Geology topics

Karin R. Bryan

Publications and source records attributed to Karin R. Bryan.

5 recordsLinked to original sources

USGS2026

The contribution of a surge event to infilling in a barrier-enclosed estuary: Insights from field observations

Many estuaries worldwide face increasing sediment loading caused by catchment land use change and intensification, creating subsequent adverse effects on estuarine ecosystems. Extreme weather events can disproportionately alter sediment pathways and loading. Although storm-driven sediment exchange has been widely examined at open coasts and inlets, key transport mechanisms within constricted, sheltered estuaries remain understudied. This study presents an observational dataset capturing the impact of a 99th percentile water-level event (based on 20 years of records) on sediment transport pathways in a sheltered, barrier-enclosed estuary. This event, driven by a 3-day storm surge (>0.5 m) combined with a spring tide, was recorded during a 3-week field campaign. Sediment transport pathways and riverine contributions were analysed, and observations revealed substantial changes in suspended sediment concentrations increasing from 18 mg/l to 70 mg/l during the event. The elevated water levels and resulting pressure gradient at the constricted study site entrance caused by the storm surge increased local flood dominance. Combined with higher flow velocities and resuspension, the storm led to a sixfold increase in sediment import at the estuary entrance and a 600-fold increase in sediment flux to the upper estuary. The decoupling of peak suspended sediment concentrations from streamflow indicates that the resuspension of estuarine legacy sediment, rather than catchment inputs, dominated the system's response. These findings challenge assumptions about estuarine sediment budgets and emphasise that incorporating high water-level surge events into models can enhance the prediction of long-term estuarine evolution. Given projected increases in storm frequency under climate change, understanding these episodic but highly consequential sediment pulses can support the assessment of wetland resilience and inform estuarine management strategies.

Whangateau Estuary↗

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↗

USGS2020

Blind testing of shoreline evolution models

Beaches around the world continuously adjust to daily and seasonal changes in wave and tide conditions, which are themselves changing over longer time-scales. Different approaches to predict multi-year shoreline evolution have been implemented; however, robust and reliable predictions of shoreline evolution are still problematic even in short-term scenarios (shorter than decadal). Here we show results of a modelling competition, where 19 numerical models (a mix of established shoreline models and machine learning techniques) were tested using data collected for Tairua beach, New Zealand with 18 years of daily averaged alongshore shoreline position and beach rotation (orientation) data obtained from a camera system. In general, traditional shoreline models and machine learning techniques were able to reproduce shoreline changes during the calibration period (1999–2014) for normal conditions but some of the model struggled to predict extreme and fast oscillations. During the forecast period (unseen data, 2014–2017), both approaches showed a decrease in models’ capability to predict the shoreline position. This was more evident for some of the machine learning algorithms. A model ensemble performed better than individual models and enables assessment of uncertainties in model architecture. Research-coordinated approaches (e.g., modelling competitions) can fuel advances in predictive capabilities and provide a forum for the discussion about the advantages/disadvantages of available models.

Scientific Reports↗

USGS2018

Field observations of alongshore runup variability under dissipative conditions in presence of a shoreline sandwave

Video measurements of runup were collected at low tide along several profiles covering an alongshore distance of 500 m. The morphology displayed a complex shape with a shoreline sandwave in the lower beach face of about 250 m long mirrored in the inner sandbar. Wave conditions were stationary and moderate (offshore height of 2 m and peak period of nearly 13 s) but yet dissipative. Runup energy was dominated by infragravity frequencies. Alongshore variations in runup (by a factor up to 3) observed both in the incident and infragravity bands were much higher than reported previously (e.g., Guedes et al., 2012, https://doi.org/10.1016/j.csr.2012.08.022 ; Ruggiero et al., 2004, https://doi.org/10.1029/2003JC002160 ) while the alongshore variations in other environmental parameters (e.g., foreshore beach slope) appear to be much lower. Our data suggest that the beach morphology in the inner surf zone plays a crucial role by inducing rapid and significant modification in the incident wave pattern and the alongshore coherence length scales were consistent with the typical alongshore length scale of the morphology.

Journal of Geophysical Research C: Oceans↗

USGS2015

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↗