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中文摘要：
新安江模型是我国研制的经典的概念性流域水文模型，其参数往往通过人工试错法进行率定，在洪水的实时预报中需建立误差自回归模型来修正预报值。人工神经网络模型是一种数据驱动模型，它可以通过算法调节权值和偏置值来模拟信息，实现了模型参数的自动率定。在实时预报的应用中，人工神经网络模型可以根据计算误差调节权值和偏置值，反映水文过程的时变性，模型结构显得更加简洁。本文将两种模型应用于潢川流域并作比较。它们的预报结果都达到了作业预报要求。在实际应用中可以根据资料情况选择模型进行洪水预报。
英文摘要：
Xinanjiang model is a classic conceptual rainfall runoff model of river basins developed in China. The parameters of the model are always calibrated in the way of manual trail and error. In real time flood forecasting, it is necessary to modify the forecasted values with an error regression model. Artificial neural network （ANN） is a data driven model, which can adjust weights and bias automatically in terms of calculation error to reflect timing variety of hydrological process. The structure of ANN model is simpler than Xinanjiang model. In this paper, both of the models were applied for flood forecasting in the Huangchuan River Basin. The forecasted results by the models all met the requirement of the operational. In practice, operators can choose model according to data condition for flood forecasting.
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