水库泥沙来源定量判别方法的判别能力对比

doi:10.7522/j.issn.1000-694X.2021.00110

摘要/Abstract

摘要：

水库淤积问题是干旱、半干旱沙区水库面临的主要环境问题之一。物源定量判别法是识别水库泥沙来源的新兴手段，而筛选某一区域泥沙来源的最优判别方法是精准识别物源区的重要前提。选取党河水库作为研究对象，基于野外调查、室内分析、模型模拟等手段，对比分析了多组复合指纹法、最优复合指纹法和距离法在党河水库泥沙来源判别过程中的适用性。结果表明：在该研究区多组复合指纹法和最优复合指纹法判别结果较为理想，且判别结果接近，而距离法表现不理想，有待进一步检验。增加复合指纹因子组合数（19组）能使95%的置信区间变窄，理论上具有统计意义。从统计学角度分析，多组复合指纹法表现更好一些，将在一定程度上提高定量判别结果精度。

关键词: 指纹法, 水库淤积, 物源判别, 党河水库

Abstract:

Reservoir siltation is one of the main environmental problems in arid and semi-arid sandy areas. The sediment source fingerprinting is a new method to identify reservoir sediment sources， and screening an optimal discriminant model for sediment sources in a certain area is an important prerequisite for accurate identification of sediment source. In this study， Danghe Reservoir was selected as the research object. Based on field investigation， indoor analysis， model simulation and other means， the applicability of multiple composite fingerprints， optimal composite fingerprint， and distance weight method in the identification process of sediment source were compared and analyzed. The results showed that both multiple composite fingerprints and optimal composite fingerprint could obtain reasonable contributions and were relatively close， which were suitable for the quantitative identification of sediment sources in this watershed. However， the distance weighting method was not satisfactory and needed to be further tested. Increasing the number of composite fingerprints （19） could narrow the 95% confidence interval， which has statistical significance. From a statistical point of view. Theoretically the multiple composite fingerprints perform better， which will improve the accuracy of quantitative discrimination results to a certain extent.

Key words: fingerprinting method, reservoir sedimentation, provenance identification, Danghe Reservoir

中图分类号:

P333.4

牛百成, 刘峰贵, 周强, 陈琼, 柳本立. 水库泥沙来源定量判别方法的判别能力对比[J]. 中国沙漠, 2022, 42(2): 36-43.

Baicheng Niu, Fenggui Liu, Qiang Zhou, Qiong Chen, Benli Liu. Comparative analysis of discriminant ability of quantitative discriminant models for reservoir sediment sources[J]. Journal of Desert Research, 2022, 42(2): 36-43.

图/表 8

图1 研究区概况和采样点

Fig.1 Location of the study area， and sampling sites

图2 基于判别式分析的距离来推断沉积物来源贡献率（D1为上游山区的质心到沉积区质心的绝对距离）

Fig.2 Inferring sediment source contributions using DFA and calculating distances. Here， D1 is the absolute X-value （Function 1） of the source centroid for cultivated land to the X-value of the sediment centroid

表1 各物源区和党河水库中指纹因子浓度的平均值、标准差和非参数检验值

Table 1 The fingerprints of average concentration， standard deviation， and the results f the Kruskal-Walls H test in each sediment sources and Danghe Reservoir

指纹因子	沙丘		戈壁		上游山区		党河水库		H值	P值
指纹因子	平均值	标准差	平均值	标准差	平均值	标准差	平均值	标准差	H值	P值
Ti	5 391.6	864.2	5 457.7	743.0	4 215.1	412.0	5 112.7	538.5	14.24	0.001
Mn	657.0	67.6	681.5	50.7	613.2	30.8	638.6	33.7	10.75	0.005
Co	74.4	30.6	39.1	7.1	33.7	4.1	44.2	23.6	23.21	0.000
Cu	18.9	1.2	22.0	2.4	24.3	1.6	22.9	1.0	20.59	0.000
Zn	28.7	6.0	42.8	3.8	46.3	4.6	39.5	8.8	21.79	0.000
Sr	212.4	1.9	239.8	33.1	218.0	7.0	222.1	5.4	18.50	0.000
Nd	34.0	7.0	38.1	8.7	24.4	4.1	35.4	7.2	16.74	0.000
Al₂O₃	8.0	0.5	8.7	0.4	9.5	0.4	8.9	0.5	24.31	0.000

图3 19组复合指纹因子组合的泥沙贡献率

Fig.3 The estimated proportions of 19 composite fingerprints

图4 各物源区对党河水库泥沙贡献率的频数分布图和平均泥沙贡献率

Fig.4 Relative frequency distributions of the contributions of each sediment source and their average proportion

表2 通过逐步判别式分析为最优复合指纹法选取最佳指纹因子组合

Table 2 Using stepwise discriminant function analysis to select fingerprints for optimum composite fingerprint

步骤	选入的指纹因子变量	Wilks’lambda	累计判别力/%
1	Zn	0.290	66.7
2	Al₂O₃	0.116	86.1
3	Co	0.087	88.9
4	Cu	0.068	94.4
5	Mn	0.052	97.2
6	Ti	0.040	97.2

图5 最优复合指纹法和距离法定量判别不同物源区对党河水库的泥沙贡献率

Fig.5 Quantitative identification the contributions of the three potential sediment sources using composite fingerprints and the distance weighting method

图6 19组沙丘、戈壁和上游山区对党河水库泥沙贡献率的95%置信区间

Fig.6 95% confidence interval of 19 groups of dunes， gobi and upstream mountains to the sediment contribution of danghe reservoir

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