Multi-Scale Comparison of Flood Socioeconomic Vulnerability for Urban and Agricultural Communities
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Tanır, Tuğkan
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Abstract
Flood events are one of the common natural hazards causing a considerable amount of damage to different sectors and communities all around the world. Due to several factors, such as climate change, urbanization, and deforestation, the impacts of different flood types, including riverine flood, coastal storms, and urban pluvial, increase in urban and agricultural communities. Especially, the co-occurrence of flood drivers (i.e compound floods) cause severe damages on coastal metropolitan areas, such as DC. Riverine flood events can also have destructive effects on agricultural production and threaten food security on both national and local scales, such as Potomac River Watershed. In this context, this study proposes two separate modules to assess flood socio-economic vulnerability (FSOEVI) to quantify both urban compound and riverine flood risks on the residential population in Washington, DC metropolitan area and agricultural communities in the Potomac River Watershed (PRW), respectively. A combination of the HAZUS-MH flood damage estimation tool and the Social Vulnerability Index (SOVI) were used to quantify overall vulnerability for both communities. For urban populations, two different compound flood scenarios were used to estimate socioeconomic losses, while 100-year riverine flood event was used for agricultural crop damage analysis. Although the agricultural communities in Highland and Prince George’s were more vulnerable, they did not experience high flood damages in any scenarios. The spatiotemporal distribution of vulnerabilities indicated that agricultural populations in Shenandoah County were most vulnerable in September and October, which were months with the highest flood probability. The compound event with coastal surge and riverine flood caused high damage on the banks of the Potomac River. In addition, a high precipitation scenario led to severe damages in locations with denser infrastructures, such as DC and Arlington County. The block level analysis was more sensitive to vulnerability and flood damages compared to coarser scales i.e. group and tract. The distribution of the risk was found significantly dependent on the compound flood event type and scale of the analysis for urban populations, while time of the year of a flood event and dominant crop type were the main determinant of the risk for agricultural communities. The method presented in this study is a tool that can identify most vulnerable agricultural and urban communities in order to aid vulnerability reduction efforts in flood risk management.
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Flood risk management, Urban flood vulnerability, Agricultural flood vulternability, Urban compound flooding, Flood damage