自然资源学报 ›› 2019, Vol. 34 ›› Issue (8): 1759-1770.doi: 10.31497/zrzyxb.20190815

• 资源评价 • 上一篇    下一篇

黄河流域水资源承载力评价

张宁宁(), 粟晓玲(), 周云哲, 牛纪苹   

  1. 西北农林科技大学水利与建筑工程学院,杨陵 712100
  • 收稿日期:2019-01-07 修回日期:2019-05-19 出版日期:2019-08-28 发布日期:2019-08-28
  • 作者简介:

    作者简介:张宁宁(1994- ),女,陕西延安人,硕士,研究方向为水资源承载力研究。E-mail: 1062153157@qq.com

  • 基金资助:
    “十三五”国家重点研发计划(2016YFC0401306)

Water resources carrying capacity evaluation of the Yellow River Basin based on EFAST weight algorithm

ZHANG Ning-ning(), SU Xiao-ling(), ZHOU Yun-zhe, NIU Ji-ping   

  1. College of Water Resources and Architectural Engineering, Northwest Agriculture and Forestry University, Yangling 712100, Shaanxi, China
  • Received:2019-01-07 Revised:2019-05-19 Online:2019-08-28 Published:2019-08-28

摘要:

定量评价水资源承载力,可为有效调控水资源,提高水资源承载力和消除水资源超载区提供依据。从水资源承载力新内涵出发,构建“量—质—域—流”的四维水资源承载力评价指标体系,确定指标评价等级标准。针对水资源承载力评价涉及许多不确定因素以及指标间存在耦合关系等特点,采用可考虑指标间耦合关系的EFAST算法计算权重,结合可处理评价不确定性问题的联系熵模型进行水资源承载力评价。以黄河流域为例,计算得权重与熵权法进行比较,对2015年流域61个地市的水资源承载力状况进行了综合评价。结果表明:EFAST算法计算权重比熵权法更合理;黄河流域水资源承载力处于Ⅰ级(极高)、Ⅱ级(较高)、Ⅲ级(中等)、Ⅳ级(较低)和Ⅴ级(极低)的地市数量占评价总地市数的比例分别为0、4.9%、18.1%、63.9%和13.1%,其中Ⅳ级和Ⅴ级分布在除青海省外的其他省区的地市。

关键词: 黄河流域, 水资源承载力, 联系熵模型, EFAST算法

Abstract:

Quantitative evaluation of water resources carrying capacity can provide a basis for effective regulation of water resources, improvement of water resources carrying capacity and elimination of water resources overload areas. Based on the new connotation of water resources carrying capacity, an evaluation index system for water resources carrying capacity was constructed which considered four aspects of water quantity, water quality, watershed and water flow. In traditional research of water resources carrying capacity, there existed many uncertain factors and coupling relationships between indicators. In order to address this issue, this paper calculated the weights using EFAST method, which considers the coupling relationship between indicators. The connection entropy model that can overcome the uncertainty of evaluation was carried out to evaluate comprehensive water resources carrying capacity. By taking the Yellow River Basin as an example, the weights of the carrying capacity indices were calculated using EFAST method and weight entropy method respectively and made a comparison between the two methods. Finally, the water resources carrying capacity of 61 cities in this basin in 2015 was comprehensively evaluated. The results showed that: EFAST method was more reasonable than entropy weight method in identifying important indicators. Cities whose water resources carrying capacity were at grade I (very high), grade II (higher), grade III (medium), grade IV (lower) and grade V (very low) levels accounted for 0%, 4.9%, 18.1%, 63.9% and 13.1% respectively of the number of cities in the Yellow River Basin. The cities of grades IV and V were distributed in provinces except Qinghai.

Key words: Yellow River Basin, water resources carrying capacity, connection entropy model, EFAST algorithm