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Mitchell D. Harley

Publications and source records attributed to Mitchell D. Harley.

4 recordsLinked to original sources

Benchmarking shoreline prediction models over multi-decadal timescales

Robust predictions of shoreline change are critical for sustainable coastal management. Despite advancements in shoreline models, objective benchmarking remains limited. Here we present results from ShoreShop2.0, an international collaborative benchmarking workshop, where 34 groups submitted shoreline change predictions in a blind competition. Subsets of shoreline observations at an undisclosed site (BeachX) over short (5-year) and medium (50-year) periods were withheld from modelers and used for model benchmarking. Using satellite-derived shoreline datasets for calibration and evaluation, the best performing models achieved prediction accuracies on the order of 10 m, comparable to the accuracy of the satellite shoreline data, indicating that certain beaches can be modelled nearly as well as they can be remotely observed. The outcomes from this collaborative benchmarking competition critically review the present state-of-the-art in shoreline change prediction as well as reveal model limitations, facilitate improvements, and offer insights for advancing shoreline-prediction capabilities.

New South Wales

Evaluating five shoreline change models against 40 years of field survey data at an embayed sandy beach

Robust and reliable models are needed to understand how coastlines will evolve over the coming decades, driven by both natural variability and climate change. This study evaluated how accurately five popular ‘reduced-complexity’ models replicate multi-decadal shoreline change at Narrabeen-Collaroy Beach, a sandy embayment in Sydney, Australia. Measured shoreline positions derived from approximately monthly field surveys were used for 20-year calibration and 20-year validation periods. The models performed similarly on average but with large variability between transects. The set-up of several models was modified to compensate for their sensitivity to imperfect input wave data, and further site-specific improvements were identified. Capturing interannual to decadal-scale variability in cross-shore and longshore dynamics at this site was challenging for all five models. Models appeared to aggregate key processes at this timescale into parameter values rather than representing them directly. This suggests time-varying parameters or changes to model structure may be necessary for decadal-scale simulations.

Coastal Engineering

Shoreline seasonality of California’s beaches

We report on remote sensing techniques developed to characterize seasonal shoreline cycles from satellite-derived shoreline measurements. These techniques are applied to 22-yr of shoreline measurements for over 777 km of beach along California's 1,700-km coast, for which the general understanding is that shorelines exhibit winter-narrow and summer-recovery seasonality. We find that approximately 90% of beach transects exhibit significant and recurring seasonal cycles in the shoreline position. Seasonal shoreline excursions are twice as large in northern and central California (17.5–32.2 m) than southern California (7.3–15.9 m; interquartile ranges). Clustering analyses were effective at characterizing the temporal patterns of the seasonality, revealing that ∼459 km of beach (59%) exhibit winter-narrow conditions, whereas ∼189 km (24%) and ∼50 km (6.4%) exhibit spring-narrow and summer-narrow conditions, respectively. These spring- and summer-narrow conditions are most common in southern California, where they represent over half of the total length of beach shoreline. Multivariate analyses reveal that wave climate and geomorphic setting are significantly related to the magnitude and timing of shoreline seasonal cycles. Combinations of these variables explain 44% of the seasonality variance of the complete data set and 85% of the variance for a subset of 93 long (>1 km) continuous beaches. We conclude that diversity in waves and geomorphic setting along California cause a broad range of seasonal patterns in the shoreline. Combined, this indicates that the overly generalized “winter-narrow/summer-recovery” conventions for California beaches are not expressed universally and that shoreline seasonality is far more diverse than these simple canonical rules.

California

Coastal vulnerability across the Pacific dominated by El Niño-Southern Oscillation

To predict future coastal hazards, it is important to quantify any links between climate drivers and spatial patterns of coastal change. However, most studies of future coastal vulnerability do not account for the dynamic components of coastal water levels during storms, notably wave-driven processes, storm surges and seasonal water level anomalies, although these components can add metres to water levels during extreme events. Here we synthesize multi-decadal, co-located data assimilated between 1979 and 2012 that describe wave climate, local water levels and coastal change for 48 beaches throughout the Pacific Ocean basin. We find that observed coastal erosion across the Pacific varies most closely with El Niño/Southern Oscillation, with a smaller influence from the Southern Annular Mode and the Pacific North American pattern. In the northern and southern Pacific Ocean, regional wave and water level anomalies are significantly correlated to a suite of climate indices, particularly during boreal winter; conditions in the northeast Pacific Ocean are often opposite to those in the western and southern Pacific. We conclude that, if projections for an increasing frequency of extreme El Niño and La Niña events over the twenty-first century are confirmed, then populated regions on opposite sides of the Pacific Ocean basin could be alternately exposed to extreme coastal erosion and flooding, independent of sea-level rise.

Pacific Ocean