用于洪水应急管理的双向耦合 CHANS 模型,重点关注临时防洪设施

IF 4.8 2区 环境科学与生态学 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Environmental Modelling & Software Pub Date : 2024-07-26 DOI:10.1016/j.envsoft.2024.106166
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引用次数: 0

摘要

本研究提出了一种新颖的 "人类与自然系统耦合(CHANS)"建模框架,该框架在多 GPU 计算环境中将水动力模型与基于代理的内存级模型集成在一起。该双向耦合模型捕捉了人类活动与洪水动态之间的实时互动,重点研究了 2015 年英国卡莱尔德斯蒙德洪水期间临时防洪设施的部署情况。研究结果表明,通过预警和实时决策,临时防洪设施可将洪水淹没率分别大幅降低 30%和 15%,从而分别节省 3000 万英镑和 1500 万英镑的资金。该研究进一步探讨了有效应急洪水管理的决策过程,强调了预警和资源优化的重要性。新的 CHANS 模型为测试和优化紧急洪水管理策略提供了宝贵的工具,强调了将人类活动直接纳入洪水风险管理的必要性。
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A two-way coupled CHANS model for flood emergency management, with a focus on temporary flood defences

This study presents a novel Coupled Human And Natural Systems (CHANS) modelling framework that integrates a hydrodynamic model with an agent-based model at the memory level within a multi-GPU computing environment. This two-way coupled model captures real-time interactions between human activities and flood dynamics, with a focus on the deployment of temporary flood defences during the 2015 Desmond flood in Carlisle, UK. The findings reveal that temporary defences can significantly reduce flood inundation by 30% with early warnings and 15% through real-time decision-making, leading to financial savings of £30 million and £15 million, respectively. The study further explores the decision-making process for effective emergency flood management, emphasising the importance of early warnings and resources optimisation. The new CHANS model provides a valuable tool for testing and optimising emergency flood management strategies, highlighting the necessity of directly incorporating human activities into flood risk management.

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来源期刊
Environmental Modelling & Software
Environmental Modelling & Software 工程技术-工程:环境
CiteScore
9.30
自引率
8.20%
发文量
241
审稿时长
60 days
期刊介绍: Environmental Modelling & Software publishes contributions, in the form of research articles, reviews and short communications, on recent advances in environmental modelling and/or software. The aim is to improve our capacity to represent, understand, predict or manage the behaviour of environmental systems at all practical scales, and to communicate those improvements to a wide scientific and professional audience.
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