Geology topics

Erdinc Sogut

Publications and source records attributed to Erdinc Sogut.

4 recordsLinked to original sources

USGS2025

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↗

USGS2023

Temporal variability of runup and total water level on Cape Cod sandy beaches

In the present study, we evaluate the temporal variability in runup and total water level for sandy beaches along Cape Cod (Massachusetts, USA), and their impact on dune and beach erosion. We use a 43-year hindcast of waves and water levels and calculate runup and total water level based on the Stockdon formulation using previously extracted beach slopes. The dominant components of the runup are identified and their temporal variability evaluated. The seasonal and interannual variability of total water level is evaluated. For most locations along the outer Cape Cod coast, the comparison between total water level and dune elevations suggested that the coastal response remained predominantly under swash regime. The results over these study locations could be extended to other similar areas at regional scales to provide better characterization of total water level and coastal change at long temporal scales.

Massachusetts↗

USGS2023

Contributions to uncertainty in runup forecasts

The U.S. Geological Survey (USGS) provides operational forecasts of total water levels (TWL) and coastal change. Uncertainties around forecast TWL are based on the temporal and spatial range of observed beach slopes near the forecast site. This paper investigates other sources of uncertainty that are not accounted for, focusing on four beaches where the USGS has deployed remote cameras, and on outer Cape Cod, which has diverse bar morphologies. We find that the range of runup indicated by ten formulae is nearly as large as the variations caused by the range of beach slopes. A formula that accounts for bar morphology substantially decreases calculated runup, and might improve forecasts. Errors in the timing of forecast storm landfall generate uncertainties in TWL where tides are large. Analyses suggest that the effect of off-normal incident waves is relatively small. These results suggest opportunities for improving the TWL forecasts.

Massachusetts↗

USGS2023

Toward a total water level forecast of the Great Lakes

The combined effect of storm surge and large waves is the main driving mechanism that erodes beaches, inundates low-lying areas, leading to millions of dollars in property damage, loss of natural resources, and lives. The U.S. Geological Survey (USGS) aims to expand the real-time total water level (TWL) forecast provided in the Operational Total Water Level and Coastal Change Forecasts (TWL&CC) to the Great Lakes short- (0 – 36 hours) to medium-term (3 – 5 days) coastal-hazard forecasts to inform planners and emergency responders. This study assesses the skill of forecast water levels and wave characteristics required as input to the TWL forecasts. It finds that, while skill generally decreases as forecast period increases, these data are suitable as input to the TWL forecast system. As the TWL predictions depend on the water level and wave forecasts, validation against field observations allow evaluation of their suitability for the Great Lakes. These results have implications on the prediction of water levels and their potential impacts on coastal resiliency in North America.

Great Lakes↗