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混沌与随机是本质上不同的两种特性。区分产生洪水过程系统的混沌性和随机性是进行洪水模拟和预测的基础。从洪水时间序列出发，通过非线性动力系统重构和信息提取识别其基本特征。初步结果表明，洪水时间序列具有混沌动力系统的一些特征，即存在具有较低分维值、正的Ｌｙａｐｕｎｏｖ指数和Ｋｏｌｏｍｏｇｏｌｏｖ熵的奇怪吸引子，从而表明看起来异常复杂的洪水现象可能是由内在的非线性动力系统演化的结果。
Chaos and random are essentially two different characteristics. Distinguishing the chaos and randomness of the flood process system is the basis for flood simulation and prediction. Based on the flood time series, the basic features are identified through nonlinear dynamical system reconstruction and information extraction. The preliminary results show that the flood time series possesses some characteristics of the chaotic dynamic system, that is, strange attractors with lower fractal values, positive Lyapunov exponents and Kolomogolov entropies, indicating that the seemingly complex flood phenomena may be caused by intrinsic The result of nonlinear dynamical system evolution.