自然资源学报

自然资源学报 ›› 2014, Vol. 29 ›› Issue (8): 1441-1452.doi: 10.11849/zrzyxb.2014.08.016

• 资源研究方法 • 上一篇    

区域水资源可持续利用评价指标体系构建

王壬1, 陈莹1,2,3, 陈兴伟1,2,3   

  1. 1. 福建师范大学地理科学学院, 福州 350007;
    2. 湿润亚热带山地生态国家重点实验室培育基地, 福州 350007;
    3. 福建省陆地灾害监测评估工程技术研究中心, 福州 350007
  • 收稿日期:2013-06-04 修回日期:2013-12-17 出版日期:2014-08-20 发布日期:2014-08-20
  • 通讯作者: 陈兴伟（1963-），教授，博导。E-mail：cxwchen215@163.com E-mail:cxwchen215@163.com
  • 作者简介:王壬（1991-），男，江西赣州人，硕士研究生，主要从事水文水资源与GIS应用研究。E-mail：wangrengis@126.com
  • 基金资助:

    国家自然科学基金项目（41301031）；福建省公益科研院所专项重点项目（2013R04）

Establishment of Indicators System for Sustainability Assessment of Regional Water Resources Use

WANG Ren1, CHEN Ying1,2,3, CHEN Xing-wei1,2,3   

  1. 1. College of Geographical Science, Fujian Normal University, Fuzhou 350007, China;
    2. Cultivation Base of State Key Laboratory of Humid Subtropical Mountain Ecology, Fuzhou 350007, China;
    3.Fujian Provincial Engineering Research Center for Monitoring and Assessing Terrestrial Disasters, Fuzhou 350007, China
  • Received:2013-06-04 Revised:2013-12-17 Online:2014-08-20 Published:2014-08-20

PDF (PC)

赞

被引次数

14 | 5

摘要：

基于区域水资源可持续利用评价指标体系（Indicators System for Sustainability AssessmentofWater Resources Use， ISSAWRU）构建的一般方法与步骤，论文围绕初始、优化和评价检验三个过程构建ISSAWRU；针对ISSAWRU构建中的指标信息重复和干扰问题，提出相关分析与粗糙集Horafa 属性约简算法相结合的方法实现指标体系的优化，并采用灰色系统理论与粗糙集耦合的评价方法对优化结果进行评价检验。以福建省为例，9 个设区市为研究单元，依据可持续发展理论，从水资源条件、开发利用状况、生态环境和社会经济四个方面，构建由30 项指标组成的初始ISSAWRU，通过筛选得到由12 项指标构成的优化ISSAWRU，进而对这两套指标体系进行评价。结果分析表明：相关分析与粗糙集Horafa 属性约简算法相结合的指标信息优化方案是可靠的；筛除重复和干扰指标信息，简化了繁杂的指标体系，降低了后续评价的计算复杂度，并且信息筛选后的优化ISSAWRU比初始ISSAWRU评价结果更合理。

关键词: 水资源学, 相关分析, 粗糙集, 评价指标体系, 灰色系统理论

Abstract:

Based on the general methods and steps of establishing the indicators system for sustainability assessment of regional water resources use (ISSAWRU), this paper focused on three steps of revolving around initialization, optimization and evaluation test to establish ISSAWRU. In order to decrease the information of overlapping and interfering of indicators, correlation analysis and Horafa algorithm for attribute reduction of rough set were combined to optimize the initial ISSAWRU. Moreover, the objective evaluation method coupling grey system theory with attribute importance degree computed by rough set was proposed to examine the optimized result. Fujian Province was taken as an example in this research, the initial ISSAWRU which is composed of 30 indicators selecting from four aspects including water resources condition, utilization status, ecological environment and socio- economy, was established based on the theory of sustainable development. Then, the optimized ISSAWRU composed of 12 indicators was obtained through applying correlation analysis and Horafa algorithm. And the data of those indicators are from census database of the first national water conservancy as well as the water resources bulletin and statistical yearbook in Fujian. Finally, the objective evaluation method was applied to evaluate those two indicator systems, and the results showed that the method combined correlation analysis with Horafa algorithm is reliable to optimize ISSAWRU. Additionally, screening repetitive and interferential information can simplify the complexity of indicators system and reduce the computational complexity of followup evaluation. What's more, the evaluation result of optimized ISSAWRU is more scientific and reasonable than that of initial ISSAWRU in this case study of Fujian Province.

Key words: water resources science, correlation analysis, rough set, indicators system of evaluation, grey system theory

中图分类号: 

  • TV211