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Bridge-specific flood risk assessment of transport networks using GIS and remotely sensed data

桥(图论) 大洪水 地理信息系统 遥感 环境科学 计算机科学 水文学(农业) 地质学 土木工程 地理 工程类 岩土工程 考古 医学 内科学
作者
Marianna Loli,George Kefalas,Stavros Dafis,Stergios-Aristoteles Mitoulis,Franziska Schmidt
出处
期刊:Science of The Total Environment [Elsevier BV]
卷期号:850: 157976-157976 被引量:48
标识
DOI:10.1016/j.scitotenv.2022.157976
摘要

A novel framework for the expedient assessment of flood risk to transportation networks focused on the response of the most critical and vulnerable infrastructure assets, the bridges, is developed, validated and applied. Building upon the recent French guidelines on scour risk (CEREMA, 2019), this paper delivers a thorough methodology, that incorporates three key, risk parameters: (i) the hydrodynamic loading, a hazard component of equal significance to scour, for the assessment of hazard; (ii) the correlation of select scour indicators with a new index relating to flow velocity, a primary measure of the adverse impacts of flow-structure interaction, enabling a more accurate and automated, assessment of bridge susceptibility to scour; (iii) the use of a new, comprehensive indicator, namely the Indicator of Flood Hazard Intensity (IFHI) which incorporates, in a simple yet efficient way, the key parameters controlling the severity of flood impact on bridges, namely flow velocity, floodwater height, flow obstruction, and sediment type. The framework is implemented for the analysis of flood risk in a case study area, considering an inventory of 117 bridges of diverse construction characteristics, which were affected by a major flood that impacted Greece in September 2020. The reliability of the method is validated against an extensive record of inspected and documented bridge damages. Regional scale analysis is facilitated by the adoption of the Multi-Criteria Decision-Making method for flood hazard indexing, considering geomorphological, meteorological, hydrological, and land use/cover data, based on the processing of remotely sensed imagery and openly available geospatial datasets in GIS.
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