| 摘要: |
| 为解决区域水资源承载力综合评价中指标数据多维、非线性的问题,采用基于最大信息熵原理的投影寻踪水资源承载力评价方法,并将该方法应用于2015年安徽省16个地级市水资源承载力的空间分布评价中；最后对2005-2015年安徽省全省水资源承载力进行动态评价,并将该评价结果与灰色GM(1,1)模型结合,对2018-2020年安徽省区域水资源承载状况进行预测。结果表明：2015年,安徽省水资源承载空间分布状况整体表现为皖南地区优于皖中地区,皖中地区优于皖北地区；2005-2015年期间,全省水资源承载力虽基本处于临界超载状态,但年际间承载状况逐年好转。预测结果表明2018-2020年全省水资源承载力保持良好的发展态势,总体向可载趋势发展。参考该地区水资源承载力评价的相关文献,其结果基本一致,表明该方法在区域水资源承载力评价中有较好的应用价值。 |
| 关键词: 水资源承载力 评价 预测 投影寻踪 信息熵 加速遗传算法 GM(1,1) 安徽省 |
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| 基金项目:国家自然科学基金项目（面上项目，重点项目，重大项目）,国家重点基础研究发展计划（973计划） |
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| Application of projection pursuit method in assessment and prediction of water resources carrying capacity |
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JIN Juliang1, YANG Tongzhu1, LI Jianqiang2, CHEN Menglu1, NING Shaowei3, ZHANG Haoyu1
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1.School of Civil Engineering,Hefei University of Technology;2.Water Resources and Hydropower Planning and Design General Institute,MWR;3.Institute of Water Resources and Environmental Systems Engineering,Hefei University of Technology
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| Abstract: |
| In order to solve the problem of multi-dimensional and non-linearity of index data in the comprehensive evaluation of regional water resources carrying capacity, this paper adopts the method of projection pursuit water resources carrying capacity based on the principle of maximum information entropy, and applies this method to 16 cities in Anhui Province in 2015. In the spatial distribution evaluation of water resources carrying capacity of the city, the dynamic evaluation of the water resources carrying capacity of Anhui Province in 2005-2015 is carried out, and the evaluation results are combined with the gray GM (1,1) model for 2018-2020. The regional water resources carrying status of Anhui Province was predicted. The results show that in 2015, The overall distribution of water resources carrying capacity in Anhui Province is better than that of the central Anhui Province in the southern part of Anhui Province, and the central Anhui area is better than the northern part of Anhui Province; During 2005-2015, the water resources carrying capacity of the province is basically at a critical point. Overloaded, but the inter-annual load status has improved year by year. The forecast results show that the water resources carrying capacity of the province has maintained a good development trend from 2018 to 2020, and the overall development trend is toward the loadable trend. Referring to the relevant literature on the assessment of water resources carrying capacity in the region, the results are basically consistent, indicating that the method has a good application value in the evaluation of regional water resources carrying capacity. |
| Key words: water resources carrying capacity evaluation prediction projection pursuit accelerated genetic algorithm information entropy GM (1, 1) Anhui Province |
