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Sea level rise will increase the frequency and severity of coastal flooding events. Compound coastal flooding is characterized by multiple flooding pathways (i.e., high offshore water levels, streamflow, energetic waves, precipitation) acting concurrently. This study explores the joint flood risks caused by the co-occurrence of high marine water levels and precipitation in a highly urbanized semi-arid, tidally dominated region. A novel structural function developed from the multivariate analysis is proposed to consider the implications of flood control infrastructure in compound coastal flood risk assessments. Univariate statistics are analyzed for individual sites and events. Conditional, and joint probabilities are developed using a range of copulas and sampling methods. The Independent, and Cubic copulas produced poor results while the Fischer-Kock, and Roch-Alegre generally produced robust results across a range of sampling methods. The impacts of sampling are considered using annual maximum, annual coinciding, wet season monthly coinciding, and wet season monthly maximum sampling. Although, annual maximum sampling is commonly recommended for characterizing compound events, this work suggests annual maximum sampling does not produce "worst-case" event pairs and substantially underestimates marine water levels for extreme events. Wet season coinciding water level and precipitation pairs benefit from a dramatic increase in available data, improved goodness of fit statistics, and provide a range of physically realistic pairs. Wet season coinciding sampling may provide a more accurate compound flooding risk characterization for long return periods in semi-arid regions. [ABSTRACT FROM AUTHOR]

Coastal flooding is a significant and increasing hazard. There are multiple drivers including rising coastal water levels, more intense hydrologic inputs, shoaling groundwater and urbanization. Accurate coastal flood event prediction poses numerous challenges: representing boundary conditions, depicting terrain and hydraulic infrastructure, integrating spatially and temporally variable overtopping flows, routing overland flows and incorporating hydrologic signals. Tremendous advances in geospatial data quality, numerical modeling and overtopping estimation have significantly improved flood prediction; however, risk assessments do not typically consider the co-occurrence of multiple flooding pathways. Compound flooding refers to the combined effects of marine and hydrologic processes. Alternatively, multiple flooding source–receptor pathways (e.g., groundwater–surface water, overtopping–overflow, surface–sewer flow) may simultaneously amplify coastal hazard and vulnerability. Currently, there is no integrated framework considering compound and multi-pathway flooding processes in a unified approach. State-of-the-art urban coastal flood modeling methods and research directions critical to developing an integrated framework for explicitly resolving multiple flooding pathways are presented. [ABSTRACT FROM AUTHOR]