Multiple factors including rainfall and underlying surface conditions make river basin real-time flood forecasting very challenging. It is often necessary to use real-time correction techniques to modify the forecasting results so that they reach satisfactory accuracy. There are many such techniques in use today; however, they tend to have weak physical conceptual basis, relatively short forecast periods, unsatisfactory correction effects, and other problems. The mechanism that affects real-time flood forecasting error is very complicated. The strongest influencing factors corresponding to this mechanism affect the runoff yield of the forecast model. This paper proposes a feedback correction algorithm that traces back to the source of information, namely, modifies the watershed runoff. The runoff yield error is investigated using the principle of least squares estimation. A unit hydrograph is introduced into the real-time flood forecast correction; a feedback correction model that traces back to the source of information. The model is established and verified by comparison with an ideal model. The correction effects of the runoff yield errors are also compared in different ranges. The proposed method shows stronger correction effect and enhanced prediction accuracy than the traditional method. It is also simple in structure and has a clear physical concept without requiring added parameters or forecast period truncation. It is readily applicable in actual river basin flood forecasting scenarios.

中文翻译：

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实时洪水预报径流误差的系统响应曲线修正方法

包括降雨量和下垫面条件在内的多种因素使流域实时洪水预报非常具有挑战性。通常需要使用实时校正技术来修改预测结果，使其达到令人满意的准确性。今天有许多这样的技术在使用。但它们往往存在物理概念基础薄弱、预测周期较短、修正效果不理想等问题。影响实时洪水预报误差的机制非常复杂。与该机制对应的最强影响因素影响预测模型的产流量。本文提出了一种回溯信息源的反馈修正算法，即修正流域径流。使用最小二乘估计原理研究径流产量误差。将单位水位线引入实时洪水预报修正；一个回溯到信息来源的反馈修正模型。建立模型并与理想模型进行对比验证。径流产率误差的修正效果也在不同范围内进行了比较。与传统方法相比，该方法显示出更强的校正效果和更高的预测精度。它结构简单，物理概念清晰，无需增加参数或预测期截断。它很容易应用于实际的流域洪水预报场景。一个回溯到信息来源的反馈修正模型。建立模型并与理想模型进行对比验证。径流产率误差的修正效果也在不同范围内进行了比较。与传统方法相比，该方法显示出更强的校正效果和更高的预测精度。它结构简单，物理概念清晰，无需增加参数或预测期截断。它很容易应用于实际的流域洪水预报场景。一种追溯信息源的反馈修正模型。建立模型并与理想模型进行对比验证。径流产率误差的修正效果也在不同范围内进行了比较。与传统方法相比，所提出的方法显示出更强的校正效果和更高的预测精度。它结构简单，物理概念清晰，无需增加参数或预测期截断。它很容易应用于实际的流域洪水预报场景。与传统方法相比，所提出的方法显示出更强的校正效果和更高的预测精度。它结构简单，物理概念清晰，无需增加参数或预测期截断。它很容易应用于实际的流域洪水预报场景。与传统方法相比，所提出的方法显示出更强的校正效果和更高的预测精度。它结构简单，物理概念清晰，无需增加参数或预测期截断。它很容易应用于实际的流域洪水预报场景。