摘要
沙澧河流域致洪预警系统基于中小河流致洪预警气象服务需求,以气象与水文相结合,应用地理信息(GIS)先进技术,利用气象常规数据、地面自动雨量站资料、数值模式、卫星雷达资料及水文雨量、水位数据等资料,运用动力学诊断和统计分析、多元线性回归方法、模式输出法、相似预报等方法,输出暴雨和水位增量预报模型。该系统通过C/C++语言编程,集气象水文信息显示分析、数据库、预报模型和用户界面于一体,建立了涵盖流域暴雨预报、水位增量监测预测、洪涝灾害预警服务等多功能的可视化业务技术平台。在本地基层台站首次将气象和水文两个学科结合,建立降水、水文和洪涝数据库;首次对沙澧河流域进行暴雨形势分型,并建立流域暴雨预报模型;首次建立沙澧河流域五大水库水位增量预报模型。自系统运行以来,成功对沙澧河流域出现的几次致洪暴雨进行了预警,服务效果明显。
Based on the meteorological service demanding of medium and small river flood forecasting,combining meteorology and hydrology,using the advanced technology of geographic information system(GIS) and using meteorological routine data,ground automatic rainfall station data,numerical model,satellite radar data and hydrological rainfall and water level data,the flood early warning system in Sha-Li River basin outputs heavy rainfall and water level increment forecasting model by using dynamic diagnosis and statistical analysis,multiple linear regression method,model output method,similarity prediction and other methods. The system integrates meteorological and hydrological information display and analysis system,database,forecasting model and user interface through the C/C + + language programming. It is a multi-functional and visual operational technology platform,covering rainstorm forecasting,water level increment monitoring and forecasting,flood disaster warning service,etc. The rainstorm situation in Sha-Li River basin is first classified and rainstorm forecasting model is built,while the water level increment forecasting model of 5 large reservoirs in Sha-Li River basin is first established. The system is successful in several flood-induced rainstorm early warning in the flood season in the Sha-Li River basin since in operation and makes obvious service effect.
作者
李戈
武威
Li Ge;Wu Wei(Pingdingshan Meteorological Office,Pingdingshan 467001,China;Luohe Meteorological Office,Luohe 462300,China)
出处
《气象与环境科学》
2018年第1期138-143,共6页
Meteorological and Environmental Sciences
基金
河南省气象局预报员专项"沙澧河流域对流性暴雨多元资料中尺度特征分析"(KQ201741)资助
关键词
沙澧河流域
致洪预警
模式输出
预报模型
Sha-Li river basin
flood warning
model output
torecasting model