基于水沙组合分类的黄河中下游水沙变化特点研究

为进一步揭示黄河中下游水沙关系及变化规律,本文通过自组织映射(Self-Organizing Map)-K均值聚类(K-means clustering)耦合方法,利用黄河中游潼关水文站1919—2018年的年径流量及年输沙量数据,对该站的水沙组合进行分类。结果表明:潼关站水沙类型有沙多水多、沙多水中、沙中水中及沙少水中4种。结合新中国成立后黄河流域水土保持事业的发展情况,以1960年及2000年为时间节点将研究时段分为3个阶段,分析了上述4种类型在3个阶段的出现频率及变化特点。考虑到黄河水沙条件的变化,又对1986年以来潼关站的水沙组合进行分类。结果表明:该站在1986年后的水沙类型有沙中水中及沙少水中2种。两种时间序列下的分类结果略有差异,体现出黄河水沙变化的复杂性。

Research on variation of runoff and sediment load based on the combination patterns in the Middle and Lower Yellow River

A coupled clustering method of the Self-Organizing Map and K-means clustering is developed and adopted on the annual runoff and sediment load data (1919-2018) at Tongguan (TG) station to fur-ther reveal the runoff-sediment patterns of the middle and lower Yellow River. The results indicate that the runoff-sediment patterns of TG station can be divided into four types and their occurrence frequencies vary significantly in the three characteristic periods of the Yellow River. Moreover, considering the variation of annual runoff and sediment load in the Yellow River after 1986, the annual runoff and sediment load data at TG station from 1987 to 2018 are also analyzed and divided into two types using the coupled clustering method. The difference between the two sets results reflects that the rows of runoff and sediment load varia-tion in the Yellow River are very complicated.