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降雨监测与预报技术在防洪减灾中的应用进展

原文林 杨逸凡 赵小棚 郭进军 胡少伟

人民长江2024,Vol.55Issue(8):8-14,22,8.
人民长江2024,Vol.55Issue(8):8-14,22,8.DOI:10.16232/j.cnki.1001-4179.2024.08.002

降雨监测与预报技术在防洪减灾中的应用进展

Application progress of rainfall monitoring and forecasting techniques in flood control and disaster reduction

原文林 1杨逸凡 1赵小棚 1郭进军 1胡少伟1

作者信息

  • 1. 郑州大学水利与交通学院,河南郑州 450001
  • 折叠

摘要

Abstract

Flood disasters are highly sudden and develop rapidly,posing significant threats to people's lives and properties safe-ty.Rainfall is a disaster-causing factor for floods,and the accuracy of rainfall data is of great significance for flood control and disaster reduction.Focusing on rainfall monitoring and forecasting technology,we summarized the current state of rain gauge obser-vations,weather radar rainfall estimation and forecasting,numerical weather prediction,and satellite remote sensing inversion.By analyzing the application of spatiotemporal downscaling methods and multi-source data fusion technology in rainfall monitoring and forecasting,we reveal their effectiveness in improving the accuracy of both the"quantity"and"type"of rainfall data.Re-search indicates that significant progress has been made in rainfall monitoring and forecasting technology.However,challenges re-main in complex terrains,such as mountainous and urban environments,where resolution is limited and accuracy and timeliness are insufficient.Multi-source data fusion can improve the accuracy of rainfall data,spatiotemporal coverage,and prediction accu-racy.Therefore,optimizing algorithm models and integrating multi-source data from"space-sky-ground"to create high-res-olution forecasts is a future research direction.

关键词

降雨监测/降雨预报/防洪减灾/卫星遥感/天气雷达/数值预报/降尺度/多源数据融合

Key words

rainfall monitoring/rainfall forecasting/flood control and disaster reduction/satellite remote sensing/weather ra-dar/numerical prediction/downscaling/multi-source data fusion

分类

建筑与水利

引用本文复制引用

原文林,杨逸凡,赵小棚,郭进军,胡少伟..降雨监测与预报技术在防洪减灾中的应用进展[J].人民长江,2024,55(8):8-14,22,8.

基金项目

国家重点研发计划项目(2022YFC3004401) (2022YFC3004401)

人民长江

OA北大核心CSTPCD

1001-4179

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