"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.
WANG Zhongjing
The dataset of surface roughness measurements was obtained in No. 1 and 2 quadrates of the E’bao foci experimental area during the pre-observation period. Both the quadrates were divided into 3×3 subsites, with each one spanning a 30×30 m2 plot. With the roughness board 110cm long and the measuring points distance 1cm, the samples were collected along the strip from south to north and from east to west, respectively. The coordinates of the sample would be got with the help of ArcView; and after geometric correction, surface height standard deviation (cm) and correlation length (cm) could be calculated based on the formula listed on pages 234-236, Microwave Remote Sensing, Vol. II. The original photos of each sampling point, surface height standard deviation (cm) and correlation length (cm) were archived. The roughness data were initialized by the sample name, which was followed by the serial number, the name of the file, standard deviation and correlation length. Each .txt file is matched with one sample photo and standard deviation and correlation length represent the roughness. In addition, the length of 101 needles is also included for further validation.
CAO Yongpan, CHAO Zhenhua, CHE Tao, QIN Chun, WU Yueru,
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
The data came from the badain jilin 1:500,000 wind-sand landform data set compiled by the desert research institute of the Chinese academy of sciences (now the institute of cold and drought of the Chinese academy of sciences. The dataset mainly includes :dimao(landform),height(dune height),lake(lake),lvzhou(oasis), river(river), road (road).
ZHU Zhenda, WANG Yimou, D Jeremy kyle, J Hofer
The dataset contains vegetation type and plant structure in the middle reaches of the Heihe River Basin, which was used to validate products from remote sensing. It was generated from investigating the land cover strips of CASI and SASI the middle reaches of the Heihe River Basin between 25 June and 6 August in 2012. Instruments: High-precision handheld GPS (2-3 m) and digital camera were used as main tools in the survey. Measurement method: Vegetation range in the middle reaches of the Heihe River Basin and survey route could be decided with the help of Google Earth. Wuxing village in Xiaoman town was selected to survey detailed and other places were investigated as far to reach as possible. Main methods were to write down the longitude and latitude, phenology of the plant structure, take photos for the vegetation. Dataset contains: longitude and latitude, vegetation type, area and phenology. Observation Place: CASI flight area in artificial oasis in the middle reaches, CASI stripe flight area in the middle reaches and Zhangye district. Date: From 25 June and 6 August in 2012.
Zhang Miao
1. Data overview: This data set is the scale meteorological gradient data of qilian station from January 1, 2012 to December 31, 2012 (installed at the end of September 2011).VG1000 gradient observation system carries out long-term monitoring of wind speed, wind direction, air temperature, humidity, radiation and other conventional meteorological elements, and carries out data storage and processing analysis in combination with the data collector with high precision and high scanning frequency. 2. Data content: The main observation factors include four layers of air temperature, humidity and two-dimensional ultrasonic wind, rain and snow volume meter, eight layers of ground temperature, soil moisture content, etc. 3. Space and time range: Geographical coordinates: longitude: longitude: 99° 52’e;Latitude: 38°15 'N;Height: 3232.3 m
CHEN Rensheng, HAN Chuntan
This data was compiled by Qiu Baoming, Gao Qianzhao, Peng Qilong, etc. of Lanzhou Desert Research Institute, Chinese Academy of Sciences, and published by Xi'an map publishing house in 1988 (Qiu Baoming, etc., 1988). The grassland is mainly divided into eleven categories: swamp grassland, low humidity grassland, plain desert grassland, plain semi desert grassland, desert riverside sparse forest shrub grassland, mountain desert grassland, mountain semi desert grassland, mountain grassland grassland, mountain meadow grassland, mountain meadow grassland, mountain shrub meadow grassland and ancillary grassland. Property fields include: Grassland code, type, and subclass.
Chou Baoming, Peng Qilong, Gao Qianzhao
The dataset of ground truth measurements synchronizing with MODIS was obtained in C1, W2 and B2 of the Biandukou foci experimental area from 12:00-15:00 on Mar. 14, 2008. Observation items included: (1) the frost depth from 11:37-12:11 by the chopstick and the ruler. The soil was considered frozen when it was hard and with ice crystal. The cover type photos were archived. (2) the gravimetric soil moisture (soil samples from 0-1cm, 1-3cm, 3-5cm, 5-10cm and 10-20cm) by the microwave drying method. (3) the surface radiative temperature by the handheld infrared thermometer and the physical temperature by the thermocouple thermometer. (4) the soil roughness, which can be acquired from related dataset of other period.
CHANG Sheng, Fang Qian, QU Ying, LIANG Xingtao, LIU Zhigang, PAN Jinmei, PENG Danqing, REN Huazhong, ZHANG Yongpan, ZHANG Zhiyu, ZHAO Shaojie, Zhao Tianjie, ZHENG Yue, Zhou Ji, LIU Chenzhou, YIN Xiaojun, ZHANG Zhiyu
The spot satellite series in France consists of five stars, of which spot 5 is the best. It was launched in May 2002, with a height of 830km, an orbit inclination of 98.7 degrees, and a sun synchronous quasi regression orbit, with a regression period of 26 days. Linear array sensor (CCD) and push scan scanning technology were used for imaging. SPOT5 satellite carries two high-resolution geometric imagers (HRG), one high-resolution Stereo Imager (HRS) and one wide field vegetation detector (VGT). It has five working bands, multi spectral band spatial resolution is 10m (short wave infrared spatial resolution is 20m), panchromatic band spatial resolution is 2.5m. At present, there are three spots of SPOT5 data in Heihe River Basin. The coverage and acquisition time are respectively: 1 scene in Linze area, including multispectral image with resolution of 10m and panchromatic image with resolution of 2.5m, with time of 2008-07-04; 1 scene in Zhangye City, with resolution of 2.5m, with time of 2008-03-29; 1 scene of multispectral data with resolution of 10m, with time of 2008-08-10. The product level is L1, and the product has undergone rough geometric correction. SPOT5 image is mainly used as the base map of geometric precision correction in Heihe experiment. The spot 5 remote sensing data set of Heihe comprehensive remote sensing joint experiment was purchased by Beijing Normal University.
Institute of Remote Sensing and Digital earth, Chinese Academy of Sciences
The dataset of ground truth measurements synchronizing with ALOS PALSAR was obtained in the Linze station foci experimental area on Jul. 10, 2008. The ALOS PALSAR data were in FBS mode and HH polarization combinations, and the overpass time was approximately at 23:39 BJT. Soil moisture (0-5cm) data were measured by the cutting ring method (50cm^3) in LY07 and LY08 quadrates (repeated nine times). The quadrate location information was listed in coordinates.xls and data were archived as Excel files. See the metadata record “WATER: Dataset of setting of the sampling plots and stripes in the Linze station foci experimental area” for more information of the quadrate locations.
PAN Xiaoduo, SONG Yi
The dataset of airborne WiDAS mission was obtained in the national observatory on climatology at Zhangye-Zhangye flight zone on Jun. 29, 2008. Intra-band data available for general users include Level-2C data (after geometric, radiometric and atmospheric corrections), Level-1B browse image (after intra-band matching) and Level-2B browse image (after registration). The raw data, Level-1A, and data processing parameters were filed; applications would be evaluated prior to access. Data processing started in Aug. 2008 and ended in Apr. 2009, and in Nov. 2009, CCD data were reprocessed to adjust radiometric calibration. The flying time of each route was as follows: {| ! id ! flight ! relative height ! starttime ! endtime ! data size ! data state ! data quality ! ground targets |- | 1 || 2#5 || 1500m || 13:14:39 || 13:22:43 || 122 || processed;complete || good || National observatory on climatology at Zhangye;Gulou in Zhangye |- | 2 || 2#7 || 1500m || 13:28:23 || 13:35:31 || 108 || processed;complete || good |- | 3 || 2#9 || 1500m || 13:41:11 || 13:49:03 || 119 || processed;complete || good || wetland park in Zhangye |}
Liu Qiang, XIAO Qing, Wen Jianguang, FANG Li, Wang Heshun, LI Bo, LIU Zhigang, LI Xin, MA Mingguo
The aim of the simultaneous observation of land surface temperature is obtaining the land surface temperature of different kinds of underlying surface, including greenhouse film, the roof, road, ditch, concrete floor and so on, while the sensor of thermal infrared go into the experimental areas of artificial oases eco-hydrology on the middle stream. All the land surface temperature data will be used for validation of the retrieved land surface temperature from thermal infrared sensor 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 and other details On 25 June, 2012, ditch and asphalt road surface temperatures were observed once every five minutes using handheld infrared thermometers recorded. On 26 June, 2012, ditch and asphalt road surface temperatures were observed once every five minutes using handheld infrared thermometers while greenhouse film and concrete floor surface temperatures were observed once every one second using self-recording point thermometer. On 29 June, 2012, concrete floor surface temperatures were observed continuously using handheld infrared thermometers during the sensor of TASI go into the region. At the same time, greenhouse film and concrete floor surface temperatures were observed once every one second using self-recording point thermometer. On 30 June, 2012, asphalt road, ditch, bare soil, melonry and ridge of field surface temperatures were observed continuously using handheld infrared thermometers during the sensor of TASI go into the region. At the same time, greenhouse film and concrete floor surface temperatures were observed once every one second using self-recording point thermometer. On 10 July, 2012, asphalt road, ditch, bare soil, melonry and ridge of field surface temperatures were observed once every one minute using handheld infrared thermometers during the sensor of TASI go into the region. At the same time, concrete floor surface temperatures were observed once every six second using self-recording point thermometer. On 26 July, 2012, asphalt road, concrete floor, bare soil and melonry surface temperatures were observed once every one minute using handheld infrared thermometers during the sensor of WiDAS go into the region. At the same time, greenhouse film and concrete floor surface temperatures were observed once every six second using self-recording point thermometer. On 2 August, 2012, corn field and concrete floor surface temperatures were observed using handheld infrared thermometers. At the same time, greenhouse film and concrete floor surface temperatures were observed once every six second using self-recording point thermometer. For corn field, twelve sites were selected according to the flight strip of the WiDAS sensor, and for each site one plot surface temperatures were recorded continuously during the sensor of WiDAS go into the region. On 3 August, 2012, corn field and concrete floor surface temperatures were observed using handheld infrared thermometers. At the same time, greenhouse film and concrete floor surface temperatures were observed once every six second using self-recording point thermometer. For corn field, fourteen sites were selected according to the flight strip of the WiDAS sensor, and for each site three plots surface temperatures were recorded continuously during the sensor of WiDAS go into the region. 2. Instrument parameters and calibration The field of view of the self-recording point thermometer and the handheld infrared thermometer are 10 and 1 degree, respectively. The emissivity of the latter was assumed to be 0.95. The observation heights of the self-recording point thermometer for the greenhouse film and the concrete floor were 0.5 m and 1 m, respectively. All instruments were calibrated three times (on 6 July, 5 August and 20 September, 2012) using black body during observation. 3. Data storage All the observation data were stored in excel.
GENG Liying, Jia Shuzhen, WANG Haibo, PENG Li, Dong Cunhui
The dataset of regimen change statistics was obtained at the hydrological section of the Dayekou watershed reservoir from Jan. 1, 2007 to May 23, 2008. Ten days observations were carried out from Oct. 21, 2007 to Apr. 11, 2008, and diurnal observations from Apr. 15 to Oct. 21, 2007, and from Apr. 16 to May 23, 2008. Data record fields included: inflow (m^3/s), water level (m), impoundment (ten thousand m^3/s), outflow (m^3/s), ten days mean inflow (m^3/s), ten days mean outflow (m^3/s), monthly mean inflow (m^3/s), and monthly mean outflow (m^3/s).
MA Mingguo
The dataset of ground truth measurement synchronizing with MODIS was obtained in the Linze grassland foci experimental area on Jun. 10, 2008. Simultaneous east-west ground measurements on the canopy temperature, the half-height temperature and the surface radiative temperature were carried out by the hand-held infrared thermometer at intervals of 125m in 8 quadrates (2km×2km), No.1 quadrat (H01-H08), No.2 quadrat (H09-H16), No.3 quadrat (H17-H24), No.4 quadrat (H25-H32), No.5 quadrat (H33-H40), No.6 quadrat (H41-H48), No.7 quadrat (H49-H56) and No.8 quadrat (H57-H64). Data were archived in Excel file. See WATER: Dataset of setting of the sampling plots and stripes in the foci experimental area of Linze station for more information.
GE Chunmei, HAO Xiaohua, HUANG Chunlin, WANG Xufeng
1、 The basin boundary of Heihe River Basin is based on the high-precision digital elevation model (DEM), which is obtained by using GIS hydrological analysis function analysis, and refers to remote sensing image, topographic map, ground investigation and previous research results. The surface catchment area of Heihe River basin covers an area of about 255000 km2, starting from the middle section of Qilian Mountains in the south, the Gobi Altai Mountains in Mongolia in the north, the Mazong mountains in the West and the Yabulai mountains in the East. Compared with the traditional Heihe River Basin, the new basin has increased Badain Jilin desert, Guizi lake, the northern part of Mazong mountain and the southern foot of Altai Mountain in Outer Mongolia Gobi. Explanation: the nanshihe River and beishihe River are the rivers formed by the leakage of the alluvial fan of Shule River. They form an independent hydrological unit (Huahai basin water systems) with Ganhaizi as the end lake, together with youYou River, Baiyang River and duanshankou river. The relationship between the hydrological unit and the Heihe River Basin is greater than that between the hydrological unit and the Shule River, which should be regarded as a part of the Heihe River Basin. Considering the current situation of modern water resources utilization, Beishi river has been directly connected with the main stream of Shule River through artificial transformation, and it is an important channel for water transmission from Shule River to Ganhaizi, and has become an important tributary of Shule River in fact. Under the influence of a series of water conservancy projects, the surface hydraulic connection between youyou River, Baiyang River and Shule River is far greater than that between youyou River and TaoLai river. 2、 Revised boundary of Yellow River Commission in Heihe River Basin On the basis of the Heihe River basin boundary revised by the Yellow River Water Conservancy Commission of the Ministry of water resources in 2005, the revised boundary of Heihe River Basin is obtained by using high-precision digital elevation model (DEM), reference remote sensing image, 1:100000 topographic map, ground investigation and other data. The basin boundary is about 76000 km2, among which the upper Qilian mountain middle section boundary is extracted strictly according to the ridge line by using DEM according to the GIS hydrological analysis function, and the lower north boundary is divided according to the boundary line according to the international convention. 3、 Study area boundary of Heihe River Basin According to the extended study area generated by the basin boundary of Heihe River Basin, it is mainly for the demand of model data input. The above three boundaries are to provide a unified study area boundary for the planned project of Heihe River Basin. It is suggested to use the revised boundary of Heihe River Basin yellow Committee as the core study area boundary.
WU Lizong
The dataset includes the chlorophyll content of vegetation in different site which has different types of vegetation, acquired on 8 July, 2012, in order to validate the Chlorophyll products. Observation instruments: Sampling, Acetone extraction method Measurement methods: To analyze the influence height on chlorophyll , we select 12 different corn samples based on the height of corn. To compare the chlorophyll content of different types of vegetation, we also select 3 types of vegetation sample on the first EC tower, 1 beans sample near the seventeenth EC tower and 3 reed samples on wetland. A total of selected 19 different samples are analyzed in the laboratory in the College of Life Science, Hexi. We extract chlorophyll a, chlorophyll b, the content of total chlorophyll of selected samples. Dataset contents: Chlorophyll a, chlorophyll b, the content of total chlorophyll Measurement time: 8 July, 2012
Jia Shuzhen
The dataset of airborne WiDAS mission was obtained in the A'rou flight zone on Jul. 7, 2008. Due to cloud/cloud shadow influence, atmospheric correction could not be performed, and geometric registration was performed manually instead of automatic matching. Level-2B (after radiometric and manual geometric corrections) and mosaic images were available for users. For the visible near infrared band the resolution is 1.25m, Radiance was recorded (W/ (sr•m^2•nm);DN=Radiance*100000); for TIR band, the brightness temperature was recorded (℃; DN=Brightness_Temperature*100) . The flying time of each route was as follows: {| ! id ! flight ! relative height ! starttime ! endtime ! data size ! data state ! data quality ! ground targets |- | 1 || 6#1 || 1500m || 13:43:18 || 13:46:26 || 48 || incomplete || incomplete |- | 2 || 6#3 || 1500m || 13:52:26 || 13:55:18 || 43 || incomplete || incomplete |- | 3 || 6#5 || 1500m || 13:59:30 || 14:02:38 || 48 || incomplete || incomplete || A’rou freeze/thaw observation station |- | 4 || 6#7 || 1500m || 14:08:02 || 14:11:02 || 46 || incomplete || incomplete |}
Liu Qiang, XIAO Qing, Wen Jianguang, FANG Li, WANG Heshun, LI Bo, LIU Zhigang, LI Xin, MA Mingguo
The dataset of airborne Polarimetric L-band Multibeam Radiometers (PLMR) was acquired on 10 July, 2012, located in the middle reaches of the Heihe River Basin. The aircraft took off at 10:30 am (UTC+8) from Zhangye airport and landed at 15:30 pm, with the flight time of 5 hours. The flight was performed in the altitude of about 2500 m and at the speed of about 220-250 km during the observation, corresponding to an expected ground resolution of about 750 m. The PLMR instrument flown on a small aircraft operates at 1.413 GHz (L-band), with both H- and V-polarizations at incidence angles of ±7.5°, ±21.5° and ±38.5°. PLMR ‘warm’ and ‘cold’ calibrations were performed before and after each flight. The processed PLMR data include 2 DAT files (v-pol and h-pol separately) and 1 KMZ file for each flying day. The DAT file contains all the TB values together with their corresponding beam ID, incidence angle, location, time stamp (in UTC) and other flight attitude information as per headings. The KMZ file shows the gridded 1-km TB values corrected to 38.5 degrees together with flight lines. Cautions should be taken when using these data, as the RFI contaminations are often higher than expected at v-polarization.
CHE Tao, Gao Ying, LI Xin
This dataset contains the flux measurements from site No.14 eddy covariance system (EC) in the flux observation matrix from 30 May to 21 September, 2012. The site (100.35310° E, 38.85867° N) was located in a cropland (maize surface) in Yingke irrigation district, which is near Zhangye, Gansu Province. The elevation is 1570.23 m. The EC was installed at a height of 4.6 m; 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 (CSAT3&Li7500) was 0.15 m. Raw data acquired at 10 Hz were processed using the Edire post-processing software (University of Edinburgh, http://www.geos.ed.ac.uk/abs/research/micromet/EdiRe/), including 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. Moreover, 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), which was proposed by Foken and Wichura [1996]: class 1 (level 0: Δst<30 and ITC<30), class 2 (level 1: Δst<100 and ITC<100), and class 3 (level 2: Δst>100 and ITC>100), representing high-, medium-, and low-quality data, respectively. 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 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; the missing data were replaced with -6999. Moreover, suspicious data were marked in red. The released data contained the following variables: data/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/m^3), CO2 mass density (CO2, mg/m^3), friction velocity (ustar, m/s), stability (z/L), sensible heat flux (Hs, W/m^2), latent heat flux (LE, W/m^2), carbon dioxide flux (Fc, mg/ (m^2s)), 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). 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 *.xlsx format. For more information, please refer to Liu et al. (2016) (for multi-scale observation experiment or sites information), Xu et al. (2013) (for data processing) in the Citation section.
LIU Shaomin, LI Xin, XU Ziwei
This data set includes the observation data of 25 water net sensor network nodes in Babao River Basin in the upper reaches of Heihe River from January 2015 to December 2015. 4cm and 20cm soil moisture / temperature is the basic observation of each node; some nodes also include 10cm soil moisture / temperature, surface infrared radiation temperature, snow depth and precipitation observation. The observation frequency is 5 minutes. The data set can be used for hydrological simulation, data assimilation and remote sensing verification. For details, please refer to "2015 data document 20160501. Docx of water net of Babao River in the upper reaches of Heihe River"
KANG Jian, LI Xin, MA Mingguo
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