The data set contains three tables: the livestock number and meat production in each county, the production of milk and fur, and the year-end livestock number. These tables contain time series data on the livestock number and livestock products in Tibet from 1951 to 2016. The data were derived from the Tibet Society and Economics Statistical Yearbook and Tibet Statistical Yearbook. The accuracy of the data is consistent with that of the statistical yearbooks. Table 1: The table of livestock number and meat production contains 8 fields. Field 1: Year of the data Field 2: Districts and counties included in the data Field 3: The year-end number of all year-end livestock, unit: 10,000 Field 4: The number of large livestock, unit: 10,000 Field 5: The number of sheep, unit: 10,000 Field 6: Total meat production, unit: ton Field 7: Beef production, unit: ton Field 8: Sheep meat production, unit: ton Table 2: The table of milk and fur production contains 8 fields. Field 1: Year of the data Field 2: Districts and counties included in the data Field 3: Milk production, unit: ton Field 4: Cow milk production, unit: ton Field 5: Goat wool production, unit: ton Field 6: Sheep wool production, unit: ton Field 7: The number of sheep skins, unit: piece Field 8: The number of cattle hides, unit: piece Table 3: The table of year-end livestock number contains 7 fields. Field 1: Year of the data Field 2: The total number of all livestock, unit: 10,000 Field 3: The number of large livestock unit: 10,000 Field 4: The number of cattle, unit: 10,000 Field 5: The number of goats, unit: 10,000 Field 6: The number of sheep, unit: 10,000 Field 7: The number of pigs, unit: 10,000
National Bureau of Statistics
The data set contains statistics on enterprises in Tibet over time. The data were derived from the Tibet Society and Economics Statistical Yearbook and Tibet Statistical Yearbook. The accuracy of the data is consistent with that of the statistical yearbooks. The table contains 5 fields. Field 1: Districts and counties Field 2: Year Field 3: Number of industrial enterprises above the state-designated scale Field 4: Total industrial output value of industrial enterprises above the state-designated scale (current price), unit: 10,000 yuan Field 5: Urban completed investment in fixed assets, unit: 10,000 yuan
National Bureau of Statistics
The data set describes the social welfare and medical care statistics in Tibet over time. The data include the number of beds in hospitals, the number of social welfare institutions, and the number of beds in social welfare institutions. The data were derived from the Tibet Society and Economics Statistical Yearbook and Tibet Statistical Yearbook. The accuracy of the data is consistent with that of the statistical yearbooks. The table contains 6 fields. Field 1: Districts and counties Field 2: Year Field 3: Number of beds in hospitals per 10,000 people Field 4: Number of beds in hospitals Field 5: Number of social welfare institutions Field 6: Number of beds in social welfare institutions
National Bureau of Statistics
This data set contains statistics on the social welfare and medical care in Qinghai over time. The data set includes the number of beds in hospitals, the number of social welfare institutions, and the number of beds in social welfare institutions. The data were derived from the Qinghai Society and Economics Statistical Yearbook and Qinghai Statistical Yearbook. The accuracy of the data is consistent with that of the statistical yearbooks. The table contains 6 fields. Field 1: Districts and counties Field 2: Year Field 3: Number of beds in hospitals per 10,000 people Field 4: Number of beds in hospitals Field 5: Number of social welfare institutions Field 6: Number of beds in social welfare institutions
Qinghai Provincial Bureau of Statistics
The data set recorded the sequence local fiscal revenue, state financial subsidy revenue and local fiscal expenditure data in Qinghai from 1957 to 2016. The data were derived from the Qinghai Society and Economics Statistical Yearbook and the Qinghai Statistical Yearbook. The accuracy of the data is consistent with that of the statistical yearbook. Table 1: The table of fiscal revenue and expenditure in Qinghai contains 9 fields. Field 1: Year Interpretation: Year of the data Field 2: Total fiscal revenue Unit: 10,000 yuan Field 3: State financial subsidy revenue Unit: 10,000 yuan Field 4: General Budget Expenditure Unit: 10,000 yuan Field 5: Central Interpretation: Fiscal revenue transferred from the central finance Unit: 10,000 yuan Field 6: Local Interpretation: Local fiscal revenue Unit: 10,000 yuan Field 7: Fiscal expenditure Unit: 10,000 yuan Field 8: The proportion of local general budget fiscal revenue in total revenue Unit: % Field 9: The proportion of local general budget fiscal revenue in total expenditure Unit: % Table 2: The table of the individual counties’ fiscal revenues and expenditures contains 6 fields. Field 1: Districts and counties Field 2: Year Field 3: Local general budget fiscal revenue Unit: 10,000 yuan Field 4: Local general budget fiscal expenditure Unit: 10,000 yuan Field 5: Savings and deposit balances of urban and rural residents Unit: 10,000 yuan Field 6: Year-end balance of various loans of financial institutions Unit: 10,000 yuan
Qinghai Provincial Bureau of Statistics
This data set contains time series data on rural electronic power, irrigated area, and fertilizer application in Qinghai from 1978 to 2016. The data were derived from the Qinghai Society and Economics Statistical Yearbook and Qinghai Statistical Yearbook. The accuracy of the data is consistent with that of the statistical yearbooks. Table 1: The table of rural electronic power, irrigated area, and fertilizer application contains 6 fields. Field 1: Year of the data Field 2: Number of township hydropower stations Field 3: Capacity of township hydropower stations, unit: 10,000 kilowatt Field 4: Electricity consumption in rural areas, unit: 10,000 kW/h Field 5: Fertilizer application amount, unit: ton Field 6: Effective irrigation area, unit: 1000 hectares Table 2: The table of electricity power, telephone, fertilizer and plastic-film application in each county contains 7 fields. Field 1: Districts and counties Field 2: Year Field 3: Total power of agricultural machinery, unit: 10,000 kW Field 4: Year-end local telephone users Field 5: Fertilizer application amount, unit: ton Field 6: Plastic-film application amount, unit: ton Field 7: Electricity consumption in rural areas, unit: 10,000 kW/h
Qinghai Provincial Bureau of Statistics, Qinghai Provincial Bureau of Statistics
The data set contains data on the natural resources in Tibet from 1988 to 1994. The data were derived from the Tibet Society and Economics Statistical Yearbook and Tibet Statistical Yearbook. The accuracy of the data is consistent with that of the statistical yearbooks. The table contains 37 fields. Field 1: Year Field 2: Total surface area of the whole region, unit: 10,000 square kilometres. Field 3: Cultivated land area, unit: 10,000 mu (1 mu=0.0667 hectares) Field 4: Paddy field area, unit: 10,000 mu (1 mu=0.0667 hectares) Field 5: Forest area, unit: 10,000 mu (1 mu=0.0667 hectares) Field 6: Forest coverage proportion, unit: % Field 7: Forest stocks, unit: 100 million cubic metres Field 8: Grassland area, unit: 100 million mu (1 mu=0.0667 hectares) Field 9: Grassland available area, unit: 100 million mu (1 mu=0.0667 hectares) Field 10: Total annual runoff of rivers, unit: 100 million cubic metres. Field 11: Hydraulic resource reserves, unit: 10,000 kilowatt Field 12: Hydraulic potential exploitation amount, unit: 10,000 kilowatt Field 13: Length of the national boundary, unit: kilometres Field 14: Iron mine reserve amount, unit: 100 million tons Field 15: Chromite reserve amount, unit: 10,000 tons Field 16: Copper (ore), unit: 100 million tons Field 17: Borate ore reserve amount, unit: 10,000 tons Field 18: Salt reserve amount, unit: 100 million tons Field 19: Graphite reserve amount, unit: 10,000 tons Field 20: Gypsum reserve amount, unit: 100 million tons Field 21: Coal reserve amount, unit: 10,000 tons Field 22: Peat reserve amount, unit: 10,000 tons Field 23: Geothermal reserve amount, unit: 10,000 cubic metres / day and night Field 24: Species number of national key protected animals Field 25: Species number of class 1 national key protected animals Field 26: Species number of class 2 national key protected animals Field 27: Species number of national key protected plants Field 28: Species number of class 1 national key protected plants Field 29: Species number of class 2 national key protected plants Field 30: Species number of class 3 national key protected plants Field 31: Number of nature reserves Field 32: Number of national nature reserves Field 33: Number of local nature reserves Field 34: Total area of nature reserves, unit: 10,000 mu Field 35: Proportion of nature reserves to the total area of the region Field 36: Annual average precipitation, unit: mm Field 37: Annual sunshine duration, unit: hour
National Bureau of Statistics
The data set contains two tables detailing the total cultivated land area and the cultivated land area in every county at the end of each year. The data are time series data of cultivated land, dry land, paddy field and effective irrigated area in Tibet from 1959 to 2016 and were derived from the Tibet Society and Economics Statistical Yearbook and Tibet Statistical Yearbook. The accuracy of the data is consistent with that of the statistical yearbooks. Table 1: The table of cultivated land area contains 7 fields. Field 1: Year of the data Field 2: Year-end actual cultivated land area, unit: 1000 hectares Field 3: Dry land area, unit: 1000 hectares Field 4: Paddy field area, unit: 1000 hectares Field 5: Reduced area in the current year, unit: 1000 hectares Field 6: Land occupation of national infrastructure, unit: 1000 hectares Field 7: Increased area in the current year, unit: 1000 hectares Table 2: The table of year-end cultivated land area in each county contains 5 fields. Field 1: Year of the data Field 2: The districts and counties included in the data Field 3: Actual cultivated land area, unit: hectare Field 4: Dry land area, unit: hectare Field 5: Effective irrigated area, unit: hectare
National Bureau of Statistics
The data set contains time series data on the number and proportion of employees in state-owned enterprises, urban collective-owned enterprises and other types of enterprises in Tibet over time. The data were derived from the Tibet Society and Economics Statistical Yearbook and Tibet Statistical Yearbook. The accuracy of the data is consistent with that of the statistical yearbooks. The table contains 8 fields. Field 1: Year of the data Field 2: Total number of employees Field 3: Number of employees in state-owned enterprises Field 4: Number of employees in urban collective-owned enterprises Field 5: Number of employees in other types of enterprises Field 6: Proportion of workers employed by state-owned enterprises, unit: % Field 7: Proportion of workers employed by urban collective-owned enterprises, unit: % Field 8: Proportion of workers employed by other types of enterprises, unit: %
National Bureau of Statistics
The data set mainly recorded the series data of GDP, gross industrial output, and gross agricultural output in major cities and counties of the Tibetan Plateau from 1970 to 2006. It is used to study social and economic changes on the Tibetan Plateau. The table has ten fields. Field 1: Year Interpretation: Year of the data Field 2: Province Interpretation: The province from which the data were obtained Field 3: City/Prefecture Interpretation: The city or prefecture from which the data were obtained Field 4: County Interpretation: The name of the county Field 5: GDP (10,000 yuan) Interpretation: Gross domestic product Field 6: Gross Industrial and Agricultural Output (10,000 Yuan) Interpretation: Gross Industrial and Agricultural Output Field 7: Gross Agricultural Output (10,000 Yuan) Interpretation: Gross Agricultural Output Field 8: Gross Industrial Output (10,000 Yuan) Interpretation: Gross Industrial Output Field 9: Data Sources Interpretation: Source of Data Extraction Field 10: Remarks Interpretation: Calculation method of gross out value and description of constant prices The data comes from the statistical yearbook and county annals. Some are listed as follows. [1] Gansu Yearbook Editorial Committee. Gansu Yearbook [J]. Beijing: China Statistics Press, 1984, 1988-2009 [2] Statistical Bureau of Yunnan Province. Yunnan Statistical Yearbook [J]. Beijing: China Statistics Press, 1988-2009 [3] Statistical Bureau of Sichuan Province, Sichuan Survey Team. Sichuan Statistical Yearbook [J]. Beijing: China Statistics Press, 1987-1991, 1996-2009 [4] Statistical Bureau of Xinjiang Uighur Autonomous Region . Xinjiang Statistical Yearbook [J]. Beijing: China Statistics Press, 1989-1996, 1998-2009 [5] Statistical Bureau of Tibetan Autonomous Region. Tibet Statistical Yearbook [J]. Beijing: China Statistics Press, 1986-2009 [6] Statistical Bureau of Qinghai Province. Qinghai Statistical Yearbook [J]. Beijing: China Statistics Press, 1986-1994, 1996-2008. [7] County Annals Editorial Committee of Huzhu Tu Autonomous County. County Annals of Huzhu Tu Autonomous County [J]. Qinghai: Qinghai People's Publishing House, 1993 [8] Haiyan County Annals Editorial Committee. Haiyan County Annals[J]. Gansu: Gansu Cultural Publishing House, 1994 [9] Menyuan County Annals Editorial Committee. Menyuan County Annals[J]. Gansu: Gansu People's Publishing House, 1993 [10] Guinan County Annals Editorial Committee. Guinan County Annals [J]. Shanxi: Shanxi People's Publishing House, 1996 [11] Guide County Annals Editorial Committee. Guide County Annals[J]. Shanxi: Shanxi People's Publishing House, 1995 [12] Jianzha County Annals Editorial Committee. Jianzha County Annals [J]. Gansu: Gansu People's Publishing House, 2003 [13] Dari County Annals Editorial Committee. Dari County Annals [J]. Shanxi: Shanxi People's Publishing House, 1993 [14] Golmud City Annals Editorial Committee. Golmud City Annals [J]. Beijing: Fangzhi Publishing House, 2005 [15] Delingha City Annals Editorial Committee. Delingha City Annals [J]. Beijing: Fangzhi Publishing House, 2004 [16] Tianjun County Annals Editorial Committee. Tianjun County Annals [J]. Gansu: Gansu Cultural Publishing House, 1995 [17] Naidong County Annals Editorial Committee. Naidong County Annals [J]. Beijing: China Tibetology Press, 2006 [18] Gulang County Annals Editorial Committee. Gulang County Annals [J]. Gansu: Gansu People's Publishing House, 1996 [19] County Annals Editorial Committee of Akesai Kazak Autonomous County. County Annals of Akesai Kazakh Autonomous County [J]. Gansu: Gansu People's Publishing House, 1993 [20] Minxian County Annals Editorial Committee. Minxian County Annals [J]. Gansu: Gansu People's Publishing House, 1995 [21] Dangchang County Annals Editorial Committee. Dangchang County Annals [J]. Gansu: Gansu Cultural Publishing House, 1995 [22] Dangchang County Annals Editorial Committee. Dangchang County Annals(Sequel) (1985-2005) [J]. Gansu: Gansu Cultural Publishing House, 2006 [23] Wenxian County Annals Editorial Committee. Wenxian County Annals[J]. Gansu: Gansu Cultural Publishing House, 1997 [24] Kangle County Annals Editorial Committee. Kangle County Annals [J]. Shanghai: Sanlian Bookstore. 1995 [25] County Annals Editorial Committee of Jishishan (Baoan, Dongxiang, Sala) Autonomous County. County Annals of Jishishan (Baoan, Dongxiang, Sala) Autonomous County[J], Gansu: Gansu Cultural Publishing House, 1998 [26] Luqu County Annals Editorial Committee. Luqu County Annals [J]. Gansu: Gansu People's Publishing House, 2006 [27] Zhouqu County Annals Editorial Committee. Zhouqu County Annals [J]. Shanghai: Sanlian Bookstore. 1996 [28] Xiahe County Annals Editorial Committee. Xiahe County Annals [J]. Gansu: Gansu Cultural Publishing House, 1999 [29] Zhuoni County Annals Editorial Committee. Zhuoni County Annals [J]. Gansu: Gansu Nationality Publishing House, 1994 [30] Diebu County Annals Editorial Committee. Diebu County Annals [J]. Gansu: Lanzhou University Press, 1998 [31] Pengxian County Annals Editorial Committee. Pengxian County Annals [J]. Sichuan: Sichuan People's Publishing House, 1989 [32] Guanxian County Annals Editorial Committee. Guanxian County Annals [J]. Sichuan: Sichuan People's Publishing House, 1991 [33] Wenjiang County Annals Editorial Committee. Wenjiang County Annals [J]. Sichuan: Sichuan People's Publishing House, 1990 [34] Shifang County Annals Editorial Committee. Shifang County Annals [J]. Sichuan: Sichuan University Press, 1988 [35] Tianquan County Annals Editorial Committee. Tianquan County Annals [J]. Sichuan: Sichuan Science and Technology Press, 1997 [36] Shimian County Annals Editorial Committee. Shimian County Annals [J]. Sichuan: Sichuan Cishu Publishing House, 1999 [37] Lushan County Annals Editorial Committee. Lushan County Annals [J]. Sichuan: Fangzhi Publishing House, 2000 [38] Hongyuan County Annals Editorial Committee. Hongyuan County Annals [J]. Sichuan: Sichuan People's Publishing House, 1996 [39] Wenchuan County Annals Editorial Committee. Wenchuan County Annals [J]. Sichuan: Bayu Shushe, 2007 [40] Derong County Annals Editorial Committee. Derong County Annals [J]. Sichuan: Sichuan University, 2000 [41] Baiyu County Annals Editorial Committee. Baiyu County Annals [J]. Sichuan: Sichuan University Press, 1996 [42] Batang County Annals Editorial Committee. Batang County Annals [J]. Sichuan: Sichuan Nationality Publishing House, 1993 [43] Jiulong County Annals Editorial Committee. Jiulong County Annals(Sequel) (1986-2000) [J]. Sichuan: Sichuan Science and Technology Press, 2007 [44] County Annals Editorial Committee of Derung-Nu Autonomous County Gongshan. County Annals of Derung-Nu Autonomous County Gongshan [J]. Beijing: Nationality Publishing House, 2006 [45] Lushui County Annals Editorial Committee. Lushui County Annals [J]. Yunnan: Yunnan People's Publishing House, 1995 [46] Deqin County Annals Editorial Committee. Deqin County Annals [J]. Yunnan: Yunnan Nationality Publishing House, 1997 [47] Yutian County Annals Editorial Committee. Yutian County Annals [J]. Xinjiang: Xinjiang People's Publishing House, 2006 [48] Cele County Annals Editorial Committee. Cele County Annals [J]. Xinjiang: Xinjiang People's Publishing House, 2005 [49] Hetian County Annals Editorial Committee. Hetian County Annals [J]. Xinjiang: Xinjiang People's Publishing House, 2006 [50] Qiemo County Local Chronicles Editorial Committee. Qiemo County Annals [J]. Xinjiang: Xinjiang People's Publishing House, 1996 [51] Shache County Annals Editorial Committee. Shache County Annals [J]. Xinjiang: Xinjiang People's Publishing House, 1996 [52] Yecheng County Annals Editorial Committee. Yecheng County Annals [J]. Xinjiang: Xinjiang People's Publishing House, 1999 [53] Akto County Local Chronicles Editorial Committee. Akto County Annals [J]. Xinjiang: Xinjiang People's Publishing House, 1996 [54] Wuqia County Local Chronicles Editorial Committee. Wuqia County Annals [J]. Xinjiang: Xinjiang People's Publishing House, 1995
National Bureau of Statistics
The data set contains time series data on the local fiscal revenue, state financial subsidy revenue, local fiscal expenditure, and general budget expenditure in the Tibetan Autonomous Region from 1959 to 2016. The data were derived from the Tibet Society and Economics Statistical Yearbook and Tibet Statistical Yearbook. The accuracy of the data is consistent with that of the statistical yearbooks. Table 1: The table of total fiscal revenue, expenditure and related indexes contains 9 fields. Field 1: Year of the data Field 2: Total revenue, unit: 10,000 yuan Field 3: Local fiscal revenue of Tibet, unit: 10,000 yuan Field 4: General budget revenue, unit: 10,000 yuan Field 5: State financial subsidy revenue, unit: 10,000 yuan Field 6: Total fiscal expenditure, unit: 10,000 yuan Field 7: General budget expenditure, unit: 10,000 yuan Field 8: Total revenue index, unit: % Field 9: Total expenditure index, unit: % Table 2: The table of fiscal revenue and expenditure for each county contains 5 fields. Field 1: Districts and counties Field 2: Year Field 3: Local fiscal revenue, unit: 10,000 yuan Field 4: Local general budget fiscal revenue, unit: 10,000 yuan Field 5: Year-end balance of various loans of financial institutions
National Bureau of Statistics
The data set contains time series data of various industrial products in the Tibetan Autonomous Region from 1956 to 2016, such as chrome ore, power generation, hydroelectric power, cement, etc. The data were derived from the Tibet Society and Economics Statistical Yearbook and Tibet Statistical Yearbook. The accuracy of the data is consistent with that of the statistical yearbook. The table contains 13 fields. Field 1: Year of the data Field 2: Chromium ore production, unit: ton Field 3: Power generation, unit: 10,000 kilowatt per hour Field 4: Hydroelectric power, unit: 10,000 kilowatt per hour Field 5: Cement, unit: ton Field 6: Beer production, unit: ton Field 7: Mineral water, unit: ton Field 8: Chinese traditional patent medicines, unit: ton Field 9: Flour, unit: ton Field 10: Edible vegetable oil, unit: ton Field 11: Woollen yarn, unit: ton Field 12: Carpet, unit: square metre Field 13: Clothing, unit: pair/piece
National Bureau of Statistics
The data set contains sequence data on regional GDP, primary industry, secondary industry, industry, construction business, tertiary industry and per capita regional GDP in Tibet from 1951 to 2016. The data were derived from the Tibet Society and Economics Statistical Yearbook and Tibet Statistical Yearbook. The accuracy of the data is consistent with that of the statistical yearbooks. Table 1: The table of regional GDP contains 8 fields. Field 1: Year Field 2: Regional GDP, unit: 100 million yuan Field 3: Primary industry, unit: 100 million yuan Field 4: Secondary industry, unit: 100 million yuan Field 5: Industry, unit: 100 million yuan Field 6: Construction business, unit: 100 million yuan Field 7: Tertiary industry, unit: 100 million yuan Field 8: Per capita regional GDP, unit: Yuan Table 2: The table of GDP statistics for districts and counties contains 5 fields. Field 1: Districts and counties Field 2: Year Field 3: Regional GDP, unit: 10,000 yuan Field 4: Value added of primary industry, unit: 10,000 yuan Field 5: Value added of secondary industry, unit: 10,000 yuan
National Bureau of Statistics
Taking 2005 as the base year, the future population scenario was predicted by adopting the Logistic model of population. It not only can better describe the change pattern of population and biomass but is also widely applied in the economic field. The urbanization rate was predicted by using the urbanization Logistic model. Based on the existing urbanization horizontal sequence value, the prediction model was established by acquiring the parameters in the parametric equation by nonlinear regression. The urban population was calculated by multiplying the predicted population by the urbanization rate. The data adopted the non-agricultural population. The Logistic model was used to predict the future gross national product of each county (or city), and then, according to the economic development level of each county (or city) in each period (in terms of GDP per capita),the corresponding industrial structure scenarios in each period were set, and the output value of each industry was predicted. The trend of changes in industrial structure in China and the research area lagged behind the growth of GDP and was therefore adjusted according to the need of the future industrial structure scenarios of the research area.
ZHONG Fanglei
By applying Supply-demand Balance Analysis, the water resource supply and demand of the whole river basin and each county or district were calculated, on which basis the vulnerability of the water resources system of the basin was evaluated. The IPAT equation was used to set a future water resource demand scenario, setting variables such as future population growth rate, economic growth rate, and unit GDP water consumption to establish the scenario. By taking 2005 as the base year and using assorted forecasting data of population size and economic scale, the future water demand scenarios of various counties and cities from 2010 to 2050 were predicted. By applying the basic structure of the HBV conceptual hydrological model of the Swedish Hydrometeorological Institute, a model of the variation tendency of the basin under climate change was designed. The glacial melting scenario was used as the model input to construct the runoff scenario under climate change. According to the national regulations for the water resources allocation of the basin, a water distribution plan was set up to calculate the water supply comprehensively. Considering the supply and demand situation, the water resource system vulnerability was evaluated by the water shortage rate. By calculating the (grain production) land pressure index of the major counties and cities in the basin, the balance of supply and demand of land resources under the climate change, glacial melt and population growth scenarios was analyzed, and the vulnerability of the agricultural system was evaluated. The Miami formula and HANPP model were used to calculate the human appropriation of net primary biomass and primary biomass in the major counties and cities for the future, and the vulnerability of ecosystems from the perspective of supply and demand balance was assessed.
YANG Linsheng, ZHONG Fanglei
Taking 2000 as the base year, the future population scenario prediction adopted the Logistic model of population, and it not only can better describe the change pattern of population and biomass but also is widely applied in the economic field. The urbanization rate was predicted using the urbanization Logistic model. Based on the existing urbanization horizontal sequence value, the prediction model was established by acquiring the parameters in the parametric equation applying nonlinear regression. The urban population was calculated by multiplying the predicted population by the urbanization rate. The Logistic model was used to predict the future gross national product of each county (or city), and then, according to the economic development level of each county (or city) in each period (in terms of real GDP per capita), the corresponding industrial structure scenarios in each period were set, and the output value of each industry was predicted. The trend of industrial structure changing in China and the research area lagged behind the growth of GDP, so it was adjusted according to the need of the future industrial structure scenarios of the research area.
ZHONG Fanglei
By applying supply-demand balance analysis, the water resource supply and demand of the whole river basin and each county or district were calculated, and the results were used to assess the vulnerability of the water resources system in the basin. The IPAT equation was used to establish a future water resource demand scenario, which involved setting various variables, such as the future population growth rate, economic growth rate, and water consumption per unit GDP. By taking 2005 as the base year and using assorted forecasting data of population size and economic scale, the future water demand scenarios of various counties and cities from 2010 to 2050 were predicted. By applying the basic structure of the HBV conceptual hydrological model of the Swedish Hydro-meteorological Institute, a model of the variation trends of the basin under a changing climate was designed. The glacial melting scenario was used as the model input to construct the runoff scenario in response to climate change. According to the national regulations of the water resource allocation in the basin, a water distribution plan was set up to calculate the water supply comprehensively. Considering the supply and demand situation, the water resource system vulnerability was evaluated by the water shortage rate. By calculating the grain production-related land pressure index of the major counties and cities in the basin, the balance of supply and demand of land resources in scenarios of climate change, glacial melting and population growth was analysed, and the vulnerability of the agricultural system was evaluated. The Miami formula and HANPP model were used to calculate the human appropriation of net primary biomass and primary biomass in the major counties and cities in the future, and the vulnerability of ecosystems from the perspective of supply and demand balance was assessed.
YANG Linsheng, ZHONG Fanglei
Taking 2005 as the base year, the future population scenario was predicted by adopting the logistic model of population. This model not only effectively describes the pattern of changes in population and biomass but is also widely applied in the field of economics. The urbanization rate was predicted using the urbanization logistic model. Based on the observed horizontal pattern of urbanization, a predictive model was established by determining the parameters in the parametric equation by applying nonlinear regression. The urban population was calculated by multiplying the predicted population by the urbanization rate. The data represent the non-agricultural population. The logistic model was used to predict the future gross domestic product of each county (or city), and then the economic development level of each county (or city) in each period (in terms of GDP per capita). The corresponding industrial structure scenarios in each period were set, and the output value of each industry was predicted. The trend of industrial structure changes in China and the research area lagged behind the growth in GDP, so the changes were adjusted according to the need for future industrial structure scenarios in the research area.
YANG Linsheng, ZHONG Fanglei
The main body of the Tibetan Plateau is Qinghai Province and the Tibetan Autonomous Region. The economic and social data of Qinghai Province and the Tibetan Autonomous Region are the basis for the analysis and assessment of the basic data of sustainable development of populations, resources, environment and economic society on the Tibetan Plateau by integrating the basic data of natural sciences. Under normal circumstances, the statistical yearbooks of all provinces and regions are all in paper and CD-ROM versions, and users need to perform secondary editing before they can use them. This data set mainly relies on the raw data of the Statistical Yearbook of Qinghai Province and the Tibetan Autonomous Region to carry out data conversion and integrate the current economic and social data sets. The temporal coverage of the data is from 2007 to 2016, and the temporal resolution is one year. The spatial coverage is Qinghai Province and the Tibetan Autonomous Region of the Tibetan Plateau. The spatial resolution is the administrative unit of the prefecture or city. The data include information on population, economy, finance, agriculture, forestry, animal husbandry and fishery, investment in fixed assets, education and health.
WANG Shijin
Taking 2005 as the base year, the future population scenario prediction adopted the Logistic model of population, and it not only can better describe the change pattern of population and biomass but is also widely applied in the economic field. The urbanization rate was predicted using the urbanization Logistic model. Based on the existing urbanization horizontal sequence value, the prediction model was established by acquiring the parameters in the parametric equation applying nonlinear regression. The urban population was calculated by multiplying the predicted population by the urbanization rate. The Logistic model was used to predict the future gross national product of each county (or city), and then, according to the economic development level of each county (or city) in each period (in terms of real GDP per capita),the corresponding industrial structure scenarios in each period were set, and each industry’s output value was predicted. The trend of changes in industrial structure in China and the research area lagged behind the growth of GDP, and, therefore, it was adjusted according to the need of the future industrial structure scenarios of the research area.
ZHONG Fanglei, YANG Linsheng
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