Search USGSSearch

USGS · 70186176

A model integrating longshore and cross-shore processes for predicting long-term shoreline response to climate change

Abstract

We present a shoreline change model for coastal hazard assessment and management planning. The model, CoSMoS-COAST (Coastal One-line Assimilated Simulation Tool), is a transect-based, one-line model that predicts short-term and long-term shoreline response to climate change in the 21 st century. The proposed model represents a novel, modular synthesis of process-based models of coastline evolution due to longshore and cross-shore transport by waves and sea-level rise. Additionally, the model uses an extended Kalman filter for data assimilation of historical shoreline positions to improve estimates of model parameters and thereby improve confidence in long-term predictions. We apply CoSMoS-COAST to simulate sandy shoreline evolution along 500 km of coastline in Southern California, which hosts complex mixtures of beach settings variably backed by dunes, bluffs, cliffs, estuaries, river mouths, and urban infrastructure, providing applicability of the model to virtually any coastal setting. Aided by data assimilation, the model is able to reproduce the observed signal of seasonal shoreline change for the hindcast period of 1995-2010, showing excellent agreement between modeled and observed beach states. The skill of the model during the hindcast period improves confidence in the model's predictive capability when applied to the forecast period (2010-2100) driven by GCM-projected wave and sea-level conditions. Predictions of shoreline change with limited human intervention indicate that 31% to 67% of Southern California beaches may become completely eroded by 2100 under sea-level rise scenarios of 0.93 to 2.0 m.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Sean Vitousek, Patrick L. Barnard, Patrick W. Limber, Li H. Erikson, Blake Cole. 2017-04-06. A model integrating longshore and cross-shore processes for predicting long-term shoreline response to climate change. https://doi.org/10.1002/2016jf004065

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related USGS reports

Water tracks enhance water flow above permafrost in upland Arctic Alaska hillslopes

Upland permafrost regions occupy approximately one third of the Arctic landscape. In upland regions, hydrologic fluxes are influenced by water tracks, curvilinear features on hillslopes that preferentially fill with and route water in response to snowmelt and rainfall when the soil above continuous permafrost thaws in the summer. As continued warming of the Arctic may alter hydrologic cycling leading to increased frequency of extreme hydrologic events like drought and flooding as well as modification of biogeochemical cycling, it is imperative to untangle the interplay between precipitation, runoff, and subsurface flow as water is routed from upland Arctic regions to the Arctic Ocean. This study quantifies how ground surface temperatures affect groundwater discharge from hillslopes with water tracks in the upland Arctic by employing a three-dimensional, physically based subsurface flow model with variable saturation and freeze and thaw capabilities that is calibrated to field measurements from the Upper Kuparuk River watershed on the North Slope of Alaska, USA. Model analysis indicates that higher ground surface temperatures along water track hillslopes promote increases in groundwater discharge where water tracks act as conduits for large recharge events and continue to discharge groundwater into the autumn after the adjacent hillslope has frozen. Simulating the conditions that distinguish water tracks from their hillslope watersheds changes subsurface water storage and ground thermal responses but does not alter the total magnitude of groundwater discharge outside of parameter uncertainty. These findings suggest that water tracks play a complex and critical role in hydrologic cycles of the upland Arctic.

Alaska

Reducing sampling uncertainty in aeolian research to improve change detection

Measurements of aeolian sediment transport support our understanding of mineral dust impacts on Earth and human systems and assessments of aeolian process sensitivities to global environmental change. However, sample design principles are often overlooked in aeolian research. Here, we use high‐density field measurements of sediment mass flux across land use and land cover types to examine sample size and power effects on detecting change in aeolian transport. Temporal variances were 1.6 to 10.1 times the magnitude of spatial variances in aeolian transport for six study sites. Differences in transport were detectable for >67% of comparisons among sites using ~27 samples. Failure to detect change with smaller sample sizes suggests that aeolian transport measurements and monitoring are much more uncertain than recognized. We show how small and selective sampling, common in aeolian research, gives the false impression that differences in aeolian transport can be detected, potentially undermining inferences about process and impacting reproducibility of aeolian research.

Journal of Geophysical Research F: Earth Surface

Prediction of ice‐free conditions for a perennially ice‐covered Antarctic lake

Although perennially ice‐covered Antarctic lakes have experienced variable ice thicknesses over the past several decades, future ice thickness trends and associated aquatic biological responses under projected global warming remain unknown. Heat stored in the water column in chemically stratified Antarctic lakes that have middepth temperature maxima can significantly influence the ice thickness trends via upward heat flux to the ice/water interface. We modeled the ice thickness of the west lobe of Lake Bonney, Antarctica, based on possible future climate scenarios utilizing a 1D thermodynamic model that accounts for surface radiative fluxes as well as the heat flux associated with the temperature evolution of the water column. Model results predict that the ice cover of Lake Bonney will shift from perennial to seasonal within one to four decades, a change that will drastically influence ecosystem processes within the lake.

Journal of Geophysical Research F: Earth Surface