an ASCII text file. Ⅲ. Data content description Standard station data, temperature and precipitation are stored separately, which are temperature file and precipitation file. Ⅳ. Data usage description In terms of resources and environment, meteorological data is used to simulate the regional climate change and runoff, sediment, water and soil loss and vegetation changes in the basin, and is also a necessary input condition for remote sensing inversion.
XUE Xian, DU Heqiang
I. Overview The Yellow River is the second longest river in our country. The problem of the Yellow River's sediment has attracted the attention of people all over the world. The watershed is an important natural unit. Using the SRTM-DEM and ASTER-GEDEM data sets as the data source, under the ArcGIS software platform, the method of combining river burning method and river scalar method is used to extract the upper reaches of the Yellow River basin. The boundary of the basin from the source area of the Yellow River to the upper reaches of the Yellow River in Hekou Town. Ⅱ. Data processing description Using SRTM-DEM and ASTER-GDEM issued by the United States as data sources, under the ArcGIS software platform, the method of combining river burning method and river scalar method was used to extract the upper reaches of the Yellow River basin. Because the ratio of the rivers from the Three Lakes Estuary to Hekou Town is extremely small, there is a certain error in the boundary of the basin. Ⅲ. Data content description The map is stored in ArcGIS and .shp files. The river basin boundary spans five provinces (autonomous regions) of Qinghai, Sichuan, Gansu, Ningxia, and Inner Mongolia, with a total area of 55.06 × 104 km2. Ⅳ. Data usage description Watershed boundary is an important natural unit for hydrology, soil erosion, and non-point source pollution research. By extracting watershed boundaries, the migration range of soil erosion and non-point source pollution can be delineated.
XUE Xian, DU Heqiang
Ⅰ. Overview FAO (Food and Agriculture Organization of the United Nations) and IIASA (International Institute for Applied Systems Analysis) combined the soil information of all regions and countries in the world with the world soil map of FAO-UNESCO, formed a new soil database - Harmonized World Soil Database (HWSD). The data source in China is 1:1 million soil data provided by Nanjing Soil Research Institute of the second national land survey. The database will be of great significance to improve people's understanding of current and future soil productivity, soil carbon storage, land resources, water resources and soil degradation. Ⅱ. Data processing description The data comes from the Harmonized World Soil Database (HWSD) constructed by FAO and IIASA. The data in China comes from the 1:1 million soil data provided by Nanjing Soil Research Institute of the second national land survey. The main soil classification system is FAO-90. Ⅲ. Data content description The main fields of soil attribute table include: SU_SYM90 (soil name in FAO90 soil classification system): SU_SYM85 (FAO85 classification); T_TEXTURE (top soil texture); DRAINAGE (19.5); ROOTS: String (depth classification with obstacles to the bottom of soil); SWR: String (soil water content characteristics); ADD_PROP: Real (agricultural use related in soil unit) Specific soil type); T_GRAVEL: Real (gravel volume percentage); T_SAND: Real (sand content); T_SILT: Real (silt content); T_CLAY: Real (clay content); T_USDA_TEX: Real (USDA soil texture classification); T_REF_BULK: Real (soil bulk weight); T_OC: Real (organic carbon content); T_PH_H2O: Real (PH); T_CEC_CLAY: Real (cation exchange of clayey soil); T_CEC_SOIL: Real (cation exchange capacity of soil); T_BS: Real (basic saturation); T_TEB: Real (exchangeable base); T_CACO3: Real (carbonate or lime content); T_CASO4: Real (sulfate content); T_ESP: Real (exchangeable sodium salt); T_ECE: Real (conductivity). The attribute field beginning with T_ represents the upper soil attribute (0-30cm), and the attribute field beginning with S_ represents the lower soil attribute (30-100cm) (FAO 2009). Ⅳ. Data usage description Through this database, people's understanding of current and future soil productivity, soil carbon storage and global soil carbon storage will be improved. It can help people to understand the limitation of land and water resources, and correctly assess the risk of soil degradation, especially soil loss. Through understanding the physical and chemical properties of soil, it can also help people to obtain the following information, such as the filtering function of soil on waste, the impact on biological growth, etc. The potential of soil production and the response of soil to climate change were correctly judged.
XUE Xian, DU Heqiang, Food and Agriculture Organization of the United Nations（FAO）
一.An overview The 1:100,000 soil database in the upper reaches of the Yellow River was tailored from the 1:100,000 soil database in China.The 1:100,000 soil database of China is based on the 1:100,000 soil map of the People's Republic of China compiled and published by the national soil census office in 1995.The database adopts the traditional "soil genetic classification" system, and the basic mapping unit is subcategories, which are divided into 12 classes of soil, 61 classes of soil and 227 classes of soil, covering all kinds of soil and its main attribute data in China. 二. Data processing instructions The 1:1 million soil database of China was established by the soil resources and digital management innovation research team led by shi xuezheng of nanjing soil research institute, Chinese academy of sciences, after four years.The database consists of two parts: soil spatial database and soil attribute database.The establishment of the database was funded by the knowledge innovation program of the Chinese academy of sciences and completed under the leadership of liu jiyuan and zhuang dafang. 三. data content description The soil spatial database, 1:1 million digitized soil maps of the country, is based on the 1:1 million soil maps of the People's Republic of China compiled and published by the national census offices in 1995.The digitized soil map faithfully reflects the appearance of the original soil map and inherited the mapping unit when the original soil map was compiled. Most of the basic mapping units are soil genera, which are divided into 12 classes, 61 classes and 235 subclasses. It is the only and most detailed digitized soil map in China. The soil attribute database, whose attribute data is quoted from the soil species record of China, is divided into six volumes, and nearly 2,540 soil species are collected.Soil property data can be divided into soil physical properties, soil chemical properties and soil nutrients.Soil physical properties soil particle composition and soil texture, soil chemical properties such as PH value, organic matter, soil nutrients include all N, all P, all K and effective P and effective K. 四. Data usage instructions Soil types and soil properties are an important content in the study of physical geography. With the help of 1:100,000 soil database in the upper reaches of the Yellow River, the type, quantity and spatial distribution of soil resources in the upper reaches of the Yellow River as well as the soil environment and characteristics can be understood and analyzed.This data set is of great significance for the early warning of large-scale soil erosion and the prediction of natural disasters in the upper reaches of the Yellow River.
XUE Xian, DU Heqiang
Ⅰ. Overview This data set is based on Landsat MSS, TM and ETM Remote sensing data by means of satellite remote sensing. Using a hierarchical land cover classification system, the data divides the whole region into six first-class classifications (cultivated land, forest land, grassland, water area, urban and rural areas, industrial and mining land, residential land and unused land), and 31 second-class classifications. Ⅱ. Data processing description The data set is based on Landsat MSS, TM and ETM Remote sensing data as the base map, the data set projection is set as Alberts equal product projection, the scale is set at 1:24,000 for human-computer interactive visual interpretation, and the data set storage form is ESRI coverage format. Ⅲ. Data content description The data set adopts a hierarchical land cover classification system, which is divided into 6 first-class classifications (cultivated land, forest land, grassland, water area, urban and rural areas, industrial and mining land, residential land and unused land), and 31 second-class classifications. Ⅳ. Data use description The data can be mainly used in national land resources survey, climate change, hydrology and ecological research.
XUE Xian, DU Heqiang
The dataset of automatic meteorological observations was obtained at the Dayekou Guantan forest station (E100°15′/N38°32′, 2835m), south of Zhangye city, Gansu province, from Oct. 1, 2007 to Dec. 31, 2009. Guantan forest station was dominated by the 15-20m high spruce and the surface was covered by 10cm deep moss. All the vegetation was in good condition. Observation items were the multilayer (2m and 10m) wind speed and direction, the air temperature and moisture, rain and snow gauges, snow depth, photosynthetically active radiation, four components of radiation from two layers (, 1.68m and 19.75 m), stem sap flow, the surface temperature, the multi-layer soil temperature (5cm, 10cm, 20cm, 40cm, 80cm and 120cm),soil moisture (5cm, 10cm, 20cm, 40cm, 80cm and 120cm) and soil heat flux (5cm & 15cm). As for detailed information, please refer to Meteorological and Hydrological Flux Data Guide.
MA Mingguo, Wang Weizhen, TAN Junlei, HUANG Guanghui, Zhang Zhihui
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