基于熵权TOPSIS法的我国养殖海域承载力评价研究

养殖海域承载力是衡量海水养殖业可持续发展水平的重要判据。文章构建包含压力、状态、响应3个准则层共14个评价指标的养殖海域承载力评价指标体系，基于2008-2019年我国沿海地区数据，运用熵权TOPSIS法确定指标权重并计算养殖海域承载力综合得分。研究结果表明：我国养殖海域承载力逐年提高，综合得分从2008年的0.342升至2019年的0.458;压力层和状态层得分较高，年均值分别为0.689和0.799,响应层得分较低，年均值仅为0.318;响应层得分较低是我国养殖海域承载力综合得分较低的最重要原因。研究期间，我国沿海地区社会经济活动对养殖海域产生的资源环境压力先下降、后持平、再上升，近岸海域的健康状态和受污染程度呈波动趋势。我国养殖海域承载力具有明显的区域差异，其中综合得分平均值最高的是广东，其次是海南、山东和江苏；水产技术推广机构数量、海洋科研教育管理服务业占比、海水养殖业绿色全要素生产率是影响养殖海域承载力的最重要指标，海水养殖产值占GDP比重、工业废水中化学需氧量排放量、近岸海域水质等指标也对养殖海域承载力有较大贡献。

Evaluation of Carrying Capacity of Mariculture Region in China Based on Entropy Weight TOPSIS Method

The carrying capacity of mariculture region is an important criterion to evaluate the sustainable development level of mariculture. This paper established an evaluation index system for carrying capacity of mariculture region which included pressure, state and response criterion layers with 14 evaluation indexes. Based on the data of coastal areas in China from 2008 to 2019, the entropy weight TOPSIS method was used to determine the weights of the indexes and calculate the comprehensive scores of the carrying capacity of mariculture region. The results showed that the carrying capacity of mariculture region in China increased year by year, and the comprehensive score increased from 0.342 in 2008 to 0.458 in 2019. Among them, the scores of the pressure layer and the state layer were higher, with an annual mean of 0.689 and 0.799 respectively, while the scores of the response layer were lower, with an annual mean of 0.318. The low response layer score was the most important reason for the low comprehensive score of carrying capacity of mariculture region in China. During the study period, the pressure of resources and environment caused by social and economic activities of coastal areas on mariculture region first decreased, then remained flat and then increased, and the health status and pollution degree of coastal areas showed a fluctuating trend. There were significant differences in the carrying capacity of mariculture region among the coastal areas. Guangdong Province had the highest average comprehensive score, followed by Hainan, Shandong and Jiangsu. The number of aquaculture technology extension institutions, the proportion of marine scientific research, education and management service industry, and the green total factor productivity of mariculture industry were the most important indicators affecting the carrying capacity of mariculture region. The proportion of mariculture output value in GDP, the discharge of chemical oxygen demand in wastewater, and the water quality of offshore sea areas also made great contributions to the carrying capacity of mariculture region.