河南晚更新世—全新世黄土记录的环境变化及物源特征  

Environment Evolution and Provenance Characteristics of the Loess Since the Late Pleistocene in Henan Province

作　　者：王兆夺 黄春长 周亚利 庞奖励 查小春 郭永强 WANG Zhaoduo;HUANG Chunchang＊;ZHOU Yali;PANG Jiangli;ZHAXiaochun;GUO Yongqiang(National Demonstration Center for Experimental Geography Edueafion,Sehool of Geography and Tourism,Shanxl Normal University,Xi＇ an 710119,China)

机构地区：[1]陕西师范大学地理科学与旅游学院地理学国家级实验教学示范中心,西安710119

出　　处：《高校地质学报》2018年第3期380-389,共10页Geological Journal of China Universities

基　　金：国家自然科学基金项目(41771110);中央高校基本科研业务费专项基金(GK.201704013)联合资助

摘　　要：基于河南新郑县的一套完整晚更新世—全新世黄土古土壤剖面(格大张剖面),应用端元分析模型,对75个沉积样品的粒度分析数据进行分析,并对各端元组分在地层深度对应的时间尺度上做了小波变换。结果认为,从格大张剖面沉积物粒级组分中可以分离出三个沉积端元,端元1可能指示了东亚夏季风作用动力特征,夏季风的强弱引起的温湿变化造成相应时期内沉积物的古土壤化的强弱;端元2可能指示了东亚冬季风作用下沙尘暴沉积动力作用特征,代表了典型风成黄土的粗颗粒组分特征;端元3粒级组分更粗,代表了更强搬运动力条件,应属于东北风搬运黄泛平原粗颗粒而来的近源沉积物,距今3100 a以来尤为显著。根据小波分析结果,认为各端元组分在不同的时间尺度上具有周期性特点。端元分析法在指示沉积物沉积动力环境和物源特征上具有很好的效果,各端元组合特征能够敏感地反映出沉积动力组合特征,很好地反映晚更新世以来各动力变化特征。采用小波分析方法对识别各端元组的周期性特征以及根据目前状态推断未来可能的趋势具有参考意义。End-member analysis （EMA） was performed on particle size data collected from 75 samples from the continuous Late Pleistocene-Holocene Gedazhang （GDZ） loess-palaeosol profile in Xinzheng, Henan Province. Wavelet analysis was also performed forthe EMs in the time domain. The results show that three EMs can be separated from sediment particle sizes in the GDZ profile. EM2may have been influenced by dynamic changes in the strength of the East Asian summer monsoon, with changes in temperature and humidity caused by the summer monsoon resulting in weathering and pedogenesis. EM2 appears to have been influenced by thedynamic effects of dust storm accumulation controlled by the northwesterly monsoon, and contains typical components of aeolian loess.EM3 contains coarse-grained components that are indicative of strong transporting forces and proximal sediment sources influenced bynortheasterly winds from the Yellow River flood plain, particularly significant since 3100 a. Results of wavelet analysis show that eachEM has different periodic characteristics at different time scales. The EMA method is effective in indicating the sedimentaryenvironment and sediment source characteristics. The combined characteristics of each EM reflect the sedimentary dynamics and canalso derive sedimentary dynamic changes since the Late Pleistocene. The wavelet analysis method provides important results in terms of cyclic features and trends of dynamics change in particle size within each EM.

关 键 词：晚更新世 黄土古土壤 粒度 端元分析 小波分析 

分 类 号：P642.131[天文地球—工程地质学]