This dataset includes 5 sub-datasets obtained from measurements in the flux observing matrix at observing site No.15 (the Daman superstation) and 13. Specifically, the sub-datasets include the following: (1) a dataset that contains atmospheric water vapor D/H and 18O/16O isotopic and flux ratio measurements from site No.15 from 27 May to 21 September in 2012, (2) a dataset that contains D/H and 18O/16O isotopic ratios of water in soil and in corn xylem at site No.15 from 27 May to 21 September 2012, (3) a dataset that contains atmospheric water vapor D/H and 18O/16O isotopic ratios at site No.13 when airborne surveys occurred, and (4) a dataset that contains D/H and 18O/16O isotopic ratios of water in soil and in corn xylem at sites No.13 and 15 when airborne surveys occurred, (5) a dataset that contains the ratios of evaporation and transpiration to evapotranpiration at site No.15. The experiment area was located in a corn cropland in the Daman irrigation district of Zhangye, Gansu Province, China. The positions of observing sites No.15 and 13 were 100.3722° E, 38.8555° N and 100.3785° E, 38.8607° N, respectively, with an elevation of 1552.75 m above sea level. The atmospheric water vapor D/H and 18O/16O isotopic and flux ratios at site No.15 were continuously measured using an in situ observation system. The system consisted of an H218O, HDO and H2O analyzer (Model L1102-i, Picarro Inc.), a CTC HTC-Pal liquid auto sampler (LEAP Technologies) and a multichannel solenoid valve (Model EMT2SD8 MWE, Valco Instruments CO. Inc.). The heights of the two intakes were 0.5 and 1.5 m above the corn canopy. The water vapor D/H and 18O/16O isotopic ratio analyzer recorded signals at 0.2 Hz; data were recorded for 2 minutes per intake. The data were block-averaged to hourly intervals. The sampling frequency of soil and xylem at site No. 15 was 1-3 days. The atmospheric water vapor D/H and 18O/16O isotopic and flux ratios at site No.13 were measured using a cold traps/mass spectrometer. The sampling frequency of atmospheric water vapor, soil water and xylem water at site No.13 was the same as that of the airborne surveys. Briefly, the Picarro analyzer measurements were calibrated during every 3 h switching cycle using a two-point concentration interpolation procedure in which the water vapor mixing ratio was dynamically controlled to track the ambient water vapor mixing ratio. Possible delta stretching effects were not considered. A schematic diagram of the Picarro analyzer and its operation principles and calibration procedure are described elsewhere in the literature (Huang et al., 2014; Wen et al. 2008, 2012). The dataset of atmospheric water vapor D/H and 18O/16O isotopic and flux ratios at site No.15 includes the following variables: Timestamp (time, timestamp without time zone), Number (available record number), δD for r1 (δD for the lower intake, ‰), δD for r2 (δD for the higher intake, ‰), δ18O for r1 (δ18O for the lower intake, ‰), δ18O for r2 (δ18O for the higher intake, ‰), vapor mixing ratio for r1 (vapor mixing ratio for the lower intake, mmol/mol), vapor mixing ratio for r2 (vapor mixing ratio for the higher intake, mmol/mol), δET_D (δD of evapotranspiration, ‰), and δET_18O (δ18O of evapotranspiration, ‰). The dataset of D/H and 18O/16O isotopic ratios of water in soil and in corn xylem at site No.15 includes the following variables: Timestamp (time, timestamp without time zone), Remark (treatment: soil without mulch (Ld)=1; soil with mulch (Fm)=2; soil with male corns (F)=3; Xylem=4), δD (‰), and δ18O (‰). The dataset for the ratio of soil evaporation and transpiration to the evapotranspiration at site 15 includes the following variables: Timestamp (time, timestamp without time zone), E/ET (ratio of soil evaporation to the evapotranspiration, %), and T/ET (ratio of transpiration to the evapotranspiration, %). The mean (±one standard deviation) ratio of transpiration to evapotranspiration was 86.7±5.2% (the range was 71.3 to 96.0%). The mean (±one standard deviation) ratio of soil evaporation to the evapotranspiration was 13.3 ±5.2% (the range was 4.0 to 28.7%). The dataset of atmospheric water vapor D/H and 18O/16O isotopic ratio at site No. 13 when airborne surveys occurred includes the following variables: Timestamp1 (start time, timestamp without time zone), Timetamp2 (end time, timestamp without time zone), Height (observation height, cm), δD (‰), and δ18O (‰). The dataset of D/H and 18O/16O isotopic ratios of water in soil and in corn xylem at sites No. 13 and 15 when airborne surveys occurred include the following variables, Timestamp (time, timestamp without time zone), Remark (treatment: soil without mulch (Ld)=1; soil with mulch (Fm)=2; Xylem=4), δD (‰), δ18O (‰), and Location (observing site 13 or 15) . The missing measurements were replaced with -6999. For more information, please refer to Liu et al. (2016) (for multi-scale observation experiment or sites information), Wen et al. (2016) (for data processing) in the Citation section.
0 2019-09-12
The data set includes soil pH data of representative soil samples collected from July 2012 to August 2013 in the Heihe River Basin. The first soil survey was conducted in 2012. After the representativeness evaluation of collected samples, we conducted an additional sampling in 2013. These samples are representative enough to represent the soil variation in the Heihe River Basin, of which the soil variation in each landscape could be accounted for. The sampling depths in field refer to the sampling specification of Chinese Soil Taxonomy, in which soil samples were taken from genetic soil horizons.
0 2020-09-30
The dataset of surface roughness measurements by phototaking was obtained in the Huazhaizi desert steppe foci experimental area. Observation items included: (1) Surface roughness synchronizing with ASAR and MODIS in Huazhaizi desert No. 2 plot on May 24, 2008. (2) Surface roughness synchronizing with WiDAS in Huazhaizi desert No. 1 plot on May 30, 2008. The self-made roughness reference board (Cold and Arid Regions Environmental and Engineering Research Institute, CAS), the digital camera and the compass were used. Sample points were selected at equal intervals along the diagonals and marked in the photos.
0 2019-05-23
This dataset includes data recorded by the Hydrometeorological observation network obtained from the automatic weather station (AWS) at the observation system of Meteorological elements gradient of Daman Superstation between 22 September, 2012, and 31 December, 2013. The site (100.4464° E, 38.9751° N) was located on a wetland (reed surface) in Zhangye National Wetland Park, Gansu Province. The elevation is 1460 m. The installation heights and orientations of different sensors and measured quantities were as follows: air temperature and humidity profile (HMP45AC; 5 and 10 m, north), wind speed profile (03002; 5 and 10 m, north), wind direction profile (03002; 10 m, north), air pressure (CS100; 2 m), rain gauge (TE525M; 10 m), four-component radiometer (CNR1; 6 m, south), two infrared temperature sensors (SI-111; 6 m, south, vertically downward), soil heat flux (HFP01; 3 duplicates, -0.06 m), soil temperature profile (109ss-L; 0, -0.02, -0.04, -0.1, -0.2 and -0.4 m), and four photosynthetically active radiation (PQS-1; install on 28 July, 2013, two above the plants, 6 m, south, one vertically downward and one vertically upward; two below the plants, 0.25 m, south, one vertically downward and one vertically upward). The observations included the following: air temperature and humidity (Ta_5 m and Ta_10 m; RH_5 m and RH_10 m) (℃ and %, respectively), wind speed (Ws_5 m and Ws_10 m) (m/s), wind direction (WD_10 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_1 and IRT_2) (℃), soil heat flux (Gs_1, Gs_2, and Gs_3) (W/m^2), soil temperature (Ts_0 cm, Ts_2 cm, Ts_4 cm, Ts_10 cm, Ts_20 cm and Ts_40 cm) (℃), on the plants photosynthetically active radiation of upward and downward (PAR_U_up and PAR_U_down) (μmol/ (s m^-2)), and below the plants photosynthetically active radiation of upward and downward (PAR_D_up and PAR_D_down) (μmol/ (s m^-2)). 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. Data were missing during 10 May, 2013 and 30 May, 2013 because of datalogger malfunction; the wind speed data were missing during 1 September, 2013 and 5 September, 2013 because of sensor malfunction. The missing data were denoted by -6999. (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: 2013-6-10 10:30. (6) Finally, the naming convention was AWS+ site no. Moreover, suspicious data were marked in red. For more information, please refer to Li et al. (2013) (for hydrometeorological observation network or sites information), Liu et al. (2011) (for data processing) in the Citation section.
0 2019-09-14
This data set comprises the plateau soil moisture and soil temperature observational data based on the Tibetan Plateau, and it is used to quantify the uncertainty of model products of coarse-resolution satellites, soil moisture and soil temperature. The observation data of soil temperature and moisture on the Tibetan Plateau (Tibet-Obs) are from in situ reference networks at four regional scales, which are the Nagqu network of cold and semiarid climate, the Maqu network of cold and humid climate, and the Ali network of cold and arid climate，and Pali network. These networks provided representative coverage of different climates and surface hydrometeorological conditions on the Tibetan Plateau. - Temporal resolution: 1hour - Spatial resolution: point measurement - Measurement accuracy: soil moisture, 0.00001; soil temperature, 0.1 °C; data set size: soil moisture and temperature measurements at nominal depths of 5, 10, 20, 40 - Unit: soil moisture, cm ^ 3 cm ^ -3; soil temperature, °C
0 2019-11-14
The past frozen soil map of the Tibetan Plateau was based on a small number of temperature station observations and used a classification system based on continuity. This data set used the geographically weighted regression model (GWR) to synthesize MODIS surface temperature, leaf area index, snow cover ratio and multimodel soil moisture forecast products of the National Meteorological Information Center through spatiotemporal reconstruction. In addition, precipitation observations of more than 40 meteorological stations, the precipitation products of FY2 satellite observations and the multiyear average temperature observation data of 152 meteorological stations from 2000 to 2010 were integrated to simulate the average temperature data of the Tibetan Plateau, and the permafrost thermal condition classification system was used to classify permafrost into several types: Very cold, Cold, Cool, Warm, Very warm, and Likely thawing. The map shows that, after deducting lakes and glaciers, the total area of permafrost on the Tibetan Plateau is approximately 1,071,900 square kilometers. Verification shows that this map has higher accuracy. It can provide support for future planning and design of frozen soil projects and environmental management.
0 2020-04-29
A total of 137 soil samples of different vegetation types, different altitudes and different terrains were collected from June 2012 to August 2012. The soil layer of each sample point was divided into three layers of 0-10cm, 10-20cm and 20-30cm, with an altitude of 2700-3500m m. The vegetation types were divided into five types: Picea crassifolia forest, Sabina przewalskii, subalpine scrub meadow, grassland and dry grassland. At the same time of sampling, hand-held GPS is used to record the location information and environmental information of each sampling point, including longitude, latitude, altitude, slope, aspect, terrain curvature, vegetation type, soil thickness, maximum root depth, etc. Soil bulk density: The measurement method of soil bulk density is to put the sample into an envelope and dry it in an oven at 105℃ for 24 hours, then take it out and place it for 30 minutes to weigh. The ratio of the weighing result to the volume of the ring cutter is the soil bulk density, and the unit is g/cm3. Soil mechanical composition: hydrometer method is used to measure the soil mechanical composition, which includes the content of soil sand, silt and clay.
0 2020-03-15
This data includes the accessibility of 15 kinds of public facilities and services, such as roads and schools, in the communities of 1280 households at domestic and abroad, as well as the farmers' satisfaction with these public facilities and public services by comparing that with 3 years ago and current status with neighboring village. This data is used to support the analysis of the material capital part of sustainable livelihood. The data was collected by the research group through field survey in 2019. Before collecting the data, the research group and invited experts conducted a pretest and improved the survey questionnaire; Before the formal investigation, the members participating in the data collection were strictly trained; In the formal survey, each questionnaire is checked three times before it is filed. This data is of great value for understanding the physical capital accessibility and satisfaction of rural households in environment-economic fragile areas, and is an important supplement to national and macro data.
0 2021-01-18
This data is the water level data of 2011-2012, which is observed by water level recorder. From July 14 to September 9, 2011, the observation was recordered every five minutes; from June 4 to July 10, 2012, the observation was recordered every ten minutes. The data content is the temperature and atmospheric pressure inside the hole, and the data is the daily scale data. The data shall be opened with HOBO software.
0 2020-03-14
The China Meteorological Forcing Dataset (CMFD) is a high spatial-temporal resolution gridded near-surface meteorological dataset that was developed specifically for studies of land surface processes in China. The dataset was made through fusion of remote sensing products, reanalysis dataset and in-situ observation data at weather stations. Its record starts from January 1979 and keeps extending (currently up to December 2018) with a temporal resolution of three hours and a spatial resolution of 0.1°. Seven near-surface meteorological elements are provided in CMFD, including 2-meter air temperature, surface pressure, specific humidity, 10-meter wind speed, downward shortwave radiation, downward longwave radiation and precipitation rate.
0 2020-11-13
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