A probabilistic approach to combine sea level rise, tide and storm surge into representative return periods of extreme total water levels: Application to the Portuguese coastal areas

Abstract

Coastal hazard and vulnerability assessments in the context of climate change usually rely on the estimation of total water levels (TWLs) through a deterministic approach, consisting on the simple summation of its components: mean or median sea level rise projections, maximum tide values, and extreme storm surge projections based on return periods (usually of 100 years). However, such methodology yields TWLs compatible with return periods much greater than the commonly used ones in hazard, vulnerability and risk assessments, occasionally by more than one order of magnitude (thousands of years). Deterministic approaches also neglect uncertainties in TWL components, or other sources of variability, as random variables with known probability density functions. Here, we present, validate, evaluate and apply a methodology to provide a numerical solution for the estimation of representative return periods of extreme TWLs, for any coastal area, to which the three cumulative density functions of SLR, tide and storm surge are given. The use of representative TWLs is crucial for accurate hydrodynamical modelling of coastal flooding, both along inland waters and coastlines facing the open ocean, as well as to coastal vulnerability and risk assessments. Using two dynamic ensembles, the projected 4-, 25- and 100-year representative TWL return periods are estimated across five vulnerable areas along the Portuguese coastline and compared with deterministic TWLs. Our results show that the methodology can accurately reproduce the observed TWL distributions and return values associated with extreme events, these being generally lower than the deterministic ones, undergoing, nevertheless, greater changes towards the end of the 21st century. We provide a baseline for future studies to delve into more accurate and realistic translation of physical, anthropogenic-driven climate change effects into socioeconomic impacts along the coastal areas.