Coastal managers have faced increasing pressure to manage their resources wisely over the last century as a result of heightened development and changing environmental forcing. It is crucial to understand seasonal changes in beach volume and shape in order to identify areas vulnerable to accelerated erosion. Shepard (1950) was among the first to quantify seasonal beach cycles. Sonu and Van Beek (1971) and Wright et al. (1985) described commonly occurring beach states. Most studies utilize widest spaced 2-D cross shore profiles or shorelines extracted from aerial photographs (e.g. Winant et al. 1975; Aubrey, 1979, Aubrey and Ross, 1985; Larson and Kraus, 1994; Jimenez et al., 1977; Lacey and Peck, 1998; Guillen et al., 1999; Norcorss et al., 2002) to analyzed systematic changes in beach evolution. But with the exception of established field stations, such as Duck, NC (Birkemeier and Mason, 1984), ans Hazaki Oceanographical Research Station (HORS) in Japan (Katoh, 1997), there are very few beach change data sets with high temporal and spatial resolutions (e.g. Dail et al., 2000; Ruggiero et al., 2005; Yates et al., in press). Comprehensive sets of nearshore morphological data and local in situ measurements outside of these field stations are very rare and virtually non-existent high-energy coasts. Studied that have attempted to relate wave statistics to beach morphology change require some knowledge of the nearshore wave climate, and have had limited success using offshore measurement (Sonu and Van Beek, 1971; Dail et al., 2000).

The primary objective of this study is to qualitatively compare spatially variable nearshore wave predictions to beach change measurements in order to understand the processes responsible for a persistent erosion 'hotspot' at Ocean Beach, San Francisco, CA. Local wave measurements are used to calibrate and validate a wave model that provides nearshore wave prediction along the beach. The model is run for thousands of binned offshore wave conditions to help isolate the effects of offshore wave direction and period on nearshore wave predictions. Alongshore varying average beach change statistics are computed at specific profile locations from topographic beach surveys and lidar data.

The study area is located in the San Francisco Bight in central California. Ocean Beach is a seven kilometer long north-south trending sandy coastline located just south of the entrance to the San Francisco Bay Estuary (Figure 1). It contains an erosion hotspot in the southern part of the beach which has resulted in damage to local infrastructure and is the cause of continued concern. A wide range of field data collection and numerical modeling efforts have been focused here as part of the United States Geological Survey's (USGS) San Francisco Bight Coastal Processes Study, which began in October 2003 and represents the first comprehensive study of coastal processes at the mouth of San Francisco Bay.

Ocean Beach is exposed to very strong tidal flows, with measured currents often in excess of 1 m/s at the north end of the beach. Current profiler measurements indicate that current magnitudes are greater in the northern portion of the beach, while wave energy is greater in the southern portion where erosion problems are greatest (Barnard et al., 2007). The sub-aerial beach volume fluctuates seasonally over a maximum envelope of 400,000 m³ for the seven kilometer stretch (Barnard et al, 2007). The wave climate in the region is dominated by an abundance of low frequency energy (greater than 20 s period) and prevailing northwest incident wave angles. The application of a wave model to the region is further complicated by the presence of the Farallon Islands 40 kilometers west, and a massive ebb tidal delta at the mouth of San Francisco Bay (~150 km²), which creates complicated refraction patterns as wave energy moves from offshore Ocean Beach; however the cost and threat of the energetic nearshore environment have limited the temporal and spatial resolution of these measurements. Applying numerical models to predict wave and current patterns along the beach can help supplement the filed data that exists and provide opportunities to make prediction about the impacts of changing environmental forcing.