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基于土壤墒情抗差的降雨径流预报模型——设计与实验流域应用
引用本文:沈丹丹,包为民,江鹏,张阳,费如君.基于土壤墒情抗差的降雨径流预报模型——设计与实验流域应用[J].湖泊科学,2017,29(6):1510-1519.
作者姓名:沈丹丹  包为民  江鹏  张阳  费如君
作者单位:河海大学水文水资源学院, 南京 210098,河海大学水文水资源学院, 南京 210098,Desert Research Institute, Las Vegas Nevada USA, 89119,中国电建集团中南勘测设计研究院有限公司, 长沙 410014,中国电建集团中南勘测设计研究院有限公司, 长沙 410014
基金项目:国家重点研发计划专项(2016YFC0402703)和国家自然科学基金项目(41371048,51479062)联合资助.
摘    要:本文旨在将实时监测得到的土壤墒情转化为流域水文模型可以直接使用的土壤含水量,论证将实时土壤墒情资料用于实时预报的可行性;利用实时监测土壤墒情,改进传统的模型结构,设计基于实测土壤墒情的降雨径流水文预报模型.采用土壤含水量误差抗差估计技术以抵御观测资料粗差的影响,提高系统的稳定性;并在此基础上提出了土壤含水量系统响应修正方法,以提高模型计算精度.将该模型应用于实验流域——宝盖洞流域进行应用检验,洪水模拟合格率达到92.3%,整体模拟精度达到甲级.

关 键 词:土壤墒情  土壤墒情抗差  土壤含水量修正  系统响应曲线  降雨径流预报模型  洪水预报
收稿时间:2016/12/9 0:00:00
修稿时间:2017/2/19 0:00:00

Rainfall-runoff forecast model based on robust correction of soil moisture:Design and application in an experimental basin
SHEN Dandan,BAO Weimin,JIANG Peng,ZHANG Yang and FEI Rujun.Rainfall-runoff forecast model based on robust correction of soil moisture:Design and application in an experimental basin[J].Journal of Lake Science,2017,29(6):1510-1519.
Authors:SHEN Dandan  BAO Weimin  JIANG Peng  ZHANG Yang and FEI Rujun
Institution:College of Water Resources and Hydrology, Hohai University, Nanjing 210098, P. R. China,College of Water Resources and Hydrology, Hohai University, Nanjing 210098, P. R. China,Desert Research Institute, Las Vegas Nevada USA, 89119,Power China Zhongnan Engineering Corporation Limited, Changsha 410014, P. R. China and Power China Zhongnan Engineering Corporation Limited, Changsha 410014, P. R. China
Abstract:This study is aimed to convert the real-time measured soil moisture into the soil water content which can be used directly in the watershed hydrological model, and demonstrate the feasibility of using the real-time measured soil moisture for real-time forecasting. In this paper, a rainfall-runoff hydrological forecasting model based on the measured soil moisture is proposed to improve the structure of the traditional model. The soil moisture robust estimation technique is used to resist the influence of gross error, and improve the stability of the system. On that basis, a soil water content error correction method based on a system response curve is introduced into the model to improve the accuracy of the model. The model is applied in an experimental basin named Baogaidong Basin. The result indicates that the qualification rate of basin flood simulation reaches 92.3%, and the overall simulation accuracy reaches Class A.
Keywords:Measured soil moisture  robust correction of soil moisture  soil water content error correction  system response curve  rainfall-runoff forecast model  flood forecasting
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