Daily and Monthly evapotranspiration (5km x 5km spatial resolution) for global land area was derived from satellite data and a surface energy balance method (EB). The global 5 km daily and monthly ET dataset is produced with the revised SEBS algorithm in Chen et al. 2019 JGR and Chen et al. 2013 (JAMC). For how to obtain seamless daily evaporation data by thermal infrared, please refer to Chen et al. 2021 JGR. This paper also compares different evaporation products. The results show that this product is significantly better than Landflux, GLEAM, MOD16, GLDAS and ERA-Interim products in irrigation area. The downscaling of reanalysis forcing data is detailed in this paper. MODIS LST, NDVI, Global forest height, GlobAlbedo, GLASS LAI have been used in this ET calculation. The ET dataset will be updated to near-present with the availability of input dataset. The global 5 km sensible heat flux, net radiation, latent heat flux will be open with the email contact with Dr. Xuelong Chen. Daily ET File name: 20001201-ET-V1.mat, 2000-year, 12-month,01-day, ET-Evapotranspiration, V1-version 1;unit: mm/day (unit8 need transfer to single or double and should be divided by 10);data type: unit8 was used to save the disk space, 255 is used for ocean and water body pixels. Monthly ET File name: ETm200012-ET-V1.mat, 2000-year, 12-month, ET-Evapotranspiration, V1-version 1;unit: mm/month (int16 need transfer to single or double and should be divided by 10);data type: int16 was used to save the disk space, 0 is used for ocean and water body pixels. The daily ET dataset is produced with a similar method and satellite data as in Chen, X., et al., 2014: Development of a 10 year (2001–2010) 0.1° dataset of land-surface energy balance for mainland China, Atmos. Chem. Phys., 14, 13097–13117, doi:10.5194/acp-14-13097-2014. The calculation of roughness length and kB_1 for global land were updated by the method in Chen, X., et al, 2019, A Column Canopy‐Air Turbulent Diffusion Method for Different Canopy Structures, Journal of Geophysical Research: Atmospheres, 2019.01.15, 124. Most of the satellite input data were from MODIS. Meteorological data was from ERA-Interim. Global canopy height information was derived from GLAS and MODIS NDVI. The daily ET has a mean bias (MB) of 0.04 mm/day, RMSE is 1.56 (±0.25) mm/day.
CHEN Xuelong
1) This data is the aridity index data calculated based on the latest simulation results of 22 cmip6 coupled global climate models; 2) The calculation formula is p / PET (ratio of precipitation to potential evapotranspiration), and the calculation of pet is based on PM formula; 3) The monthly data of the Great Lakes region of Central Asia from January 1900 to December 2100, including ssp2-4.5 and ssp5-8.5, with a resolution of 1 degree * 1 degree; 4) The data can be used to analyze the distribution and evolution of dry and wet pattern in the Great Lakes region of Central Asia under medium and high emission scenarios in the future. The data has been converted into 3-mongth running means.
HUA Lijuan
This data is generated based on meteorological observation data, hydrological station data, combined with various assimilation data and remote sensing data, through the preparation of the Qinghai Tibet Plateau multi-level hydrological model system WEB-DHM (distributed hydrological model based on water and energy balance) coupling snow, glacier and frozen soil physical processes. The time resolution is monthly, the spatial resolution is 5km, and the original data format is ASCII text format, Data types include grid runoff and evaporation (if evaporation is less than 0, it means condensation; if runoff is less than 0, it means precipitation is less than evaporation in the month). If the asc cannot be opened normally in arcmap, please top the first 5 lines of the asc file.
WANG Lei, CHAI Chenhao
The data set contains the observation data of the evapotranspiration apparatus on January 1, 2017 (solstice) and December 31, 2017.The site is located in huailai county, hebei province, east garden town, the underlying surface for corn.The latitude and longitude of the observation point is 115.7880E, 40.3491N, and the altitude is 480m. The collection frequency of the evapotranspiration permeameter is 1 time/min, and the released data is 10min output data.The evapotranspiration meter is a cylindrical structure with a surface area of 1m2 and a buried depth of 1.5m. The observation accuracy of evapotranspiration is 0.01mm.Two evapotranspiration seeptometers were installed, one kept bare soil (lysimeter_1), the other for the corn underlay (lysimeter_2) during the growing season (May 10 - September 15).Soil temperature and humidity probe, soil water potential probe and soil heat flow plate are also installed in the evapotranspiration apparatus.The buried depth of the soil temperature sensor is 5cm, 30cm, 50cm, 100cm and 140cm.The buried depth of the soil water sensor is 2cm, 10cm, 20cm and 40cm.The soil heat flux plate is buried 10cm underground;The buried depth of the soil water potential sensor was 30cm and 140cm.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;(2) delete the data of observation anomalies caused during maintenance;(3) data that is obviously beyond the physical meaning or the range of the instrument is deleted;(4) the format of date and time is unified, and the date and time are in the same column.For example, the time is: 2016-6-10-10:30. The observation data released by the evapotranspiration permeameter include:Date/Time, weighing mass (i.l._1_wag_l_000 (Kg), i.l._2_wag_l_000 (Kg)), seepage mass (i.l._1_wag_d_000 (Kg), i.l._2_wag_d_000 (Kg)), soil heat flux (Gs_1_10cm, Gs_2_10cm) (W/m2),Multi-layer soil moisture (Ms_1_5cm, Ms_1_10cm, Ms_1_30cm, Ms_1_50cm, Ms_1_50cm, Ms_1_100cm, Ms_2_5cm, Ms_2_10cm, Ms_2_30cm, Ms_2_50cm, Ms_2_100cm) (%),Multi-layer soil temperature (Ts_1_5cm, Ts_1_30cm, Ts_1_50cm, Ts_1_100cm, Ts_1_140cm, Ts_2_140cm, ts_2_2_5cm, ts_2_2_50cm, Ts_2_100cm, Ts_2_140cm) (℃), soil water potential (TS_1_30 (hPa), TS_1_140 (hPa), TS_2_30 (hPa), TS_2_30 (hPa), TS_2_140 (hPa), TS_2_140 (hPa));The data is stored in *.xls format.
LIU Shaomin, XU Ziwei, ZHU Zhongli
This dataset includes the observation data from 01 Jan. 2019 through 31 Dec. 2019, collected by lysimeters, which are located at 115.788E, 40.349N and 480 m above sea level, near the Huailai Station in East Garden Town, Huailai County, Hebei Province. The land cover around the station was maize crop. The weighable lysimeter was built by UMS GmbH (Germany), with a surface area of 1m2, and a soil column of 1.5 m high. The original data sampling frequency was 1 Hz, and then averaged to 10min for distribution. The precision of the weighing data is 10g (equivalent to 0.01mm). During the crop growth period, a lysimeter is covered by bare soil and another one is covered by planted maize. The soil moisture, temperature and soil water potential sensors are installed both inside and outside of the lysimeter to ensure that the water cycle in the soil column is consistent with that of the field. Different sensors are located at different depths: 5, 50, 100 cm for soil temperature sensors, and 5, 10, 30, 50, 100 cm for soil moisture sensors, and 30 and 140cm for soil water potential sensors (the tensionmeter here can also measure soil temperature at 30, 140 cm). The soil heat flux plates in both lysimeters are buried at 10cm depth. The data processes and quality control according to: 1) ensuring there were 144 data every day, the lost data were replaced by -6999; 2) deleting the abnormal data; 3) deleting the outlier data; 4) keeping the consistent date and time format (e.g. 2019-01-01 10:30). The distributed data include the following variables: Date-Time, Weight (I.L_1_WAG_L_000(Kg), I.L_2_WAG_L_000(Kg)), Drainage Weight (I.L_1_WAG_D_000(Kg), I.L_2_WAG_D_000(Kg)), Soil Heat Flux (Gs_1_10cm, Gs_2_10cm) (W/m2), Soil Moisture (Ms_1_5cm, Ms_1_10cm, Ms_1_30cm, Ms_1_50cm, Ms_1_100cm, Ms_2_5cm, Ms_2_10cm, Ms_2_30cm, Ms_2_50cm, Ms_2_100cm) (%), Soil Temperature (Ts_1_5cm , Ts_1_30cm, Ts_1_50cm, Ts_1_100cm, Ts_1_140cm, Ts_2_5cm , Ts_2_30cm, Ts_2_50cm, Ts_2_100cm, Ts_2_140cm) (C), Soil Water Potential (TS_1_30(hPa), TS_1_140(hPa), TS_2_30(hPa), TS_2_140(hPa)). The format of datasets was *.xls.
LIU Shaomin, ZHU Zhongli, XU Ziwei
The data set contains the observation data of the evapotranspiration apparatus on January 1, 2016, solstice, December 31, 2016.The site is located in huailai county, hebei province, east garden town, the underlying surface for corn.The latitude and longitude of the observation point is 115.7880E, 40.3491N, and the altitude is 480m. The collection frequency of the evapotranspiration permeameter is 1 time/min, and the released data is 10min output data.The evapotranspiration meter is a cylindrical structure with a surface area of 1m2 and a buried depth of 1.5m. The observation accuracy of evapotranspiration is 0.01mm.Two evapotranspiration seeptometers were installed, one kept bare soil (lysimeter_1), the other for the corn underlay (lysimeter_2) during the growing season (May 10 - September 15).Soil temperature and humidity probe, soil water potential probe and soil heat flow plate are also installed in the evapotranspiration apparatus.The buried depth of the soil temperature sensor is 5cm, 30cm, 50cm, 100cm and 140cm.The buried depth of the soil water sensor is 2cm, 10cm, 20cm and 40cm.The soil heat flux plate is buried 10cm underground;The buried depth of the soil water potential sensor was 30cm and 140cm.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;(2) delete the data of observation anomalies caused during maintenance;(3) data that is obviously beyond the physical meaning or the range of the instrument is deleted;(4) the format of date and time is unified, and the date and time are in the same column.For example, the time is: 2016-6-10-10:30. The observation data released by the evapotranspiration permeameter include:Date/Time, weighing mass (i.l._1_wag_l_000 (Kg), i.l._2_wag_l_000 (Kg)), seepage mass (i.l._1_wag_d_000 (Kg), i.l._2_wag_d_000 (Kg)), soil heat flux (Gs_1_10cm, Gs_2_10cm) (W/m2),Multi-layer soil moisture (Ms_1_5cm, Ms_1_10cm, Ms_1_30cm, Ms_1_50cm, Ms_1_50cm, Ms_1_100cm, Ms_2_5cm, Ms_2_10cm, Ms_2_30cm, Ms_2_50cm, Ms_2_100cm) (%),Multi-layer soil temperature (Ts_1_5cm, Ts_1_30cm, Ts_1_50cm, Ts_1_100cm, Ts_1_140cm, Ts_2_140cm, ts_2_2_5cm, ts_2_2_50cm, Ts_2_100cm, Ts_2_140cm) (℃), soil water potential (TS_1_30 (hPa), TS_1_140 (hPa), TS_2_30 (hPa), TS_2_30 (hPa), TS_2_140 (hPa), TS_2_140 (hPa));The data is stored in *.xls format.
LIU Shaomin, XU Ziwei, ZHU Zhongli
The data set contains the observation data of the evapotranspiration apparatus on January 1, 2015, solstice, December 31, 2015.The site is located in huailai county, hebei province, east garden town, the underlying surface for corn.The latitude and longitude of the observation point is 115.7880E, 40.3491N, and the altitude is 480m. The acquisition frequency of the evapotranspiration permeameter is 1Hz, and the released data is 10min output data.The evapotranspiration meter is a cylindrical structure with a surface area of 1m2 and a buried depth of 1.5m. The observation accuracy of evapotranspiration is 0.01mm.Two evapotranspiration seeptometers were installed, one kept bare soil (lysimeter_1), the other for the corn underlay (lysimeter_2) during the growing season (May 10 - September 15).Soil temperature and humidity probe, soil water potential probe and soil heat flow plate are also installed in the evapotranspiration apparatus.The buried depth of the soil temperature sensor is 5cm, 30cm, 50cm, 100cm and 140cm.The buried depth of the soil water sensor is 2cm, 10cm, 20cm and 40cm.The soil heat flux plate is buried 10cm underground;The buried depth of the soil water potential sensor was 30cm and 140cm.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 instruments and weather, the data was abnormal from December 6th to 31st.(2) delete the data of observation anomalies caused during maintenance;(3) data that is obviously beyond the physical meaning or the range of the instrument is deleted;(4) the format of date and time is unified, and the date and time are in the same column.For example, the time is: 10:30 on June 10, 2015. The observation data released by the evapotranspiration permeameter include:Date/Time, weighing mass (i.l._1_wag_l_000 (Kg), i.l._2_wag_l_000 (Kg)), seepage mass (i.l._1_wag_d_000 (Kg), i.l._2_wag_d_000 (Kg)), soil heat flux (Gs_1_10cm, Gs_2_10cm) (W/m2),Multi-layer soil moisture (Ms_1_5cm, Ms_1_10cm, Ms_1_30cm, Ms_1_50cm, Ms_1_50cm, Ms_1_100cm, Ms_2_5cm, Ms_2_10cm, Ms_2_30cm, Ms_2_50cm, Ms_2_100cm) (%),Multi-layer soil temperature (Ts_1_5cm, Ts_1_30cm, Ts_1_50cm, Ts_1_100cm, Ts_1_140cm, Ts_2_140cm, ts_2_2_5cm, ts_2_2_50cm, Ts_2_100cm, Ts_2_140cm) (℃), soil water potential (TS_1_30 (hPa), TS_1_140 (hPa), TS_2_30 (hPa), TS_2_30 (hPa), TS_2_140 (hPa), TS_2_140 (hPa));The data is stored in *.xls format. Please refer to Liu et al. (2013) for information of observation test or site, and Yang guangchao et al. (2015) for data processing.
LIU Shaomin, XU Ziwei, ZHU Zhongli, XIAO Qing
This dataset includes the observation data from 01 Jan. 2019 through 31 Dec. 2018, collected by lysimeters, which are located at 115.788 E, 40.349 N and 480 m above sea level, near the Huailai Station in East Garden Town, Huailai County, Hebei Province. The land cover around the station was maize crop. The weighable lysimeter was built by UMS GmbH (Germany), with a surface area of 1m2, and a soil column of 1.5 m high. The original data sampling frequency was 1 Hz, and then averaged to 10min for distribution. The precision of the weighing data is 10g (equivalent to 0.01mm). During the crop growth period, a lysimeter is covered by bare soil and another one is covered by planted maize. The soil moisture, temperature and soil water potential sensors are installed both inside and outside of the lysimeter to ensure that the water cycle in the soil column is consistent with that of the field. Different sensors are located at different depths: 5, 50, 100 cm for soil temperature sensors, and 5, 10, 30, 50, 100 cm for soil moisture sensors, and 30 and 140cm for soil water potential sensors (the tensionmeter here can also measure soil temperature at 30, 140 cm). The soil heat flux plates in both lysimeters are buried at 10cm depth. The data processes and quality control according to: 1) ensuring there were 144 data every day, the lost data were replaced by -6999; 2) deleting the abnormal data; 3) deleting the outlier data; 4) keeping the consistent date and time format (e.g.2018-6-10 10:30). The distributed data include the following variables: Date-Time, Weight (I.L_1_WAG_L_000(Kg), I.L_2_WAG_L_000(Kg)), Drainage Weight (I.L_1_WAG_D_000(Kg), I.L_2_WAG_D_000(Kg)), Soil Heat Flux (Gs_1_10cm, Gs_2_10cm) (W/m2), Soil Moisture (Ms_1_5cm, Ms_1_10cm, Ms_1_30cm, Ms_1_50cm, Ms_1_100cm, Ms_2_5cm, Ms_2_10cm, Ms_2_30cm, Ms_2_50cm, Ms_2_100cm) (%), Soil Temperature (Ts_1_5cm , Ts_1_30cm, Ts_1_50cm, Ts_1_100cm, Ts_1_140cm, Ts_2_5cm , Ts_2_30cm, Ts_2_50cm, Ts_2_100cm, Ts_2_140cm) (C), Soil Water Potential (TS_1_30(hPa), TS_1_140(hPa), TS_2_30(hPa), TS_2_140(hPa)). The format of datasets was *.xls.
LIU Shaomin, ZHU Zhongli, XU Ziwei
The evapotranspiration (ET) is an important variable connecting land energy balance, water cycle and carbon cycle. Accurate monitoring and estimations of ET are essential not only for water resources management but also for simulating regional, global climate, and hydrological cycles. Remote sensing technology is an effective method to monitor ET. At present, a variety of ET remote sensing products have been produced and released. However, in the process of validation, there is a problem of spatial scale mismatch between ET remote sensing estimation value and station observation value, especially on heterogeneous surface. Therefore, it is very important to obtain the ground truth ET values at the satellite pixel scale by upscaling method on heterogeneous surface. In this study, using the station observation data and multi-source remote sensing information, the ET observed at a single ground station is upscaled to the satellite pixel scale, and the ground truth ET values at the satellite pixel scale in Heihe River Basin is obtained. Based on the ET data observed by the eddy covariance (EC) at 15 stations (3 superstations and 12 ordinary stations) in the Heihe integrated observatory network, combined with the fused high-resolution remote sensing data (surface temperature, vegetation index, net radiation, etc.) and atmospheric reanalysis data, the upscaling is carried out to obtain the ground truth ET at the satellite pixel scale. The distribution diagram is shown in Figure 1. Specifically, firstly, the spatial heterogeneity of the spatial heterogeneity of the land surface hydrothermal conditions was evaluated; Secondly, nine upscaling methods (the integrated Priestley-Taylor equation method, the Penman-Monteith equation combined with EnKF method, the Penman-Monteith equation combined with SCE_UA method, EC observation value, artificial neural network, Bayesian linear regression, deep belief network, Gaussian process regression, and random fores and directly taking the EC observation value as the ground truth ET) were compared and analyzed through direct validation and cross-validation; Finally, a comprehensive method (directly using the EC observation value on the homogeneous underlying surface; using the Gaussian process regression method for upscaling on the moderately heterogeneous underlying surface and highly heterogeneous underlying surface) was optimized to obtain the groud truth ET at the satellite pixel scale at 15 typical underlying surfaces in Heihe River Basin (2010-2016, spatial resolution of 1km). The results showed that the ground truth ET at the satellite pixel scale is relatively reliable. Compared with the pixel scale reference value (LAS observation value), the MAPE of the ground turth ET at the satellite pixel scale at the three superstations are 1.57%, 3.23% and 4.59% respectively, which can meet the needs of the validation of ET remote sensing products. For all site information and data processing, please refer to Liu et al. (2018), and for upscaling methods, please refer to Li et al. (2021).
LIU Shaomin, LI Xiang , XU Ziwei
The data set contains the observation data of the evapotranspiration apparatus on January 1, 2013 (solstice) and December 31, 2013.The site is located in huailai county, hebei province, east garden town, the underlying surface for corn.The latitude and longitude of the observation point is 115.7880E, 40.3491N, and the altitude is 480m. The collection frequency of evapotranspiration permeameter is 1 time/minute, and the released data is the average of 10 minutes.The evapotranspiration meter is a cylindrical structure with a surface area of 1m2 and a buried depth of 1.5m. The observation accuracy of evapotranspiration is 0.01mm.Two evapotranspiration seeptometers were installed, one kept bare soil (lysimeter_1), the other for the corn underlay (lysimeter_2) during the growing season (May 10 - September 15).Soil temperature and humidity probe, soil water potential probe and soil heat flow plate are also installed in the evapotranspiration apparatus.The buried depth of the soil temperature sensor is 5cm, 30cm, 50cm, 100cm and 140cm.The buried depth of the soil water sensor is 2cm, 10cm, 20cm and 40cm.The soil heat flux plate is buried 10cm underground;The buried depth of the soil water potential sensor was 30cm and 140cm.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;(2) delete the data of observation anomalies caused during maintenance;(3) data that is obviously beyond the physical meaning or the range of the instrument is deleted;(4) the format of date and time is unified, and the date and time are in the same column.For example, the time is: 2013-6-10-10:30. The observation data released by the evapotranspiration permeameter include:Date/Time, weighing mass (i.l._1_wag_l_000 (Kg), i.l._2_wag_l_000 (Kg)), seepage mass (i.l._1_wag_d_000 (Kg), i.l._2_wag_d_000 (Kg)), soil heat flux (Gs_1_10cm, Gs_2_10cm) (W/m2),Multi-layer soil moisture (Ms_1_2cm, Ms_1_10cm, Ms_1_20cm, Ms_1_40cm, Ms_2_2cm, Ms_2_10cm, Ms_2_20cm, Ms_2_40cm) (%),Multi-layer soil temperature (Ts_1_5cm, Ts_1_30cm, Ts_1_50cm, Ts_1_100cm, Ts_1_140cm, Ts_2_140cm, ts_2_2_5cm, ts_2_2_50cm, Ts_2_100cm, Ts_2_140cm) (℃), soil water potential (TS_1_30 (hPa), TS_1_140 (hPa), TS_2_30 (hPa), TS_2_30 (hPa), TS_2_140 (hPa), TS_2_140 (hPa));The data is stored in *.xls format. Guo et al, 2020 is used for site introduction and Liu et al, 2013 for data processing
LIU Shaomin, XU Ziwei, ZHU Zhongli, XIAO Qing
The dataset contains the observation data of evapotranspiration apparatus on January 1, 2014, solstice, December 31, 2014.The site is located in huailai county, hebei province, east garden town, the underlying surface for corn.The latitude and longitude of the observation point is 115.7880E, 40.3491N, and the altitude is 480m. The collection frequency of evapotranspiration permeameter is 1 time/minute, and the released data is the average of 10 minutes.The evapotranspiration meter is a cylindrical structure with a surface area of 1m2 and a buried depth of 1.5m. The observation accuracy of evapotranspiration is 0.01mm.Two evapotranspiration seeptometers were installed, one kept bare soil (lysimeter_1), the other for the corn underlay (lysimeter_2) during the growing season (May 10 - September 15).Soil temperature and humidity probe, soil water potential probe and soil heat flow plate are also installed in the evapotranspiration apparatus.The buried depth of the soil temperature sensor is 5cm, 30cm, 50cm, 100cm and 140cm.The buried depth of the soil water sensor is 2cm, 10cm, 20cm and 40cm.The soil heat flux plate is buried 10cm underground;The buried depth of the soil water potential sensor was 30cm and 140cm.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;(2) delete the data of observation anomalies caused during maintenance;(3) data that is obviously beyond the physical meaning or the range of the instrument is deleted;(4) the format of date and time is unified, and the date and time are in the same column.For example, the time is: 2014-6-10-10:30. The observation data released by the evapotranspiration permeameter include:Date/Time, weighing mass (i.l._1_wag_l_000 (Kg), i.l._2_wag_l_000 (Kg)), seepage mass (i.l._1_wag_d_000 (Kg), i.l._2_wag_d_000 (Kg)), soil heat flux (Gs_1_10cm, Gs_2_10cm) (W/m2),Multi-layer soil moisture (Ms_1_2cm, Ms_1_10cm, Ms_1_20cm, Ms_1_40cm, Ms_2_2cm, Ms_2_10cm, Ms_2_20cm, Ms_2_40cm) (%),Multi-layer soil temperature (Ts_1_5cm, Ts_1_30cm, Ts_1_50cm, Ts_1_100cm, Ts_1_140cm, Ts_2_140cm, ts_2_2_5cm, ts_2_2_50cm, Ts_2_100cm, Ts_2_140cm) (℃), soil water potential (TS_1_30 (hPa), TS_1_140 (hPa), TS_2_30 (hPa), TS_2_30 (hPa), TS_2_140 (hPa), TS_2_140 (hPa));The data is stored in *.xls format. Please refer to Yang guangchao et al. (2015) for observation test or site introduction, and refer to Liu et al. (2013) for data processing.
LIU Shaomin, XU Ziwei, ZHU Zhongli, XIAO Qing
This data comes from the Tianlaochi watershed sample plot. The vegetation types of the sample plot are grassland, shrub, Sabina przewalskii and Picea crassifolia. The self-made Lysimeter is mainly used to observe the soil evapotranspiration characteristics in Picea crassifolia forestry. To provide basic data for the development of watershed evapotranspiration model. At about 19:00 every day, an electronic scale with an accuracy of 1g is used to weigh the inner barrel. In case of rain, observe whether there is leakage in the leakage barrel. If there is leakage, measure the leakage amount in the leakage barrel as well. The observation period in 2011 is from May 30 to September 10. The observation period in 2012 is from June 11 to September 10. Observation instrument: 1) standard 20cm diameter rain tube rain gauge. 2) self-made lysimeter (diameter 30.5cm, barrel height 28.5). 3) Electronic balance (accuracy: 0.1g) used to observe the weight change of self-made lysimeter.
ZHAO Chuanyan, MA Wenying
This meteorological data is the basic meteorological data of air temperature, relative humidity, wind speed, precipitation, air pressure, radiation, soil temperature and humidity observed in the observation site (86.56 ° e, 28.21 ° n, 4276m) of the comprehensive observation and research station of atmosphere and environment of Qomolangma, Chinese Academy of Sciences from 2019 to 2020. Precipitation is the daily cumulative value. All data are observed and collected in strict accordance with the instrument operation specifications, and some obvious error data are eliminated when processing and generating data The data can be used by students and scientific researchers engaged in meteorology, atmospheric environment or ecology (Note: when using, it must be indicated in the article that the data comes from Qomolangma station for atmospheric and environmental observation and research, Chinese Academy of Sciences (QOMS / CAS))
XI Zhenhua
This data is a 5km monthly hydrological data set, including grid runoff and evaporation (if evaporation is less than 0, it means condensation; if runoff is less than 0, it means precipitation is less than evaporation), simulated and output through the WEB-DHM distributed hydrological model of the Indus River basin, with temperature, precipitation, barometric pressure, etc. as input data.
WANG Lei, LIU Hu
Zoige Wetland observation point is located at Huahu wetland (102 ° 49 ′ 09 ″ E, 33 ° 55 ′ 09 ″ N) in Zoige County, Sichuan Province, with an initial altitude of 3435 m. The underlying surface is the alpine peat wetland, with well-developed vegetation, water and peat layer. This data set is the meteorological observation data of Zoige Wetland observation point from 2017 to 2019. It is obtained by using Kipp&Zonen CNR4, Vaisala HMP155A, PTB110 and other instruments. The time resolution is half an hour, mainly including wind speed, wind direction, air temperature, relative humidity, air pressure, downward short wave radiation, downward long wave radiation.
MENG Xianhong, LI Zhaoguo
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