Application of Response Function Model to Sediment Concentration Prediction

SHI Bao; QIN Yi; LING Yan; LI Nan; QIAN Yun-ping

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Application of Response Function Model to Sediment Concentration Prediction

- Application of Response Function Model to Sediment Concentration Prediction
- Bulletin of Soiland Water Conservation Vol. 27, Issue 2, Pages: 103-105(2008)
- 作者机构：
  
  1. 西安理工大学西北水资源与环境生态教育部重点实验室,陕西,西安,710048
  2. 黄委会水文局,河南,郑州,450004
- 作者简介：
- 基金信息：
- DOI：
  CLC：
- Published：2008
- 稿件说明：
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SHI Bao, QIN Yi, LING Yan, et al. Application of Response Function Model to Sediment Concentration Prediction[J]. Bulletin of Soiland Water Conservation, 2008, 27(2): 103-105.
DOI：

SHI Bao, QIN Yi, LING Yan, et al. Application of Response Function Model to Sediment Concentration Prediction[J]. Bulletin of Soiland Water Conservation, 2008, 27(2): 103-105. DOI：

摘要

黄河的泥沙问题一直是黄河治理的重点。依据黄河下游"多来多排"的输沙特性

建立了多输入单输出的含沙量过程预报响应函数模型。经对黄河下游花园口至夹河滩河段洪水含沙量过程预报的检验

并与常见的神经网络方法相比

其预报精度优于后者

且稳定性好。研究表明

响应函数模型适用于黄河下游河段的含沙量过程预报。

Abstract

Sediment control is the major work for the management of Yellow River.A response function is established based on the sediment transport characteristic of "more in

more out".The test for sediment concentration prediction in the lower reaches of Yellow River shows that the response function is better than neural network model.This indicates that response function model is applicable to sediment prediction.

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