甘肃省资源环境承载力时空分异

从经济、社会、环境和资源4个子系统中选取24个指标构建区域资源环境承载力评价体系,运用加权TOPSIS模型结合GIS的空间分析功能从时间和空间维度对甘肃省14个市州2004—2013年的综合承载力和4个子系统内部承载力水平进行剖析。研究表明:(1)近10年甘肃省各市州资源环境综合承载力指数呈低水平上的平稳态势,与经济发展水平一致;呈西北高东南低的空间格局和金字塔形的层次结构。嘉峪关市居第1层;金昌市、兰州市、酒泉市居第2层;其他市州居第3层;(2)各子系统对资源环境综合承载力的影响不同。生态环境子系统的承载力对资源环境综合承载力贡献最大,明显高于其他3系统,经济系统贡献很小;(3)各市州各子系统承载力指数存在明显的时空分异。经济支撑力指数呈河西(除武威外)和兰州高,东南和南部低的空间格局,呈现金字塔形的层次结构整体偏低变化较小。社会承载力指数除金昌市有较大的突变外各市区都比较平稳,空间上呈河西(除武威外)和兰州高,东南、南部低的空间格局;嘉峪关市、兰州、酒泉3市较高,其余各地都较低。环境承载力指数变动频繁,波动幅度不大,空间上基本呈两头高中间低的哑铃状空间格局。资源承载力指数偏低,武威、庆阳、定西、甘南、临夏和天水6市州指数曲线平稳,其余8市州波动频繁,波动幅度大,空间上呈河西地区(除武威外)和陇南市高,其余各州市低的集中分布格局。

The spatiotemporal variation in resource environmental carrying capacity in the Gansu Province of China

Based on the evaluation index system established for measuring the resource environmental carrying capacity (RECC), this study measured the RECC of 14 cities in the Gansu Province of China and analyzed the spatiotemporal variation in RECC. To comprehensively understand RECC and accurately identify its trend, 24 indicators with four subsystems, i.e., economic, social, resource, and ecological subsystems, were selected to build the RECC evaluation system. The evaluation index weights were calculated using the entropy weight method, whereas the indicator weights were calculated using the entropy weight TOPSIS model. Furthermore, the spatiotemporal variation in RECC in 14 cities and the internal carrying capacity of the four subsystems, from 2004 to 2013, were analyzed using the GIS spatial analysis function. The results indicate that: (1) All 14 cities in the Gansu Province showed a low composite index of RECC, with no significant variation from 2004 to 2013, and showed a trend similar to that in economic development. The spatial pattern showed that the northwest district had a higher RECC than the southeast district. It showed a pyramidal hierarchy with three levels, i.e., Jiayuguan city at the top, Lanzhou, Jiuquan, and Jinchang cities in the middle part, and the other cities at the bottom. The first and second levels showed a significant difference, whereas the second and third levels showed an insignificant difference. (2) Considerable differences were observed among effects of the four subsystems. The ecological subsystem had the largest effect, significantly higher than the other three subsystems, followed by the social and resource subsystems, whereas the economic subsystem had the smallest effect. (3) A distinct spatiotemporal variation exists in the subsystems. The economic support index and social carrying capacity were higher in the Hexi (except Wuwei city) and Lanzhou regions than in the southeast and south regions. A pyramidal hierarchical structure was observed for the economic support index, with low values and insignificant differences between levels. The social carrying capacity of all cities was similar, except Jinchang city, which showed a large change in the social carrying capacity in 2009. Although the environmental carrying capacities changed frequently, the fluctuation was insignificant. The spatial pattern was dumbbell-shaped, i.e., low in the middle and high at the two ends. In general, the resource carrying capacity indices were low; they were constant in Wuwei, Qingyang, Dingxi, Gannan, Linxia, and Tianshui cities, and variable in the remaining eight cities. The Hexi (except Wuwei city) and Longnan regions showed higher resource carrying capacity indices than the other parts. The results indicate that industry structure should be modified to promote economic development and the resources and environment must be protected to realize sustainable development in the Gansu Province of China.