中文摘要：

水资源短缺成为经济发展中重要的制约因素，目前解决这一问题行之有效的途径之一就是提高用水效率。根据辽宁省14个城市1999年～2005年的相关数据，选择生活用水和生产用水以及最基本的生产要素劳动力、固定资产投资和土地等作为输入指标，以地区生产总值（GDP）为输出指标，运用数据包络分析计算出各指标的规模冗余率与技术冗余率，进而计算出用水相对效率，并对其在时空上的分异特征进行了研究，这可为水资源的合理利用提供借鉴和参考。进一步研究发现，水资源利用的规模冗余率与人均GDP的关系同库兹涅茨理论相吻合，而技术冗余率与人均GDP呈负相关关系，从而为人们利用规律制定相关的政策提供理论依据。

英文摘要：

Liaoning Province has one of the most serious water shortages in northern China, with high seasonal and regional variation in water distribution. The demand on water resources is increasing due to industrialization, urbanization and socioeconomic development, causing increasing disparities between levels of water supply and demand. Water shortage has become a major constraint on economic development, and the effective solution is to increase the efficiency of water utilization. However, existing research on water utilization efficiency relies on qualitative analysis, with limited use of quantitative methods. Data Envelopment Analysis （DEA）, used to analyze efficiency and productivity based on input- output production functions, provides a quantitative assessment of the relative efficiency of water utilization. In this paper, DEA was used to estimate water utilization relative efficiency in Liaoning. Using data from 1999 to 2005 for fourteen cities in Liaoning, we selected domestic water usage, productive water usage, labor, fixed asset investment, and land as the inputs, and chose gross domestic product as the output. The DEA method was applied to calculate the scale redundancy ratio and technical redundancy ratio. On this basis, the water utilization relative efficiency was calculated for each city. We also discuss the spatial-temporal variation of water distribution. The scale and technical redundancy ratios of domestic water utilization among different cities were compared as well as those of productive water utilization. The spatial analysis shows that domestic water utilization efficiency, productive water utilization efficiency and total water utilization relative efficiency are distinctly different among the fourteen cities. The overall trend shows an increase in the province＇s relative efficiency from 1999 to 2005, although the efficiency decreases in 2003. The trend and one-year decline were analyzed by considering relevant influencing factors. The analysis of spatial-temporal variation may provide