Multi-Hazard Susceptibility Assessment Using the Analytical Hierarchy Process in Coastal Regions of South Aegean Volcanic Arc Islands

IF 6.5 3区 工程技术 Q1 ENGINEERING, GEOLOGICAL Georisk-Assessment and Management of Risk for Engineered Systems and Geohazards Pub Date : 2023-03-16 DOI:10.3390/geohazards4010006
P. Krassakis, A. Karavias, P. Nomikou, K. Karantzalos, N. Koukouzas, Ioannis Athinelis, S. Kazana, I. Parcharidis
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引用次数: 1

Abstract

Coastal environments are highly recognized for their spectacular morphological features and economic activities, such as agriculture, maritime traffic, fishing, and tourism. In the context of climate change and the evolution of physical processes, the occurrence of intense natural phenomena adjacent to populated coastal areas may result in natural hazards, causing human and/or structural losses. As an outcome, scientific interest in researching and assessing multi-hazard susceptibility techniques has increased rapidly in an effort to better understand spatial patterns that are threatening coastal exposed elements, with or without temporal coincidence. The islands of Milos and Thira (Santorini Island) in Greece are prone to natural hazards due to their unique volcano-tectonic setting, the high number of tourist visits annually, and the unplanned expansion of urban fabric within the boundaries of the low-lying coastal zone. The main goal of this research is to analyze the onshore coastal terrain’s susceptibility to natural hazards, identifying regions that are vulnerable to soil erosion, torrential flooding, landslides and tsunamis. Therefore, the objective of this work is the development of a multi-hazard approach to the South Aegean Volcanic Arc (SAVA) islands, integrating them into a superimposed susceptibility map utilizing Multi-Criteria Decision-Making (MCDM) analysis. The illustrated geospatial workflow introduces a promising multi-hazard tool that can be implemented in low-lying coastal regions globally, regardless of their morphometric and manmade characteristics. Consequently, findings indicated that more than 30% of built-up areas, 20% of the transportation network, and 50% of seaports are within the high and very high susceptible zones, in terms of the Extended Low Elevation Coastal Zone (ELECZ). Coastal managers and decision-makers must develop a strategic plan in order to minimize potential economic and natural losses, private property damage, and tourism infrastructure degradation from potential inundation and erosion occurrences, which are likely to increase in the foreseeable future.
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基于层次分析法的南爱琴海火山弧岛沿海地区多灾害易感性评价
沿海环境因其壮观的形态特征和经济活动(如农业、海上交通、渔业和旅游业)而得到高度认可。在气候变化和自然过程演变的背景下,沿海人口稠密地区附近发生的强烈自然现象可能导致自然灾害,造成人员和(或)结构损失。因此,科学界对研究和评估多灾害易感性技术的兴趣迅速增加,以便更好地了解威胁沿海暴露要素的空间格局,无论有无时间巧合。希腊的米洛斯岛和蒂拉岛(圣托里尼岛)由于其独特的火山构造环境、每年大量的游客以及低洼沿海地区边界内城市结构的无计划扩张,容易发生自然灾害。本研究的主要目的是分析陆上沿海地形对自然灾害的易感性,确定易受水土流失、暴雨洪水、山体滑坡和海啸影响的区域。因此,这项工作的目标是开发一种针对南爱琴海火山弧(SAVA)岛屿的多灾害方法,利用多标准决策(MCDM)分析将它们整合到叠加的易感性图中。所示的地理空间工作流程介绍了一种有前途的多灾害工具,可以在全球低洼沿海地区实施,无论其形态特征和人为特征如何。因此,研究结果表明,超过30%的建成区、20%的交通网络和50%的海港位于延伸低海拔海岸带(ELECZ)的高易感区和极高易感区。沿海管理者和决策者必须制定战略计划,以尽量减少潜在的经济和自然损失、私人财产损失以及潜在的淹没和侵蚀事件造成的旅游基础设施退化,这些在可预见的未来可能会增加。
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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来源期刊
CiteScore
8.70
自引率
10.40%
发文量
31
期刊介绍: Georisk covers many diversified but interlinked areas of active research and practice, such as geohazards (earthquakes, landslides, avalanches, rockfalls, tsunamis, etc.), safety of engineered systems (dams, buildings, offshore structures, lifelines, etc.), environmental risk, seismic risk, reliability-based design and code calibration, geostatistics, decision analyses, structural reliability, maintenance and life cycle performance, risk and vulnerability, hazard mapping, loss assessment (economic, social, environmental, etc.), GIS databases, remote sensing, and many other related disciplines. The underlying theme is that uncertainties associated with geomaterials (soils, rocks), geologic processes, and possible subsequent treatments, are usually large and complex and these uncertainties play an indispensable role in the risk assessment and management of engineered and natural systems. Significant theoretical and practical challenges remain on quantifying these uncertainties and developing defensible risk management methodologies that are acceptable to decision makers and stakeholders. Many opportunities to leverage on the rapid advancement in Bayesian analysis, machine learning, artificial intelligence, and other data-driven methods also exist, which can greatly enhance our decision-making abilities. The basic goal of this international peer-reviewed journal is to provide a multi-disciplinary scientific forum for cross fertilization of ideas between interested parties working on various aspects of georisk to advance the state-of-the-art and the state-of-the-practice.
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