The dataset of soil moisture observations was obtained by the cutting ring (50cm^3) and ML2X Soil Moisture Tachometer in the Linze station foci experimental area. Surface soil (0-5cm) was measured 2-3 times in 40 subplots of the west-east desert strip on May 24, 25, 28, Jun. 27 and Jul. 11, 2008, 2-4 times in 9 subplots of north-south strip on May 24, 25, 28, Jun. 27 and Jul. 11, 17 times from P1 to P6 strips on Jul. 4 and 8, nine times along LY06 strip on Jun. 6, 15, 29 and Jul. 11, LY07 strip on May 30, Jun. 6, 10, 15, 29 and Jul. 11 and LY08 strip on May 30, Jun. 6 and 10, and once by the cutting ring and three times by ML2X Soil Moisture Tachometer in Wulidun farmland quadrates on May 24, 25, 28, Jun. 29 and Jul. 11. 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.
0 2019-09-15
This dataset contains the flux measurements from the Zhangye wetland station eddy covariance system (EC) in the flux observation matrix from 25 June to 26 September, 2012. The site (100.44640° E, 38.97514° N) was located in a wetland surface, which is near Zhangye city, Gansu Province. The elevation is 1460.00 m. The EC was installed at a height of 5.2 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 (Gill&Li7500A) was 0.25 m. Raw data acquired at 10 Hz were processed using the Eddypro post-processing software (Li-Cor Company, http://www.licor.com/env/products/ eddy_covariance/software.html), including spike detection, lag correction of H2O/CO2 relative to the vertical wind component, sonic virtual temperature correction, angle of attack 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.
0 2019-09-15
Water scarcity，food crises and ecological deterioration caused by drought disasters are a direct threat to food security and socio-economic development. Improvement of drought disaster risk assessment and emergency management is now urgently required. This article describes major scientific and technological progress in the field of drought disaster risk assessment. Drought is a worldwide natural disaster that has long affected agricultural production as well as social and economic activities. Frequent droughts have been observed in the Belt and Road area, in which much of the agricultural land is concentrated in fragile ecological environment. Soil relative humidity index is one of the indicators to characterize soil drought and can directly reflect the status of crops' available water.
0 2020-03-10
The data set contains meteorological elements observation data of zhangye station in the middle reaches of heihe hydrometeorological observation network from January 1, 2017 to December 31, 2017.The site is located in zhangye national wetland park in gansu province.The latitude and longitude of the observation point is 100.4464E, 38.9751N, and altitude is 1460m.Air temperature and relative humidity sensors are set up at 5m and 10m, facing due north.The barometer is installed at 2m;The inverted bucket rain gauge is installed at 10m;The wind speed sensor is set up at 5m and 10m, and the wind direction sensor is set up at 10m, facing due north.The four-component radiometer is installed at 6m, facing due south;The two infrared thermometers are installed at the position of 6m, facing south, and the probe is facing vertically downward.The soil temperature probe is buried at 0cm on the surface and 2cm, 4cm, 10cm, 20cm and 40cm underground, in the south due to 2m from the meteorological tower.The soil hot flow plates (3) are successively buried in the ground 6cm;Four photosynthetic radiometers are installed above and inside the canopy respectively. The upper part of the canopy is installed at 6m (one probe vertically up and one probe vertically down), and the upper part of the canopy is installed at 0.25m (one probe vertically up and one probe vertically down), facing due south. Observation items are: air temperature and humidity (Ta_5m RH_5m Ta_10m, RH_10m) (unit: c, percentage), pressure (Press) (unit: hundred mpa), precipitation (Rain) (unit: mm), wind speed (WS_5m, WS_10m) (unit: m/s), wind (WD_10m) (unit: degrees), 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:Degrees Celsius), soil heat flux (Gs_1, Gs_2, Gs_3) (unit: watts per square meter), soil temperature (Ts_0cm Ts_2cm Ts_4cm, Ts_10cm, Ts_20cm, Ts_40cm) (unit: c), the canopy on the up and down photosynthetic active radiation (PAR_U_up, PAR_U_down) (unit: second micromoles/m2) and up and down under canopy photosynthetic active radiation (PAR_D_up, PAR_D_down) (unit: second micromoles/m2). Processing and quality control of observation data :(1) ensure 144 data per day (every 10min). If data is missing, it will be marked by -6999;Due to the power supply problem in January, the data was intermittently wrong;(2) eliminate the moments with duplicate records;(3) data that is obviously beyond the physical meaning or the range of the instrument is deleted;(4) the part marked by red letter in the data is the data in question;(5) the format of date and time is uniform, and the date and time are in the same column.For example, the time is: 2017-6-1010:30;(6) the naming rule is: AWS+ site name. Please refer to Li et al. (2013) for hydrometeorological network or site information, and Liu et al. (2011) for observation data processing.
0 2020-03-05
The time coverage of this data is (1961-1990). The station data set includes 222 stations of precipitation data and 202 stations of temperature data. In order to fill the meteorological data in the surrounding area of Xinjiang in the study area, this data set uses the Central Asia Temperature and Precipitation Data (1879-2003), and some site data of Pakistan, Afghanistan, Mongolia (Global Historical Climate Network) and CRU dataset, in addition to the Xinjiang Meteorological Data Set, Qinghai, and Gansu Daily Data. There is a large amount of missing data in the used dataset, which will affect the accuracy of the grid data generated by the extrapolation method. Therefore, this article deletes sites with consecutive missing years, and uses sites adjacent to the site to replace missing sites with fewer years (less than 3 years). For sites where the spatial distribution of sites is too sparse, BP neural network is used to fit and reconstruct sites with severely missing data, such as Tazhong (51747), Andi Township (51848), and Hangya (51915). Based on the pre-processed data, the interpolation method of this data set is the Cressman objective analysis method. The monthly average temperature and monthly precipitation are extrapolated to the study area, and the grid period observation data with a horizontal resolution of 0.5 ° is obtained. This data contains two files: temperature data of xinjiangtemp.nc and precipitation data of xinjiangpre2.nc.
0 2020-07-15
The data set contains the observation data of the eddy covariance system of Sidaoqiao superstation which is located along the lower reaches of the Heihe Hydrometeorological observation network, and the data set covers data from January 1, 2017 to December 31, 2017. The station is located in Sidao Bridge, Ejina Banner, Inner Mongolia, and the underlying surface is Tamarix. The latitude and longitude of the observation station is 101.1374E, 42.0012N, and the altitude is 873 m. The height of the eddy covariance system is 8 meters, the sampling frequency is 10Hz, the ultrasonic orientation is positive north, and the distance between the ultrasonic wind speed and temperature monitor (CSAT3) and the CO2/H2O analyzer (Li7500) is 15cm. The original observation data of the eddy covariance system is 10 Hz, and the released data is a 30-minute data processed by Eddypro software. The main steps of the processing include: outlier eliminating, delay time correction, coordinates rotation (secondary coordinates rotation), frequency response correction, ultrasonic virtual temperature correction and density (WPL) correction, etc. Meanwhile, the quality evaluation of each flux value was performed,mainly includes atmospheric stability (Δst) test and turbulence similarity (ITC) test. The 30-min flux value output of Eddypro software was also screened: (1) Data from the instrument error was eliminated; (2) Data obtained with one hour before and after precipitation was removed; (3) Data with a deletion rate greater than 10% of the 10 Hz raw data every 30 minutes was eliminated; (4) Observation data of weak turbulence at night (u* less than 0.1 m/s) was excluded. The average period of observation data is 30 minutes, 48 data per day, and the missing data is marked as -6999. The data was missing due to Li7500 calibration of the eddy system on April 7 and 8; the suspicious data caused by instrument drift and other reasons was marked by red fonts. Published observation data include: date/time Date/Time, wind direction(°), horizontal wind speed(m/s), lateral wind speed standard deviation(m/s), ultrasonic virtual temperature (°C), water vapor density (g/m3), carbon dioxide concentration(mg/m3), friction velocity (m/s), length (m), sensible heat flux(W/m2), latent heat flux (W/m2), carbon dioxide flux (mg/(m2s)), sensible heat flux quality identification QA_Hs, latent heat flux quality identification QA_LE, carbon dioxide flux quality identification QA_Fc. The quality identification of sensible heat, latent heat, and carbon dioxide flux is divided into three levels (quality mark 0: (Δst <30, ITC<30); 1: (Δst <100, ITC<100); the rest is 2). The meaning of the data time, such as 0:30 represents an average data of 0:00-0:30; the data is stored in *.xls format. For hydrometeorological network or station information, please refer to Li et al. (2013). For observation data processing, please refer to Liu et al. (2011).
0 2019-09-11
This dataset includes data recorded by the Hydrometeorological observation network obtained from the automatic weather station (AWS) at the Bajitan Gobi desert station between 21 September, 2012, and 31 December, 2013. The site (100.304° E, 38.915° N) was located on a Gobi desert surface in the Bajitan, which is near Zhangye city, Gansu Province. The elevation is 1562 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 (010C; 5 and 10 m, north), wind direction profile (020C; 10 m, north), air pressure (PTB110; 2 m), rain gauge (TE525M; 10 m), four-component radiometer (CNR1; 6 m, south), two infrared temperature sensors (IRTC3; 6 m, south, vertically downward), soil heat flux (HFT3; 3 duplicates, -0.06 m, 2 m in the south), soil temperature profile (AV-10T; 0, -0.02, -0.04, -0.1, -0.2, -0.4, -0.6, and -1 m), and soil moisture profile (ECh2o-5; -0.02, -0.04, -0.1, -0.2, -0.4, -0.6 and -1 m). 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, Ts_40 cm, Ts_60 cm and Ts_100 cm) (℃), and soil moisture (Ms_2 cm, Ms_4 cm, Ms_10 cm, Ms_20 cm, Ms_40 cm, Ms_60 cm and Ms_100 cm) (%, volumetric water content). 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 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 Liu et al. (2018) (for hydrometeorological observation network or sites information), Liu et al. (2011) (for data processing) in the Citation section.
0 2020-04-10
This data set contains the data of meteorological element gradient observation system of dashman superstation in the middle reaches of heihe hydrometeorological observation network from January 1, 2016 to December 31, 2016.The station is located in the farmland of daman irrigation district of zhangye city, gansu province.The longitude and latitude of the observation point are 100.3722e, 38.8555n and 1556m above sea level.The wind speed/direction, air temperature and relative humidity sensors are located at 3m, 5m, 10m, 15m, 20m, 30m and 40m respectively, with a total of 7 layers, facing due north.The barometer is installed at 2m;The tilting bucket rain gauge was installed at about 8m on the west side of the tower, with a height of 2.5m;The four-component radiometer is installed at 12m, facing due south;Two infrared thermometers are installed at 12m, facing due south and the probe facing vertically downward.Soil heat flow plate (self-calibration formal) (3 pieces) were buried in the ground 6cm in turn, 2m away from the tower body due south, two of which (Gs_2 and Gs_3) were buried between the trees, and one (Gs_1) was buried under the plants.The mean soil temperature sensor TCAV is buried 2cm and 4cm underground, facing due south and 2m away from the tower body.The soil temperature probe is buried at 0cm of the surface and 2cm, 4cm, 10cm, 20cm, 40cm, 80cm, 120cm and 160cm underground, 2m to the south of the meteorological tower.The soil water sensor is buried 2cm, 4cm, 10cm, 20cm, 40cm, 80cm, 120cm and 160cm underground, 2m to the south of the meteorological tower.The photosynthetic effective radiometer is installed at 12m with the probe facing vertically upward.Four other photosynthetically active radiometers were installed above and inside the canopy, 12m above the canopy (one probe vertically up and one probe vertically down), and 0.3m above the canopy (one probe vertically up and one probe vertically down), facing due south. The observation items are: wind speed (WS_3m, WS_5m, WS_10m, WS_15m, WS_20m, WS_30m, WS_40m) (unit: m/s), wind direction (WD_3m, WD_5m, WD_10m, WD_15m, WD_20m, WD_30m, WD_40m) (unit:Air temperature and humidity (Ta_3m, Ta_5m, Ta_10m, Ta_15m, Ta_20m, Ta_30m, Ta_40m and RH_3m, RH_5m, RH_10m, RH_15m, RH_20m, RH_30m, RH_40m) (unit: Celsius, percentage), air pressure (Press) (unit: hpa), precipitation (Rain) (unit: mm), four-component radiation (DR, UR, DLR_Cor, ULR_Cor, Rn) (unit:Watts/m2), surface radiant temperature (IRT_1, IRT_2) (unit: Celsius), average soil temperature (TCAV) (unit: Celsius), soil heat flux (Gs_1, Gs_2, Gs_3) (unit: watts/m2), soil moisture (Ms_2cm, Ms_4cm, Ms_10cm, Ms_20cm, Ms_40cm, Ms_80cm, Ms_120cm, Ms_160cm) (unit:Soil temperature (Ts_0cm, Ts_2cm, Ts_4cm, Ts_10cm, Ts_20cm, Ts_40cm, Ts_80cm, Ts_120cm, Ts_160cm)Mmol/m s) and the upward and downward photosynthetic effective radiation (PAR_D_up, PAR_D_down) under the canopy (in mmol/m s). Processing and quality control of observed data :(1) ensure 144 pieces of data every day (every 10min), and mark by -6999 in case of data missing;The sensor in the soil part was adjusted and the data could not be used;(2) excluding the time 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 letter in the data is the data in question;(5) date and time have the same format, and date and time are in the same column.For example, the time is: 2016-6-10-10:30;(6) the naming rule is: AWS+ site name. For information of hydrometeorological network or station, please refer to Liu et al. (2018), and for observation data processing, please refer to Liu et al. (2011).
0 2020-04-10
Zhangye basin mainly includes 20 irrigation areas. Under the restriction of water diversion, the surface water consumption of the irrigation area is under control, but the groundwater exploitation is increased, resulting in the groundwater level drop in the middle reaches, resulting in potential ecological environment risks. Due to the complex and frequent exchange of surface water and groundwater in the study area, it is possible to realize the overall water resource saving by optimizing the utilization ratio of surface water and groundwater in each irrigation area. In this project, on the premise of not changing the water demand of the middle reaches irrigation area, the two problems of maximizing the outflow of Zhengyi Gorge (given groundwater reserve constraint) and maximizing the outflow of Zhengyi Gorge (given groundwater reserve constraint) are studied.
0 2020-06-11
This dataset includes component temperatures measured by the thermal infrared (TIR) radiometers at the Mixed Forest and Sidaoqiao stations between 22 July, 2014 and 19 July, 2016. The Mixed Forest (101.1335 °E, 41.9903 °N, 874 m.a.s.l.) and Sidaoqiao (101.1374 °E, 42.0012 °N, 873 m.a.s.l.) stations were located in the downstream of the Heihe River basin, Dalaihubu Town, Ejin Banner, Inner Mongolia. At the Mixed Forest station, two TIR radiometers (SI-111, Apogee Instruments Inc., USA) connected to a data logger (CR800, Campbell Scientific Inc., USA) measured component temperatures of the sunlit canopy and shaded canopy. TIR radiometers were mounted horizontally at 5 m height on iron rods just south and north of a tree and pointed to its canopy. The distance from the sensor to the canopy was ~1 m. At the Sidaoqiao station, two SI-111 TIR radiometers connected to a CR800 data logger measured component temperatures of the soil and shrub. The first sensor pointed from 2 m height under a viewing zenith angle of 45° to bare soil; the second sensor was mounted at 1-m height and pointed horizontally into the shrub canopy.
0 2020-10-13
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