The data set records the water quality of centralized drinking water sources in county-level cities and towns of Qinghai Province in 2016. Data statistics from the Department of natural resources of Qinghai Province, the data set contains 16 data tables, which are: water quality of centralized drinking water sources in county-level cities and towns of Qinghai Province in the first quarter of 2016, water quality of centralized drinking water sources in county-level cities and towns of Qinghai Province in the second quarter of 2016, water quality of centralized drinking water sources in county-level cities and towns of Qinghai Province in the third quarter of 2016, and water quality of centralized drinking water sources in county-level cities and towns of Qinghai Province in the fourth quarter of 2016 Water quality of drinking water sources In the second half of 2016, the water quality of centralized drinking water sources in county-level cities and towns of Qinghai Province, the water quality of centralized drinking water sources in county-level cities and towns of Qinghai Province in the second half of 2016, the water quality of centralized drinking water sources in county-level cities and towns of Qinghai Province in the first quarter of 2017, and the water quality of centralized drinking water sources in county-level cities and towns of Qinghai Province in the second quarter of 2017 The quality of drinking water sources, the quality of centralized drinking water sources in county-level cities and towns of Qinghai Province in the third quarter of 2017, the quality of centralized drinking water sources in county-level cities and towns of Qinghai Province in the fourth quarter of 2017, the quality of centralized drinking water sources in county-level cities and towns of Qinghai Province in the first quarter of 2018, the quality of centralized drinking water sources in county-level cities and towns of Qinghai Province in the second quarter of 2018, and the quality of centralized drinking water sources in Qinghai Province in the third quarter of 2018 Water quality of centralized drinking water sources in county-level cities and towns, water quality of centralized drinking water sources in county-level cities and towns of Qinghai Province in the fourth quarter of 2018, water quality of centralized drinking water sources in county-level cities and towns of Qinghai Province in the first quarter of 2020, water quality of centralized drinking water sources in county-level cities and towns of Qinghai Province in the second quarter of 2020, and water quality of centralized drinking water sources in county-level cities and towns of Qinghai Province in the third quarter of 2020, The data table has the same structure. Each data table has six fields: Field 1: serial number Field 2: city name Field 3: water source name Field 4: water source type Field 5: compliance type
Department of Natural Resources of Qinghai Province
The data set records the information disclosure data (2018) of centralized drinking water quality monitoring and safety status in cities and towns at or above the county level in Xining city. The data statistics are from the Department of ecological environment of Qinghai Province, and the data set contains three documents, which are respectively: information disclosure form of centralized drinking water quality monitoring and safety status in cities and towns at or above the county level of Xining City in the first quarter of 2018, information disclosure form of centralized drinking water quality monitoring and safety status in cities and towns at or above the county level of Xining City in the second quarter of 2018, information disclosure form of centralized drinking water quality monitoring and safety status in cities and towns at or above the county level of Xining City in the second quarter of 2018 In the second half of 2018, the structure of the data sheet is the same. There are 10 fields in each data table Field 1: serial number Field 2: name of water source Field 3: water level Field 4: water source type Field 5: monitoring unit Field 6: number of monitoring indicators Field 7: monitoring frequency Field 8: evaluation criteria Field 9: pass rate Field 10: public period
Department of Ecology and Environment of Qinghai Province
The data set records the dynamic statistical data of groundwater level in the monitoring area of Ping'an district (Ping'an County) of Xining city from 2014 to 2018. The data is collected from the Department of natural resources of Qinghai Province, and the data set contains five data tables, which are: the groundwater level dynamic of Haidong monitoring area in 2014, the groundwater level dynamic statistical table of Ping'an monitoring area in 2015, the groundwater level dynamic statistical table of Ping'an monitoring area in 2016, the groundwater level dynamic statistical table of Ping'an monitoring area in 2017, and the groundwater level dynamic statistical table of Ping'an monitoring area in 2018 Sketch Map. The data table has the same structure and contains four fields Field 1: year Field 2: n16 Field 3: n34 Field 4: N46
Department of Natural Resources of Qinghai Province
The monitoring data set of surface water quality in Xining city of Qinghai Province was collected from July, 2015 to July, 2015. The data is collected from the Department of ecological environment of Qinghai Province. The data set contains 15 data tables, which are: surface water quality of Xining City in July 2015, surface water quality of Xining City in November 2015, surface water quality of Xining City in January 2016, and surface water quality of Xining City in February 2016. The data table structure is the same. There are six fields in each data table, such as the monitoring section water quality table of Xining surface water in July 2015 Field 1: serial number Field 2: section name Field 3: executive standard level Field 4: actual water quality grade Field 5: over standard items
Department of Ecology and Environment of Qinghai Province
The data set records the statistical data of groundwater levels in Beichuan, Xichuan and Nanchuan of Xining City (2012-2018). The data is collected from the Department of natural resources of Qinghai Province. The data set contains 31 data tables, including the groundwater level of Nanchuan in Xining City in 2011, the groundwater level of Beichuan in Xining City in 2011, the groundwater level of Xichuan and xinachuan in Xining City in 2011, and the groundwater level of Beichuan in Xining City in 2012. The data are grouped by year, and the unit is meter (m). The data table has the same structure and contains five fields Field 1: year G9103: Field Field 3: G31 Field 4: G23 Field 5: G27
Department of Natural Resources of Qinghai Province
The data set records the monthly water quality monitoring and evaluation data of Huangshui river monitoring section from January 2008 to June 2020. The data set consists of 146 Excel / PDF data files. They are water quality assessment.xls in January 2008, water quality assessment.xls in February 2008 Water quality assessment of national control section of Huangshui River in June 2020.xls. Data monitoring points include: Jintan and zhamalong section of Huangshui mainstream; Xiaoxia bridge section; Minhe bridge section. The detection indicators include: water environment function zoning category, water quality category, main pollution indicators, water quality status, water quality status in last month, and water quality status in the same period of last year. The data table has the same structure and contains 7 fields Field 1: section name Field 2: water environment function zoning category Field 3: water quality category Field 4: main pollution indicators Field 5: water quality status Field 6: water quality last month Field 7: water quality in the same period last year
Department of Ecology and Environment of Qinghai Province
The data set records the statistical table of groundwater level dynamic changes in various monitoring areas of Qinghai Province from 2015 to 2018. The data are recorded from the Department of natural resources of Qinghai Province, and the data set contains four data tables, which are: the statistical table of groundwater level dynamic change in each monitoring area of Qinghai Province in 2015, the statistical table of groundwater level dynamic change in each monitoring area of Qinghai Province in 2016, the statistical table of groundwater level dynamic change in each monitoring area of Qinghai Province in 2017, and the statistical table of groundwater level dynamic change in each monitoring area of Qinghai Province in 2018 The data table has the same structure and contains 7 fields Field 1: "geographic location" Field 2: "basic balance area (km2)" Field 3: "percentage of monitoring area (%)" Field 4: "weak descent area (km2)" Field 5: "percentage (%) of monitored area" Field 6: "strong uplift area (km2)" Field 7: "percentage (%) of monitored area"
Department of Natural Resources of Qinghai Province
The data set records the water quality of centralized drinking water sources in prefecture level cities of Qinghai Province from January 2016 to August 2020. The data is collected from the Department of natural resources of Qinghai Province. The data set contains 48 Excel data sheets, which are: water quality of centralized drinking water sources in prefecture level cities of Qinghai Province in January 2016, water quality of centralized drinking water sources in prefecture level cities of Qinghai Province in February 2016 In August 2020, the water quality of centralized drinking water sources in prefecture level cities of Qinghai Province has the same data table structure. There are six fields in each data table, such as the water quality of centralized drinking water sources in prefecture level cities of Qinghai Province in February 2016 Field 1: serial number Field 2: city name Field 3: water source name Field 4: water source type Field 5: compliance Field 6: over standard index and over standard multiple
Department of Natural Resources of Qinghai Province
The dataset is the ground verification point dataset of land cover and vegetation type in the Source Region of the Yangtze River (in the south of Qinghai Province) which collected during August 2018. In the dataset, the homogeneous patches are considered as the main targets of this collection. They are easy to be recognized out and distinguished from other vegetation types. And these samples have high representativeness comparing with other land surface features. In each sample, the geographical references, longitude and latitude (degree, minute, second), time (24h) and elevation (0.1m) are recorded firstly according to GPS positioning. Vegetation types, constructive species, characteristics, land types and features, landmarks, etc. are recorded into the property table manually for checking in laboratory. At last, each sample place has been taken at least 1 photography. In this dataset, 90% or more samples have been taken 2 or more in field landscape photographs for land use type and vegetation classification examination. We have carefully examined the position accuracy of each sample in Google Earth. After 2 rounds of checking and examination, the accuracy and reliability of the property of each sample have been guaranteed.
WANG Xufeng
The dataset is the ground verification point dataset of land cover and vegetation type in the Source Region of Yellow River (in the north of Zaling Lake, Qinghai Province) which collected during August 2018. In the dataset, the homogeneous patches are considered as the main targets of this collection. They are easy to be recognized out and distinguished from other vegetation types. And these samples have high representativeness comparing with other land surface features. In each sample, the geographical references, longitude and latitude (degree, minute, second), time (24h) and elevation (0.1m) are recorded firstly according to GPS positioning. Vegetation types, constructive species, characteristics, land types and features, landmarks, etc. are recorded into the property table manually for checking in laboratory. At last, each sample place has been taken at least 1 photography. In this dataset, 90% or more samples have been taken 2 or more in field landscape photographs for land use type and vegetation classification examination. We have carefully examined the position accuracy of each sample in Google Earth. After 2 rounds of checking and examination, the accuracy and reliability of the property of each sample have been guaranteed.
WANG Xufeng
The dataset is the ground verification point dataset of land cover and vegetation type in the Hoh Xil (in the northwest of Qinghai Province) which collected during August 2018. In the dataset, the homogeneous patches are considered as the main targets of this collection. They are easy to be recognized out and distinguished from other vegetation types. And these samples have high representativeness comparing with other land surface features. In each sample, the geographical references, longitude and latitude (degree, minute, second), time (24h) and elevation (0.1m) are recorded firstly according to GPS positioning. Vegetation types, constructive species, characteristics, land types and features, landmarks, etc. are recorded into the property table manually for checking in laboratory. At last, each sample place has been taken at least 1 photography. In this dataset, 90% or more samples have been taken 2 or more in field landscape photographs for land use type and vegetation classification examination. We have carefully examined the position accuracy of each sample in Google Earth. After 2 rounds of checking and examination, the accuracy and reliability of the property of each sample have been guaranteed.
WANG Xufeng
This data set includes meteorological data observed by the carbon flux station in the Guoluo Army Ranch in Qinghai. The temporal coverage is from 2005 to 2009, and the temporal resolution is 1 day. Meteorological and carbon flux data observation methods: vorticity-related observation instruments were used for automatic recording; biomass observation method: harvest method, weighing in a 60-degree oven for 48 hours. Both carbon flux and meteorological data were automatically recorded by the instruments and manually checked. During the data observation process, the operation of the instrument and the selection of the observation objects were in strict accordance with professional requirements, and the data could be applied to plant leaf photosynthetic parameter simulation and productivity estimation. This data contains observation items as follows: Temperature °C Precipitation mm Wind speed m/s Soil temperature at 5 cm depth °C Photosynthetically active radiation µmol/m²s Total radiation W/m²
ZHAO Xinquan
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