Open AccessA Coherent Statistical Model for Coastal Flood Frequency Analysis Under Nonstationary Sea Level Conditions
Author(s) -
Ghanbari Mahshid,
Arabi Mazdak,
Obeysekera Jayantha,
Sweet William
Publication year - 2019
Publication title -
earth's future
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.641
H-Index - 39
ISSN - 2328-4277
DOI - 10.1029/2018ef001089
Subject(s) - coastal flood , quantile , environmental science , flood myth , flooding (psychology) , return period , generalized additive model , generalized pareto distribution , climate change , cumulative distribution function , statistical model , oceanography , extreme value theory , geography , statistics , geology , probability density function , sea level rise , mathematics , psychology , archaeology , psychotherapist
Flood exposure is increasing in coastal communities due to rising sea levels. Understanding the effects of sea level rise (SLR) on frequency and consequences of coastal flooding and subsequent social and economic impacts is of utmost importance for policymakers to implement effective adaptation strategies. Effective strategies may consider impacts from cumulative losses from minor flooding as well as acute losses from major events. In the present study, a statistically coherent Mixture Normal‐Generalized Pareto Distribution model was developed, which reconciles the probabilistic characteristics of the upper tail as well as the bulk of the sea level data. The nonstationary sea level condition was incorporated in the mixture model using Quantile Regression method to characterize variable Generalized Pareto Distribution thresholds as a function of SLR. The performance validity of the mixture model was corroborated for 68 tidal stations along the Contiguous United States (CONUS) coast with long‐term observed data. The method was subsequently employed to assess existing and future coastal minor and major flood frequencies. The results indicate that the frequency of minor and major flooding will increase along all CONUS coastal regions in response to SLR. By the end of the century, under the “Intermediate” SLR scenario, major flooding is anticipated to occur with return period less than a year throughout the coastal CONUS. However, these changes vary geographically and temporally. The mixture model was reconciled with the property exposure curve to characterize how SLR might influence Average Annual Exposure to coastal flooding in 20 major CONUS coastal cities.