摘要
对采自西巢湖湖心的一根长为143 cm的沉积柱进行了粒度分析,重建了粒度组成的演变过程。湖心沉积物主要为粉砂和黏土,粒度参数(平均粒径、标准偏差、偏度、尖度、分维值)分析表明沉积物分选程度较好,均为正偏态,峰态为很窄到非常窄,且具有一定的分形特征。C-M图解和概率累积曲线揭示了较弱的水动力环境,颗粒的搬运方式主要为跃移和悬移,比例分别约为70%和25%~30%。结合因子分析,识别出第一主因子(PC1)对细粒物质含量存在显著影响,其值反映了碎屑物质在湖泊中的搬运距离,PC1因子与平均粒径Mz可作为巢湖湖泊水位的替代性指标。
Lacustrine sediments are ideal natural archives for studying environmental changes in the past. A sediment core, namely CHX, was collected from the western Chaohu Lake, east of China and its grain-size features at the intervals of 2 cm were investigated in the present study. The changes of grain-size compositions throughout the profile CHX were reconstructed. Grain size parameters, including mean grain-size(Mz), standard deviation(Sd), skewness(Sk) and kurtosis(Ku) were calculated. It is found that those sediments are mainly composed of fine grained silt and clay. Mz, Sd, Skand Kuand fractal dimension of the sediments suggest that those deposits were well to very well sorted, positive to very positive-skewed, very to extremely leptokurtic and also show evident fractal features. C-M pattern and probability cumulative curve of the sediments from core CHX unveiled an low-energy environment, and revealed that grains move in the major forms of saltation and suspension, which accounts for about 70% and 25% ~30%, respectively. Principal component analysis(PCA) was applied to identify controlling factors for grain size features of sediments from the Chaohu Lake.From principal component analysis, it is identified that the first principal component(PC1) controls fine-grained clay content in the bulk sediments and further reflects the offshore distance of detritus in the lake.PC1 and mean grain-size Mzare thus robust markers for lake water level and local precipitation. These sediments can be further used to reconstruct regional precipitation history.
出处
《地理科学》
CSCD
北大核心
2015年第10期1318-1324,共7页
Scientia Geographica Sinica
基金
中国博士后科学基金(2014M550338)
中央高校基本科研业务费专项资金(2013bh2x0026)
国家自然科学基金(41402148
21207031)资助
关键词
巢湖
沉积物
粒度
分维值
因子分析
Chaohu Lake
sediments
grain size
fractal dimension
factor analysis