摘要
本文结合对雨量数据的分析,总结了泥石流自动实时监测预警中的一些关键技术,并提出一种基于降雨过程的泥石流实时监测预警的解决方案。在泥石流的监测预警工作中,目前多采用雨强与累计雨量作为主要参数,如何正确识别一场降雨过程,对于提高监测预警的精度具有重要的意义。结合监测数据特征,本文采用詹钱登对降雨过程的划分标准,基于数据库技术实现对降雨过程的自动识别,为后续预警参数的获取提供支撑。由于受雨量计工作模式的影响,其原始数据的时间间隔是随机的,不能直接用于预警模型的计算,因此对雨量监测数据进行等时间间隔的处理。在预警流程方面,如何实现预警过程无人工干预的完全自动、实时与稳定运行,一直是预警工作中的难点,本研究中引入"系统服务"这一技术,将整套预警系统作为系统级别的后台服务运行于服务器上,能够保证整个预警过程稳定地运行,真正意义上实现了泥石流监测预警过程的自动化与实时化。本文研究成果应用于走马岭沟泥石流监测预警中,成功对2013年7月8日的泥石流事件进行预警。
Based on the analysis of rainfall data,this paper summarizes some key technologies of debris flow automatic real-time monitoring and early warning,and presents a solution and a system for real-time monitoring and early warning of debris flow based on rainfall process. Rainfall intensity and cumulative rainfall are the main parameters for the early warning of debris flow. Methods to correctly identify a rainfall process are of great significance for improving the accuracy of debris flow monitoring and early warning. Combined with the characteristics of the rainfall data,and the criterion of the classification of a rainfall process presented by Jan,the automatic recognition of the rainfall process is realized with the database technique. Due to the influence of the rain gauge operating mode,the time interval of the original data is random. It cannot be directly used for the calculation of the early warning model. Therefore,the rainfall data need to be treated at equal intervals. In the process of early warning,the task to achieve early warning process without manual intervention completely automatic,real-time andstable operation has been a difficult problem of early warning work. This solution introduces the ＂system services＂technology. The entire early warning system is as a system-level background service running on the server to ensure the stable operation of the whole process of early warning and to achieve a true sense of the automatic real-time process of monitoring and early warning of debris flow. The results of this study are applied to the monitoring and early warning of debris flow in Zoumaling gully,which successfully predicted the debris flow events in July 8,2013.
作者
何朝阳
许强
巨能攀
黄健
肖洋
HE Chaoyang;XU Qiang;JU Nengpan;HUANG Jian;XIAO Yang(State Key Laboratory of Geohazard Prevention and Geoenvironment Protection（Chengdu University of Technology）,Chengdu 610059)
出处
《工程地质学报》
CSCD
北大核心
2018年第3期703-710,共8页
Journal of Engineering Geology
基金
国家自然科学重点基金项目(41630640)
国家创新研究群体科学基金(41521002)资助
关键词
泥石流
监测数据
监测预警
数据库
系统服务
Debris Flow
Monitoring Data
Monitoring and early warning
Database
System service
