摘要
随着城市化进程的加速和气候变化的影响,城市内涝已经成为全球城市面临的严峻环境问题之一。在此背景下,采用文献计量分析方法,系统地整理了城市内涝预测技术的研究和发展状况。在城市内涝的形成机制方面,一是城市地表面积不足,难以有效地接收和排放降雨水,进而导致降雨径流的堆积。二是城市排水系统不完善,无法及时、有效地将雨水排走,加剧了内涝问题的发生。本文将城市内涝预测技术划分为三种:1.基于模型的预测技术,在准确性和可靠性方面表现出色,但需要面对复杂的模型建立过程和数据要求。2.基于遥感和GIS的预测技术,虽然可以提供广泛的实时数据支持,但需要解决数据处理和成本问题。3.基于人工智能算法的预测技术,具备高准确度和自适应性,但对数据质量和模型参数设置有较高要求。不同技术应根据实际情况进行选择,且需要不断优化以提高预测准确性和可靠性。在此基础上,从数据获取和处理困难、模型不确定性和误差、时间空间尺度问题和多元不确定性等四个方面分析了城市内涝预测技术所面临的问题与挑战。最后提出了未来的发展方向,包括多源数据集成、发展实时监测技术、提高模型精度和稳定性、高效计算方法的研究、多尺度预测方法的探索,以及建立全面的预警系统和应急响应机制。旨在为城市内涝预测技术的发展提供参考和启示,以期为解决城市内涝问题提供有力的支撑和帮助。
With the acceleration of urbanisation and the impact of climate change,urban flooding has become one of the serious environmental problems around the world.In this context,this paper adopts the bibliometric analysis method to systematically collate the research and development status of urban flood prediction techniques.In terms of the formation mechanisms of urban flooding,the first one is the insufficient surface area of the city,which makes it difficult to effectively receive and discharge rainfall water,which in turn leads to the accumulation of rainfall runoff.The second one is the imperfection of urban drainage system,which is unable to drain rainwater away in a timely and effective manner,exacerbating the problem of water logging.In this paper,urban flood prediction techniques are classified into three types:1.model-based prediction techniques,which excel in accuracy and reliability,but need to face complex model building processes and data requirements.2.remote sensing and GIS-based prediction techniques,which can provide extensive real-time data support,but need to solve the problems of data processing and cost.3.AI algorithmbased prediction techniques,which have high accuracy and adaptivity,but have high requirements on data quality and model parameter settings.Different techniques should be selected according to the actual situation and need to be continuously optimised to improve prediction accuracy and reliability.On this basis,the problems and challenges faced by urban flood prediction techniques are analyzed from four aspects:data acquisition and processing difficulties,model uncertainty and error,time-space scale problems and multivariate uncertainty.Finally,future development directions are proposed,including integration of multi-source data,development of real-time monitoring technology,improvement of model accuracy and stability,research on efficient computational methods,exploration of multi-scale prediction methods,and establishment of a comprehensive early warning system and emergency response mechanism.This paper aims to provide reference and inspiration for the development of urban flood prediction technology,with a view to providing strong support and assistance in solving urban flooding problems.
作者
王金龙
潘志安
黄衡
宋会萌
董梦涛
WANG Jin-long;PAN Zhi-an;HUANG Heng;SONG Hui-meng;DONG Meng-tao(Institute of Disaster Prevention,Langfang 065000,Hebei)
出处
《电脑与电信》
2023年第8期74-79,共6页
Computer & Telecommunication
关键词
城市内涝
内涝机制
影响因素
人工智能
多源融合
urban flooding
flooding mechanism
influencing factors
artificial intelligence
multi-source fusion