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首页> 外文会议>International Symposium on Flood Forecasting and Water Resources Assessment for IAHS-PUB >Real-time Flood Forecasting: A Model Based on Volterra Series and its Application in Semiarid Area
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Real-time Flood Forecasting: A Model Based on Volterra Series and its Application in Semiarid Area

机译：实时洪水预测：基于Volterra系列的模型及其在半干旱区域的应用

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摘要

Mechanism identification and model selection for hydrological modeling in semiarid river basin are of great importance and urgency, especially in ungauged basins. On the basis of the present models with systematic approach, a total runoff non-linear response model based on Volterra series (Volterra-TNLR model) is proposed, and its expressions in matrix are deduced, together with its solving process. A 3-layer artificial neural network (ANN) model is introduced to simulate the self-relative relationships of error series between observed and calculated runoff. And then the predicted runoff can be calibrated dynamically by ANN model in the process of realtime flood forecasting. Both the Volterra-TNLR and ANN model have clear structure and high capability of non-linear mapping, and {hey are easy to be programmed and integrated into a real-time flood forecasting system. A semiarid watershed (Qian River) in northwestern China was considered as an example to verify the Volterra-TNLR model. The results showed that the model has a high precision, and it can be used in the similar semiarid river basins.
机译：半干旱河流域水文模型的机制鉴定及模型选择具有重要的重要性和紧迫性，特别是在未吞噬的盆地中。在具有系统方法的本模型的基础上，提出了一种基于Volterra系列（Volterra-TNLR模型）的总径流非线性响应模型，并推导出其在矩阵中的表达式及其解决方法。引入了3层人工神经网络（ANN）模型，以模拟观察和计算径流之间的错误系列的自相对关系。然后，在实时洪水预测过程中可以通过ANN模型动态校准预测的径流。 Volterra-TNLR和ANN模型都具有明显的结构和高能力的非线性映射，{嘿易于编程并集成到实时洪水预测系统中。中国西北部的半干旱水域（Qian River）被认为是验证Volterra-TNLR模型的示例。结果表明，该模型具有高精度，可用于类似的半干旱河流域。

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