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淮河流域2016年汛期洪水预报试验

包红军 曹勇 张珂 魏丽 李致家 宗志平 谌芸 狄靖月 栾承梅 刘开磊

气象2017,Vol.43Issue(7):831-844,14.
气象2017,Vol.43Issue(7):831-844,14.DOI:10.7519/j.issn.1000-0526.2017.07.007

淮河流域2016年汛期洪水预报试验

Test on Flood Forecasts for Huaihe River in the 2016 Flood Season

包红军 1曹勇 1张珂 2魏丽 3李致家 1宗志平 4谌芸 1狄靖月 1栾承梅 1刘开磊5

作者信息

  • 1. 国家气象中心,北京 100081
  • 2. 河海大学水文水资源学院,南京 210098
  • 3. 河海大学水文水资源与水利工程科学国家重点实验室,南京 210098
  • 4. 河海大学水文水资源学院,南京 210098
  • 5. 江苏省水文水资源勘测局,南京 210029
  • 折叠

摘要

Abstract

Rainfall runoff simulation and flood forecasting of large river basins is a complex prediction problem.An integrated hydro-meteorological forecast model is developed for flood forecast test of complex river basins.Grid-based quantitative precipitation forecast products of National Meteorological Centre are applied as precipitation of lead-time period,and the Xin'anjiang hydrological model is used for rainfall-runoff process simulation.The Muskingum-Cunge model,based on diffusion,columbar storage and wedge storage theory,is introduced for channel water-level and discharge forecasting.For the test case of the upper reaches of the Lutaizi Station of the Huaihe River in flood season of 2016,the developed hydro-meteorological forecast model of complex river basins is applied in flood forecast test.The results show that the developed model can perform well.Compared with no considering the precipitation in lead-time period,the flood forecast lead time can be increased obviously.The developed model has certain reference significance for flood forecasting over similar basins.

关键词

洪水预报试验/格点化定量降水预报/新安江模型/Muskingum-Cunge/水位流量预报/淮河流域

Key words

flood forecast test/grid-based quantitative precipitation forecasting/Xin'anjiang model/Muskingum-Cunge/water level and discharge forecast/Huaihe River Basin

分类

天文与地球科学

引用本文复制引用

包红军,曹勇,张珂,魏丽,李致家,宗志平,谌芸,狄靖月,栾承梅,刘开磊..淮河流域2016年汛期洪水预报试验[J].气象,2017,43(7):831-844,14.

基金项目

国家自然科学基金项目(51509043)、国家重点研发计划项目(2016YFC0402702、2016YFC0402701和2016YFC0402705)、中国气象局首批青年英才计划“中小河流洪水气象预警关键技术研究”(2014-2017)、国家气象中心水文气象预报团队项目、中国气象局气象预报业务关键技术发展专项[YBGJXM(2017)06]和中国气象局气象预报预测业务与科研结合专项(CMAHX20160601)共同资助 (51509043)

气象

OA北大核心CSCDCSTPCD

1000-0526

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