Estimation of Return Levels for Extreme Skew Surge Coastal Flooding
Events in the Delaware and Chesapeake Bays for 1980 -2019
Abstract
Extreme storm surges can overwhelm many coastal flooding protection
measures in place and cause severe damages to private communities,
public infrastructure, and natural ecosystems. In the US Mid-Atlantic, a
highly developed and commercially active region, coastal flooding is one
of the most significant natural hazards and a year-round threat from
both tropical and extra-tropical cyclones. Mean sea levels and high-tide
flood frequency has increased significantly in recent years, and major
storms are projected to increase into the foreseeable future. We
estimate extreme surges using hourly water level data and harmonic
analysis for 1980-2019 at 12 NOAA tide gauges in and around the Delaware
and Chesapeake Bays. Return levels (RLs) are computed for 1.1, 3, 5, 10,
25, 50, and 100-year return periods using stationary extreme value
analysis on detrended skew surges. Two traditional approaches are
investigated, Block Maxima fit to General Extreme Value distribution and
Points-Over-Threshold fit to Generalized Pareto distribution, although
with two important enhancements. First, the GEV r-largest order
statistics distribution is used; a modified version of the GEV
distribution that allows for multiple maximum values per year. Second, a
systematic procedure is used to select the optimum value for r (for the
BM/GEVr approach) and the threshold (for the POT/GP approach) at each
tide gauge separately. RLs have similar magnitudes and spatial patterns
from both methods, with BM/GEVr resulting in generally larger 100-yr and
smaller 1.1-yr RLs. Maximum values are found at the Lewes (Delaware Bay)
and Sewells Point (Chesapeake Bay) tide gauges, both located in the
southwest region of their respective bays. Minimum values are found
toward the central bay regions. In the Delaware Bay, the POT/GP approach
is consistent and results in narrower uncertainty bands whereas the
results are mixed for the Chesapeake. Results from this study aim to
increase reliability of projections of extreme water levels due to
extreme storms and ultimately help in long-term planning of mitigation
and implementation of adaptation measures.