| 太湖有色可溶性有机物4种光谱模型的对比 |
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| 引用本文： | 刘明亮,张运林,王鑫,李云亮. 太湖有色可溶性有机物4种光谱模型的对比[J]. 生态与农村环境学报, 2009, 25(1) |
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| 作者姓名： | 刘明亮 张运林 王鑫 李云亮 |
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| 作者单位： | 南京农业大学资源与环境科学学院,江苏,南京,210095;中国科学院,南京地理与湖泊研究所/湖泊与环境国家重点实验室,太湖湖泊生态系统研究站,江苏,南京,210008;中国科学院,南京地理与湖泊研究所/湖泊与环境国家重点实验室,太湖湖泊生态系统研究站,江苏,南京,210008;河北省气象科学研究所,河北,石家庄,050021;南京大学地理与海洋科学学院,江苏,南京,210093 |
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| 基金项目： | 中国科学院知识创新工程项目，国家自然科学基金 |
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| 摘 要： | 利用指数函数、幂函数等4种模型对太湖2006-2007年50个站点250个样本的有色可溶性有机物(CDOM)光谱吸收系数进行拟合,发现其他3种模型都比传统的取自然对数进行线性回归的模型拟合效果好.统计检验显示,幂函数模型的光谱拟合效果最好,平均决定系数为0.999 0,大于其他3种模型,而平均相对误差、均方根误差则小于其他3种模型.利用幂函数模型计算得到,在280～500 nm光谱范围内,CDOM吸收光谱斜率均值为(6.66±0.40) nm-1,变异系数6.08%,其频率基本上遵循正态分布.对于太湖CDOM吸收光谱斜率值,在空间分布上,梅梁湾显著小于大太湖开阔水域(P< 0.001);时间分布上,最大值出现在春季,最小值在秋季,夏季值小于冬季值.CDOM吸收光谱斜率与吸收系数呈显著负相关,相关性随波长增加而增强.
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| 关 键 词： | 有色可溶性有机物 吸收系数 光谱斜率 太湖 |
Comparison Between Four Models in Modeling Spectral Absorption of Chromophoric Dissolved Organic Matter in Lake Taihu |
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| LIU Ming-liang,ZHANG Yun-lin,WANG Xin,LI Yun-liang. Comparison Between Four Models in Modeling Spectral Absorption of Chromophoric Dissolved Organic Matter in Lake Taihu[J]. Journal of Ecology and Rural Environment, 2009, 25(1) |
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| Authors: | LIU Ming-liang ZHANG Yun-lin WANG Xin LI Yun-liang |
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| Affiliation: | 1.College of Resources and Environmental Sciences;Nanjing Agricultural University;Nanjing 210095;China;2.Taihu Lake Laboratory Ecosystem Research Station;State Key Laboratory of Lake Science and Environment/Nanjing Institute of Geography and Limnology;Chinese Academy of Sciences;Nanjing 210008;3.Meteorology Institute of Hebei Province;Shijiazhuang 050021;4.School of Geography and Ocean Sciences;Nanjing University;Nanjing 210093;China |
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| Abstract: | Spectral absorption of chromophoric dissolved organic matters(CDOM) in 250 samples collected from 50 sampling stations in Lake Taihu from 2006 to 2007 were simulated using four different models in this present study.Four models included three exponential models using linear and nonlinear fitting,and a hyperbolic model.It was found that the other three models(Model 2,3 and 4) performed better than the conventional single exponential model(Model 1).Statistics show that the power function model fitted the best... |
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