基于联系数的区域水资源承载力评价方法

Evaluation Method of Regional Water Resources Carrying Capacity Based on Connection Number

为合理评价区域水资源承载力状态,给区域水资源配置提供参考,从水资源承载支撑力-压力-调控力3个子系统选取评价指标,采用基于加速遗传算法的改进层次分析法(AGA-CAHP)计算评价指标的主观权重,采用基于加速遗传算法的投影寻踪法(AGA-PP)计算评价指标的客观权重,然后用最小相对信息熵原理计算各指标的组合权重,运用灰色关联度改进的集对分析方法得到区域水资源承载力的联系数,据此建立了基于熵组合权重和灰色关联度的区域水资源承载力集对分析评价模型。模型应用于安徽省,结果表明安徽省2005—2015年水资源承载力均处于临界超载,2012—2015年安徽省水资源承载力呈逐渐上升的趋势,且南部区域强于北部区域,评价状态符合实际,该模型能充分整合评价过程中主观经验信息和客观资料信息,在区域资源、环境承载力综合评价中具有较大的推广应用价值。

In order to know the carrying capacity of regional water resources and provide reference for regional water resources allocation,this paper selects evaluation indexes from three subsystems of water resources carrying capacity(i.e.,carrying ability system,carrying pressure system and regulation ability system),calculates the subjective weights of evaluation indexes by correcting analytic hierarchy process based on accelerating genetic algorithm(AGA-CAHP),the objective weights of evaluation indexes by projection pursuit based on accelerating genetic algorithm(AGA-PP)and the combined weights of evaluation indexes by the principle of minimum relative information entropy,obtains the connection number of regional water resources carrying capacity by improved set pair analysis based on grey correlation analysis,and then establishes a set pair analysis evaluation model for regional water resources carrying capacity based on entropy principles,combined weights and grey correlation analysis,and finally applies the model in Anhui Province.The results show that the water resources carrying capacity of Anhui Province was in the critical overload from 2005 to 2015,while that was gradually increasing from 2012 to 2015,with the southern region stronger than the northern region.The evaluation results accorded with the actual situation.Therefore,the model can fully integrate the subjective experience information and objective information in the evaluation process,with reasonable results.It has great application value in the comprehensive evaluation of regional resources and environmental carrying capacity.