Soil water content is the key factor affecting the transpiration water consumption of plants in desert riparian forest. In this project, the typical plant communities in the lower reaches of Heihe River are selected, with coordinates of 42 ° 02 ′ 00.07 ″ N and 101 ° 02 ′ 59.41 ″ E. through continuous measurement of soil water data in 2010-2012, the observation instrument is environscan (Australia, ICT), with observation depth of 10, 30, 50, 80 and 140cm, and observation frequency of 0.5h Understanding the mechanism of environmental regulation of transpiration water consumption of desert riparian forest in the lower reaches of Heihe River provides basic data support.
SI Jianhua
The data set collects the long-term monitoring data on atmosphere, hydrology and soil from the Integrated Observation and Research Station of Multisphere in Namco, the Integrated Observation and Research Station of Atmosphere and Environment in Mt. Qomolangma, and the Integrated Observation and Research Station of the Alpine Environment in Southeast Tibet. The data have three resolutions, which include 0.1 seconds, 10 minutes, 30 minutes, and 24 hours. The temperature, humidity and pressure sensors used in the field atmospheric boundary layer tower (PBL) were provided by Vaisala of Finland. The wind speed and direction sensor was provided by MetOne of the United States. The radiation sensor was provided by APPLEY of the United States and EKO of Japan. Gas analysis instrument was provided by Licor of the United States, and the soil moisture content, ultrasonic anemometer and data collector were provided by CAMPBELL of the United States. The observing system is maintained by professionals on a regular basis (2-3 times a year), the sensors are calibrated and replaced, and the collected data are downloaded and reorganized to meet the meteorological observation specifications of the National Weather Service and the World Meteorological Organization (WMO). The data set was processed by forming a time continuous sequence after the raw data were quality-controlled, and the quality control included eliminating the systematic error caused by missing data and sensor failure.
MA Yaoming
The dataset of ground truth measurements synchronizing with the airborne WiDAS mission was obtained in the Linze station foci experimental area on Jun. 29, 2008. WiDAS, composed of four CCD cameras, one mid-infrared thermal imager (AGEMA 550), and one infrared thermal imager (S60), can acquire CCD, MIR and TIR band data. The simultaneous ground data included: (1) soil moisture (0-5cm) nine times by the cutting ring (50cm^3) along LY06 and LY07 strips, and once by the cutting ring method and once by ML2X Soil Moisture Tachometer in the six points of Wulidun farmland quadrates. The preprocessed soil volumetric moisture data were archived as Excel files. (2) surface radiative temperature measured three times by three handheld infrared thermometer (5# and 6# from Cold and Arid Regions Environmental and Engineering Research Institute, and one from Institute of Geographic Sciences and Natural Resources, which were all calibrated) in LY06 and LY07 strips (98 sample points and repeated three times) and the Wulidun farmland quadrates (various points and repeated three times). Data were archived as Excel files. (3) maize canopy component temperature measured by the 5# handheld infrared thermometer (from Cold and Arid Regions Environmental and Engineering Research Institute) in Wulidun farmland quadrates. Six directions were measured, canopy backlighting and frontlighting, half height backlighting and frontlighting, the light and the shaded bareland, with each direction 20 measurements. (4) spectrum of maize, soil and soil with known moisture measured by ASD Spectroradiometer (350～2 500 nm) from BNU, and the reference board (40% before Jun. 15 and 20% hereafter) in Wulidun farmland quadrates. Raw spectral data were binary files , which were recorded daily in detail, and pre-processed data on reflectance (by ViewSpecPro) were archived as Excel.files (5) mltiangle maize spectrum measured by ASD Spectroradiometer (350～2 500 nm) from BNU, the reference board (40% before Jun. 15 and 20% hereafter), two observation platforms of BNU make and one of Institute of Remote Sensing Applications make in Wulidun farmland. Raw spectral data were archived as binary files, which were recorded daily in detail, and pre-processed data on reflectance and transmittivity were archived as text files (.txt). (6) LAI of maize measured by the fisheye camera (CANON EOS40D with a lens of EF15/28), shooting straight downwards, with exceptions of higher plants, which were shot upwards. Data included original photos (.JPG) and those processed by can_eye5.0 (in excel). (7) LAI of maize measured by LAI2000 in Wulidun farmland quadrates. Data educed from LAI2000 periodically were archived as text files (.txt) and marked with one ID. Raw data (table of word and txt) and processed data (Excel) were included. Besides, observation time, the observation method and the repetition were all archived. 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.
DONG Jian, YU Yingjie, BAI Yanfen, HAO Xiaohua, Qian Jinbo, SHU Lele, WANG Yang, XU Zhen
The hydrological monitoring of Picea crassifolia and main shrub vegetation types, including canopy interception, soil moisture content and stemflow, was carried out at different altitude gradients in Pailugou catchment of Qilian Mountain. The monitoring time was the dynamic monitoring of growth season in 2012 and 2013.
LIU Xiande
The dataset of ground truth measurements synchronizing with the airborne microwave radiometers (L&K bands, between 8:06~11:17BJT) and thermal imager mission (between 12:48~16:35BJT) was obtained in L2, L3, L4, L5 and L6 of the A'rou foci experimental area on Apr. 1, 2008. The samples were collected every 100m along the strip from south to north in the the morning and from north to south in the afternoon. In L2, L4 and L6, the soil temperature, soil volumetric moisture, the loss tangent, soil conductivity, and the real part and the imaginary part of soil complex permittivity were acquired by the POGO soil sensor, the mean soil temperature from 0-5cm by the probe thermometer, the surface radiative temperature measured three times by the hand-held infrared thermometer, and soil gravimetric moisture, volumetric moisture, and soil bulk density after drying by the cutting ring (100cm^3). In L3, soil volumetric moisture was acquired by ML2X, the mean soil temperature from 0-5cm by the probe thermometer, the surface radiative temperature measured three times by the hand-held infrared thermometer, and soil gravimetric moisture, volumetric moisture, and soil bulk density after drying by the cutting ring (100cm^3). In L5, soil volumetric moisture, soil conductivity, the soil temperature, and the real part of soil complex permittivity were acquired by WET, the mean soil temperature from 0-5cm by the probe thermometer, the surface radiative temperature measured three times by the hand-held infrared thermometer, soil gravimetric moisture, volumetric moisture, and soil bulk density after drying by the cutting ring (100cm^3). Besides, the handheld thermal imager observations were carried out in L4. Those provide reliable ground data for retrieval and validation of soil moisture and freeze/thaw status from active remote sensing approaches. Seven files were included, two ground-based microwave radiometers (L&K-band and L-band) observations, L2 data, L3 data, L4 data, L5 data and L6 data.
GE Chunmei, GU Juan, HAN Xujun, HAO Xiaohua, HU Zeyong, HUANG Chunlin, LI Zhe, LIANG Ji, MA Mingguo, SHU Lele, Wang Weizhen, WU Yueru, ZHU Shijie, LI Hua, CHANG Cun, DOU Yan, MA Zhongguo
202024test test data 202024test test data 202024Test test data 202024test test data 202024test test data 202024test test data 202024test test data 202024test test data 202024test test data 202024test test data 202024test test data 202024test test data 202024test test data
MA Mingguo, DING Songchuang, GAO Song, Qian Jinbo, BAI Yunjie, WANG Xufeng, TAN Junlei, WANG Shuguo, GU Juan, WANG Shunli, LUO Longfa, WANG Rongxin, CHE Zongxi, JING Wenmao
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
On June 26, 2012, the satellite transit ground synchronous observation was carried out in the TerraSAR-X sample near the super station in the dense observation area of Daman. TerraSAR-X satellite carries X-band synthetic aperture radar (SAR). The daily transit image is HH / VV polarized, with a nominal resolution of 3 m, an incidence angle of 22-24 ° and a transit time of 19:03 (Beijing time), which mainly covers the ecological and hydrological experimental area of the middle reaches artificial oasis. The local synchronous data set can provide the basic ground data set for the development and verification of active microwave remote sensing soil moisture retrieval algorithm. Quadrat and sampling strategy: Six natural blocks are selected in the southeast of the super station, with an area of about 100 m × 100 m. One plot in the northwest corner of the sample plot is watermelon field, others are corn. The basis of sample selection is: (1) considering different vegetation types, i.e. watermelon and corn; (2) considering the visible light pixel, the sample size of 100m square can guarantee at least 4 30 M-pixel is located in the sample; (3) the location of the sample is near the super station, with convenient transportation. The observation of the super station is in the north, and there is a water net node on both sides of the East and the west, which makes it possible to integrate these observations in the future; (4) in addition, there are some obvious points around the sample, which can ensure that the geometric correction of the SAR image is more accurate in the future. Considering the resolution of the image, 21 splines (distributed from east to West) are collected at 5m intervals. Each line has 21 points (north-south direction) at 5m intervals. Three hydroprobe data acquisition systems (HDAS, reference 2) are used to measure at the same time. The sampling interval is controlled by the scale and moving splines on the measuring line to make up for the lack of using hand-held GPS. Measurement content: About 440 points on the quadrat were obtained, and each point was observed twice, i.e. two times in each sampling point, one time inside the film (marked as a in the data record) and one time outside the film (marked as B in the data record); although the watermelon land was also covered with film, considering that it was not laid horizontally, only the soil moisture at the non covered position was measured (marked as B in the two data records). As the HDAS system uses pogo portable soil sensor, the soil temperature, soil moisture (volume moisture content), loss tangent, soil conductivity, real part and imaginary part of soil complex dielectric are observed. Because the vegetation in this area has been sampled and observed once every five days, no special vegetation synchronous sampling has been carried out on that day. Data: The data format of this data set is vector file, the spatial location is the location of each sampling point (WGS84 + UTM 47N), and the measurement information of soil moisture is recorded in the attribute file.
WANG Shuguo, MA Mingguo, LI Xin
The dataset of soil moisture profile (0cm, 20cm, 40cm and 1m) observations was obtained by TDR (with the probe 12cm and 20cm) in the Yingke oasis and Huazhaizi desert steppe foci experimental areas. Observation items included: (1) Soil moisture synchronizing with TM in Yingke oasis No. 1, 4 and 5 maize plots on May 20, 2008. (2) Soil moisture synchronizing with ASTER and MODIS in Yingke oasis foci experimental areas on May 28, 2008. (3) Soil moisture synchronizing with WiDAS (Wide-angle Infrared Dual-mode line/area Array Scanner) in Yingke oasis foci experimental areas on May 30, 2008. (4) Soil moisture synchronizing with WiDAS (Wide-angle Infrared Dual-mode line/area Array Scanner) in A'rou grassland on May 31, 2008. (5) Soil moisture synchronizing with OMIS-II in Yingke oasis foci experimental areas on Jun. 4, 2008. (6) Soil moisture synchronizing with OMIS-II in Yingke oasis maize field on Jun. 16, 2008. (7) Soil moisture by TDR and the cutting ring, synchronizing with ASAR in Yingke oasis maize field and wheat field on Jun. 19, 2008. (8) Soil moisture synchronizing with WiDAS (Wide-angle Infrared Dual-mode line/area Array Scanner) in Yingke oasis foci experimental areas on Jun. 29, 2008. (9) Soil moisture synchronizing with WiDAS (Wide-angle Infrared Dual-mode line/area Array Scanner) and TM in Yingke oasis foci experimental areas on Jul. 7, 2008. (10) Soil moisture synchronizing with WiDAS (Wide-angle Infrared Dual-mode line/area Array Scanner) in Yingke oasis foci experimental areas on Jul. 11, 2008.
GE Yingchun, LI Li, XIN Xiaozhou, Zhang Yang, ZHOU Mengwei, YANG Tianfu, SHU Lele, WANG Jianhua, XU Zhen, FENG Lei, LIANG Wenguang, YU Fan, LI Xiaoyu, ZHU Xiaohua
This dataset include soil moisture and soil temperature observations of 50 SoilNET Nodes during June 2012~March 2013 (UTC+8), which located in a MODIS pixel in the observation matrix of the HiWATER artificial oasis eco-hydrology experimental area, and aim to capture the spatial-temporal variance at the ~100 m scale. Each SoilNET node observe the soil moisture and soil temperature at 4 cm, 10 cm, 20 cm and 40 cm depth using the SPADE sensor 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 "SoilNET_data_document.docx".
WANG Xufeng, KANG Jian, Li Dazhi, Wang Zuocheng, Dong Cunhui, LI Xin, MA Mingguo
This data set includes the continuous observation data set of soil texture, roughness and surface temperature measured by vehicle borne microwave radiometer from November 18 to 19, 2013 in Wuxing village farmland, Ganzhou District, Zhangye City, Gansu Province. The surface temperature and humidity include four layers of temperature sensor at the soil depth of 1cm, 5cm, 10cm, 20cm, and the observation of soil temperature and soil moisture data at the soil depth of 0-5cm. The time frequency of routine observation of soil temperature and humidity is 5 minutes. Data details: 1. Time: November 18-19, 2013 2. data: Brightness temperature: observed by vehicle mounted multi frequency passive microwave radiometer, including 6.925, 18.7 and 36.5ghz V polarization and H polarization data (10.65ghz band damage) Soil temperature: use sensor installed on dt80 to measure 1cm, 5cm, 10cm, 20cm soil temperature Soil moisture: use h-probe sensor to measure 0-5cm soil moisture, the probe can measure 0-5cm soil temperature at the same time Soil texture: soil samples measured in Beijing Normal University Soil roughness: measured by roughness meter provided by northeast geography 3. Data size: 3.5m 4. Data format:. Xls
ZHAO Shaojie, KOU Xiaokang, YE Qinyu, MA Mingguo
1. Data overview: The sampling time of this data is from May 9, 2013 to March 29, 2014.The sampling frequency is once a week. The sampling point of the river is located at the outlet weir of the small haugou watershed in the upper reaches of the heihe river, with the latitude and longitude of 99 ° 52 '47.7 "E and 38 ° 16' 11" N. The sampling location of soil water is 300m above the no. 2 meteorological station, and the lower soil profile is 99°53 '31.333 "E,38°13' 50.637" N in longitude and latitude. 2. Data content: This data set contains the anion and anion values of the river at the outlet of the basin and the soil water at 300m above the no. 2 weather station. Data acquisition means - anion values were determined by Swiss wantong model 761/813 ion chromatograph.Cation is to use the model to the United States thermoelectric IRIS Intrepid Ⅱ XSPICP - AES determination.
SUN Ziyong, CHANG Qixin
The dataset of ground truth measurements synchronizing with Envisat ASAR was obtained in No. 1 and 2 quadrates of the Biandukou foci experimental area on Oct. 18, 2007, during the pre-observation period. The ASAR data were in AP mode and VV/VH polarization combinations, and the overpass time was approximately at 11:17 BJT. Both the quadrates were divided into 3×3 subsites, with each one spanning a 30×30 m2 plot. 25 sampling points were chosen, including centers and corners. Simultaneous with the satellite overpass, numerous ground data were collected: the soil temperature , volumetric soil moisture (cm^3/cm^3), soil salinity (s/m), soil conductivity (s/m) by the Hydra probe, the surface radiative temperature by the handheld infrared thermometer, gravimetric soil moisture, volumetric soil moisture, and soil bulk density by drying soil samples from the cutting ring (100cm^3). Meanwhile, vegetation parameters as height, coverage and water content were also observed. Those provide reliable ground data for the development and validation of soil moisture, soil freeze/thaw algorithms and the forward model from active remote sensing approaches.
BAI Yunjie, CAO Yongpan, WANG Jian, Wang Weizhen, WANG Xufeng, JIN Rui, Qu Yonghua, ZHOU Hongmin
This data set includes the continuous observation data set of soil texture, roughness and surface temperature measured by vehicle borne microwave radiometer from November 22 to 24, 2013 in Desert Park desert, Ganzhou District, Zhangye City, Gansu Province. The surface temperature and humidity include four layers of temperature sensor at the soil depth of 1cm, 5cm, 10cm, 20cm, and the observation of soil temperature and soil moisture data at the soil depth of 0-5cm. The time frequency of routine observation of soil temperature and humidity is 5 minutes. Data details: 1. Time: November 22-24, 2013 2. data: Brightness temperature: observed by vehicle mounted multi frequency passive microwave radiometer, including 6.925, 18.7 and 36.5ghz V polarization and H polarization data (10.65ghz band damage) Soil temperature: use sensor installed on dt80 to measure 1cm, 5cm, 10cm, 20cm soil temperature Soil moisture: use h-probe sensor to measure 0-5cm soil moisture, the probe can measure 0-5cm soil temperature at the same time Soil texture: soil samples measured in Beijing Normal University Soil roughness: measured by roughness meter provided by northeast geography 3. Data size: 7.4M 4. Data format:. Xls
ZHAO Shaojie, KOU Xiaokang, YE Qinyu, MA Mingguo
Select the soil mechanical composition data of 0-20cm depth of soil surface, select the optimal spatial prediction mapping method of soil composition data, and make the spatial distribution data product of soil texture (particle size composition). The American system classification is used as the standard of soil particle classification. The source data of this data set comes from the soil sampling data integrated by the data center of cold and dry areas and the major research plan integration project of Heihe River Basin (spatial interpolation and dynamic simulation analysis of vegetation and environmental elements in the upper reaches of Heihe River basin / approval No. 91325204).
YUE Tianxiang, ZHAO Na
This dataset includes data recorded by the Cold and Arid Research Network of Lanzhou university obtained from an observation system of Meteorological elements gradient of Guazhou Station from September 23 to December 31, 2018. The site (95.673E, 41.405N) was located on a desert in the Liuyuan Guazhou, which is near Jiuquan city, Gansu Province. The elevation is 2016 m. The installation heights and orientations of different sensors and measured quantities were as follows: air temperature and humidity profile (2, 4, 8, 16, 32, and 48 m, towards north), wind speed and direction profile (windsonic; 2, 4, 8, 16, 32, and 48 m, towards north), air pressure (1.5 m), rain gauge (4 m), infrared temperature sensors (4 m, towards south, vertically downward), photosynthetically active radiation (4 m, towards south), soil heat flux (-0.05 m and -0.1m in south of tower), soil soil temperature/ moisture/ electrical conductivity profile -0.05, -0.1m, -0.2m, -0.4m, -0.6m and -0.8m in south of tower), four-component radiometer (4 m, towards south), sunshine duration sensor(4 m, towards south). The observations included the following: air temperature and humidity (Ta_2 m, Ta_4 m, Ta_8 m, Ta_16 m, Ta_32 m, and Ta_48 m; RH_2 m, RH_4 m, RH_8 m, RH_16 m, RH_32 m, and RH_48 m) (℃ and %, respectively), wind speed (Ws_2 m, Ws_4 m, Ws_8 m, Ws_16 m, Ws_32 m, and Ws_48 m) (m/s), wind direction (WD_2 m, WD_4 m, WD_8 m, WD_16 m, WD_32 m, and WD_48 m) (°), air pressure (press) (hpa), precipitation (rain) (mm), four-component radiation (DR, incoming shortwave radiation; UR, outgoing shortwave radiation; DLR_Cor, incoming longwave radiation; ULR_Cor, outgoing longwave radiation; Rn, net radiation) (W/m^2), infrared temperature (IRT) (℃), photosynthetically active radiation (PAR) (μmol/ (s m^2)), soil heat flux (Gs_0.05m, Gs_0.1m) (W/m^2), soil temperature (Ts_5 cm, Ts_10 cm, Ts_20 cm, Ts_40 cm, Ts_60 cm, and Ts_80 cm) (℃), soil moisture (Ms_5 cm, Ms_10 cm, Ms_20 cm, Ms_40 cm, Ms_60 cm, and Ms_80 cm) (%, volumetric water content),soil water potential (SWP_5cm, SWP_10cm, SWP_20cm, SWP_40cm, SWP_60cm, and SWP_80cm)(kpa), soil conductivity (Ec_5cm, Ec_10cm, Ec_20cm, Ec_40cm, Ec_60cm, and Ec_80cm)(μs/cm), sun time (h). The data processing and quality control steps were as follows: (1) The AWS data were averaged over intervals of 10 min for a total of 144 records per day. The soil water potential in the area is so low that it has exceeded the sensor measurements. (2) Data in duplicate records were rejected. (3) Unphysical data were rejected. (4) The data marked in red are problematic data. (5) The format of the date and time was unified, and the date and time were collected in the same column, for example, date and time: 2018-6-10 10:30.
ZHAO Changming, ZHANG Renyi
The dataset of ground truth measurement synchronizing with ALOS PALSAR was obtained in the Linze grassland foci experimental area on Jun. 10, 2008. The data were in FBS mode and HH/HV polarization combinations, and the overpass time was approximately at 23:39 BJT. Observations were carried out in plots A, B, C, D and E, which were divided into 6×6 subsites, with each one spanning a 120×120 m2 plot. Soil gravimetric moisture, volumetric moisture, and soil bulk density after drying by the cutting ring and the mean soil temperature from 0-5cm by the probe thermometer were measured in A, B and C; the soil temperature, soil moisture, the loss tangent, soil conductivity, the real part and the imaginary part of soil complex permittivity by the POGO soil sensor, and the mean soil temperature from 0-5cm by the probe thermometer in D and E. 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.
BAI Yanfen, CAO Yongpan, GE Chunmei, HU Xiaoli, WANG Shuguo, Wang Weizhen, WU Yueru, ZHU Shijie, FENG Lei
The dataset of ground-based microwave scatterometer and ground truth observations for soil freeze/thaw cycle was obtained in No. 3 quadrate of the A'rou foci experimental area from 22:33 on Mar. 16 to 15:00 on 17, 2008. Observation items included the mean soil temperature from 0-5cm by the probe thermometer, the soil temperature at 5cm and 10cm by the glass geothermometer, the soil temperature, soil volumetric moisture, the loss tangent, soil conductivity, and the real part and the imaginary part of soil complex permittivity by the POGO soil sensor, and soil gravimetric moisture, volumetric moisture, and soil bulk density after drying by the cutting ring (100cm^3). Those provide reliable ground data for retrieval and validation of soil moisture and freeze/thaw status from active remote sensing approaches. Two files were included, the microwave scatterometer and ground truth observations; both were archived in Excel format.
LIU Zengcan, LIU Zengcan, QIN Wei, CAO Yongpan, HAN Xujun, MA Mingguo
On June 15, 2012, the satellite transit ground synchronous observation was carried out in the TerraSAR-X sample near the super station in the dense observation area of Daman. TerraSAR-X satellite carries X-band synthetic aperture radar (SAR). The daily transit image is HH / VV polarized, with a nominal resolution of 3 m, an incidence angle of 22-24 ° and a transit time of 19:03 (Beijing time), which mainly covers the ecological and hydrological experimental area of the middle reaches artificial oasis. The local synchronous data set can provide the basic ground data set for the development and verification of active microwave remote sensing soil moisture retrieval algorithm. Quadrat and sampling strategy: Six natural blocks are selected in the southeast of the super station, with an area of about 100 m × 100 m. One plot in the northwest corner of the sample plot is watermelon field, others are corn. The basis of sample selection is: (1) considering different vegetation types, i.e. watermelon and corn; (2) considering the visible light pixel, the sample size of 100m square can guarantee at least 4 30 M-pixel is located in the sample; (3) the location of the sample is near the super station, with convenient transportation. The observation of the super station is in the north, and there is a water net node on both sides of the East and the west, which makes it possible to integrate these observations in the future; (4) in addition, there are some obvious points around the sample, which can ensure that the geometric correction of the SAR image is more accurate in the future. Considering the resolution of the image, 21 splines (distributed from east to West) are collected at 5 m intervals. Each line has 23 points (north-south direction) at 5 m intervals. Four hydroprobe data acquisition systems (HDAS, reference 2) are used to measure at the same time. The sampling interval is controlled by the scale and moving splines on the measuring line to make up for the lack of using hand-held GPS. Measurement content: About 500 points on the quadrat were obtained, and each point was observed twice, i.e. in each sampling point, once in the film (marked a in the data record) and once out of the film (marked b in the data record); although the watermelon land was also covered with film, considering that it was not laid horizontally, only the soil moisture at the non covered position was measured (marked b in both data records). As the HDAS system uses pogo portable soil sensor, the soil temperature, soil moisture (volume moisture content), loss tangent, soil conductivity, real part and imaginary part of soil complex dielectric are observed. The vegetation team completed the measurement of biomass, Lai, vegetation water content, plant height, row ridge distance, chlorophyll, etc. Data: This data set includes two parts: soil moisture observation and vegetation observation. The former saves the data format as a vector file, the spatial location is the location of each sampling point (WGS84 + UTM 47N), and the measurement information of soil moisture is recorded in the attribute file; the vegetation sampling information is recorded in the excel table.
WANG Shuguo, MA Mingguo, LI Xin
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
Contact Support
Northwest Institute of Eco-Environment and Resources, CAS
0931-4967287
poles@itpcas.ac.cn
Links
National Tibetan Plateau Data CenterFollow Us
A Big Earth Data Platform for Three Poles © 2018-2020 No.05000491 | All Rights Reserved
｜ 
No.11010502040845
Tech Support: westdc.cn
