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[1] Hourly time series from a quasi-global set of 145 tide gauges are used to investigate annual maximum water levels at each station. High water levels are deconstructed into (1) a predicted tidal component, (2) a seasonal component, (3) a low-frequency nontidal residual that accounts for sea level variability at time scales greater than a month but less than a year, and (4) a high-frequency nontidal residual that captures variability particularly associated with storms at time scales greater than a month. The time-averaged annual maximum water level correlates significantly with, and scales as 2.5 times, the water level standard deviation at the tide gauge stations. This relationship is used to estimate time-averaged annual maximum water level on a nearly continuous global scale (excluding ice-covered polar regions) by specifying variance maps of the tides from a tide model, the seasonal and low-frequency residual components from satellite altimetry sea surface height, and the high-frequency residual component from an atmospheric reanalysis product. The variance fields are combined to estimate time-averaged annual maximum water levels that compare well with observed values at the tide gauge stations. Spatial patterns of annual maximum water levels and relative contributions from the tides and nontidal residual components are considered.

For more information on the USGS-the Federal source for science about the Earth, its natural and living resources, natural hazards, and the environment, visit http://www.usgs.gov or call 1-888-ASK-USGS.For an overview of USGS information products, including maps, imagery, and publications, visit http://www.usgs.gov/pubprodTo order this and other USGS information products, visit http://store.usgs.gov Any use of trade, product, or firm names is for descriptive purposes only and does not imply endorsement by the U.S. Government.Although this report is in the public domain, permission must be secured from the individual copyright owners to reproduce any copyrighted materials contained within this report. Executive SummaryBeach erosion is a chronic problem along most open-ocean shores of the United States. As coastal populations expand and community infrastructure comes under increasing threat from erosion, there is a demand for accurate information about trends and rates of shoreline movement, as well as a need for a comprehensive analysis of shoreline movement that is consistent from one coastal region to another. To meet these national needs, the U.S. Geological Survey began an analysis to document historical shoreline change along open-ocean sandy shores of the conterminous United States and parts of Hawaii and Alaska. An additional purpose of this work is to develop systematic methodology for mapping and analyzing shoreline movement so that consistent periodic updates regarding coastal erosion can be made nationally.This report on shoreline change on three of the eight main Hawaii islands (Kauai, Oahu, and Maui) is one in a series of reports on shoreline change in coastal regions of the United States that currently include California, the Gulf of Mexico region, the Southeast Atlantic Coast, and the Northeast Atlantic Coast. The report summarizes the methods of analysis, documents and interprets the results, explains historical trends and rates of change, and describes the response of various communities to coastal erosion. Shoreline change in Hawaii was evaluated by comparing historical shorelines derived from topographic surveys and processed vertical aerial photography over time. The historical shorelines generally represent the past century (early 1900s-2000s). Linear regression was used to calculate rates of change with the single-transect method: long-term rates were calculated from all shorelines (from the early 1900s to the most recent), whereas short-term rates were calculated from post-World War II shorelines only.Beach erosion is the dominant trend of shoreline change in Hawaii. However, shoreline change is highly variable along Hawaii beaches with cells of erosion and accretion typically separated by only a few hundred meters on continuous beaches or by short headlands that divide the coast into many small embayments. The beaches of Kauai, Oahu, and Maui are eroding at an average long-term rate for all transects (shoreline measurement locations) of -0.11 ± 0.01 m/yr (meters per year) and an average s...

ROMINE, B.M.; FLETCHER, C.H.; FRAZER, L.N.; GENZ, A.S.; BARBEE, M.M., and LIM, S.-C.; 2009. Historical shoreline change, southeast Oahu, Hawaii; applying polynomial models to calculate shoreline change rates. Journal of Coastal Research, 25(6), 1236-1253. West Palm Beach (Florida), ISSN 0749-0208.Here we present shoreline change rates for the beaches of southeast Oahu, Hawaii, calculated using recently developed polynomial methods to assist coastal managers in planning for erosion hazards and to provide an example for interpreting results from these new rate calculation methods. The polynomial methods use data from all transects (shoreline measurement locations) on a beach to calculate a rate at any one location along the beach. These methods utilize a polynomial to model alongshore variation in the rates. Models that are linear in time best characterize the trend of the entire time series of historical shorelines. Models that include acceleration (both increasing and decreasing) in their rates provide additional information about shoreline trends and indicate how rates vary with time. The ability to detect accelerating shoreline change is an important advance because beaches may not erode or accrete in a constant (linear) manner. Because they use all the data from a beach, polynomial models calculate rates with reduced uncertainty compared with the previously used single-transect method. An information criterion, a type of model optimization equation, identifies the best shoreline change model for a beach. Polynomial models that use eigenvectors as their basis functions are most often identified as the best shoreline change models.

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A regional frequency analysis (RFA) of tide gauge (TG) data fit with a Generalized Pareto Distribution (GPD) is used to estimate contemporary extreme sea level (ESL) probabilities and the risk of a damaging flood along Pacific Basin coastlines. Methods to localize and spatially granulate the regional ESL (sub-annual to 500-year) probabilities and their uncertainties are presented to help planners of often-remote Pacific Basin communities assess (ocean) flood risk of various threshold severities under current and future sea levels. Downscaling methods include use of local TG observations of various record lengths (e.g., 1-19+ years), and if no in situ data exist, tide range information. Lowprobability RFA ESLs localized at TG locations are higher than other recent assessments and generally more precise (narrower confidence intervals). This is due to increased rareevent sampling as measured by numerous TGs regionally. For example, the 100-year ESLs (1% annual chance event) are 0.15 m and 0.25 higher (median at-site difference) than a single-TG based analysis that is closely aligned to those supporting recent Intergovernmental Panel on Climate Change (IPCC) assessments and a third-generation global tide and surge model, respectively. Height thresholds for damaging flood levels along Pacific Basin coastlines are proposed. These floods vary between about 0.6-1.2 m or more above the average highest tide and are associated with warning levels of the U.S. National Oceanic and Atmospheric Administration (NOAA). The risk of a damaging flood assessed by the RFA ESL probabilities under contemporary sea levels have about a (median) 20-25-year return interval (4-5% annual chance) for TG locations along Pacific coastlines. Considering localized sea level rise projections of the IPCC associated with a global rise of about 0.5 m by 2100 under a reduced emissions scenario, damaging floods are projected to occur annually by 2055 and >10 times/year by 2100 at the majority of TG locations.

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