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.
Soil freezing depth (SFD) is necessary to evaluate the balance of water resources, surface energy exchange and biogeochemical cycle change in frozen soil area. It is an important indicator of climate change in the cryosphere and is very important to seasonal frozen soil and permafrost. This data is based on Stefan equation, using the daily temperature prediction data and E-factor data of canems2 (rcp45 and rcp85), gfdl-esm2m (rcp26, rcp45, rcp60 and rcp85), hadgem2-es (rcp26, rcp45 and rcp85), ipsl-cm5a-lr (rcp26, rcp45, rcp60 and rcp85), miroc5 (rcp26, rcp45, rcp60 and rcp85) and noresm1-m (rcp26, rcp45, rcp60 and rcp85), The data set of annual average soil freezing depth in the Qinghai Tibet Plateau with a spatial resolution of 0.25 degrees from 2007 to 2065 was obtained.
The data set contains soil physicochemical properties of ten scientific expedition routes in Qinghai-Tibet Plateu during 2019-2021, including sample colletor, sampling time, sampling location, longitude and latitude, altitude, vegetation type, sampling depth, soil water content, pH, organic matter content, total carbon content, total nitrogen content, total phosphorus content, inorganic nitrogen content, heavy metal elements content, and etc. The physicochemical properties were measured in the laboratory with quality control, including measuring blanks, replicates and standard samples.The data set can be used for evaluating soil quality and function under the influence of climate change and human activities.
Soil is mineral particles of different sizes formed by weathering of rocks. Soil not only provides nutrients and water for crops, but also has a transforming effect on various nutrients. In addition, the soil also has a self-cleaning function, which can improve organic matter content, soil temperature and humidity, pH value, anion and cation. The soil pollution causes several environmental problems: industrial sewage, acid rain, exhaust emissions, accumulations, agricultural pollution. After the land is polluted, the contaminated tops with high concentration of heavy metals are easily entered under the action of wind and water. Other secondary ecological and environmental problems such as air pollution, surface water pollution, groundwater pollution and ecosystem degradation in the atmosphere and water.he data set comes from the World Soil Database (Harmonized World Soil Database version 1.1) (HWSD) UN Food and Agriculture (FAO) and the Vienna International Institute for Applied Systems Research Institute (IIASA) constructed, which provides data model input parameters for the modeler, At the same time, it provides a basis for research on ecological agriculture, food security and climate change.
Field surveys and soil sample collection were carried out in river and lake source of the Tibet Autonomous Region, and a total of 150 soil samples were collected, from August to September 2020. The data set includes serial number, plot number, latitude and longitude, altitude, soil moisture content, bulk density, organic matter, total nitrogen, total phosphorus, total potassium, pH and mechanical composition (sand, silt and clay content). The data format is an Excel table . The determination of various soil properties refers to the requirements of the "Technical Specifications for Soil Environmental Quality Monitoring" and is obtained through field sampling and indoor testing. Soil bulk density was measured in 5–10 cm and 15–20 cm soil layers, respectively. The mechanical composition is divided into sand (2–0.02 mm), silt (0.02–0.002 mm) and clay (< 0.002 mm) according to the International System of Classification. The soil is removed from impurities such as gravel and roots and crushed. The determination of soil organic matter, total nitrogen, total phosphorus and total potassium is a complete sample. The pH was determined by potentiometric method, and the water-soil ratio was 2.5:1. The collection of soil samples refers to the soil sample collection specifications, and the indoor analysis and testing refers to standard analysis methods. The data quality is controlled by measuring duplicate samples and standard samples. This data can provide data supporting for comprehensive assessment of the environmental effects of typical land use changes.
This data-set contains the field measurements of ecosystem respiration, soil temperature and soil water content along the altitudinal gradient (30°30′-30°32′N, 91°03′E; 4500 m, 4600 m, 4700 m, 4800 m, 4900 m, 5000 m, 5100 m, 5200 m). The period of this data-set is from June to September of 2021. On sunny days during the growing season (June–September) of 2021, diurnal variation (08:00–18:00, local time) of ecosystem respiration were measured using the opaque chamber of Li-8100 103 automatic soil CO2 flux system (LI-COR Biosciences, Lincoln, NE, USA). Soil temperature and soil moisture at each collar were measured simultaneously with Re by a Time Domain Reflectometer.
This data set includes 4 data files, which are: (1) Land use survey data set_ Qilian - Altun Mountain (2021), including 31 survey points at the Qilian - Altun Mountain land use survey data, including survey time, location, latitude and longitude, altitude, slope aspect, main vegetation types and dominant species. (2) chlorophyll content of dominant species data_ Qilian - Altun Mountain (2021), including the chlorophyll content of dominant species in 31 investigation points of Qilian- Altun area. Five leaves are selected for each plant to measure the chlorophyll content in the upper, middle and lower parts of the leaves; (3) Leaf area index survey data _ Qilian - Altun Mountain (2021), including the survey data and calculated average value of leaf area index of main vegetation types at 31 survey points in Qilian-Altun area, the data was measured by SunScan canopy analyzer; (4) Survey data of soil temperature and humidity _ Qilian - Altun Mountain (2021), including longitude and latitude, altitude, soil surface temperature and soil humidity at 30cm of 31 survey points in Qilian-Altun area, the data are recorded as three repeated measurements at each survey point. This data set can be used to analyze and study the law of vegetation environmental change on the Qinghai Tibet Plateau.
The data set is defined as the content of carbon and nutrition along a vertical and horizontal transect in the Tibetan Plateau: including the soil content of carbon and nutrition data at the 8 sites, and the data of leaf carbon and nutrition content at the 22 sites of vertical transect and the 5 sites of horizontal transect.
1) Data content: data set of soil physical and chemical properties compared inside and outside the grassland fence project, including quadrat number, grassland type, survey County, survey location, project type, sampling time, project start time, duration, "longitude (° E)", "latitude (° n)", "altitude (m)", "pH (0-15cm)", "pH (15-30cm)", "SOM (0-15cm (‰))," SOM 15-30cm (‰)) "TN(0-15（‰）)"、"TN(15-30（‰）)"、"TP(0-15（‰）)"、"TP(15-30（‰）)" 2) Data source: field sampling data 3) Data quality: high quality 4) Data application prospect: the grassland fence project on the Qinghai Tibet Plateau will achieve remarkable results in protecting grassland and restoring regional vegetation productivity. The implementation of the project provides a broader space for the development of regional animal husbandry and ensures the stable growth of local farmers' and herdsmen's income and regional economy. In addition, the implementation of the project ensures and supports the normal production and life of herdsmen in Tibet, and realizes the grassland protection in the pastoral area and the stable development of herdsmen's animal husbandry production, which is of great significance to maintaining the overall stability of Tibetan society and promoting the sound and rapid development of Tibet
Soil is the basis of human survival and development. Many United Nations Sustainable Development Goals (SDGs) are directly related to the utilization and management of soil resources. However, most of the existing soil information in the world and China comes from historical soil survey, which is coarse and out-of-date, and can not meet the needs of dealing with global and regional problems such as food security, water shortage, land degradation and climate change. China has a vast territory with complex and diverse soil landscape and strong human activities. The establishment of high-precision soil information grid is of great significance in scientific frontier breakthrough and has broad prospects in applications. Here, we adopted predictive soil mapping paradigm and developed adaptive depth function fitting method and integrated it with state-of-the-art ensemble machine learning in a high performance parallel computing environment to generate 90-m resolution national gridded maps of soil properties (soil organic carbon, pH value, total nitrogen, total phosphorus, total potassium, cation exchange capacity, coarse fragments (> 2mm), sand, silt, clay, soil texture classes, bulk density, soil thickness, etc.) at multiple depths across China. Their uncertainty in soil predictions is also estimated in a spatial way. This was based on more than 5000 representative soil profile samples obtained from the "project of National Soil Series Survey and Compilation of Soil Series of China" in recent years and a suite of detailed covariates to characterize soil-forming environments using geographical information and remote sensing techniques. Compared with previous soil maps, we achieved significantly more detailed and accurate predictions which could well represent soil variations across the territory. This work has constructed China's first version of high-resolution National Soil Information Grids, which is also a significant contribution to the GlobalSoilMap.net project. It is expected to have a wide application prospect in the fields of soil resources, agriculture, hydrology, ecology, climate, environment and so on, such as soil monitoring and management, soil function evaluation, land surface process modelling and forensic soil evidence provenance.