虚拟水贸易能重新分配区域间的水资源。在京津冀协同发展的背景下,厘清京津冀城市群与外部的虚拟水贸易及城市群内部的虚拟水流动,有助于深入理解该地区的水资源供需现状及问题,为制定虚拟水贸易相关策略、实现区域水资源优化配置、保障区域水资源安全提供决策支持。本文基于2010年全国区域间投入产出表,测算了京津冀城市群各省（市）水足迹及与全国各省域单元的虚拟水贸易量。从近远程视角定量评估城市群地区对内、外部水资源的依赖程度,并分析虚拟水贸易的距离特征。研究发现：① 京津冀城市群各省（市）各部门用水系数显现出差异性,农业部门用水强度最高,直接用水与完全用水系数分别超过300 m 3/万元和400 m 3/万元;② 京津冀城市群内部各省（市）人均消费水足迹差异大,北京、天津、河北的人均水足迹分别为405 m 3、565 m 3、191 m 3;③ 京津冀城市群的消费水足迹遍布全国各省域单元,近程水足迹与远程水足迹分别为91.4亿m 3、198.5亿m 3,其中,近程水足迹主要来源于本省（市）,西部地区对远程水足迹的贡献最大;④ 京津冀城市群的虚拟水输入总体偏向来源于距离较近的省域单元,北京、天津、河北水足迹距离来源地的平均距离分别为1049 km、1297 km、688 km;⑤ 北京和天津为虚拟水贸易的净流入区,对外部水资源的依赖性强;河北为虚拟水贸易的净流出区,为京津冀城市群及其他地区供给水资源,虚拟水净流出进一步加剧了河北的水资源短缺。未来,受人口增长、经济发展等因素影响,京津冀城市群的水资源压力将进一步加剧,提高用水效率、升级产业结构、提倡低水足迹消费模式、实行虚拟水战略是实现京津冀城市群可持续发展的有效途径。 相似文献
Journal of Geographical Sciences - The terrestrial hydrological process is an essential but weak link in global/regional climate models. In this paper, the development status, research hotspots and... 相似文献
A voice enhancement algorithm based on the Empirical Mode Decomposition (EMD) and the improved spectral subtraction is proposed for the low-SNR (Signal Noise Ratio) shortwave time signal. This method is proposed to solve the problem that the shortwave time signal cannot be used for timing in complex noisy environments. The core idea of this method is to use the Hilbert-Huang Transform (HHT) algorithm to make the empirical mode decomposition on the noisy shortwave signal, and to select the intrinsic mode functions containing the shortwave signal information for the signal reconstruction by through the maximum correlation. Then, to make the spectral subtraction on the reconstructed signal to achieve the purpose of noise reduction. The experimental result shows that this method has a better noise reduction than the traditional methods. 相似文献
A model integrating geo-information and self-organizing map (SOM) for exploring the database of soil environmental surveys was established. The dataset of 5 heavy metals (As, Cd, Cr, Hg, and Pb) was built by the regular grid sampling in Hechi, Guangxi Zhuang Autonomous Region in southern China. Auxiliary datasets were collected throughout the study area to help interpret the potential causes of pollution. The main findings are as follows: (1) Soil samples of 5 elements exhibited strong variation and high skewness. High pollution risk existed in the case study area, especially Hg and Cd. (2) As and Pb had a similar topo-logical distribution pattern, meaning they behaved similarly in the soil environment. Cr had behaviours in soil different from those of the other 4 elements. (3) From the U-matrix of SOM networks, 3 levels of SEQ were identified, and 11 high risk areas of soil heavy metal-contaminated were found throughout the study area, which were basically near rivers, factories, and ore zones. (4) The variations of contamination index (CI) followed the trend of construction land (1.353) > forestland (1.267) > cropland (1.175) > grassland (1.056), which suggest that decision makers should focus more on the problem of soil pollution surrounding industrial and mining enterprises and farmland.
