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作为雨洪系统的输出——洪水时间序列，它包含了系统中各种变量的过去信息，同时蕴含着大量关于系统演变的规律和趋势，这样的时间序列往往是不可逆的，非性线相依的偏态序列，并且存在着广泛的频幅相依特性。在进行洪水预报时，传统法多采用线性化技术，但预报精度并不理想，因此要提高预报精度，有必要考虑洪水的非线性特性。基于此，本文用指数自回归模型进行洪水预报研究，实例分析表明该模型可提高洪水预报精度。本文的尝试工作为洪水预报提供了一种可行的模型。
As the output-flood time series of flood system, it contains the past information of various variables in the system and contains a large number of laws and trends about the evolution of the system. Such time series are often irreversible and non-linearly dependent Skewed sequence, and there is a wide range of frequency-dependent characteristics. In flood forecasting, the traditional method mostly uses the linearization technique, but the prediction accuracy is not ideal. Therefore, to improve the forecasting accuracy, it is necessary to consider the nonlinear characteristics of the flood. Based on this, this paper uses exponential autoregressive model to carry out flood forecasting research. The case study shows that the model can improve flood forecasting accuracy. The work of this paper provides a feasible model for flood forecasting.