关键词: 水-能源-粮食, 压力指数, 时空变异, 驱动力, 主成分分析, 地理加权回归

Abstract:

As the basis of regional development, water-energy-food (W-E-F) is usually a bottleneck too. China’s strategy of sustainable development has been threatened and challenged by the spatially unbalanced distribution and the insufficient total amount of the water-energy-food supply, and the unbalanced socioeconomic development. Each year from 1997 to 2015, three pressure indices (i.e. water pressure index, energy pressure index and food pressure index) were decomposed into three orthotropic vectors by using principal component analysis, and the W-E-F pressure index were then calculated and created by vector synthesis method. For the thirty province units in China (no data are available for Hong Kong, Macao and Taiwan and no energy data for Tibet), after the temporal variations of the water pressure index, the energy pressure index, the food pressure index and the W-E-F pressure index were checked, eight variables (i.e. degree of per capita education, per capita GDP, per capita farmland area, per capita meat production, per capita aquatic product, population density, effective irrigation area, urbanization rate) which related to the W-E-F pressure were employed and three cross-section (i.e. 1997, 2004 and 2015) were chosen to carry out the geographically weighted regression (GWR) analysis. In the three developed GWR models, the dependent variable was the z-score standardized W-E-F pressure index differences between the start year and the end year, i.e. 1997 and 2004 (for model 1), 2004 and 2015 (for model 2), 1997 and 2015 (for model 3), and the eight independent variables were the respective z-score standardized differences (i.e. for the eight employed variables) between the start year and the end year. The factors which influence the variation of W-E-F index can be discovered from the developed GWR models and the conclusions are as follows: 1) The W-E-F pressure index rose initially and then declined from 1997 to 2015. Spatially, the W-E-F pressure decreased progressively from Southeast China to Northwest China, and larger pressure happened in Northeast China and those coastal provinces where urbanization level was higher. 2) The energy pressure index had made more significant contribution to the W-E-F pressure index than the water pressure index and the food pressure index. The energy pressure index was higher in central and east China and the water pressure index was bigger for those provinces in the north of Huaihe river. However, the food pressure index was higher for those coastal provinces in the south of the Yangtze River and for those provinces in west China. 3) In China, the water pressure index rose in most provinces, and the energy pressure index and the food pressure index declined in most provinces from 1997 to 2015. 4) The driving forces of the W-E-F pressure changes were different for the different phases. Overall, the same change direction was observed between most of the variables and the W-E-F pressure index. However, the opposite change direction existed between degree of per capita education and the W-E-F pressure index, so did between per capita GDP and the W-E-F pressure index. The main causes of the increased W-E-F pressure were the increased population density, the changed component of food supply, the conditions of food production and the economic development. The influences of socioeconomic factors on the W-E-F pressure rose progressively from 1997 to 2015. The effectual ways to reduce the W-E-F pressure were to improve the degree of per capita education and to reshape the economic development.

Key words: water-energy-food, pressure index, spatio-temporal variation, driving forces, principal component analysis, geographically weighted regression