China meteorological assimilation datasets for the SWAT model - soil temperature version 1.0 (2009-2013)

CMADS (The China Meteorological Assimilation Driving Datasets for The SWAT model) The soil temperature component (hereinafter referred to as cmads-st) USES The China Meteorological Administration Land Data Assimilation System [CLDAS] to force The common Land surface model3.5 [CLM3.5]) (Community Land model, numerical simulation of Land surface, circulation 10 spin - up simulation, get basic stability model initial field, and obtain high space-time resolution of soil temperature data sets, eventually hierarchical data model is utilized to extract, quality control, a nested loop, re-sampling, and a variety of technologies such as bilinear interpolation method is finally established. Cmads-st series data set space covers the whole east Asia (0 ° n-65 ° N, 60 ° e-160 ° E), the spatial resolution is respectively cmads-st V1.0 version: 1/3 °, cmads-st V1.1 version: 1/4 °, cmads-st V1.2 version: 1/8 ° and cmads-st V1.3 version:The above resolutions are daily (the basic resolution of the soil temperature component output in CLM3.5 mode is 1/16°, which ensures the highest resolution of the cmads-st data set is 1/16°). The time scale is 2009-2013.The data set published on this page is the cmads-st V1.0 data set (spatial resolution :1/3°).Temporal resolution: daily.Space coverage: east Asia (0 ° n-65 ° N, 60 ° e-160 ° E).Number of stations: 58,500.Supply factors: the average daily soil temperature of 10 layers (the depth of node hierarchy is in order: the first layer :0.00710063521m; the second layer :0.0279249996m; the third layer :0.0622585751m; the fourth layer :0.118865065m; the fifth layer :0.2121934m; the sixth layer :0.3660658m; the seventh layer :0.619758487m; the eighth layer :1.03802705m; the ninth layer :1.72763526m;Floor 10 :2.8646071m).Provide data format: TXT. The path of the cmads-st V1.0 soil temperature data set is: CMADS - ST - V1.0\2009 \ layer1 V1.0\2009 \ layer10 to CMADS - ST CMADS - ST - V1.0\2010 \ layer1 V1.0\2010 \ layer10 to CMADS - ST CMADS - ST - V1.0\2011 \ layer1 V1.0\2011 \ layer10 to CMADS - ST CMADS - ST - V1.0\2012 \ layer1 V1.0\2012 \ layer10 to CMADS - ST CMADS - ST - V1.0\2013 \ layer1 V1.0\2013 \ layer10 to CMADS - ST Cmads-st V1.0 subset file path and file name description Where, daily soil temperature (ten layers) is shown in layer1-layer10\.Are located in the following directories (take 2009 as an example): \2009\layer1\ 2009 layer1 (0.00710063521m) soil temperature directory \2009\layer2\ 2009 layer2 (0.0279249996m) soil temperature directory \2009\layer3\ 2009 layer3 (0.0622585751m) soil temperature catalogue \2009\layer4\ 2009 layer4 (0.118865065m) soil temperature catalogue \2009\layer5\ 2009 layer5 (0.2121934m) soil temperature catalogue \2009\layer6\ 2009 layer6 (0.3660658m) soil temperature catalogue \2009\layer7\ 2009 layer7 (0.619758487m) soil temperature directory \2009\layer8\ 2009 layer8 (1.03802705m) soil temperature catalogue \2009\layer9\ 2009 layer9 (1.72763526m) soil temperature catalogue \2009\layer10\ 2009 10th layer (2.8646071m) soil temperature catalogue

0 2020-07-30

Field soil survey and analysis data in the upper reaches of Heihe River Basin (2013-2014)

The dataset is the field soil measurement and analysis data of the upstream of Heihe River Basin from 2013 to 2014, including soil particle analysis, water characteristic curve, saturated water conductivity, soil porosity, infiltration analysis, and soil bulk density I. Soil particle analysis 1. The soil particle size data were measured in the particle size laboratory of the Key Laboratory of the Ministry of Education, West Ministry of Lanzhou University.The measuring instrument is Marvin laser particle size meter MS2000. 2. Particle size data were measured by laser particle size analyzer.As a result, sample points with large particles cannot be measured, such as D23 and D25 cannot be measured without data.Plus partial sample missing. Ii. Soil moisture characteristic curve 1. Centrifuge method: The unaltered soil of the ring-cutter collected in the field was put into the centrifuge, and the rotor weight of each time was measured with the rotation speed of 0, 310, 980, 1700, 2190, 2770, 3100, 5370, 6930, 8200 and 11600 respectively. 2. The ring cutter is numbered from 1 to the back according to the number. Since three groups are sampled at different places at the same time, in order to avoid repeated numbering, the first group is numbered from 1, the second group is numbered from 500, and the third group is numbered from 1000.It's consistent with the number of the sampling point.You can find the corresponding number in the two Excel. 3. The soil bulk density data in 2013 is supplementary to the sampling in 2012, so the data are not available at every point.At the same time, the soil layer of some sample points is not up to 70 cm thick, so the data of 5 layers cannot be taken. At the same time, a large part of data is missing due to transportation and recording problems.At the same time, only one layer of data is selected by random points. 4. Weight after drying: The drying weight of some samples was not measured due to problems with the oven during the experiment. 3. Saturated water conductivity of soil 1. Description of measurement method: The measurement method is based on the self-made instrument of Yiyanli (2009) for fixing water hair.The mariot bottle was used to keep the constant water head during the experiment.At the same time, the measured Ks was finally converted to the Ks value at 10℃ for analysis and calculation.Detailed measurement record table refer to saturation conductivity measurement description.K10℃ is the data of saturated water conductivity after conversion to 10℃.Unit: cm/min. 2. Data loss explanation: The data of saturated water conductivity is partly due to the lack of soil samples and the insufficient depth of the soil layer to obtain the data of the 4th or 5th layer 3. Sampling time: July 2014 4. Soil porosity 1. Use bulk density method to deduce: according to the relationship between soil bulk density and soil porosity. 2. The data in 2014 is supplementary to the sampling in 2012, so the data are not available at every point.At the same time, the soil layer of some sample points is not up to 70 cm thick, so the data of 5 layers cannot be taken. At the same time, a large part of data is missing due to transportation and recording problems.At the same time, only one layer of data is selected by random points. 5. Soil infiltration analysis 1. The infiltration data were measured by the "MINI DISK PORTABLE specific vector INFILTROMETER".The approximate saturation water conductivity under a certain negative pressure is obtained.The instrument is detailed in website: http://www.decagon.com/products/hydrology/hydraulic-conductivity/mini-disk-portable-tension-infiltrometer/ 2.D7 infiltration tests were not measured at that time because of rain. Vi. Soil bulk density 1. The bulk density of soil in 2014 refers to the undisturbed soil taken by ring cutter based on the basis of 2012. 2. The soil bulk density is dry soil bulk density, which is measured by drying method.The undisturbed ring-knife soil samples collected in the field were kept in an oven at 105℃ for 24 hours, and the dry weight of the soil was divided by the soil volume (100 cubic centimeters). 3. Unit: G /cm3

0 2020-07-30

Data set of plant physiological indexes and soil water, salt and nutrient in the lower reaches of Tarim River (2000-2006)

In the ecosystem, soil and vegetation are two interdependent factors. Plants affect soil and soil restricts vegetation. On the one hand, there are a lot of nutrients such as carbon, nitrogen and phosphorus in the soil. On the other hand, the availability of soil nutrients plays a key role in the growth and development of plants, directly affecting the composition and physiological activity of plant communities, and determining the structure, function and productivity level of ecosystems. Soil moisture content (or soil moisture content): In the 9 sections from Daxihaizi to taitema lake in the lower reaches of Tarim River, plant sample plots are set in the direction perpendicular to the river channel according to the arrangement of groundwater level monitoring wells. Dig one soil profile in each sample plot, collect one soil sample from 0-5 cm, 5-15 cm, 15-30 cm, 30-50 cm, 50-80 cm, 80-120 cm and 120-170cm soil layers from bottom to top in each profile layer, each soil sample is formed by multi-point sampling and mixing of corresponding soil layers, each soil layer uses aluminum boxes to collect soil samples, weighs wet weight on site, and measures soil moisture content (or soil moisture content) by drying method. Soil nutrient: the mixed soil sample is used for determining soil nutrient after removing plant root system, gravel and other impurities, air-drying indoors and sieving. Organic matter is heated by potassium dichromate, total nitrogen is treated by semi-micro-Kjeldahl method, total phosphorus is treated by sulfuric acid-perchloric acid-molybdenum antimony anti-colorimetric method, total potassium is treated by hydrofluoric acid-perchloric acid-flame photometer method, effective nitrogen is treated by alkaline hydrolysis diffusion method, effective phosphorus is treated by sodium bicarbonate leaching-molybdenum antimony anti-colorimetric method, effective potassium is treated by ammonium acetate leaching-flame photometer method, PH and conductivity are measured by acidimeter and conductivity meter respectively (water to soil ratio is 5: 1). Soil water-soluble total salt was determined by in-situ salinity meter. Drought stress is the most common form of plant adversity and is also the main factor affecting plant growth and development. Plant organs will undergo membrane lipid peroxidation under adverse circumstances, thus accumulating malondialdehyde (MDA), the final decomposition product of membrane lipid peroxide. MDA content is an important indicator reflecting the strength of membrane lipid peroxidation and the damage degree of plasma membrane, and is also an important parameter reflecting the damage of water stress to plants. At the same time, under adverse conditions, the increased metabolism of reactive oxygen species in plants will lead to the accumulation of reactive oxygen species or other peroxide radicals, thus damaging cell membranes. Superoxide dismutase (SOD) and peroxidase (POD) in plants can remove excess active oxygen in plants under drought and other adversities, maintain the metabolic balance of active oxygen, protect the structure of the membrane, and finally enhance the resistance of plants to adversities. The analysis samples take Populus euphratica, Tamarix chinensis and Phragmites communis as research objects. According to the location of groundwater monitoring wells, six sample plots are set up starting from the riverside, with an interval of 50 m between each sample plot, which are sample plots 1, 2, 3, 4, 5 and 6 in turn. Fresh leaves of plants are collected, stored at low temperature, and pretreated (dried or frozen) on the same day. PROline (Pro), cell membrane system protective enzymes superoxide dismutase (SOD) and peroxidase (POD) were tested indoors. Preparation of enzyme solution: weigh 0.5g of fresh material and add 4.5mL pH7.8 with ph 7.8. The materials were homogenized in a pre-frozen mortar, which was placed in an ice bath. Centrifuge at 10000 r/min for 15 min. The supernatant was used for determination of superoxide dismutase, peroxidase and malondialdehyde (MDA). PRO determination: put 0.03 g of material into a 20 mL large test tube, add 10mL ammonia-free distilled water, seal it, put it in a boiling water bath for 30min, cool it, filter, filtrate 5 mL+ ninhydrin 5 mL, develop color in boiling water for 60min, and extract with toluene. The extract was colorized with Shimadzu UV-265 UV spectrophotometer at 515 nm. SOD activity was measured by NBT photoreduction. The order of sample addition for enzyme reaction system is: pH 7.8 PBS 2.4mL+ riboflavin 0.2 mL+ methionine 0.2 mL+EDTA0.1 mL+ enzyme solution 0.1 mL+NBT0.2 mL. Then the test tube was reacted under 40001ux light for 20 min, and photochemical reduction was carried out. SOD activity was measured at 650 nm wavelength by UV-265 ultraviolet spectrophotometer. POD activity determination: the reaction mixture was 50 ml PBS with pH 6.0+28 μ L guaiacol+19 UL30% H2O2. 2 mL of reaction mixture +1 mL of enzyme solution, immediately start timing, reading every 1 min, reading at 470 nm. Determination of chlorophyll: ethanol acetone mixed solution method. After cutting the leaves, the mixed solution of 0.2 g and acetone: absolute ethanol = 1: 1 was weighed as the extraction solution. After extracting in the dark for 24 h, the leaves turned white and chlorophyll was dissolved in the extraction solution. The OD value of chlorophyll was measured by spectrophotometer at 652nm. Determination method of soluble sugar: phenol sulfate method is adopted. (1) The standard curve is made by taking 11 20 ml graduated test tubes, numbering them from 0 to 10 points, and adding solution and water according to Table 1 respectively. Then add 1 ml of 9% phenol solution to the test tube in sequence, shake it evenly, then add 5 ml of concentrated sulfuric acid from the front of the tube for 5 ~ 20 s, the total volume of the colorimetric solution is 8 ml, and leave it at constant temperature for 30 minutes for color development. Then, with blank as control, colorimetric determination was carried out at 485 nm wavelength. With sugar as abscissa and optical density as ordinate, a standard curve was drawn and the equation of the standard curve was obtained. (2) Extraction of soluble sugar: fresh plant leaves are taken, surface dirt is wiped clean, cut and mixed evenly, 0.1-0.3 g are weighed, 3 portions are respectively put into 3 calibration test tubes, 5-10 ml distilled water is added, plastic film is sealed, extraction is carried out in boiling water for 3O minutes, the extraction solution is filtered into a 25 ml volumetric flask, repeated flushing is carried out, and the volume is fixed to the calibration. (3) Absorb 0.5 g of sample solution into the test tube, add 1.5 ml of distilled water, and work out the content of soluble sugar in the same way as the standard curve. The amount of solution and water in each test tube Pipe number 0 1-2 3-4 5-6 7-8 9-10 1.100μg/L sugar solution 0.20 0.40 0.60 1.0 2. water/ml 2.0 1.8 1.6 1.4 1.2 1.0 3. Soluble sugar content/μ g 0 20 40 60 80 100 Determination of malondialdehyde: thiobarbituric acid method. Fresh leaves were cut to pieces, 0.5 g was weighed, 5% TCA5 ml was added, and the homogenate obtained after grinding was centrifuged at 3 000 r/rain for 10 rain. Take 2 ml supernatant, add 0.67% TBA 2 ml, mix, boil in 100 water bath for 30 rain, cool and centrifuge again. Using 0.67% TBA solution as blank, the OD values at 450, 532 and 600 nm were determined. Methods for analysis and testing of plant hormones (GA3, ABA, CK, IAA): 0.1 0.005 g plant samples were taken and ground in liquid nitrogen. 500μl methanol was extracted overnight at 4℃. Centrifuge the sample and freeze-dry the supernatant. 30μl10%% CH3CN dissolved the sample. 10μl of sample solution was analyzed by HPLC. The external standard method was used to quantify plant hormones. Standard plant hormones were purchased from sigma Company. See (Ruan Xiao, Wang Qiang, et al., 2000, Journal of Plant Physiology.26 (5), 402-406) for analysis methods.

0 2020-07-30

Spatial distribution data of soil bulk density, irrigation experiment and field water holding capacity in Linze Pingchuan irrigation area of Heihe River Basin (2012)

In the transition zone from Heihe River to desert oasis in Pingchuan oasis of Linze, soil texture, bulk density, field capacity, saturated water capacity, soil organic matter, total nitrogen and inorganic carbon content were studied. PH value, electrical conductivity, total carbon, SiC and C / N were monitored to determine the physical and chemical properties of 0-20cm topsoil and the soil particle size composition of 0-20cm and 20-80cm soil layers. According to the soil properties of five different soil in cotton field, cotton irrigation experiment was carried out: irrigation amount, seed cotton yield, straw parameters, lint percentage, coat index, seed index, single boll weight, flower rate before frost, unit boll number, single boll weight, irrigation water productivity, etc.

0 2020-07-30

Vegetation quadrat survey data in the middle of Heihe River Basin (2013-2014)

The survey data of vegetation quadrat in the middle reaches of Heihe River consists of the field survey data in 2013 and 2014, including the vegetation and soil data of the survey quadrat. The data of each survey sample includes the following information: sample longitude and latitude, sample size, elevation, sample overview, plant name, plant height, crown width, coverage, total coverage, number of trees, plant spacing, row spacing, large row spacing, DBH. The soil is divided into 6 layers according to 0-100cm below the ground, which are 0-10cm, 10-20cm, 20-40cm, 40-60cm, 60-80cm and 80-100cm respectively.

0 2020-07-30

Sample ponit distribution in the upstream of the Heihe River Basin

This data is the longitude and latitude information of soil water sampling points in the "observation experiment of Soil Hydrological heterogeneity in the upper reaches of Heihe River and its impact on the hydrological process in mountainous areas" (91125010) of Heihe project, which is mainly used to express the spatial distribution of soil water sampling points in this project.

0 2020-07-28

Qilian Mountains integrated observatory network: Dataset of Qinghai Lake integrated observatory network (an observation system of meteorological elements gradient of Alpine meadow and grassland ecosystem superstation, 2018)

This dataset includes data recorded by the Qinghai Lake integrated observatory network obtained from an observation system of Meteorological elements gradient of the Alpine meadow and grassland ecosystem Superstation from August 31 to December 24, 2018. The site (98°35′41.62″E, 37°42′11.47″N) was located in the alpine meadow and alpine grassland ecosystem, near the SuGe Road in Tianjun County, Qinghai Province. The elevation is 3718m. The installation heights and orientations of different sensors and measured quantities were as follows: air temperature and humidity profile (HMP155; 3, 5, 10, 15, 20, 30, and 40 m, towards north), wind speed and direction profile (windsonic; 3, 5, 10, 15, 20, 30, and 40 m, towards north), air pressure (PTB110; 3 m), rain gauge (TE525M; 10m of the platform in west by north of tower), four-component radiometer (CNR4; 6m, towards south), two infrared temperature sensors (SI-111; 6 m, towards south, vertically downward), photosynthetically active radiation (PQS1; 6 m, towards south, each with one vertically downward and one vertically upward, soil heat flux (HFP01; 3 duplicates below the vegetation; -0.06 m), soil temperature profile (109; -0.05、-0.10、-0.20、-0.40、-0.80、-1.20、-2.00、-3.00 and -4.00m), soil moisture profile (CS616; -0.05、-0.10、-0.20、-0.40、-0.80、-1.20、-2.00、-3.00 and -4.00m). The observations included the following: air temperature and humidity (Ta_3 m, Ta_5 m, Ta_10 m, Ta_15 m, Ta_20 m, Ta_30 m, and Ta_40 m; RH_3 m, RH_5 m, RH_10 m, RH_15 m, RH_20 m, RH_30 m, and RH_40 m) (℃ and %, respectively), wind speed (Ws_3 m, Ws_5 m, Ws_10 m, Ws_15 m, Ws_20 m, Ws_30 m, and Ws_40 m) (m/s), wind direction (WD_3 m, WD_5 m, WD_10 m, WD_15 m, WD_20 m, WD_30m, and WD_40 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_5cm、Ts_10cm、Ts_20cm、Ts_40cm、Ts_80cm、Ts_120cm、Ts_200cm、Ts_300cm、Ts_400cm) (℃), soil moisture (Ms_5cm、Ms_10cm、Ms_20cm、Ms_40cm、Ms_80cm、Ms_120cm、Ms_200cm、Ms_300cm、Ms_400cm) (%, volumetric water content), 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. 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: 2018/8/31 10:30. Moreover, suspicious data were marked in red.

0 2020-07-25

Qilian Mountains integrated observatory network: Dataset of Heihe integrated observatory network (an observation system of meteorological elements gradient of Sidaoqiao superstation, 2018)

This dataset includes data recorded by the Heihe integrated observatory network obtained from an observation system of Meteorological elements gradient of Sidaoqiao Superstation from January 1 to December 31, 2018. The site (101.137° E, 42.001° N) was located on a tamarix (Tamarix chinensis Lour.) surface in the Sidaoqiao, Dalaihubu Town, Ejin Banner, Inner Mongolia Autonomous Region. The elevation is 873 m. The installation heights and orientations of different sensors and measured quantities were as follows: air temperature and humidity profile (HC2S3; 5, 7, 10, 15, 20 and 28 m, towards north), wind speed profile (010C; 5, 7, 10, 15, 20 and 28 m, towards north), wind direction profile (020C; 15 m, towards north), air pressure (CS100; in waterproof box), rain gauge (TE525M; 28 m, towards south), four-component radiometer (CNR4; 10 m, towards south), two infrared temperature sensors (SI-111; 10 m, towards south, vertically downward), two photosynthetically active radiation (PQS-1; 10 m, towards south, one vertically upward and one vertically downward), soil heat flux (HFP01SC; 3 duplicates with G1 below the tamarix; G2 and G3 between plants, -0.06 m), a TCAV averaging soil thermocouple probe (installed on 17 July, 2013, TCAV; -0.02, -0.04 m), soil temperature profile (109ss-L; 0, -0.02, -0.04, -0.1, -0.2, -0.4, -0.8, -1.2, -1.6, -2.0 m), and soil moisture profile (install on 7 December, 2013, ML2X; -0.02, -0.04, -0.1, -0.2, -0.4, -0.8, -1.2, -1.6, -2.0 m). The observations included the following: air temperature and humidity (Ta_5 m, Ta_7 m, Ta_10 m, Ta_15 m, Ta_20 m and Ta_28 m; RH_5 m, RH_7 m, RH_10 m, RH_15 m, RH_20 m and RH_28 m) (℃ and %, respectively), wind speed (Ws_5 m, Ws_7 m, Ws_10 m, Ws_15 m, Ws_20 m and Ws_28 m) (m/s), wind direction (WD_15 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) (℃), photosynthetically active radiation of upward and downward (PAR_up and PAR_down) (μmol/ (s m^-2)), average soil temperature (TCAV, ℃), 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_80 cm, Ts_120 cm, Ts_160 cm, Ts_200 cm) (℃), and soil moisture (Ms_2 cm, Ms_4 cm, Ms_10 cm, Ms_20 cm, Ms_40 cm, Ms_80 cm, Ms_120 cm, Ms_160 cm, Ms_200 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 precipitation data was wrong during January to June because of the sensor problem; the air pressure data was wrong during July to October because of sensor line broken. 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: 2018-9-10 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 sites information), Liu et al. (2011) for data processing) in the Citation section.

0 2020-07-25

Qilian Mountains integrated observatory network: Dataset of Heihe integrated observatory network (an observation system of meteorological elements gradient of A’rou Superstation, 2018)

This dataset includes data recorded by the Heihe integrated observatory network obtained from an observation system of Meteorological elements gradient of A’rou Superstation from January 1 to December 31, 2018. The site (100.464° E, 38.047° N) was located on a cold grassland surface in the Caodaban village, A’rou Town, Qilian County, Qinghai Province. The elevation is 3033 m. The installation heights and orientations of different sensors and measured quantities were as follows: air temperature and humidity profile (HMP45C; 1, 2, 5, 10, 15 and 25 m, towards north), wind speed profile (010C; 1, 2, 5, 10, 15 and 25 m, towards north), wind direction profile (020C; 2 m, towards north), air pressure (CS100; 2 m), rain gauge (TE525M; 5 m, towards south), four-component radiometer (CNR4; 5 m, towards south), two infrared temperature sensors (SI-111; 5 m, towards south, vertically downward), photosynthetically active radiation (PAR-LITE; 5 m, towards south, vertically upward), soil heat flux (HFP01SC; 3 duplicates, -0.06 m, 2 m in the south of tower), a TCAV averaging soil thermocouple probe (TCAV; -0.02, -0.04 m, 2 m in the south of tower), soil temperature profile (109; 0, -0.02, -0.04, -0.06, -0.1, -0.15, -0.2, -0.3, -0.4, -0.6, -0.8, -1.2, -1.6, -2, -2.4, -2.8 and -3.2 m, 3 duplicates in -0.04 m and -0.1 m), and soil moisture profile (CS616; -0.02, -0.04, -0.06, -0.1, -0.15, -0.2, -0.3, -0.4, -0.6, -0.8, -1.2, -1.6, -2, -2.4, -2.8 and -3.2 m, 3 duplicates in -0.04 m and -0.1 m). The observations included the following: air temperature and humidity (Ta_1 m, Ta_2 m, Ta_5 m, Ta_10 m, Ta_15 m and Ta_25 m; RH_1 m, RH_2 m, RH_5 m, RH_10 m, RH_15 m and RH_25 m) (℃ and %, respectively), wind speed (Ws_1 m, Ws_2 m, Ws_5 m, Ws_10 m, Ws_15 m and Ws_25 m) (m/s), wind direction (WD_2 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/m2), infrared temperature (IRT_1 and IRT_2) (℃), photosynthetically active radiation (PAR) (μmol/(s m-2)), average soil temperature (TCAV, ℃), soil heat flux (Gs_1, Gs_2 and Gs_3) (W/m2), soil temperature (Ts_0 cm, Ts_2 cm, Ts_4 cm_1, Ts_4 cm_2, Ts_4 cm_3, Ts_6 cm, Ts_10 cm_1, Ts_10 cm_2, Ts_10 cm_3, Ts_15 cm, Ts_20 cm, Ts_30 cm, Ts_40 cm, Ts_60 cm, Ts_80 cm, Ts_120 cm, Ts_160 cm, Ts_200 cm, Ts_240 cm, Ts_280 cm and Ts_320 cm) (℃), and soil moisture (Ms_2 cm, Ms_4 cm_1, Ms_4 cm_2, Ms_4 cm_3, Ms_6 cm, Ms_10 cm_1, Ms_10 cm_2, Ms_10 cm_3, Ms_15 cm, Ms_20 cm, Ms_30 cm, Ms_40 cm, Ms_60 cm, Ms_80 cm, Ms_120 cm, Ms_160 cm, Ms_200 cm, Ms_240 cm, Ms_280 cm and Ms_320 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 average soil temperature was rejected during February 16 to March 31 and April 15 to May 20 because of broken of the sensor line; Soil heat flux were wrong occasionally during November to December. 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: 2018-9-10 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 sites information), Liu et al. (2011) for data processing) in the Citation section.

0 2020-07-25

Qilian Mountains integrated observatory network: Dataset of Heihe integrated observatory network (an observation system of meteorological elements gradient of Daman superstation, 2018)

This dataset includes data recorded by the Heihe integrated observatory network obtained from an observation system of Meteorological elements gradient of Daman Superstation from January 1 to December 31, 2018. The site (100.372° E, 38.856° N) was located on a cropland (maize surface) in the Daman irrigation, which is near Zhangye city, Gansu Province. The elevation is 1556 m. The installation heights and orientations of different sensors and measured quantities were as follows: air temperature and humidity profile (AV-14TH;3, 5, 10, 15, 20, 30, and 40 m, towards north), wind speed and direction profile (windsonic; 3, 5, 10, 15, 20, 30, and 40 m, towards north), air pressure (CS100; 2 m), rain gauge (TE525M; 2.5 m, 8 m in west of tower), four-component radiometer (PIR&PSP; 12 m, towards south), two infrared temperature sensors (IRTC3; 12 m, towards south, vertically downward), photosynthetically active radiation (LI190SB; 12 m, towards south, vertically upward; another four photosynthetically active radiation, PQS-1; two above the plants (12 m) and two below the plants (0.3 m), towards south, each with one vertically downward and one vertically upward), soil heat flux (HFP01SC; 3 duplicates with G1 below the vegetation; G2 and G3 between plants, -0.06 m), a TCAV averaging soil thermocouple probe (TCAV; -0.02, -0.04 m), soil temperature profile (AV-10T; 0, -0.02, -0.04, -0.1, -0.2, -0.4, -0.8, -1.2, and -1.6 m), soil moisture profile (CS616; -0.02, -0.04, -0.1, -0.2, -0.4, -0.8, -1.2, and -1.6 m). The observations included the following: air temperature and humidity (Ta_3 m, Ta_5 m, Ta_10 m, Ta_15 m, Ta_20 m, Ta_30 m, and Ta_40 m; RH_3 m, RH_5 m, RH_10 m, RH_15 m, RH_20 m, RH_30 m, and RH_40 m) (℃ and %, respectively), wind speed (Ws_3 m, Ws_5 m, Ws_10 m, Ws_15 m, Ws_20 m, Ws_30 m, and Ws_40 m) (m/s), wind direction (WD_3 m, WD_5 m, WD_10 m, WD_15 m, WD_20 m, WD_30m, and WD_40 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) (℃), photosynthetically active radiation (PAR) (μmol/ (s m-2)), average soil temperature (TCAV, ℃), soil heat flux (Gs_1, below the vegetation; Gs_2, and Gs_3, between plants) (W/m^2), soil temperature (Ts_0 cm, Ts_2 cm, Ts_4 cm, Ts_10 cm, Ts_20 cm, Ts_40 cm, Ts_80 cm, Ts_120 cm, and Ts_160 cm) (℃), soil moisture (Ms_2 cm, Ms_4 cm, Ms_10 cm, Ms_20 cm, Ms_40 cm, Ms_80 cm, Ms_120 cm, and Ms_160 cm) (%, volumetric water content), above 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.The meterological data during September 17 and November 7 and TCAV data after November 7 were wrong because the malfunction of datalogger. 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: 2018-6-10 10:30. Moreover, suspicious data were marked in red. For more information, please refer to Liu et al. (2018) (for sites information), Liu et al. (2011) for data processing) in the Citation section.

0 2020-07-25