多组复合指纹示踪法及其应用

doi:10.11867/j.issn.1001-8166.2019.10.1092

地球科学进展 ›› 2019, Vol. 34 ›› Issue (10): 1092 -1098. doi: 10.11867/j.issn.1001-8166.2019.10.1092

多组复合指纹示踪法及其应用

柳本立 ¹(

),牛百成 ^1, ³,屈建军 ¹

1. 中国科学院西北生态环境资源研究院/沙漠与沙漠化重点实验室，敦煌戈壁荒漠研究站，甘肃兰州 730000
2. 美国农业部农业研究局草地研究中心，俄克拉荷马厄尔里诺 73036
3. 中国科学院大学，北京 100049

收稿日期:2019-04-15 修回日期:2019-08-16 出版日期:2019-10-10
基金资助:
美丽中国生态文明建设科技工程专项“沙漠边缘扩张带稳固技术与示范”(XDA23060201);中国科学院青年创新促进会(2016373)

A Multiple Composite Fingerprinting Method and Its Application

Benli Liu ¹( ),Xunchang John Zhang ²,Baicheng Niu ^1, ³,Jianjun Qu ¹

1. Dunhuang Gobi Desert Research Station, Key Laboratory of Desert and Desertification/Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China
2. Grazinglands Research Laboratory, Agricultural Research Service, United States Department of Agriculture, El Reno, OK 73036, USA
3. University of Chinese Academy of Sciences, Beijing 100049, China

Received:2019-04-15 Revised:2019-08-16 Online:2019-10-10 Published:2019-12-09
About author:Liu Benli (1986-), male, Luohe City, He'nan Province, Associate professor. Research areas include aeolian disaster and aeolian engineering. E-mail: liubenli@lzb.ac.cn
Supported by:
the Strategic Priority Research Program of the Chinese Academy of Sciences “Technologies and demonstration on the stabilization of expanding desert margin belt”(XDA23060201);The Youth Innovation Promotion Association of the Chinese Academy of Sciences(2016373)

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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。

关键词: 多组复合指纹法, 泥沙来源, 贡献率判别, 风沙物质

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.

Key words: Multiple composite fingerprints, Sediment source, Contribution discrimination, Aeolian sediment.

中图分类号:

P931.3

图1 两种元素组合的解析解关系
（a）有效组合；（b）无效组合

Fig.1 Two types of element groups based on analytical solution
（a） Feasible; （b） Conflicting

图2 不同元素组合判别能力与源区贡献率预测误差的关系（数据源自参考文献[ 20 ]）

Fig. 2 Relationship between discriminate ability and predict error on source contributions of the multiple element groups（data from reference [ 20 ]）

图3 基于元素本身分布产生随机数进行蒙特卡洛模拟获得的源区贡献率分布、平均值及标准误（数据源自参考文献[ 20 ]）

Fig.3 Frequency distributions, mean proportions and their standard errors of the three sources from Monte Carlo simulation using generated random numbers based on the identical distribution of each element（data from reference [ 20 ]）

图4 预测的同一河道上游、中游和下游3种泥沙源区平均贡献率（数据源自参考文献[ 21 ]）

Fig.4 Estimated mean proportional contributions from the cropland, rangeland, and gully sources at the three trap locations on the main stream（data from reference [ 21 ])

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