Coastal Flood Risk Assessment: An Approach to Accurately Map Flooding through National Registry-Reported Events

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Abstract

The escalating frequency and severity of climate-related hazards in the Mediterranean, particularly in the historic town of Piran, Slovenia, underscore the critical need for enhanced coastal flood prediction and efficient early warning systems. This study delves into the impediments of available coastal flood hazard maps and the existing early warning system, which rely on distant sensors, neglecting the town’s unique microclimate. The current study leverages the public registry maintained by the Administration of the Republic of Slovenia for Civil Protection and Disaster Relief (URSZR), an underutilized resource for generating comprehensive and accurate flooding maps for Piran. Here, we show that in the historic town of Piran, floodings reported through the national registry can be used to map coastal flooding by means of verification and validation of the georeferenced reports therein, with subsequent correlation analysis (hotspot, cluster, and elevation polygons) that show temporal and spatial patterns. The innovative approach adopted in this study aims to bolster the accuracy and reliability of flooding data, offering a more nuanced understanding of flood patterns (in Piran, but generally applicable where national or regional registries are available). The findings of this research illuminate the pressing need for localized field-report and sensor systems to enhance the precision of flood predictions. The study underscores the pivotal role of accurate, localized data in fortifying coastal towns against the escalating impacts of climate change, safeguarding both the inhabitants and the invaluable architectural heritage of historic areas.

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CITATION STYLE

APA

Kralj, E., Kumer, P., & Meulenberg, C. J. W. (2023). Coastal Flood Risk Assessment: An Approach to Accurately Map Flooding through National Registry-Reported Events. Journal of Marine Science and Engineering, 11(12). https://doi.org/10.3390/jmse11122290

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