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水生植被恢复对东莞生态工业园区水质改善的影响研究
引用本文:戴玉女,吴鹏举,杨扬,池逸涵,廖凌娟,乔永民.水生植被恢复对东莞生态工业园区水质改善的影响研究[J].生态环境,2014(9):1463-1471.
作者姓名:戴玉女  吴鹏举  杨扬  池逸涵  廖凌娟  乔永民
作者单位:1. 暨南大学水生生物研究中心,广东 广州,510632
2. 广东东莞生态产业园区管委会,广东 东莞,523668
3. 暨南大学水生生物研究中心,广东 广州 510632; 热带亚热带水生态工程教育部工程研究中心,广东 广州 510632
4. 中山大学生命科学学院,广东 广州,510006
基金项目:国家科技重大专项(2012ZX07206004-05);生态园
摘    要:为促进工业园区水生态环境建设,以东莞生态产业园区水生态系统恢复为研究对象,研究了其建园初期水生植被恢复对重污染水体水质修复的影响,并应用因子分析法对水质与主要生态因子之间的相互关系进行了研究,探讨了水体修复效果与水生植被覆盖率的关系.结果表明:水生植被恢复可使园区生态岛群与月湖主要水质指标(总氮、总磷、氨氮和高锰酸盐指数)从建设初期(2011 年5 月)的劣V 类改善为II-III 类(2012 年),透明度提高约1 倍,而下沙与大圳埔湿地也从劣V类(2011 年5 月)改善为IV-V 类(2012 年),透明度提高约50%.10 项水质指标的因子分析表明,园区水质成因可归为综合营养因子(氨氮、高锰酸盐指数、叶绿素、透明度、总磷和总氮)、温度因子(温度、电导率、硝态氮)和光合作用因子(溶解氧和pH),其中主导指标为氨氮、高锰酸盐指数、叶绿素a、透明度和总磷等.三类因子分别客观反映了修复水体的水质变化特点:氮磷及有机物的含量越低则水体透明度越高,水质越优;温度升高有利于水质改善;藻类光合作用减弱,则水质变优.生态岛群、月湖、下沙、大圳埔湿地的水生植被覆盖率分别为43.8%、22%、4.3%、9.1%,此差异与水质修复效果相关.回归分析显示水质指标与水生植被覆盖率呈极显著的二项式关系(p〈0.01),根据拟合方程计算得出污染物浓度最低、透明度最高、综合水质最优时的水生植被覆盖率变动范围为30%~35%.因此,生态岛群与月湖的水质改善效果优于大圳埔湿地,大圳埔湿地则又优于下沙湿地;下沙与大圳埔湿地可通过适当增加浮、挺水植物的面积比例,提高水体修复能力.文中所得最适水生植被覆盖率范围可为华南地区工业园区水生态初期修复提供一定的参考价值.

关 键 词:生态工业园  水生植被  覆盖率  生态恢复  水质改善  因子分析

Impact of Aquatic Macrophyte Restoration on Water Quality Improvement in Dongguan Ecological Industrial Park
DAI Yunv,WU Pengju,YANG Yang,CHI Yihan,LIAO Lingjuan,QIAO Yongmin.Impact of Aquatic Macrophyte Restoration on Water Quality Improvement in Dongguan Ecological Industrial Park[J].Ecology and Environmnet,2014(9):1463-1471.
Authors:DAI Yunv  WU Pengju  YANG Yang  CHI Yihan  LIAO Lingjuan  QIAO Yongmin
Institution:DAI Yunv, WU Pengju, YANG Yang, CHI Yihan, LIAO Lingjuan, QIAO Yongmin 1. Research Center of Hydrobiology, College of Life Science and Technology, Jinan University, Guangzhou 510632, China;2. Dongguan ecology management committee, Dongguan 523668, China;3. Engineering Research Center of Tropical and Subtropical Aquatic Ecological Engineering, Ministry of Education, Guangzhou 510632, China;4. School of life sciences, Sun Yat-Sen University, Guangzhou 510006, China
Abstract:Aquatic environment construction is an important foundation for the construction of the eco-industrial park. However, currently,the research on eco-industrial park only focused on economic development, production material reduction and recycling, pollution controlduring produce process and management in the park etc. There is little information about aquatic environment construction. In order toraise attention to the restoration of aquatic environment in industrial park, the effect of aquatic macrophyte restoration on water quality inDongguan Eco-industrial Park in Dongguan city was investigated. Relationships among water quality parameters were analyzed by factoranalysis, and the impact of vegetation coverage rate was also discussed. According to the Surface Water Environment Quality Standard(GB 3838-2002), our results showed that the major parameters (et., total nitrogen (TN), total phosphorus (TP), ammonia (NH3-N) andpermanganate index (CODMn)) of ‘Central Eco-island Cluster’ and ‘Yuehu lake’ were improved form worse than grades V to grades II-IIIwith about 100% increase for water transparency.Meanwhile water qualityin ‘Dazhenbu’ and ‘Xiasha’ wetlands were improved form worsethan grades V to grades IV-V with about 50% increase for water transparency after aquatic macrophyte restoration. 10 parameters wereclassified into three categories to reflect the water quality according to factor analysis, which were nutritional factor (et., NH3-N, CODMn,chlorophyll a (Chl-a), transparency, TP and TN), temperature factor (et., temperature, conductivity and nitrate) and photosynthesis factor(et., dissolved oxygen and pH), respectively. Among which the leading parameter were NH3-N, CODMn, Chl-a, transparency and TP. Thesefactors revealed the characteristic of water quality. Low nutrition level will result in high transparency, which indicate better water quality.Increased temperature and decreased photosynthesis of phytoplankton will help to improve water quality. The
Keywords:ecological industrial Park  aquatic macrophyte  coverage rate  ecological restoration  water quality improvement  factor analysis
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