时空多特征流域场景模式库构建方法

通过构建流域时空场景表征水文事件，提出一种创新的时空多特征流域场景模式库构建方法。对水文原始数据进行事件化分割，去除场景要素数据的时空冗余；基于要素关联关系分析，以多类型方法构造场景要素的对应特征；通过特征选择算法，选取场景关键特征，实现场景初始化；以初始化场景为特征空间，通过聚类提取场景模式，完成场景模式库构建。试验结果表明，创新的时空多特征流域场景模式库构建方法能高效提取水文事件中关键的时空场景数据，挖掘场景模式，形成场景模式库，可以为小样本条件下的水文事件预测提供准确高效的结果。

Construction method of watershed scene pattern library via spatio-temporal multiple features

By representing hydraulic events via constructing multiple features of the watershed spatio-temporal scene, this study proposed a construction method of watershed scene pattern library via the spatio-temporal multiple features. The original hydrological data was firstly divided into events to remove the spatio-temporal redundancy of scene element data. Based on the analysis of element association relation, the corresponding features of scene elements were constructed via multiple ways. Afterwards, key features of watershed scene were selected by the feature selection algorithm to realize the scene initialization. Finally, the initial scene was regarded as the feature space, where the cluster extraction of scene pattern and scene pattern library construction could be carried out. Experimental results show that the proposed method can not only extract the key spatio-temporal scene data of hydrological events, but also mine scene patterns to form a scene pattern library, thus providing accurate and efficient prediction results for the hydrological event with small dataset.