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第二阶梯湖泊富营养化自然地理因素及效应 被引量:4

Physical geography drivers of lake eutrophication and the characteristics of eutrophication effects in the secondary topography ladder in China
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摘要 为了明晰影响我国地形地貌第二级阶梯湖泊富营养化的主要自然地理驱动因素,为湖泊富营养化的有效治理提供参考,采用曲线回归方法分析了位于我国第二级阶梯的云南和新疆湖泊中Chl-a以及营养状态综合指数(TLI)与自然地理特征的相关性.结果表明,平均水深、海拔以及年均温与TLI指数具有较好的相关性,拟合模型分别符合三次/对数模型、二次模型和三次模型.Chl-a与年平均日照时数具有较好的相关性,拟合模型符合二次/三次模型.分析富营养化效应,藻类生长对透明度的影响以及营养物质对浮游藻类的生态效应(Chl-a/TP),结果发现,新疆湖泊中Chl-a与透明度呈倒数关系,云南湖泊中Chl-a与透明度呈幂函数关系;Chl-a与总磷的线性方程的斜率分别为177.595(云南)和222.758(新疆).影响我国第二级阶梯湖泊富营养化的主要自然地理驱动因素是湖泊的平均水深、海拔、年均温度及年平均日照时数,透明度与Chl-a含量的相关性以及营养物质TP对浮游藻类的生态效应存在区域差异. In order to investigate the key physical geography drivers of lake eutrophication in the secondary topography ladder in China, curve estimation in SPSS was used tO analyze the relationships between tropic level index (TLI)/Chl-a and physical geography characteristics of lakes, relationships between TLI and depth, altitude, temperature were fit to cubic/logarithm, quadratic and cubic model, respectively. The relationship between Chl-a and annual sunshine hours (ASH) was fit to quadratic/cubic model. It indicated that the key physical geography drivers of lake eutrophication in the second geography ladder were depth, altitude, temperature and ASH. Lake eutrophication effects, the relationship between Chl-a and transparency andthe slopes of linear equation for Chl-a and TP were also analyzed. Transparency was the reciprocal of Chl-a in the lakes in Xinjiang Province, and in the lakes in Yunnan Province transparency and Chl-a were in power function. The slopes of linear equation for Chl-a and TP were 177.595 and 222.758 in lakes in Yunnan and Xinjiang respectively. This results indicated that the efficiencies of nutrients used by algae were different in the second geography ladder in China.
出处 《中国环境科学》 EI CAS CSCD 北大核心 2011年第11期1849-1855,共7页 China Environmental Science
基金 国家"973"项目(2008CB418006) 国家水体污染控制与治理科技重大专项(2009ZX07106-001)
关键词 湖泊富营养化 驱动因素 富营养化效应 综合营养状态指数 曲线估计 拟合模型 lake eutrophicatiom dfivers eutrophication effects trophiclevelindex curve estimatiom model fitting
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