The data sets of 2005-2007, heihe river middle reaches area of underground water level monitoring value, contains the shandan bridge, children's pawn, fountain, the king of the brake, big full, PCCW main canal, under the new ditch, Shi Gangdun, Ann, under the qin dynasty, the stockade, taiping fort, yue jia pfe, zhang ye, liao home fort, Yang's farm village, railway stations, three gates, tile kiln, xiejiawan, under the cliff, meteor smoke, oasis, xiguan, ShaJingZi, river hydrological station 3 years of monthly average water level.The data are from the hydrological yearbook. Due to the lack of data, the average water level data of some hydrological stations are missing.
HU Litang, XU Zongxue
This data set includes the 2015 observation data of 9 water net nodes in the 5.5km × 5.5km observation matrix (red box in the thumbnail) of Yingke / Daman irrigation area in the middle reaches of Heihe River. The nine nodes contain 4cm and 10cm two-layer hydro probe II probes to observe the main variables such as soil moisture, soil temperature, conductivity and complex permittivity; the si-111 infrared temperature probe is set up at 4m height to observe the surface radiation infrared temperature of the underlying surface. The observation time frequency is 5 minutes. This data set can provide spatiotemporal continuous observation data set for remote sensing estimation of key water and heat variables of heterogeneous surface, remote sensing authenticity test, ecological hydrology research, irrigation optimization management and other research.
KANG Jian, LI Xin, MA Mingguo
1. The data set is the soil water content data set of the upper reaches of Heihe River Basin, and the data is the measured data of location points from 2013 to 2014. 2. The infiltration data is measured with ech2o. Including 5 layers of soil moisture content and soil temperature 3. Some instruments lack of data due to insufficient battery life, broken roads, stolen instruments and other reasons
HE Chansheng
The dataset is the field soil measurement and analysis data of the upstream of Heihe River Basin from 2013 to 2014, including soil particle analysis, water characteristic curve, saturated water conductivity, soil porosity, infiltration analysis, and soil bulk density I. Soil particle analysis 1. The soil particle size data were measured in the particle size laboratory of the Key Laboratory of the Ministry of Education, West Ministry of Lanzhou University.The measuring instrument is Marvin laser particle size meter MS2000. 2. Particle size data were measured by laser particle size analyzer.As a result, sample points with large particles cannot be measured, such as D23 and D25 cannot be measured without data.Plus partial sample missing. Ii. Soil moisture characteristic curve 1. Centrifuge method: The unaltered soil of the ring-cutter collected in the field was put into the centrifuge, and the rotor weight of each time was measured with the rotation speed of 0, 310, 980, 1700, 2190, 2770, 3100, 5370, 6930, 8200 and 11600 respectively. 2. The ring cutter is numbered from 1 to the back according to the number. Since three groups are sampled at different places at the same time, in order to avoid repeated numbering, the first group is numbered from 1, the second group is numbered from 500, and the third group is numbered from 1000.It's consistent with the number of the sampling point.You can find the corresponding number in the two Excel. 3. The soil bulk density data in 2013 is supplementary to the sampling in 2012, so the data are not available at every point.At the same time, the soil layer of some sample points is not up to 70 cm thick, so the data of 5 layers cannot be taken. At the same time, a large part of data is missing due to transportation and recording problems.At the same time, only one layer of data is selected by random points. 4. Weight after drying: The drying weight of some samples was not measured due to problems with the oven during the experiment. 3. Saturated water conductivity of soil 1. Description of measurement method: The measurement method is based on the self-made instrument of Yiyanli (2009) for fixing water hair.The mariot bottle was used to keep the constant water head during the experiment.At the same time, the measured Ks was finally converted to the Ks value at 10℃ for analysis and calculation.Detailed measurement record table refer to saturation conductivity measurement description.K10℃ is the data of saturated water conductivity after conversion to 10℃.Unit: cm/min. 2. Data loss explanation: The data of saturated water conductivity is partly due to the lack of soil samples and the insufficient depth of the soil layer to obtain the data of the 4th or 5th layer 3. Sampling time: July 2014 4. Soil porosity 1. Use bulk density method to deduce: according to the relationship between soil bulk density and soil porosity. 2. The data in 2014 is supplementary to the sampling in 2012, so the data are not available at every point.At the same time, the soil layer of some sample points is not up to 70 cm thick, so the data of 5 layers cannot be taken. At the same time, a large part of data is missing due to transportation and recording problems.At the same time, only one layer of data is selected by random points. 5. Soil infiltration analysis 1. The infiltration data were measured by the "MINI DISK PORTABLE specific vector INFILTROMETER".The approximate saturation water conductivity under a certain negative pressure is obtained.The instrument is detailed in website: http://www.decagon.com/products/hydrology/hydraulic-conductivity/mini-disk-portable-tension-infiltrometer/ 2.D7 infiltration tests were not measured at that time because of rain. Vi. Soil bulk density 1. The bulk density of soil in 2014 refers to the undisturbed soil taken by ring cutter based on the basis of 2012. 2. The soil bulk density is dry soil bulk density, which is measured by drying method.The undisturbed ring-knife soil samples collected in the field were kept in an oven at 105℃ for 24 hours, and the dry weight of the soil was divided by the soil volume (100 cubic centimeters). 3. Unit: G /cm3
HE Chansheng
This data is the longitude and latitude information of soil water sampling points in the "observation experiment of Soil Hydrological heterogeneity in the upper reaches of Heihe River and its impact on the hydrological process in mountainous areas" (91125010) of Heihe project, which is mainly used to express the spatial distribution of soil water sampling points in this project.
HE Chansheng
The dataset includes the saturated hydraulic conductivity data of typical soil samples in Heihe River Basin from July 2012 to August 2013. The collection method of typical soil sample points in Heihe River Basin is representative sampling, which means that the typical soil types in the landscape area can be collected, and the sample points with higher representativeness can be collected as much as possible, and the saturated hydraulic conductivity of each type of soil can be measured three times for the average value.
ZHANG Ganlin,
The 30 m / month vegetation index (NDVI / EVI) data set of Heihe River basin provides the monthly NDVI / EVI composite products from 2011 to 2014. This data uses the characteristics of HJ / CCD data of China's domestic satellite, which has both high time resolution (2 days after Networking) and spatial resolution (30 m), to construct multi angle observation data set. The average composite MC method is used as the main algorithm for synthesis, and the backup algorithm uses VI method. At the same time, the main observation angles of the multi-source data set are used as part of the quality descriptor to help analyze the angle effect of the composite vegetation index residue. 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 the multi-temporal and multi angle observation data, before using the multi-source data set to synthesize the vegetation index, the algorithm designs the data quality inspection of the multi-source data set, removing the observation with large error and inconsistent observation. The verification results in the middle reaches of Heihe River show that the NDVI / EVI composite results of the combined multi temporal and multi angle observation data are in good agreement with the ground measured data (R2 = 0.89, RMSE = 0.092). In a word, the 30 m / month NDVI / EVI 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 realize the stable standardized products from scratch and better serve the application of remote sensing data products.
LI Jing, LIU Qinhuo, ZHONG Bo, WU Junjun, WU Shanlong
The fraction of absorbed photosynthetically active radiation data set of the Heihe River Basin provides the fraction of absorbed photosynthetically active radiation data products from 2013 to 2014. The fraction of absorbed photosynthetically active radiation is the the ratio of photosynthetically active radiation absorbed by the canopy that passes through the canopy and then reflected from the canopy during the passage of the canopy to total photosynthetically active radiation. It is determined by the physiological and ecological characteristics and structural characteristics of vegetation canopy. This data set algorithm is developed on the basis of the energy conservation-based FPAR inversion method, in order to reflect the different path and the absorption probability of direct radiation and scattered radiation in the canopy, a FPAR inversion model is developed, which can distinguish direct radiation from scattering radiation. The algorithm can invert the direct FPAR, scattered FPAR and total FPAR of the canopy of the vegetation. The RMSE obtained from the inversion between the instantaneous FPAR and the observed FPAR is 0.0289, and the R2 is 0.8419.
LI Li, ZHONG Bo, WU Junjun, WU Shanlong, XIN Xiaozhou
The 1km / 5day vegetation index (NDVI / EVI) data set of Heihe River basin provides a 5-day resolution NDVI / EVI composite product from 2011 to 2014. The data uses the characteristics of FY-3 data, a domestic satellite, with high time resolution (1 day) and spatial resolution (1km), to construct a multi angle observation data set, which is the basis for analyzing multi-source data sets and existing composite vegetation index products and algorithms On the basis of this, an algorithm system of global composite vegetation index production based on multi-source data set is proposed. The vegetation index synthesis algorithm of MODIS is basically adopted, that is, the algorithm system of BRDF angle normalization method, cv-mvc method and MVC method based on the semi empirical walthal model. Using the algorithm system, the composite vegetation index is calculated for the first level data and the second level data, and the quality is identified. Multi-source data sets can provide more angles and more observations than a single sensor in a limited time. However, due to the difference of on orbit running time and performance of sensors, the observation quality of multi-source data sets is uneven. Therefore, in order to make more effective use of multi-source data sets, the algorithm system first classifies the quality of multi-source data sets, which can be divided into primary data, secondary data and tertiary data according to the observation rationality. The third level data are observations polluted by thin clouds and are not used for calculation. In the middle reaches of Heihe River, the verification results of farmland and forest areas show that the NDVI / EVI composite results of combined multi temporal and multi angle observation data are in good agreement with the ground measured data (RMSE = 0.105). Compared with the time series of MODIS mod13a2 product, it fully shows that when the time resolution is increased from 16 days to 5 days, a stable and high-precision vegetation index can describe the details of vegetation growth in detail. In a word, the NDVI / EVI data set of Heihe River Basin, which is 1km / 5day, comprehensively uses multi temporal and multi angle observation data to improve the estimation accuracy and time resolution of parameter products and better serves the application of remote sensing data products.
LI Jing, LIU Qinhuo, ZHONG Bo, YANG Aixia
The datasets of “Land Cover Map of Heihe River Basin” provide monthly land cover classification data in 2012-2013. The HJ-1/CCD data with both high spatial resolution (30 m) and high temporal (2 days) frequency was used to construct the time series data. The NDVI curves from the time series HJ-1/CCD data can depict the variation of typical land surface. Different land use type has different NDVI curve. Rules were set to extract every land use type information. The datasets of “Land Cover Map of Heihe River Basin” hold the traditional land use types including water bodies, urban and built-up, croplands, evergreen coniferous forests, deciduous broadleaf forests and so on. Crop type classification (including maize, spring wheat, highland barely, rape and so on), snow and ice and glaciers information updates, make the datasets more detailed. Compared with previous land cover map and other products, the classification result of the datasets is visually bette. Especially in middle stream, the accuracy of crop classification is quite high compared with the data from the ground campaign. The accuracy of land cover map of the datasets in 2012 was evaluated using very high spatial resolution remote sensing data within Google Earth and data from campaign, and the overall accuracy can be as high as 92.19%. In a word, the datasets of “Land Cover Map of Heihe River Basin” is not only high in overall accuracy, but also more detailed in crop fine classification. Furthermore, it updated some new classes like glaciers and snow. The datasets of “Land Cover Map of Heihe River Basin” are consequently the classification datasets with the highest accuracy and most detailed information up to now.
ZHONG Bo, YANG Aixia
The 30 m / month synthetic photosynthetic effective radiation absorption ratio (fAPAR) data set of Heihe River basin provides the monthly Lai synthetic products from 2011 to 2014. This data uses the characteristics of HJ / CCD data of China's domestic satellite, which has both high time resolution (2 days after Networking) and spatial resolution (30 m), to construct multi angle observation data set, considering different vegetation types, based on land cover classification map, combined with 30 m /Monthly synthetic leaf area index (LAI) products were produced by fapar-p model based on energy conservation. Based on the principle of energy conservation, the algorithm considers the multiple bounces between vegetation, soil and vegetation, as well as the influence of various factors such as sky scattered light. By analyzing the process of the interaction between photons and canopy, from the point of view that the movement of photons in the canopy is equal to the probability of re collision when multiple scattering occurs, a uniform and continuous vegetation fAPAR model is established. In addition, the effects of various factors on the fAPAR model were analyzed, including soil and leaf reflectance, aggregation index, and G function. The algorithm is highly dynamic, and can get better results for different soil background, vegetation type, radiation conditions, light and observation geometry, weather conditions. Compared with the data of corn canopy par measurement in Yingke irrigation area of Zhangye City, Gansu Province on July 8, 2012, the 30 m / month fAPAR product has a high consistency with the ground observation data, and the error with the observation value is less than 5%. In a word, the 30 m / month synthetic photosynthetic effective radiation absorption ratio (fAPAR) data set of Heihe River Basin comprehensively uses the multi temporal and multi angle observation data to improve the estimation accuracy and time resolution of parameter products, and better serves the application of remote sensing data products.
FAN Wenjie, LIU Qinhuo, ZHONG Bo, WU Junjun, WU Shanlong
The 1 km / 5-day FVC data set of Heihe River basin provides the 5-day FVC synthesis results from 2011 to 2014. The data uses the data of Terra / MODIS, Aqua / MODIS, and domestic satellites fy3a / MERSI and fy3b / MERSI to build a multi-source remote sensing data set with a spatial resolution of 1 km and a time resolution of 5 days. The whole country is divided into different vegetation divisions and land types, and the conversion coefficient of NDVI and FVC is calculated respectively. The conversion coefficient look-up table and 1km / 5-day synthetic NDVI product production area 1km / 5-day synthetic FVC product are used. In the Heihe River Basin, 1 km / 5-day synthetic FVC products can directly obtain vegetation coverage ratio through high-resolution data to reduce the impact of low-resolution data heterogeneity; in addition, select the typical period of vegetation growth and change, obtain the corresponding growth curve parameters of each pixel by fitting the vegetation index of each pixel time series; and then cooperate with land use map and vegetation classification map, To find the representative uniform pixel of the region to train the conversion coefficient of vegetation index. Compared with the results of high-resolution aster reference FVC in Heihe River Basin, the first step is to aggregate the aster products in Heihe River basin to 1km scale by combining the measured ground data and using the scale up method, and to obtain the aster aggregate FVC data, which is based on spot vegetation remote sensing data released by geoland 2 project (geov1 for short) The results show that the results of geov1 are higher than those of ASTER image combined with ground measurement, and the results of 1 km / 5-day synthetic FVC products in Heihe River Basin are between the two, and the results of 1 km / 5-day synthetic FVC products in Heihe River Basin in the experimental area are better than those of geov1 products. In a word, the comprehensive utilization of multi-source remote sensing data to improve the estimation accuracy and time resolution of FVC parameter products can better serve the application of remote sensing data products.
MU Xihan, RUAN Gaiyan, ZHONG Bo, LIU Qinhuo
一. Data overview This data interchange is the second data interchange of "genomics research on drought tolerance mechanism of typical desert plants in heihe basin", a key project of the major research program of "integrated research on eco-hydrological processes in heihe basin".The main research goal of this project is a typical desert sand Holly plants as materials, using the current international advanced a new generation of gene sequencing technology to the whole genome sequence and gene transcription of Holly group sequence decoding, so as to explore related to drought resistance gene and gene groups, and transgenic technology in model plants such as arabidopsis and rice) verify its drought resistance. 二, data content 1.Sequencing of the genome and transcriptome of lycophylla SPP. The genome size of Mongolian Holly was about 926 Mb, GC content 36.88%, repeat sequence proportion 66%, genome heterozygosity rate 0.56%, which indicated that the genome has many repeat sequences, high heterozygosity and belongs to a complex genome.Based on the predicted sequence results, we subsequently carried out in-depth sequencing of the genome of lysiopsis SPP. The obtained data were assembled to obtain a 937 Mb genome sequence (table 1), which was basically the same as the predicted genome size.Through to the sand Holly transcriptome sequencing and sequence assembly (table 2), received more than 77000 genes coding sequence (Unigene), these sequences are comments found that most of the gene sequence and legumes and soybean, garbanzo beans and bean has a higher similarity (figure 1), consistent with the fact of sand ilex leguminous plants. 一), and the sand Holly is a leguminous plants consistent with the fact. 2.Discovery of simple repeat sequence (SSR) molecular markers of sand Holly: There is a transcriptome data set of sand Holly in the network public database, and the sample collection site is zhongwei city, ningxia.But this is the location of the project team samples in minqin county, gansu province, in order to study whether this sand in different areas of the Holly sequence has sequence polymorphism, we first identify the minqin county plant samples in the genomes of simple sequence repeat (SSR) markers (table 3), and then, compares the transcriptome sequences of plant sample, found in part of SSR molecular marker polymorphism (table 4), these molecular markers could be used for the species of plant genetic map construction, QTL mapping and genetic diversity analysis in the study. 三, data processing instructions Sample collection place: minqin county, gansu province, latitude and longitude: N38 ° 34 '25.93 "E103 ° 08' 36.77".Genome sequencing: a total of 8 genomic DNA libraries of different sizes were constructed and determined by Illumina HiSeq 2500 instrument.Transcriptome sequencing: a library of 24 transcriptome mrnas was constructed and determined by Illumina HiSeq 4000. 四, the use of data and meaning We selected a typical desert plant as the research object, from the Angle of genomics, parse the desert plant genome and transcriptome sequences, excavated its precious drought-resistant gene resources, and to study their drought resistance mechanism of favorable sand Holly this ancient and important to the utilization of plant resources, as well as the heihe river basin of drought-resistant plant genetic breeding, ecological restoration and sustainable development.
HE Junxian, FENG Lei
According to the sample survey data, in August 2013, 30 forest plots were set up in the Tianlaochi watershed, with a plot size of 10 m×20 m. The long side of the plot was parallel to the slope of the hillside, including 26 blocks of Picea crassifolia forest. 2 blocks of Sabina Przewalsskii forest and 2 mixed forests of Picea and Sabina. In the plot, the diameter of the breast of each tree (the diameter of the trunk at a height of 1.3 m) is measured by a diameter tape, and the height of each tree and the height under the branches (the height of the first live branch at the lower end of the canopy) is measured by a hand-held ultrasonic altimeter. The north-south direction and the east-west crown width are measured with a tape measure, and the sample site is positioned by differential GPS. The parallel version of HASM-AD algorithm is used to simulate the classified LIDAR point cloud data. DEM is generated from ground points, DSM is generated from all points, and the height of surface features is obtained by differential operation between DSM and DEM. In forest area, it is called Canopy Height Model (CHM). A circular window with a given search radius is used to find the local maximum value on CHM. If the central pixel value is the maximum value, it is determined as the crown vertex. The pixel attribute value of the tree vertex is the tree height, and the spatial resolution is 1m.
YUE Tianxiang, WANG Yifu
30m month compositing Fraction Vegetation Cover (FVC) data set of Heihe River Basin provides the results of monthly FVC synthesis in 2011-2014. The data constructs multi-angle observation data sets by using China's domestic satellite HJ/CCD data with high temporal resolution (2 days after networking) and spatial resolution (30m) , and divides the country into different vegetation divisions and land types. The conversion coefficients of NDVI and FVC are calculated respectively, and use the calculated conversion coefficient lookup table and monthly compositing NDVI to produce the regional monthly compositing FVC products. The 30m month compositing FVC product in the Heihe River Basin can directly obtain the vegetation coverage ratio through high-resolution data, and mitigate the influence of low-resolution data heterogeneity; in addition, selecting the typical period of vegetation growth change, by fitting the vegetation index of each pixel time series to obtain the growth curve parameters that correspond to each pixel; then the land use map and the vegetation classification map are combined to find the representative uniform pixels of the region for training the conversion coefficients of the vegetation index. Compared with the ASTER reference FVC results, the 30m/month compositing FVC product in the Heihe River Basin is slightly higher than the ASTER reference result, but the overall deviation is not large, and the maximum value of the root mean square error (RMSE) of the product and the reference value is less than 0.175. In addition, compared with the ground survey data of Huailai experimental site in Hebei Province, the 30 m/month compositing FVC products generally reflect the seasonal variation of vegetation growth, and the deviation from the ground survey data is less than 0.1. At the same time, compared with the ground measurements of vegetation coverage in many watersheds in Northeast, North China and Southeast China, the overall error between the compositing FVC products and the ground measurements is less than 0.2. In all, the 30m/month compositing FVC data set of Heihe River Basin comprehensively utilizes multi-temporal and multi-angle remote sensing data to improve the estimation accuracy and time resolution of FVC parameter products, so as to better serve the application of remote sensing data products.
MU Xihan, RUAN Gaiyan, ZHONG Bo, WU Junjun, WU Shanlong, LIU Qinhuo
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 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
Water resources bulletin is a comprehensive annual report reflecting the situation of water resources. It is the basic work of unified planning, management and protection of water resources. It is an important basis for the preparation of national economic and social development planning, and also an important responsibility of water administrative departments. The contents of the water resources bulletin include precipitation, surface water resources, groundwater resources, total water resources, water storage dynamics, social and economic indicators, water supply, water consumption, water consumption, water use indicators, water pollution overview and important water affairs, etc. data and information are provided according to administrative divisions and flow area divisions respectively. The data set contains various statistical data of Gansu Provincial Water Resources Bulletin from 2000 to 2011.
DENG XiangZheng
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
The experimental data of Yingke Daman in Heihe River Basin is supported by the key fund project of Heihe River plan, "eco hydrological effect of agricultural water saving in Heihe River Basin and multi-scale water use efficiency evaluation". Including: soil bulk density, soil water content, soil texture, corn sample biomass, cross-section flow, etc Data Description: 1. Sampling location of Lai and aboveground biomass: Yingke irrigation district; sampling time: May 2012 to September 2012; Lai and aboveground biomass of maize were measured by canopy analyzer (lp-80), and aboveground biomass was measured by sampling drying method; sample number: 16. 2. Soil texture: Sampling location: Yingke irrigation district and Shiqiao Wudou Er Nongqu farmland in Yingke irrigation district; soil sampling depth is 140 cm, sampling levels are 0-20 cm every 10 cm, 20-80 cm every 20 cm, 80-140 cm every 30 cm; sampling time: 2012; measurement method: laboratory laser particle size analyzer; sample number: 38. 3. Soil bulk density: Sampling location: Yingke irrigation district and Daman irrigation district; sampling depth of soil bulk density is 100 cm, sampling levels are 0-50 cm and 50-100 cm respectively; sampling time: 2012; measurement method: ring knife method; number of sample points: 34. 4. Soil moisture content: this data is part of the monitoring content of hydrological elements in Yingke irrigation district. The specific sampling location is: Shiqiao Wudou Er Nongqu farmland in Yingke Irrigation District, planting corn for seed production; soil moisture sampling depth is 140 cm, sampling levels are 0-20 cm every 10 cm, 20-80 cm every 20 cm, 80-140 cm every 30 cm Methods: soil drying method and TDR measurement; sample number: 17. 5. Cross section flow: Sampling location: the farmland of Wudou Er Nong canal in Shiqiao, Yingke irrigation district; measure the flow velocity, water level and water temperature of different canal system sections during each irrigation, record the time and calculated flow, monitor once every 3 hours until the end of irrigation; sampling time: 2012.5-2012.9; measurement method: Doppler ultrasonic flow velocity meter (hoh-l-01, Measurement times: Yingke irrigation data of four times.
HUANG Guanhua, JIANG Yao
The output data of the distributed eco hydrological model in the upper reaches of Heihe River includes the spatial distribution data of 1-km grid and the discharge time series data of the outlet of the basin. (1) Spatial distribution data of 1-km grid, monthly average soil moisture, actual evapotranspiration, runoff depth and other spatial distribution data of 1-km resolution. (2) Runoff time series daily flow data of river basin outlet.
YANG Dawen
This data set contains the element content data of a deep drilled formation near the open sea in the middle reaches of Heihe River. The borehole is located at 99.432 E and 39.463 n with a depth of 550m. The element scanning analysis was carried out at 1-3cm intervals for the drilled strata. The scanning was completed in the Key Laboratory of Western Ministry of environmental education, Lanzhou University, and 38705 effective element data were obtained.
HU Xiaofei, PAN Baotian
This data set contains a deep drilling paleomagnetic age data near the open sea in the middle reaches of Heihe River. The borehole is located at 99.432 E and 39.463 n with a depth of 550m. The samples of paleomagnetic age were taken at the interval of 10-50 cm. The paleomagnetic test was carried out in the Key Laboratory of Western Ministry of environmental education of Lanzhou University. The primary remanence of the samples was obtained by alternating demagnetization and thermal demagnetization, and the whole formation magnetic formation was obtained by using the primary remanence direction of each sample, and then the sedimentary age of the strata was obtained by comparing with the standard polarity column. The results show that the bottom boundary of the borehole is about 7 Ma and the top boundary is 0 ma.
HU Xiaofei, PAN Baotian
Through the questionnaire survey of different water users in Zhangye City, the data on the implementation of water-saving society construction policies in Zhangye City are sorted out. The survey is mainly carried out on farmers and urban residents in all counties under Zhangye City's jurisdiction. The main contents include: people's awareness of water resources, water pollution, water-saving policies and willingness to participate in water conservation; The social and economic situation, gender, age, educational level, occupation, etc. of the interviewees. Survey objects: urban and rural residents over 18 years old in Minle County, Shandan County, Ganzhou District, Linze County, Gaotai County and Sunan County of Zhangye City.
ZHANG Zhiqiang
In the late June and early July of 2014, the dominant species of desert plants in the lower reaches of Heihe River, Lycium barbarum and Sophora alopecuroides, were selected. Using the LI-6400 portable photosynthesis system (LI-COR, USA), the photosynthetic and water physiological characteristics of desert plants were measured and analyzed.
SU Peixi
This data includes the distribution along the height of the blowing snow flux collected during the wind-blown snow event at the big winter tree pass observation station (longitude 100 degrees 14 minutes 28 seconds east and latitude 38 degrees 00 minutes 58 seconds north) on December 17, 2013 at solstice on July 9, 2014.
HUANG Ning, WANG Zhengshi
Soil particle size data: clay, silt and sand data of different sizes in sample plots (alpine meadow and grassland); soil moisture: soil moisture content.
SI Jianhua
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
"Hydrologic - ecological - economic process coupling and evolution of heihe Basin governance under the framework of water rights" (91125018) project data exchange 4-basin-plan-mdb 1. Data overview: a watershed plan revision for the Murray darling river in Australia, adopted in 2012, for catchment comparisons 2. Data content: the public plan
WANG Zhongjing
Irrigation area data of Zhangye City from 1999 to 2011, including total irrigation area (effective irrigation area, forest irrigation area, orchard irrigation area, forage irrigation area and other irrigation areas), water-saving irrigation area (sprinkler irrigation area, micro irrigation area, low-pressure pipe irrigation area, canal seepage prevention area and other water-saving irrigation areas), effective irrigation area data, and Ganzhou District, Shandan District Corresponding data of county, Gaotai County, Sunan County, Linze County and Minle County
ZHANG Dawei
The leaf area of five typical species of jinjier, jilialu, jinlumei, huangxiaoba and Ganqing jinjier in Dayekou watershed of Qilian Mountain was measured by LAI-2200 canopy analyzer.
LIU Xiande
Input output table of 11 districts and counties in Heihe River Basin in 2012
DENG XiangZheng
This dataset contains soil organic matter content data of typical soil samples in heihe river basin from July 2012 to August 2013.The collection method of typical soil sample points in heihe river basin is representative sampling, which refers to the collection of typical soil types in the landscape area and the collection of highly representative sample points as far as possible.Soil samples from each profile were taken on the basis of diagnostic layers and diagnostic characteristics, classified according to the Chinese soil system.
ZHANG Ganlin
1、 Data Description: the data includes the observation data of groundwater level in the delta area of hulugou small watershed from July 24, 2014 to September 11, 2014, with the monitoring frequency of 1H / time. 2、 Sampling location: the groundwater level observation point is located at the top of the alluvial proluvial fan in front of the delta mountain, with the coordinates of 99 ° 52'45.38 "E, 38 ° 15'21.27" n.
MA Rui
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