干旱区生态环境知识资源中心(Arid): 多组复合指纹示踪法及其应用

Arid

	多组复合指纹示踪法及其应用
其他题名	AMultiple Composite Fingerprinting Method and Its Application
	柳本立 1; 牛百成 ; 屈建军1
来源期刊	地球科学进展
ISSN	1001-8166
出版年	2019
卷号	34 期号:10 页码:1092-1098
中文摘要	指纹示踪法是确定水力作用下流域泥沙物质来源贡献率的重要手段,其中选用多个指纹因子组成一组最优指纹的复合指纹示踪法应用最为广泛。该类方法不受空间尺度或沉积物传输过程的限制,因此可以采用相似的步骤,应用到风力沉积问题当中。然而对比研究发现,一组复合指纹判别能力的高低并不能代表其优化求解判别结果的准确程度,二者之间没有正相关性。介绍了基于指标之间解析解关系筛选多个指标组合的多组复合指纹示踪法,以及该方法在不同尺度流域的检验。相对于蒙特卡洛方法进行优化获得数值解的方法,采用所有具有有效解析解的多组指纹组合结果平均值,可获得同样合理的结果,但大大减少了计算量。该方法已被推广应用于风沙堆积物质,以及风沙、水沙共同作用下的干旱区水库泥沙淤积物质来源的定量判别中。
英文摘要	Fingerprinting technique provides an essential means for estimating source contributions of watershed sediments,in which a single group of "optimum composite fingerprints" has been widely used in the literature to estimate sediment provenance. This type of methods is not restricted by the scale or process of sediment transportation so that similar procedures can be applied in sediment provenance research for aeolian depositions. However,recent studies found no direct link(positive relationship)between the ability of the tracer group to discriminate sources and its rigor in estimating source contributions after optimization. Here,we introduced a recently developed multiple composite fingerprinting method with additional screening based on analytical solutions,and further reviewed its verification in watersheds at different scales. It turned out that compared to Monte Carlo optimization method,a reasonable estimation can be achieved using the mean of the maximum number of composite fingerprints that given analytical solution to the mixing model,but the computational cost can be reduced significantly. The reliability of this new method was also tested in source contribution estimating of aeolian sediments,and the provenance quantification of reservoir sediment in an arid region experiencing both wind and water sediments.
中文关键词	多组复合指纹法 ; 泥沙来源 ; 贡献率判别 ; 风沙物质
英文关键词	Multiple composite fingerprints Sediment source Contribution discrimination Aeolian sediment
语种	中文
收录类别	CSCD
WOS类目	GEOSCIENCES MULTIDISCIPLINARY
WOS研究方向	Geology
CSCD记录号	CSCD:6625856
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/315803
作者单位	1.中国科学院西北生态环境资源研究院/敦煌戈壁荒漠研究站, 中国科学院沙漠与沙漠化重点实验室, 兰州, 甘肃 730000, 中国; 2.美国农业部农业研究局草地研究中心, 厄尔里诺, 73036
推荐引用方式 GB/T 7714	柳本立,牛百成,屈建军. 多组复合指纹示踪法及其应用[J],2019,34(10):1092-1098.
APA	柳本立,牛百成,&屈建军.(2019).多组复合指纹示踪法及其应用.地球科学进展,34(10),1092-1098.
MLA	柳本立,et al."多组复合指纹示踪法及其应用".地球科学进展 34.10(2019):1092-1098.