关键词: 信息熵, 斯皮尔曼等级相关系数, 水资源配置方案, 综合评价, 信息损失

Abstract: The characterof multiple attributes in water resource allocation makes the ranking of schemes incompletely consistent by using different aggregating methods. This paper discusses the quantity of information loss from given decision-making metrics to ranking results. Then information entropy theory and Spearman’s rank correlation coefficient are adopted to measure information loss in evaluation of water resource allocation schemes and the Shannon-Spearman measure is proposed. Six composite evaluation models are constructed by combining two weight sets(weight based on entropy and weight based on evidence theory)and three evaluation models (namely sample additive weighting, fuzzy selection method and TOPSIS). Finally, the Shannon-Spearman measure is adopted to calculate information loss in the process of composite evaluation of Tianjin water resource allocation schemes. And composite evaluationresultsare compared with a given composite evaluation model in reference. The results show that the result from combining weight based on entropy and fuzzy selection method obtains the least absolute/relative information loss in seven results. Through the measure of information loss in evaluation of water resource allocation schemes, it could make evaluation process more transparent and provide policy-making departmentwith decision support for choosing ideal composite evaluation method of water resource allocation schemes.

Key words: information entropy, spearman’s rank correlation coefficient, water resource allocation schemes, composite evaluation, information loss