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区域水资源可持续利用评价方法对比研究 被引量:21

Comparison of Assessment Methods for Regional Water Resources Sustainable Utilization
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摘要 为进一步揭示几种典型的区域水资源可持续利用评价方法的特点与应用效果,论文选取两类共7种评价方法或模型,即综合指数型的PCA法、AHP法、灰色关联度法、改进序关系法和等级分类型的模糊综合评判法、BP神经网络、SVM模型。以福建省9个设区市为评价对象,结合DPSIR概念模型的内容,构建水资源可持续利用评价指标体系,从而在指标体系不变的条件下,分别进行区域水资源可持续利用评价,进而比较分析各方法的特点及其评价结果。研究表明:1)相同评价指标体系下,不同方法得到的评价结果有一定差别。2)PCA法和改进序关系法的评价结果一致性最高,其次是AHP与改进序关系法,且综合指数型方法中改进序关系法应用结果更可靠;灰色关联度法存在高估水资源可持续利用水平较低区域的评价值,且综合评价指数分布范围小、区域间分辨间隔较小的不足,而模糊综合评判、BP神经网络和SVM的评价结果差异较大,规律性不明显。3)常规的PCA、AHP、灰色关联度和模糊综合评判法的评价过程相对稳定,虽然BP神经网络和SVM模型能减少赋权的主观干预,但受指标等级标准划分、训练样本生成和参数设置等因素的影响,评价应用的稳定性相对差。4)与BP神经网络相比,SVM用于水资源可持续利用评价相对稳定,但SVM分类器对样本空间划分的状况则直接影响评价结果的可靠程度。 The assessment method of regional water resources sustainable utilization is one of the core issues for water resources sustainable utilization evaluation. In order to reveal several typical evaluation methods of regional water resources sustainable utilization and its application effect, in this paper, seven evaluation methods or models which can be grouped into two categories have been selected. The first category is consist of principal component analysis(PCA), analytic hierarchy process(AHP), gray correlation method and improved rank correlation analysis. And fuzzy comprehensive evaluation method, BP neural network and support vector machine(SVM) composite the other category. Above seven methods were selected to evaluate indicator system for sustainability assessment of water resources use(ISSAWRU) which has been built in Fujian Province. Then nine districts of Fujian Province were taken as the example. Firstly, the initial ISSAWRU of Fujian Province is constructed from 24 indicators based on the content of Driving-Pressure-State-Impact-Response conceptual model which is abbreviated as DPSIR. The related evaluation results and characteristics of those seven methods or models were compared subsequently. Final analysis of results shows that: 1) The evaluation results of PCA and improved rank correlation analysis method have the highest consistency, and the latter is AHP and improved rank correlation analysis method. Furthermore, improved rank correlation analysis has the most reliable among the comprehensive index type methods. While gray correlation method has some shortages that it may obtain smaller range of evaluation value and higher assessment value of some regions, which actually has lower level of regional water resources sustainable utilization. In addition, the evaluation results of fuzzy comprehensive evaluation, BP neural network and SVM are quite different without obvious regularity. 2) In general, traditional methods including PCA, AHP, gray correlation degree and fuzzy comprehensive evaluation method are relatively simple and stable. Although BP neural network and SVM can reduce subjective intervention, they show poor stability because of the impacts of index ranking standard, training sample, parameter settings and other factors. 3) Compared with BP neural network, evaluation stability of SVM is better, but the reliability of SVM is greatly affected by division of sample space. This research can provide scientific reference for selecting or analyzing assessment method of water resources sustainable utilization.
出处 《自然资源学报》 CSSCI CSCD 北大核心 2015年第11期1943-1955,共13页 Journal of Natural Resources
基金 国家自然科学基金项目(41301031) 福建省高校产学合作项目(2015Y4002)
关键词 水资源学 可持续利用 评价方法 对比研究 福建省 water resources science sustainable utilization assessment methods comparison Fujian Province
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参考文献3

  • 1Li Gong,Chunling Jin.Fuzzy Comprehensive Evaluation for Carrying Capacity of Regional Water Resources[J]. Water Resources Management . 2009 (12)
  • 2Cabrera Jr., Enrique,Cobacho, Ricardo,Estruch, Vicent,Aznar, Jerónimo.Analytical hierarchical process (AHP) as a decision support tool in water resources management. Journal of Water Supply: Research and Technology - AQUA . 2011
  • 3De Z.,Liming L.,Rongqun Z.,Lingling G.,Simin C.A study on water resources consumption by principal component analysis in Qingtongxia irrigation areas of Yinchuan Plain, China. Journal of Food, Agriculture and Environment . 2009

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