﻿ 基于改进灰靶模型的水资源利用效率评价

# 基于改进灰靶模型的水资源利用效率评价Evaluation of Water Use Efficiency Based on Improved Grey Target Model

Abstract: Water efficiency is a key part of implementing the most stringent water management system, and objective evaluation of it is the prerequisite for water efficiency control. In this paper, the CRITIC weight is introduced into the traditional gray target model for objective weighting, which overcomes the shortcomings of the use of equal weight in the traditional model. An improved gray target model based on CRITIC weight is proposed. At the same time, the obstacle factor diagnosis model is used to analyze the main obstacles affecting water use efficiency. Taking the water efficiency evaluation of various districts in Zhengzhou in 2017 as an example, the evaluation results of the two methods are in good agreement compared with the TOPSIS method, indicating that the improved gray target model has certain application in the evaluation of water use efficiency. Through the analysis of the obstacle degree model, the ecological environment water use index is the main factor hindering the improvement of water use efficiency in Zhengzhou City.

1. 引言

2. 区域概况及评价指标体系

2.1. 研究区域概况

2.2. 评价指标体系及数据来源

Table 1. Zhengzhou City water resources utilization efficiency evaluation index system and index weight value

3. 研究方法

3.1. 改进的CRITIC赋权法

CRITIC赋权法由Diakoulaki提出的一种新型客观赋权方法，以指标特征的对比强度和冲突性来综合反映指标的客观权重，它不仅考虑指标内部的变异程度，而且还考虑了指标之间的冲突性，充分考虑了指标的内部和外部特性，赋权结果更为客观、合理。传统的CRITIC赋权法存在下列两方面的不足：第一，带量纲的标准差无法反映出指标内部的对比强度大小；第二，出现负相关时，用相关系数反映指标冲突性显然不合理，参考王瑛等 [16] 的研究成果，利用变异系数和带绝对值的Pearson相关系数对传统CRITIC赋权法进行改进，则改进后的赋权公式为：

${C}_{j}={\delta }_{j}\underset{i=1}{\overset{n}{\sum }}\left(1-|{r}_{ij}|\right),j=1,2,\cdots ,n$ (1)

${w}_{j}={C}_{j}/\underset{i=1}{\overset{n}{\sum }}{C}_{j},j=1,2,\cdots ,n$ (2)

3.2. 改进的灰靶模型

$\gamma \left[{x}_{0}\left({u}_{j}\right),{x}_{i}\left({u}_{j}\right)\right]=\frac{\underset{i}{\mathrm{min}}\underset{j}{\mathrm{min}}{\Delta }_{0i}\left({u}_{j}\right)+\rho \underset{i}{\mathrm{max}}\underset{j}{\mathrm{max}}{\Delta }_{0i}\left({u}_{j}\right)}{{\Delta }_{0i}\left({u}_{j}\right)+\rho \underset{i}{\mathrm{max}}\underset{j}{\mathrm{max}}{\Delta }_{0i}\left({u}_{j}\right)}=\frac{0.477}{{\Delta }_{0i}\left({u}_{j}\right)+0.477}$ (3)

$\phi \left({x}_{0},{x}_{i}\right)=\underset{j=1}{\overset{n}{\sum }}{w}_{j}\gamma \left[{x}_{0}\left({u}_{j}\right),{x}_{i}\left({u}_{j}\right)\right]$ (4)

3.3. 水资源利用效率障碍因子诊断模型

${M}_{j}={I}_{j}\cdot {w}_{j}/\left(\underset{j=1}{\overset{n}{\sum }}{I}_{j}\cdot {w}_{j}\right)$ (5)

4. 郑州市水资源利用效率评价

4.1. 郑州市水资源利用效率评价过程

Table 2. Actual value of indicator data and gray target transformation result

Table 3. Grey relation difference information space and bull's-eye coefficient, bull's-eye value

Table 4. Results of classification criteria by natural breakpoint method

4.2. 评价结果

Table 5. Evaluation results of water resources utilization efficiency in Zhengzhou City

Figure 1. Main obstacle factors and obstacles of water resources utilization efficiency in Zhengzhou City

5. 结论

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