Compound Flood Analysis with GIS-Integrated Dynamic Flood Models for Coastal Urban Areas
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Kim, Minjae
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Abstract
This study addresses the complex challenges of compound flooding in coastal urban areas, specially focusing on the City of Savannah and the Savannah River Basin, which are highly vulnerable to flooding risk. Compound flooding in these areas arises from the interplay of fluvial, coastal, and flash flooding, which are further exacerbated by climate change and urbanization. To tackle these risks, this research conducts three main investigations: (1) fluvial flood analysis using a physical model integrated with geospatial data, (2) development of a high-resolution hydrology-hydraulics urban flood model, and (3) flood driver analysis based on scenario simulations. The first investigation introduces the Physics-Informed Geostatistical Approach (PIGA), which leverages spatial correlations and real -time data to enhance flood prediction. PIGA demonstrates enhanced accuracy and computational efficiency during hurricane events, particularly in data-sparse regions, compared to traditional models. The second investigation develops a high resolution urban flood model that captures the dynamics of surface runoff and drainage systems through a multi-scale, 2D nested simulation process. This model, supported by GIS, achieves a balance between computational efficiency and the detailed accuracy required for complex urban environments. The third investigation quantifies the contributions of key flood drivers— precipitation, riverine inflow, and coastal surge—through advanced statistical analysis using the developed integrated model. Findings reveal that precipitation and downstream conditions are the primary contributors to urban flooding in the study area, with coastal surge significantly increasing flood risk in the area. These spatially distributed insights offer critical information for resilience planning against compound flooding in coastal urban areas. Collectively, this research establishes a comprehensive framework for real-time flood prediction, high-resolution urban modeling, and flood driver analysis. The results provide practical tools for improving flood management strategies and enhancing resilience in vulnerable coastal urban communities.
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2024-12-04
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Text
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Dissertation