Preprints
https://doi.org/10.5194/nhess-2021-241
https://doi.org/10.5194/nhess-2021-241
 
12 Aug 2021
12 Aug 2021
Status: a revised version of this preprint was accepted for the journal NHESS and is expected to appear here in due course.

Compound coastal flood risk in a semi-arid urbanized region: The implications of copula choice, sampling, and infrastructure

Joseph T. D. Lucey and Timu W. Gallien Joseph T. D. Lucey and Timu W. Gallien
  • Department of Civil and Environmental Engineering, University of California, Los Angeles, CA 90095, USA

Abstract. 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.

Joseph T. D. Lucey and Timu W. Gallien

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse

Joseph T. D. Lucey and Timu W. Gallien

Joseph T. D. Lucey and Timu W. Gallien

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Latest update: 25 Jun 2022
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Short summary
Compound coastal flooding results from multiple flood drivers (e.g., tides, waves, river flows, rainfall) occurring at the same time. Sea level rise will increase coastal flooding. This study estimates joint flood risks caused by large tides and rain. Results show, in dry regions where tides and rainfall are often separate events, wet season coinciding sampling better describes extreme flooding events. A new function based on the joint probabilities was then used to estimate sea wall impacts.
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