农业工程学报Issue(13)：200-207,8.DOI:10.3969/j.issn.1002-6819.2013.13.026
基于主成分分析的水平潜流湿地磷去除模型
Modeling phosphorus removal in horizontal subsurface constructed wetland based on principal component analysis
摘要
Abstract
Performance of a horizontal subsurface constructed wetland (HSSF―CW) running for three years was studied. Response curves of the area removal of total phosphorus (TP) to the changes in water temperature were analyzed for different treatment cells. The temporal changes in the area removal of TP in different treatment cells were simulated by the sinusoidal function. Based on the statistical methods of principal component analysis (PCA) and redundancy analysis (RDA), the main environmental factors influencing the removal of TP were selected. Afterwards, the effluent TP concentration (TPo) was simulated and predicted through the artificial neural network (ANN). The results suggested that the area removal of TP was insensitive to water temperature changes when the water temperature was low (<20℃), while great fluctuations combined with an increase of the area removal of TP occurred as the water temperature increased to a higher degree (>20℃). The highest value of area removal TP (3.27 g/(m2·d)) was reached at the temperature of 24.5℃. The relationship between the area removal of TP and the water temperature in different treatment cells was described by the polynomial function, and consequently reasonable accuracy was obtained (R2=0.1082, p=0.000). The variation of area removal of TP in different months was found to be in line with sinusoidal changes (R2=0.231, p=0.000). The area removal of TP with a plateau of 0.397±0.125 g/(m2·d) observed in August was higher than that in autumn. The average area removal of TP was 0.331±0.132 g/(m2·d) in summer. With the method of PCA and RDA, the relationship between the area removal of TP and different environmental factors was analyzed. As a result, the main impact factors including the influent TP concentration (TPi), wastewater temperature (Temp), flow rate (Flow), dissolved oxygen (DO), pH and evapotranspiration (ET) were found, and subsequently selected as the input parameters for ANN modeling. Comparison of the actual and simulated TPo values indicated a certain accuracy of the model in predicting the trend and scale of TPo in the HSSF―CW (R2=0.677-0.800). The results of this research could provide scientific support for the improvement and management of HSSF―CWs.关键词
磷/主成分分析/模型/水平潜流湿地/人工神经网络Key words
phosphorus/principal component analysis/models/horizontal subsurface constructed wetland/artificial neural network分类
资源环境引用本文复制引用
张岩,崔丽娟※,李伟,张曼胤,赵欣胜,王义飞,张亚琼..基于主成分分析的水平潜流湿地磷去除模型[J].农业工程学报,2013,(13):200-207,8.基金项目
中央级公益性科研院所基本科研业务费专项“潜流湿地磷去除动力学机制研究”（CAFINT2013C13）；中国林业科学研究院基本科研业务费项目“兼顾景观功能的小型人工湿地设计研究” （）
