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地理空间测绘与气象洪水风险评估:全球研究趋势分析

Geospatial Mapping and Meteorological Flood Risk Assessment: A Global Research Trend Analysis.

作者信息

Sibandze Phila, Kalumba Ahmed Mukalazi, H Aljaddani Amal, Zhou Leocadia, Afuye Gbenga Abayomi

机构信息

Department of GIS and Remote Sensing, University of Fort Hare, P/Bag X1314, Alice, 5700, South Africa.

Department of Geography and Environmental Science, University of Fort Hare, Private Bag X1314, Alice, 5700, Eastern Cape Province, South Africa.

出版信息

Environ Manage. 2025 Jan;75(1):137-154. doi: 10.1007/s00267-024-02059-0. Epub 2024 Oct 12.

DOI:10.1007/s00267-024-02059-0
PMID:39395037
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11717870/
Abstract

Flooding is a global threat causing significant economic and environmental damage, necessitating a policy response and collaborative strategy. This study assessed global research trends and advances in geospatial and meteorological flood risk assessment (G_MFRA), considering the ongoing debate on flood risk management and adaptation strategies. A total of 1872 original articles were downloaded in BibTex format using the Web of Science (WOS) and Scopus databases to retrieve G_MFRA studies published from 1985 to 2023. The annual growth rate of 15.48% implies that the field of G_MFRA has been increasing over time during the study period. The analysis of global trends in flood risk research and practice highlights the key themes, methodologies, and emerging directions. There exists a notable gap in data and methodologies for flood risk assessment studies between developed and developing countries, particularly in Africa and South America, highlighting the urgency of coordinated research efforts and cohesive policy actions. The challenges identified in the body of extant literature include technical expertise, complex communication networks, and resource constraints associated with the application gaps of the study methodologies. This study advocates for a holistic research approach to flood disaster management through ecosystem-based adaptation that underpins the Sustainable Development Goals to develop innovative flood techniques and models with the potential to influence global decision-making in the G_MFRA domain. Addressing these global challenges requires a networked partnership between the research community, institutions, and countries.

摘要

洪水是一种全球性威胁,会造成重大的经济和环境破坏,因此需要政策应对和协作战略。本研究评估了地理空间和气象洪水风险评估(G_MFRA)的全球研究趋势和进展,同时考虑了正在进行的关于洪水风险管理和适应战略的辩论。使用科学网(WOS)和Scopus数据库以BibTex格式下载了1872篇原创文章,以检索1985年至2023年发表的G_MFRA研究。15.48%的年增长率表明,在研究期间,G_MFRA领域一直在不断发展。对洪水风险研究与实践的全球趋势分析突出了关键主题、方法和新兴方向。发达国家和发展中国家,特别是非洲和南美洲,在洪水风险评估研究的数据和方法方面存在显著差距,这凸显了协调研究工作和连贯政策行动的紧迫性。现有文献中确定的挑战包括技术专长、复杂的通信网络以及与研究方法应用差距相关的资源限制。本研究倡导通过基于生态系统的适应采取整体研究方法来进行洪水灾害管理,这是可持续发展目标的基础,以开发有潜力影响G_MFRA领域全球决策的创新洪水技术和模型。应对这些全球挑战需要研究界、机构和国家之间建立网络化伙伴关系。

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本文引用的文献

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Infectious Diseases Associated with Hydrometeorological Hazards in Europe: Disaster Risk Reduction in the Context of the Climate Crisis and the Ongoing COVID-19 Pandemic.在欧洲与水灾害相关的传染病:气候危机和持续的 COVID-19 大流行背景下的灾害风险减少。
Int J Environ Res Public Health. 2022 Aug 17;19(16):10206. doi: 10.3390/ijerph191610206.
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Flood exposure and poverty in 188 countries.188 个国家的洪水暴露和贫困情况。
Nat Commun. 2022 Jun 28;13(1):3527. doi: 10.1038/s41467-022-30727-4.
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Global exposure to flood risk and poverty.
全球洪水风险与贫困状况。
Nat Commun. 2022 Jun 28;13(1):3529. doi: 10.1038/s41467-022-30725-6.
4
Impacts of climate change to African indigenous communities and examples of adaptation responses.气候变化对非洲土著社区的影响及适应对策实例。
Nat Commun. 2021 Oct 28;12(1):6224. doi: 10.1038/s41467-021-26540-0.
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A bibliometric review of vegetation response to climate change.植被对气候变化响应的文献计量学研究综述。
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Geospatial indicators of exposure, sensitivity, and adaptive capacity to assess neighbourhood variation in vulnerability to climate change-related health hazards.评估邻里对气候变化相关健康危害脆弱性的暴露、敏感性和适应能力的地理空间指标。
Environ Health. 2021 Mar 22;20(1):31. doi: 10.1186/s12940-021-00708-z.
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Prenatal metal mixtures and child blood pressure in the Rhea mother-child cohort in Greece.希腊 Rhea 母婴队列研究中产前金属混合物与儿童血压的关系。
Environ Health. 2021 Jan 6;20(1):1. doi: 10.1186/s12940-020-00685-9.
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A Machine Learning Ensemble Approach Based on Random Forest and Radial Basis Function Neural Network for Risk Evaluation of Regional Flood Disaster: A Case Study of the Yangtze River Delta, China.基于随机森林和径向基函数神经网络的区域洪灾风险评估的机器学习集成方法:以中国长三角地区为例。
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Global mapping of eco-environmental vulnerability from human and nature disturbances.全球人类和自然干扰下的生态环境脆弱性制图。
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