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何艳虎, 李深林, 杨 洁, 许洋洋, 温智文, 涂传鹏.我国不同区域用水结构变化及其驱动因素分析水资源与水工程学报[J].,2016,27(4):1-6
我国不同区域用水结构变化及其驱动因素分析
Change of water use structure and its driving factors in different regions of China
  
DOI:10.11705/j.issn.1672-643X.2016.04.01
中文关键词:  用水结构  信息熵  主成分分析  最严格水资源管理制度  驱动因素
英文关键词:water structure  information entropy  principal component analysis  the most stringent water management system  driving factor
基金项目:国家自然科学基金项目(51509127、51210013、51569009); 南昌工程学院大学生科研训练计划项目(2015)
作者单位
何艳虎1,2, 李深林1, 杨 洁2, 许洋洋2, 温智文2, 涂传鹏2 (1.中山大学 水资源与环境研究中心 广东 广州 510275
2.南昌工程学院 江西 南昌 330099) 
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中文摘要:
      以江西、湖北,山东、江苏,以及贵州、西藏等6省(自治区)为例,采用信息熵和主成分分析方法,从经济社会、水文气象、农业及用水4方面选取了13个因子,揭示了我国中、东、西部地区1999-2014年间用水结构变化特征及各主导因素的影响机制,分析了最严格水资源管理制度实施于用水结构产生的效果。结果表明:(1)近16年来,东部地区的山东省总用水量持续下降,用水结构信息熵值上升降趋势明显,处于较高水平;西部地区的西藏自治区总用水量增加显著,用水结构信息熵值处于较低水平,其余地区总用水量总体保持平稳,生产用水量占总用水量的平均比重为91%;(2)最严格水资源管理制度实施以来,各省生产用水量逐渐减少,用水结构的信息熵值表现为不同程度的上升趋势;(3)影响各地区用水结构变化的主要驱动因子依次为各产业产值和人口、地区水资源禀赋和总耗水量。
英文摘要:
      Taking 6 provinces including Jiangxi, Hubei, Shangdong, Jiangsu, Guizhou and Tibet for example,the paper used information entropy theory and principal component analysis to open out the variation characters of water structure as well as the impact mechanism of driving factors in different areas in China from 13 factors which involves four aspects such as economy, society, hydro meteorology, agriculture and water resources.It also analyzed the effect of the most stringent water management system on water use structure.The results showed that (1) In the past 16 years, the total amount of water used in Shandong Province in east China continually declined, and its information entropy of water use structure was at a high level with an obvious rising trend; the total amount of use water in Tibet in west China increased markedly, and its information entropy was at a low level. There is no big change of the total amount of water use in other areas, and 91 percent of water is production water supply on average. (2)The production water has gradually decreased since the most stringent water management system was published, and the information entropy of water structure in each province has a rising trend. (3) The main factors driving the variation of water structure in these areas are industrial output value, population, and local water resources amount and total water consumption.
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