基于复合指纹法的岩溶洼地小流域泥沙来源解析

陈英; 魏兴萍; 张爱国; 雷珊

doi:10.13870/j.cnki.stbcxb.2020.05.019

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基于复合指纹法的岩溶洼地小流域泥沙来源解析

更新时间：2025-03-12

- 基于复合指纹法的岩溶洼地小流域泥沙来源解析
- Analysis of Sediment Source in Small Watershed of Karst Depression Based on Composite Fingerprint Method
- 水土保持学报 2020年34卷第5期页码：131-136
- 作者机构：
  
  重庆师范大学地理与旅游学院,重庆,401331
- 作者简介：
  
  [ "陈英(1990-),女,硕士研究生,主要从事水土保持与生态化建设研究。E-mail:yingchenczx@126.com" ]
- 基金信息：
  
  国家自然科学基金项目（41701252）重庆市自然科学基金项目（cstc2016jcyiA0150）重庆师范大学研究生科研创新项目（YKC19002）
- DOI：10.13870/j.cnki.stbcxb.2020.05.019
  中图分类号： S157.1
- 纸质出版：2020
- 稿件说明：
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陈英, 魏兴萍, 张爱国, 等. 基于复合指纹法的岩溶洼地小流域泥沙来源解析[J]. 水土保持学报, 2020,34(5):131-136.

CHEN Ying, WEI Xingping, ZHANG Aiguo, et al. Analysis of Sediment Source in Small Watershed of Karst Depression Based on Composite Fingerprint Method[J]. 2020, 34(5): 131-136.
陈英, 魏兴萍, 张爱国, 等. 基于复合指纹法的岩溶洼地小流域泥沙来源解析[J]. 水土保持学报, 2020,34(5):131-136. DOI： 10.13870/j.cnki.stbcxb.2020.05.019.

CHEN Ying, WEI Xingping, ZHANG Aiguo, et al. Analysis of Sediment Source in Small Watershed of Karst Depression Based on Composite Fingerprint Method[J]. 2020, 34(5): 131-136. DOI： 10.13870/j.cnki.stbcxb.2020.05.019.

摘要

岩溶洼地是重庆岩溶地区常见的一种地貌类型，洼地小流域是人们从事农事活动的重要场所，研究流域不同土地利用侵蚀产沙特征，对认识流域侵蚀产沙规律和治理水土流失具有重要意义。选取了1个建有水库的岩溶洼地小流域，分析源地和泥沙样品的39个地球化学特征，利用复合指纹和多元混合模型计算各源地侵蚀泥沙贡献率。结果表明：流域筛选出的最佳指纹因子组合为U、χlf、Rb、Li、137Cs、χ、Mn，正确判别累积率为99.93%，6种泥沙源地的总正确判别率为91.49%，符合复合指纹法应用的条件。碳酸盐岩耕地、碳酸盐岩林地、碳酸盐岩草地、碎屑岩林地、碎屑岩草地和沟道/裂隙对流域沉积泥沙的相对贡献分别为16.29%，41.16%，13.03%，16.67%，4.48%，8.37%，拟合优度为93.57%，相对误差平均值为8.26%，表明模型判别结果可信。各泥沙源地中碳酸盐岩耕地单位面积泥沙贡献值远高于其他泥沙源地，是碳酸盐岩林地的1.98倍，碳酸盐岩草地的2.07倍，碎屑岩林地的2.13倍，碎屑岩草地的2.21倍，即单位面积碳酸盐岩耕地土壤抗蚀能力最弱。

Abstract

Karst depression is a common landform type in karst areas of Chongqing. Small depression watershed is an important place for agricultural activities. Studying the characteristics of erosion and sediment yield of different land uses in the watershed is of great significance for understanding the laws of erosion and sediment production and controlling soil and water loss. A small karst depression basin with a reservoir was selected

and 39 geochemical properties of the sediment source as well as sediment samples were analyzed. The composite fingerprint and multivariate mixed model were used to calculate the erosion and sediment contribution rate of each sediment source. The results showed that the best fingerprint factor combination screened by the catchment was U

χlf

137Cs

χ and Mn. The cumulative rate of correct discrimination was 99.93%

and the total correct discrimination rate of the six sediment sources was 91.49%

which accorded to the application conditions of compound fingerprint method. The relative contributions to sediments in the basin of carbonate arable land

carbonate woodland

carbonate grassland

clastic rock forest

clastic grassland and trench/fissure soil were 16.29%

41.16%

13.03%

16.67%

4.48% and 8.37%

respectively

the goodness of fit of the model was 93.57%

and the average relative error was 8.26%

indicating that the model result was credible. Among all sediment source areas

the sediment contribution per unit area of carbonate rock farmland was far higher than that of other sediment source areas

which was 1.98 times that of carbonate forest land

2.07 times that of carbonate grassland

2.13 times that of clastic rock forest land

and 2.21 times that of clastic rock grassland. The soil corrosion resistance of carbonate rock farmland per unit area was the weakest.

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