Observation of water and heat flux in alpine meadow ecosystem——an observation system of Meteorological elements gradient of A’rou Superstation, 2015-2017

The data set contains the data of the meteorological element gradient observation system of the upper reaches of the heihe hydrological and meteorological observation network's arou super station on January 1, 2015 and December 31, 2017.Site is located in qilian county, qinghai province, arou township grass daban village, the underlying surface is alpine grassland.The longitude and latitude of the observation point are 100.4643E,38.0473N, and the altitude is 3033m.The air temperature, relative humidity and wind speed sensors are installed at 1m, 2m, 5m, 10m, 15m and 25m, respectively. There are 6 floors in total, facing due north.Wind direction sensor is mounted at 10m, facing due north;The barometer is installed at 2m;The tilting rain gauge is installed on the 40m observation tower of the super station in aru.The four-component radiometer is installed at 5m, facing due south;Two infrared thermometers are mounted at 5m, facing due south, with the probe facing down vertically;The photosynthetic effective radiometer was installed at 5m, facing south, and the probe direction was vertical upward.Part of the soil sensor is buried 2m away from the south of the tower, and the soil heat flow plate (self-calibration) (3 pieces) are all buried 6cm underground.Mean soil temperature sensor (tcavr) was buried 2cm and 4cm underground.The soil temperature probe is buried at the surface 0cm and underground 2cm, 4cm, 6cm, 10cm, 15cm, 20cm, 30cm, 40cm, 60cm, 80cm, 120cm, 160cm, 200cm, 240cm, 280cm and 320cm. There are three duplicates in the two layers of 4cm and 10cm.The soil moisture sensor was buried in the ground at 2cm, 4cm, 6cm, 10cm, 15cm, 20cm, 30cm, 40cm, 60cm, 80cm, 120cm, 160cm, 200cm, 240cm, 280cm and 320cm respectively, and there were three replications in the two layers of 4cm and 10cm. Observation items include: wind speed (WS_1m, WS_2m, WS_5m, WS_10m, WS_15m, WS_25m) (unit: m/s), wind direction (WD_10m) (unit: degrees), air temperature and humidity (Ta_1m, Ta_2m, Ta_5m, Ta_10m, Ta_15m, Ta_25m and RH_1m, RH_2m, RH_5m, RH_10m, RH_5m) (unit: Celsius, percentage), air pressure (Press) (unit:Hundred mpa), precipitation (Rain) (unit: mm), the radiation of four component (DR, UR, DLR_Cor, ULR_Cor, Rn) (unit: watts per square meter), the surface radiation temperature (IRT_1, IRT_2) (unit: c), photosynthetic active radiation (PAR) (unit: second micromoles/m2), the average soil temperature (TCAV) (unit: c), soil heat flux (Gs_1, Gs_2, Gs_3) (unit:W/m2), soil moisture (Ms_2cm, Ms_4cm_1, Ms_4cm_2, Ms_4cm_3, Ms_6cm, Ms_10cm_1, Ms_10cm_2, Ms_10cm_3, Ms_15cm, Ms_20cm, Ms_30cm, Ms_60cm, Ms_80cm, Ms_120cm, Ms_160cm, Ms_280cm, Ms_320cm) (unit:Soil temperature (Ts_0cm, Ts_2cm, Ts_4cm_1, Ts_4cm_2, Ts_4cm_3, Ts_6cm, Ts_10cm_1, Ts_10cm_2, Ts_15cm, Ts_20cm, Ts_30cm, Ts_60cm, Ts_80cm, Ts_120cm, Ts_160cm, Ts_280cm, Ts_320cm) (unit:Degrees Celsius. Processing and quality control of observation data :(1) 144 data per day (every 10min) should be ensured.The data of soil temperature and humidity and soil heat flux were missing between September 9, 2015 and September 19, 2015 and between September 30 and October 20, 2015 due to power supply problems.(2) eliminate the moments with duplicate records;(3) data that obviously exceeds the physical significance or the range of the instrument is deleted;(4) the part marked with red letters in the data is questionable data;(5) the format of date and time is uniform, and the date and time are in the same column.For example, the time is: June 10, 2015 10:30;(6) naming rules: AWS+ site name. For information of hydrometeorological network or site, please refer to Li et al. (2013), and for data processing, please refer to Liu et al. (2011).

0 2020-05-03

Bacteria distribution in Tibetan soils (version 1.0) (2015)

The data set of bacterial diversity in Tibetan soil provides the microbial distribution characteristics of the soil surface (0-2 cm) of the Tibetan Plateau. The samples were collected from July 1st to July 15th, 2015, from three types of ecosystems: meadows, grasslands and desert. The soil samples were stored in ice packs and transported to the Ecological Laboratory of the Institute of Tibetan Plateau Research in Beijing. The DNA from the soil was extracted using an MO BIO Power Soil DNA kit. The soil surface samples were stored in liquid nitrogen after collection, shipped to the Sydney laboratory, and then extracted using a Fast Prep DNA kit. The extracted DNA samples adopted 515F (5'-GTGCCAGCMGCCGCGGTAA-3') and 909r (5'-GGACTACHVGGGTWTCTAAT-3') to amplify the 16S rRNA gene fragments. The amplified fragments were sequenced by the Illumina Miseq PE250 method, and the raw data were analyzed using Mothur software. The sequences with poor sequencing quality were first removed; the sequences were sorted, and the chimeric sequences were removed. The similarities between the sequences were then calculated, the sequences with similarities above 97% were clustered into one OTU, and the OTU representative sequence was defined. The OTU representative sequence was compared with the Silva database and identified as level one when the reliability exceeded 80%. The microbial diversities in these data on the Tibetan Plateau were systematically compared, which made them significant to the study of the microbial distribution on the Tibetan Plateau.

0 2020-04-29

Soil salinization observation data in the Syr Dayra River Basin on May and Sep, 2017

(1) Content: This data contains two tables: SyrDarya_201705_part.xlsx and SyrDarya_201709_part.xlsx attribute field: "Point", "Longitude", "Latitude", and "SAL" represent "Point Id", "Longitude", "Latitude", and "Total salt (‰)". (a) SyrDarya_201705_part.xlsx is sample data of the Syr Dayra River Basin in May 2017, which lack of the "PH" field. (b) SyrDarya_201709_part.xlsx is sample data of the Syr Dayra River Basin in September 2017, it contains the "PH" field. (2) According to the standard process of data processing(①Soil Testing Part 16: Method for determination of total water-soluble salt,②Soil Testing Part 2:Method for determination of soil PH), the soil sampling data in the Syr Dayra River Basin are processed, analyzed and sorted out, so as to select the soil sample collection and detection data set in the Syr Dayra River Basin. (3) This data is soil sampling data, which can be used to monitor soil salinization and other studies.

0 2020-04-23

Hourly meteorological forcing & land surface state dataset of Tibet Plateau with 10 km spatial resolution (2000-2010)

The near surface atmospheric forcing and surface state dataset of the Tibetan Plateau was yielded by WRF model, time range: 2000-2010, space range: 25-40 °N, 75-105 °E, time resolution: hourly, space resolution: 10 km, grid number: 150 * 300. There are 33 variables in total, including 11 near surface atmospheric variables: temperature at 2m height on the ground, specific humidity at 2m height on the ground, surface pressure, latitudinal component of 10m wind field on the ground, longitudinal component of 10m wind field on the ground, proportion of solid precipitation, cumulative cumulus convective precipitation, cumulative grid precipitation, downward shortwave radiation flux at the surface, downward length at the surface Wave radiation flux, cumulative potential evaporation. There are 19 surface state variables: soil temperature in each layer, soil moisture in each layer, liquid water content in each layer, heat flux of snow phase change, soil bottom temperature, surface runoff, underground runoff, vegetation proportion, surface heat flux, snow water equivalent, actual snow thickness, snow density, water in the canopy, surface temperature, albedo, background albedo, lower boundary Soil temperature, upward heat flux (sensible heat flux) at the surface and upward water flux (sensible heat flux) at the surface. There are three other variables: longitude, latitude and planetary boundary layer height.

0 2020-04-21

HiWATER: Dataset of hydrometeorological observation network (cosmic-ray soil moisture of Daman Superstation, 2013)

This dataset includes the observational data from 20 September, 2012, through 31 December, 2013, collected by the Cosmic-ray Soil Moisture Observation System (COSMOS), called crs, which waslocated at 100.372° E, 38.856° N and 1557 m above sea level,near the Daman Superstation in the Daman Irrigation District, Zhangye City, Gansu Province. The land cover in the footprint was a maize crop. The bottom of the probe was 0.5 m above the ground, and the sampling interval was 1 hour. The raw COSMOS data include the following: battery (Batt, V), temperature (T, ℃), relative humidity (RH, %), air pressure (P, hPa), fast neutron counts (N1C, counts per hour), thermal neutron counts (N2C, counts per hour), the sample time of fast neutrons (N1ET, s), and the sample time of thermal neutrons (N2ET, s). The distributed data include the following variables: Date, Time, P, N1C, N1C_cor (corrected fast neutron counts) and VWC (volume soil moisture, %), which were processed as follows: 1) Quality control Data were deleted and replaced by -6999 when (a) the battery voltage was less than 11.8 V, (b) the relative humidity exceeded 80% inside the probe box, (c) the samping durationwere less than 59 minutes or greater than 61 minutes and (d) the neutron count differed from the previous value by more than 20%. 2) Air pressure correction An air pressure correction was applied to the quality-controlled raw data according to the equation containedin the equipment manual. 3) Calibration After the quality control and corrections were applied, the soil moisture was calculated using the equation in Desilets et al. (2010), where N0 is the neutron counts above dry soil and the other variables are fitted constants that define the shape of the calibration function. Here, the parameter N0 was calibrated using the in situ observed soil moisture recordedby SoilNET within the footprint. 4) Soil moisture computation Based on the calibrated N0 and corrected N1C, the hourly soil moisture was computed using the equation specified in the equipment manual. For more information, please refer to Liu et al. (2018) (for hydrometeorological observation network or sites information), Zhu et al. (2015) (for data processing) in the Citation section.

0 2020-04-10

HiWATER: Dataset of hydrometeorological observation network (cosmic-ray soil moisture of Daman Superstation, 2017)

The data set contains observation data of cosmic-ray instrument (crs) from January 1, 2017 to December 31, 2017. The site is located in the farmland of Daman Irrigation District, Zhangye, Gansu Province, and the underlying surface is cornfield. The latitude and longitude of the observation site is 100.3722E, 38.8555N, the altitude is 1556 meters. The bottom of the instrument probe is 0.5 meter from the ground, and the sampling frequency is 1 hour. The original observation items of the cosmic-ray instrument include: voltage Batt (V), temperature T (°C), relative humidity RH (%), air pressure P (hPa), fast neutron number N1C (number / hour), thermal neutron number N2C (number / hour), fast neutron sampling time N1ET (s) and thermal neutron sampling time N2ET (s). The data was released after being processed and calculated. The data includes: Date Time, P (pressure hPa), N1C (fast neutrons one/hour), N1C_cor (pressure-corrected fast neutrons one/hour) and VWC ( soil water content %), it was processed mainly by the following steps: 1) Data Screening There are four criteria for data screening: (1) Eliminating data with a voltage less than or equal to 11.8 volts ; (2) Eliminating data with a relative humidity greater than or equal to 80%; (3) Eliminating data with a sampling time interval not within 60 ± 1 minute; (4) Eliminating data with fast neutrons that vary by more than 200 in one hour. In addition, missing data is supplemented with -6999. 2) Air Pressure Correction The original data is corrected by air pressure according to the fast neutron pressure correction formula mentioned in the instrument manual, and the corrected fast neutron number N1C_cor is obtained. 3) Instrument Calibration In the process of calculating soil moisture, it is necessary to calibrate the N0 in the calculation formula. N0 is the number of fast neutrons under the situation with low antecedent soil moisture . Usually, soil samples in the source area are used to obtain measured soil moisture (or obtained by relatively dense soil moisture wireless sensors) θm (Zreda et al. 2012) and the fast neutron correction data N in corresponding time periods, then NO can be obtained by reversing the formula. Here, the instrument is calibrated according to the Soilnet soil moisture data in the source region of the instrument, and the relationship between the soil volumetric water content θv and the fast neutron is established. The data of June 26-27, and July 16-17, respectively, which have obvious differences in dry and wet conditions, were selected. The data from June 26 to 27 showed low soil moisture content, so the average of the three values of 4 cm, 10 cm and 20 cm was used as the calibration data, and the variation range was 22% to 30%; meanwhile , the data from July 16 to 17 showed high soil moisture content, so the average of the two values of 4cm and 10 cm was used as the calibration data, and the variation range was 28% - 39%, and the final average N0 was 3597. 4) Soil Moisture Calculation According to the formula, the hourly soil water content data is calculated. Please refer to Liu et al. (2018) for information of hydrometeorological network or site, and Zhu et al. (2015) for observation data processing.

0 2020-04-10

HiWATER: Dataset of hydrometeorological observation network (cosmic-ray soil moisture of Daman Superstation, 2016)

The data set contains cosmic ray instrument (CRS) observations from January 1, 2016 to December 31, 2016.The station is located in gansu province zhangye city da man irrigated area farmland, under the surface is corn field.The longitude and latitude of the observation point are 100.3722e, 38.8555n, and 1556m above sea level. The bottom of the instrument probe is 0.5m from the ground, and the sampling frequency is 1 hour. Original observations of cosmic ray instruments include: voltage Batt (V), temperature T (c), relative humidity RH (%), pressure P (hPa), fast neutron number N1C (hr), thermal neutron number N2C (hr), fast neutron sampling time N1ET (s) and thermal neutron sampling time N2ET (s).The data published are processed and calculated. The data headers include Date Time, P (pressure hPa), N1C (fast neutron number/hour), N1C_cor (fast neutron number/hour with revised pressure) and VWC (soil volume moisture content %). The main processing steps include: 1) data filtering There are four criteria for data screening :(1) data with voltage less than and equal to 11.8 volts are excluded;(2) remove the data of air relative humidity greater than and equal to 80%;(3) data whose sampling interval is not within 60±1 minute are excluded;(4) the number of fast neutrons removed changed by more than 200 in one hour compared with that before and after.In addition, the missing data was supplemented by -6999. 2) air pressure correction According to the fast neutron pressure correction formula mentioned in the instrument instruction manual, the original data were revised to obtain the revised fast neutron number N1C_cor. 3) instrument calibration In the process of calculating soil moisture, N0 in the calculation formula should be calibrated.N0 is the number of fast neutrons under the condition of soil drying. The measured soil moisture (or through relatively dense soil moisture wireless sensor) m (Zreda et al. Here, according to Soilnet soil water data in the source area of the instrument, the instrument was calibrated to establish the relationship between soil volumetric water content v and fast neutrons.Selection of dry and wet conditions are the obvious difference of June 26, 2012-27 and July 16-17, four days of data, including June 26-27 rate data showed that soil moisture is small, so the selection of 4 cm, 10 and 20 cm as the rate of the three values of average data, its range is 22% 30%, and July 16-17 rate data showed that soil moisture is bigger, so select 4 cm and 10 cm as two value average rate data, the range of 28% - 39%, final N0 an average of 3597. 4) soil moisture calculation According to the formula, the hourly soil water content data were calculated. Please refer to Liu et al. (2018) for information of hydrometeorological network or site, and Zhu et al. (2015) for observation data processing.

0 2020-04-10

HiWATER: Dataset of Hydrometeorological observation network (cosmic-ray soil moisture of Daman Superstation, 2015)

The data set contains cosmic ray instrument (CRS) observations from January 1, 2015 to December 31, 2015.The station is located in dachman super station, dachman irrigation district, zhangye city, gansu province.The longitude and latitude of the observation point are 100.3722e, 38.8555n, and 1556m above sea level. The bottom of the instrument probe is 0.5m from the ground, and the sampling frequency is 1 hour. Original observations of cosmic ray instruments include: voltage Batt (V), temperature T (c), relative humidity RH (%), pressure P (hPa), fast neutron number N1C (hr), thermal neutron number N2C (hr), fast neutron sampling time N1ET (s) and thermal neutron sampling time N2ET (s).The data published are processed and calculated. The data headers include Date Time, P (pressure hPa), N1C (fast neutron number/hour), N1C_cor (fast neutron number/hour with revised pressure) and SW (soil volume moisture content %). The main processing steps include: 1) data filtering There are four criteria for data screening :(1) data with voltage less than and equal to 11.8 volts are excluded;(2) remove the data of air relative humidity greater than and equal to 80%;(3) data whose sampling interval is not within 60±1 minute are excluded;(4) the number of fast neutrons removed changed by more than 200 in one hour compared with that before and after.In addition, the missing data was supplemented by -6999. 2) air pressure correction According to the fast neutron pressure correction formula mentioned in the instrument instruction manual, the original data were revised to obtain the revised fast neutron number N1C_cor. 3) instrument calibration In the process of calculating soil moisture, N0 in the calculation formula should be calibrated.N0 is the number of fast neutrons under the condition of soil drying. The measured soil moisture (or through relatively dense soil moisture wireless sensor) m (Zreda et al. Here, according to Soilnet soil water data in the source area of the instrument, the instrument was calibrated to establish the relationship between soil volumetric water content v and fast neutrons.Selected dry wet condition are the obvious difference of June 26-27 and July 16-17, four days of data, including June 26-27 rate data showed that soil moisture is small, so the selection of 4 cm, 10 and 20 cm the three values of average as calibration data, the change range of 22% to 30%, and July 16-17 rate data showed that soil moisture is bigger, so select 4 cm and 10 cm as two value average rate data, the range of 28% - 39%, final N0 an average of 3597. 4) soil moisture calculation According to the formula, the hourly soil water content data were calculated. Please refer to Liu et al. (2018) for information of hydrometeorological network or site, and Zhu et al. (2015) for observation data processing.

0 2020-04-10

HiWATER: Dataset of hydrometeorological observation network (cosmic-ray soil moisture of Daman Superstation, 2014)

This data set contains cosmic ray instrument (CRS) observations from January 1, 2014 to December 31, 2014.The station is located in gansu province zhangye city da man irrigated area farmland, under the surface is corn field.The longitude and latitude of the observation point are 100.3722e, 38.8555n, and 1556m above sea level. The bottom of the instrument probe is 0.5m from the ground, and the sampling frequency is 1 hour. The original observations of the cosmic ray instrument (CRS1000B) included: voltage Batt (V), temperature T (c), relative humidity RH (%), pressure P (hPa), fast neutron number N1C (hr), thermal neutron number N2C (hr), fast neutron sampling time N1ET (s) and thermal neutron sampling time N2ET (s).The data published are processed and calculated. The data headers include Date Time, P (pressure hPa), N1C (fast neutron number/hour), N1C_cor (fast neutron number/hour with revised pressure) and VWC (soil volume moisture content %). The main processing steps include: 1) data filtering There are four criteria for data screening :(1) data with voltage less than and equal to 11.8 volts are excluded;(2) remove the data of air relative humidity greater than and equal to 80%;(3) data whose sampling interval is not within 60±1 minute are excluded;(4) the number of fast neutrons removed changed by more than 200 in one hour compared with that before and after.In addition, the missing data was supplemented by -6999. 2) air pressure correction According to the fast neutron pressure correction formula mentioned in the instrument instruction manual, the original data were revised to obtain the revised fast neutron number N1C_cor. 3) instrument calibration In the process of calculating soil moisture, N0 in the calculation formula should be calibrated.N0 is the number of fast neutrons under the condition of soil drying. The measured soil moisture (or through relatively dense soil moisture wireless sensor) m (Zreda et al. (1) Where m is mass water content, N is the number of fast neutrons after revision, N0 is the number of fast neutrons under dry conditions, a1=0.079, a2=0.64, a3=0.37 and a4=0.91 are constant terms. Here, the instrument was calibrated according to Soilnet soil water data in the source area of the instrument, and the relationship between soil volumetric water content (v) and fast neutrons was established according to the actual situation. In formula (1), m was replaced by v.Selected dry wet condition are the obvious difference of June 26-27 June and July 16 - July 17 four days of data, including June 26-27 rate data showed that soil moisture is small, so the selection of 4 cm, 10 and 20 cm as the rate of the three values of average data, its range is 22% 30%, and July 16 - July 17 rate data showed that soil moisture is bigger, so select 4 cm and 10 cm as two value average rate data, the range of 28% - 39%,Finally, the average values of crs_a and crs_b, N0, were 3252 and 3597, respectively. 4) soil moisture calculation According to formula (1), the hourly soil water content data is calculated. Please refer to Liu et al. (2018) for information of hydrometeorological network or site, and Zhu et al. (2015) for observation data processing.

0 2020-04-10

Dataset of parameterization scheme of distributed eco-hydrological model

This data set is a database for the application of SWAT Model in the upper reaches of Heihe River and the source area of the Yellow River, mainly including soil and vegetation, and DEM. There are many parameters involved in soil and vegetation, including conventional soil physical and chemical parameters, vegetation parameters and biomass parameters. The determination method of parameter value includes sampling measurement, literature and other related databases, as well as calculation through related software. As the soil and vegetation database of SWAT model involves comprehensive parameters, most of them can also be used as reference for other ecological and hydrological models driving data besides SWAT model.

0 2020-04-09