岩溶洼地小流域具有岩溶地区典型流域特征,作为一个独立的侵蚀产沙单元,开展岩溶洼地小流域泥沙来源研究,对于查明洼地泥沙的来源,研究土壤侵蚀过程,发挥着重要的作用。选择重庆青木关岩溶槽谷区的典型洼地,采用复合指纹示踪技术等方法,确定岩溶洼地泥沙来源的地球化学元素指纹特征,得出了重庆岩典型岩溶洼地的沉积泥沙来源和贡献比例。结果 表明:从38种因子中筛选,找到了最佳指纹因子组合,其中U,χhf,AP,Mn的累积判别率分别为63.4%,68.3%,73.2%,82.9%,总累积判别率高达82.9%,说明指纹法可用于岩溶洼地小流域泥沙来源研究。同时利用多元混合模型得出3种泥沙来源地贡献百分比均值分别为碳酸盐岩表层土壤(50.2%)、深层土壤(11.6%)、碎屑岩表层土壤(38.2%),且多元混合模型优度拟合检验值为0.83,相对平均误差为13.9%,进一步说明岩溶洼地碳酸盐岩地区土壤流失严重,远高于碎屑岩土壤。研究为开展岩溶洼地土壤侵蚀特征演变研究提供了基础。
The karst depression small watershed has the characteristics of typical watershed in karst area. As an independent erosive sediment-generating unit, the study of sediment source in small karst depression watershed plays an important role in identifying the source of sediment in the depression and studying soil erosion process. The typical depression of the Qingmuguan karst trough valley in Chongqing was selected as study area. The method of composite fingerprint tracing was used to determine the geochemical element fingerprint characteristics of the sediment source in the karst depression, and the sediment source and contribution proportion of the typical karst depression in Chongqing rock were determined. The results showed that the best fingerprint factor combinations were found from 38 factors; the cumulative discrimination rates of U, χhf, AP and Mn were 63.4%, 68.3%, 73.2% and 82.9%, respectively, indicating that the fingerprint method can be used for the study of sediment sources in small watersheds in karst depressions; at the same time, the multivariate mixed model was used to indentify the mean percentages of contribution of the three sediment sources were carbonate surface soil(50.2%), deep soil(11.6%), clastic surface soil(38.2%), and the multi-mix model goodness fit test value was 0.83, and the relative average error was 13.9%, which further indicated that the soil loss in the karst depression carbonate area was serious, and much higher than the clastic soil. This study can provide the basis for the study of the evolution of soil erosion characteristics in karst depressions.
