辽宁省资料短缺地区中小河流洪水预报方法

我国中小河流大多位于山丘区,水文站点稀少,资料短缺,而产生的洪水往往突发性强、破坏力大,中小河流洪水预报研究是重要课题。针对辽宁中小河流洪水预报特点,本文提出了一种资料缺乏地区中小河流洪水预报方法。首先收集与提取中小河流流域的下垫面、水文、气象等基本资料,采用主成分分析方法形成新指标,降低指标维数并减少相关性;利用可变模糊聚类方法对辽宁省中东部30个参证站和84个中小河流站进行水文相似性分类识别,划分为8个水文相似组;建立Topmodel洪水预报模型进行洪水模拟,对参数移植前后模拟精度进行对比分析,验证了方法的有效性与实用性。本文研究成果可为辽宁省中小河流洪水预报提供支撑,可为其他资料短缺地区洪水预报方案编制提供参考。

Flood forecasting method for medium- and small-size rivers short of hydrological data in Liaoning Province

Most of the medium- and small-size rivers in China are located in hilly areas where hydrological stations are sparse and limited monitoring data are available, but these rivers can generate floods characterized by sudden, strong and great destructiveness. Thus, how to predict the floods in such rivers attracts much attention. This paper presents a flood prediction method for medium and small rivers for better consideration of the characteristics of these rivers in Liaoning Province. We collect and extract the basic data of underlying surface, hydrology, meteorology, etc. , and extract a new set of irrelevant indexes using the principal component analysis that can reduce the dimension and influence of related indexes. Then, a variable fuzzy model is used to classify and identify the hydrological similarity of 30 reference stations and 84 river stations. Finally, we construct a Topmodel model for prediction of distributed floods, and verify its effectiveness and practicability through comparison of its accuracies in flood predictions for the reference stations before and after parameter transplantation. Our results lay a basis for flood prediction of the medium- and small-size rivers in Liaoning Province, and are also useful to flood forecasting of other valleys short of hydrological data.