Challenges and Technical Advances in Flood Early Warning Systems (FEWSs)

Duminda Perera, O. Seidou, Jetal Agnihotri, H. Mehmood, M. Rasmy
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引用次数: 13

Abstract

Flood early warning systems (FEWSs)—one of the most common flood-impact mitigation measures—are currently in operation globally. The UN Office for Disaster Risk Reduction (UNDRR) strongly advocates for an increase in their availability to reach the targets of the Sendai Framework for Disaster Risk Reduction and Sustainable Development Goals (SDGs). Comprehensive FEWS consists of four components, which includes (1) risk knowledge, (2) monitoring and forecasting, (3) warning, dissemination, and communication, and (4) response capabilities. Operational FEWSs have varying levels of complexity, depending on available data, adopted technology, and know-how. There are apparent differences in sophistication between FEWSs in developed countries that have the financial capabilities, technological infrastructure, and human resources and developing countries where FEWSs tend to be less advanced. Fortunately, recent advances in remote sensing, artificial intelligence (AI), information technologies, and social media are leading to significant changes in the mechanisms of FEWSs and provide the opportunity for all FEWSs to gain additional capability. These technologies are an opportunity for developing countries to overcome the technical limitations that FEWSs have faced so far. This chapter aims to discuss the challenges in FEWSs in brief and exposes technological advances and their benefits in flood forecasting and disaster mitigation.
洪水预警系统的挑战与技术进步
洪水预警系统(FEWSs)是最常见的洪水影响缓解措施之一,目前正在全球范围内运行。联合国减少灾害风险办公室(UNDRR)强烈主张增加其可用性,以实现仙台减少灾害风险框架和可持续发展目标(SDGs)的目标。综合FEWS由四个部分组成,包括(1)风险知识,(2)监测和预测,(3)预警、传播和沟通,以及(4)响应能力。可操作的fews具有不同程度的复杂性,这取决于可用的数据、采用的技术和专门知识。在拥有财政能力、技术基础设施和人力资源的发达国家和发展中国家,少数信息系统的复杂性明显不同,而发展中国家的少数信息系统往往不那么先进。幸运的是,遥感、人工智能(AI)、信息技术和社交媒体的最新进展正在导致fews机制的重大变化,并为所有fews提供了获得额外能力的机会。这些技术是发展中国家克服迄今为止所面临的技术限制的机会。本章旨在简要讨论洪水预报系统的挑战,并揭示技术进步及其在洪水预报和减灾方面的好处。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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