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The purpose of this study is to analyse the shoreline response of a beach protected by a system of low crested structures (LCS) and to apply the results to the management of coastal stability problems. This contribution aims to provide heretofore scarce detailed data and observations of the shoreline variability of coasts protected by LCS. These aims are acheived by selecting and monitoring the appropriate Coastal State Indicator (CSI) to describe the state of the beach. The CSI used is the Mean Intertidal Position (MIP), which has been detected by the ARGUS system installed in Lido di Dante, Italy. The error in the shoreline estimation from video was assessed by comparing shorelines detected with global positioning system (GPS) and image analysis over a large number of cases. The horizontal error in the shoreline detection is estimated to be on the order of 0.90 ± 0.74 m, which is acceptable because it is on the same order of magnitude as the swash width. The MIP, which has been monitored over a forty month period with elevated spatial and temporal resolution, was monitored in several transects of the beach protected by a system of LCS and boundary groins, creating two cells. The behaviour of the section in the middle of the cell was comparable to the behaviour of the total beach. Results were analysed with respect to the fixed beach state of the initial beach position (January 2004). The MIP regression rate is around 2.3 m/y, which is modest considering the local subsidence magnitude (1.8 cm/y). Therefore, the actual data do not show any evidence of immediaste risk, either for the present structures on the beach or for the infrastructure immediately behind; however, the results do show a risk for the sustainability of the characteristics that permit tourist development. The use of video-derived CSIs is confirmed to offer a valuable tool for coastal management. [ABSTRACT FROM AUTHOR]

Historical sources indicate that, in the late 19th century, the portion of the southern California coastline between Palos Verdes Peninsula and San Mateo Point was composed of a series of barrier spits backed by estuaries, beaches backed by cliffs, and occasional rocky headlands. Nearly natural conditions, a reflection of minimal human impact, prevailed during this relatively stormy interval. US Coast [and Geodetic] Survey materials, early scientific work, newspaper articles, and the accounts of travelers provide much of the information utilized to reconstruct the shoreline. Serving as a major roadway, the beach that extended between San Juan Creek and San Mateo Creek was especially well known. The barrier spits were capped by low dunes and were separated by migrating inlets connecting the ocean with the backing estuaries. Rivers discharged into the estuaries at times, decreasing salinities and depositing sediments. Rocky coastlines are believed to have experienced substantial erosion as high levels of bioerosion and vigorous attack by storm waves is inferred, giving rise to notched cliffs, sea caves, and other erosional forms. Forming part of the seaward fringe of the greater Los Angeles region, today this shoreline is completely developed, serving the commercial and recreational needs of millions of residents and visitors. [ABSTRACT FROM AUTHOR]

Management of uncertainty in model predictions of long-term coastal change begins by admitting uncertainty. In the case of geometric mass-balance models, the first step is to relax restrictive assumptions to allow for open sediment budgets, time-dependent morphology, effects of mixed sediment sizes, and variable resistance in substrate material. These refinements introduce new uncertainty regarding the choice of parameter values. The next step is to actively manage uncertainty using techniques readily available from information science. The final step requires a shift in coastal management culture to accept decision making based on risk-management protocols. Stochastic simulation was applied to manage predictive uncertainty in cases involving complications resulting from open sediment budgets, rock reefs, and seawalls. In these examples, the respective effects caused between 20% and 60% difference from conventional predictions based solely on equilibrium assumptions and substrates comprised entirely of sand. Stochastic simulation makes it possible to establish confidence limits and determine the statistical significance of differences caused by varying effects such as substrate resistance and shoreface geometry. It also enables the likelihood of critical impacts to be specified in terms of probability. Moreover, probabilistic forecasts provide a transparent basis for coastal management decisions by revealing the consequences if quantitative estimates prove to be wrong. [ABSTRACT FROM AUTHOR]