江苏省用水演变驱动因素研究
Study on Driving Factors of Water Utilization Structure Evolution in Jiangsu Province

作者: 李晓惠 , 张玲玲 :河海大学公共管理学院,南京; 王宗志 , 金菊良 :南京水利科学研究院水文水资源与水利工程科学国家实验室,南京;

关键词: 结构分解用水结构产业技术效应用水强度效应最终需求效应Structural Decomposition Water Structure Industrial Technology Effect Water Utilization Intensity Effect Final Demand Effect

摘要: 为正确理解江苏省社会经济发展与产业水资源利用量变化之间的关系,对产业用水变动进行影响因素分析。以扩展型可比价投入产出序列表数据为基础,构建投入产出结构分解模型,将1997~2007年四个时间段江苏省产业用水变动的影响因素分解为产业技术效应、用水强度效应和最终需求效应。从“产业整体三大产业各国民经济部门”三个层面剖析产业用水结构演变的三大影响因素的效应,并应用模糊聚类的方法,将各国民经济部门的三大影响因素进行分异分析。研究结果表明,最终需求效应对产业用水变动的影响最大,是产业用水的拉动效应,产业技术效应和用水强度效应是产业用水的抑制效应,其中用水强度效应是节水的关键因素;三大效应对三产用水变动所起的正负效应方向整体一致,但驱动强度不同,且随着时间的推移,呈现不同的发展态势;在未来一定时期内,最终需求效应所起的拉动作用将越来越小,而用水强度效应的抑制作用将越来越明显。

Abstract: In order to indicate the relation between social development and water resources use in Jiangsu Province, this paper analyzes the factors driving the change of water uses. Based on the statistics provided by the extended comparable I-O tables, this paper established an I-O structural decomposition model in which influence factors during four time periods from 1997-2007 of Jiangsu Province’s industrial water change have been decomposed into industrial technology effect, water utilization intensity effect as well as final demand effect. In three aspects “the whole industry-three industries-every national economic sector”, we analyze the three influence factors’ effects of industrial water utilization structure evolution and adopt the method of fuzzy clustering to make the differentiation analysis of the three influence factors of every sector. The results show that final demand effect which pulls industrial water utilization is the most significant factor in industrial water utilization change, and that industrial technology effect and water utilization intensity effect restrain water utilization, the former of which is the key factor of water-saving. Three effects’ driving direction (positive or negative) remained much same during the four periods, but effects driving strengths were different. With the passage of time, they present different development trends; in the next period of time, the pulling effect of final demand effect will become smaller and smaller while the inhibitory effect of water utilization intensity effect will become more and more obvious.

文章引用: 李晓惠 , 张玲玲 , 王宗志 , 金菊良 (2014) 江苏省用水演变驱动因素研究。 水资源研究, 3, 50-56. doi: 10.12677/JWRR.2014.31008

参考文献

[1] 张强, 王本德, 曹明亮. 基于因素分解模型的水资源利用变动分析[J]. 自然资源学报, 2011, 26(7): 1219-1226.
ZHANG Qiang, WANG Bende and CHAO Mingliang. Analysis of water resource utilization change based on factor decomposition model. Journal of Natural Resources, 2011, 26(7): 12191226.

[2] RICHARD, F. G., MUN, S. H. and DALE, W. J. Why has the energy-output ratio fallen in China? The Energy Journal, 1999, 20(3), 63-92.

[3] MA, C. B., STERN, D. I. China’s changing energy intensity trend: A decomposition analysis. Energy Economics, 2008, 30 (3): 1037-1053.

[4] 夏炎, 杨翠红, 陈锡康, 等. 基于可比价投入产出表分解我国能源强度影响因素[J]. 系统工程理论与实践, 2009, 29(10): 21-27.
XIA Yan, YANG Cuihong, CHEN Xikang, et al. Analysis on determining factors of energy intensity in China based on comparable price input-output table. Systems Engineering-Theory, 2009, 29(10): 21-27.

[5] 梁进社, 郑蔚, 蔡建明. 中国能源消费增长的分解——基于投入产出方法[J]. 自然资源学报, 2007, 22(6): 853-864.
LIANG Jinshe, ZHENG Wei and CAI Jianming. The decomposition of energyconsumption growth in China: Based on input-output model. Journal of Natural Resources, 2007, 22(6): 853-864.

[6] ANG, B. W., LEE, S. Y. Decomposition of industrial energy consumption: Some methodological and application issues. Energy Economics, 1994, 16(2), 83-92.

[7] Sun, J. W. Energy demand in the Fifteen European Union Countries by 2010: A Forecasting model based on the decomposition approach. Energy, 2001, 26(6): 549-560.

[8] 刘云枫, 孔伟. 基于因素分解模型的北京市工业用水变化分析[J]. 水电能源科学, 2013, 31(4): 26-29.
LIU Yunfeng, KONG Wei. Analysis of industry water utilization Chang in Beijing based on factor decomposition model. Water Resources and Power, 2013, 31(4): 26-29.

[9] 孙才志, 王妍. 基于因素分解模型的辽宁省用水变化驱动力测度及时空分异[J]. 干旱区地理, 2009, 32(6): 850-858.
SUN Caizhi, WANG Yan. Driving force mea-surement of water utilization change in Liaoning Province and analysis of their spatial-temporal difference based on factor de-composition model. Arid Land Geography, 2009, 32(6): 850-858.

[10] 贾绍凤, 张士锋, 夏军, 等. 经济结构调整的节水效应[J]. 水利学报, 2004, 3: 111-116.
JIA Shaofeng, ZHANG Shifeng, XIA Jun, et al. Effect of Economic Structure Adjustment on Water Saving. Journal of Hydraulic Engineering, 2004, 3: 111-116.

[11] ANG, B. W., ZHANG, F. Q. A survey of index decomposition analysis in energy and environmental studies. Energy, 2000, 25(12): 1149-1176.

[12] Boyd, G. A., Roop, J. M. A note on the fisher ideal index decomposition for structural change in energy intensity. Energy, 2004, 25(1): 87-101.

[13] 方开泰. 聚类分析[M]. 北京: 地质出版社, 1982.
FANG Kaitai. Cluster analysis. Beijing: Geological Publishing House, 1982.

[14] 杨虎, 钟波, 刘琼荪. 应用数理统计[M]. 北京: 清华大学出版社, 2006.
YANG Hu, ZHONG Bo and LIU Qiongsun. Application mathematical statistic study. Beijing: Tsinghua University Press, 2006.

[15] 谢中华. MATLAB统计分析与应用: 40个案例分析[M]. 北京: 北京航空航天大学出版社, 2010.
XIE Zhonghua. Analysis and application of statistics by MATLAB: Based on 40 cases. Beijing: Beihang University Press, 2010.

分享
Top