Geology topics

Sean Vitousek

Publications and source records attributed to Sean Vitousek.

52 records · Page 3Linked to original sources

USGS2020

Large-scale erosion driven by intertidal eelgrass loss in an estuarine environment

Seagrasses influence local hydrodynamics by inducing drag on the flow and dampening near-bed velocities and wave energy. When seagrasses are lost, near-bed currents and wave energy can increase, which enhances bottom shear stresses, destabilizes sediment, and promotes suspension and erosion. Though seagrasses are being lost rapidly globally, the magnitude of change in sediment stabilization following ecosystem-wide eelgrass loss has rarely been measured. In this study, we explored the geomorphological changes associated with an unprecedented estuary-wide collapse of a seagrass (eelgrass, Zostera marina ) in Morro Bay, CA, USA. Morro Bay has historically suffered from accelerated sedimentation and accretion. However, following massive eelgrass loss since 2010, over 90% of locations that previously had eelgrass experienced erosion. Elevation losses (erosion) reached 0.50 m in some places (mean loss of 0.10 m) with as much as a 50% decrease (median decrease of 13.6%) in elevation (i.e., increase in depth) compared to pre-decline levels. In comparison, the mouth of the estuary, where eelgrass was largely retained, had only 27.7% of the locations with prior eelgrass experiencing erosion and underwent a mean elevation increase (accretion) of 0.32 m. Thus, the loss of eelgrass appears to have altered dynamics at the seabed and transitioned large regions of the estuary from an environment that promotes deposition and accretion to one that promotes suspension and erosion. Large-scale erosion following seagrass loss may be predictive of future shoreline and coastal habitat changes and is likely to be exacerbated by increased storm surge and sea level rise expected with climate change.

California↗

USGS2019

Dynamic flood modeling essential to assess the coastal impacts of climate change

Coastal inundation due to sea level rise (SLR) is projected to displace hundreds of millions of people worldwide over the next century, creating significant economic, humanitarian, and national-security challenges. However, the majority of previous efforts to characterize potential coastal impacts of climate change have focused primarily on long-term SLR with a static tide level, and have not comprehensively accounted for dynamic physical drivers such as tidal non-linearity, storms, short-term climate variability, erosion response and consequent flooding responses. Here we present a dynamic modeling approach that estimates climate-driven changes in flood-hazard exposure by integrating the effects of SLR, tides, waves, storms, and coastal change (i.e. beach erosion and cliff retreat). We show that for California, USA, the world’s 5 th largest economy, over $150 billion of property equating to more than 6% of the state’s GDP and 600,000 people could be impacted by dynamic flooding by 2100; a three-fold increase in exposed population than if only SLR and a static coastline are considered. The potential for underestimating societal exposure to coastal flooding is greater for smaller SLR scenarios, up to a seven-fold increase in exposed population and economic interests when considering storm conditions in addition to SLR. These results highlight the importance of including climate-change driven dynamic coastal processes and impacts in both short-term hazard mitigation and long-term adaptation planning.

Scientific Reports↗

USGS2018

A model ensemble for projecting multi‐decadal coastal cliff retreat during the 21st century

Sea cliff retreat rates are expected to accelerate with rising sea levels during the 21 st century. Here we develop an approach for a multi‐model ensemble that efficiently projects time‐averaged sea cliff retreat over multi‐decadal time scales and large (>50 km) spatial scales. The ensemble consists of five simple 1‐D models adapted from the literature that relate sea cliff retreat to wave impacts, sea level rise (SLR), historical cliff behavior, and cross‐shore profile geometry. Ensemble predictions are based on Monte Carlo simulations of each individual model, which account for the uncertainty of model parameters. The consensus of the individual models also weights uncertainty, such that uncertainty is greater when predictions from different models do not agree. A calibrated, but unvalidated, ensemble was applied to the 475 km‐long coastline of Southern California (USA), with 4 SLR scenarios of 0.5, 0.93, 1.5, and 2 m by 2100. Results suggest that future retreat rates could increase relative to mean historical rates by more than two‐fold for the higher SLR scenarios, causing an average total land loss of 19 – 41 m by 2100. However, model uncertainty ranges from +/‐ 5 – 15 m, reflecting the inherent difficulties of projecting cliff retreat over multiple decades. To enhance ensemble performance, future work could include weighting each model by its skill in matching observations in different morphological settings

Journal of Geophysical Research F: Earth Surface↗

USGS2018

Projected 21st century coastal flooding in the Southern California Bight. Part 2: Tools for assessing climate change-driven coastal hazards and socio-economic impacts

This paper is the second of two that describes the Coastal Storm Modeling System (CoSMoS) approach for quantifying physical hazards and socio-economic hazard exposure in coastal zones affected by sea-level rise and changing coastal storms. The modelling approach, presented in Part 1, downscales atmospheric global-scale projections to local scale coastal flood impacts by deterministically computing the combined hazards of sea-level rise, waves, storm surges, astronomic tides, fluvial discharges, and changes in shoreline positions. The method is demonstrated through an application to Southern California, United States, where the shoreline is a mix of bluffs, beaches, highly managed coastal communities, and infrastructure of high economic value. Results show that inclusion of 100-year projected coastal storms will increase flooding by 9–350% (an additional average 53.0 ± 16.0 km 2 ) in addition to a 25–500 cm sea-level rise. The greater flooding extents translate to a 55–110% increase in residential impact and a 40–90% increase in building replacement costs. To communicate hazards and ranges in socio-economic exposures to these hazards, a set of tools were collaboratively designed and tested with stakeholders and policy makers; these tools consist of two web-based mapping and analytic applications as well as virtual reality visualizations. To reach a larger audience and enhance usability of the data, outreach and engagement included workshop-style trainings for targeted end-users and innovative applications of the virtual reality visualizations.

California↗

USGS2018

Projected 21st century coastal flooding in the Southern California Bight. Part 1: Development of the third generation CoSMoS model

Due to the effects of climate change over the course of the next century, the combination of rising sea levels, severe storms, and coastal change will threaten the sustainability of coastal communities, development, and ecosystems as we know them today. To clearly identify coastal vulnerabilities and develop appropriate adaptation strategies due to projected increased levels of coastal flooding and erosion, coastal managers need local-scale hazards projections using the best available climate and coastal science. In collaboration with leading scientists world-wide, the USGS designed the Coastal Storm Modeling System (CoSMoS) to assess the coastal impacts of climate change for the California coast, including the combination of sea-level rise, storms, and coastal change. In this project, we directly address the needs of coastal resource managers in Southern California by integrating a vast range of global climate change projections in a thorough and comprehensive numerical modeling framework. In Part 1 of a two-part submission on CoSMoS, methods and the latest improvements are discussed, and an example of hazard projections is presented.

Journal of Marine Science and Engineering↗

USGS2018

Assessing and communicating the impacts of climate change on the Southern California coast

Over the course of this and the next century, the combination of rising sea levels, severe storms, and coastal erosion will threaten the sustainability of coastal communities, development, and ecosystems as we currently know them. To clearly identify coastal vulnerabilities and develop appropriate adaptation strategies for projected increased levels of coastal flooding and erosion, coastal managers need user-friendly planning tools based on the best available climate and coastal science. In anticipation of these climate change impacts, many communities are in the early stages of climate change adaptation planning but lack the scientific information and tools to adequately address the potential impacts. In collaboration with leading scientists worldwide, the USGS designed the Coastal Storm Modeling System (CoSMoS) to assess the coastal impacts of climate change for the California coast, including the combination of sea level rise, storms, and coastal change. In this project, we directly address the needs of coastal resource managers in Southern California by integrating a vast range of global climate change projections and translate that information using sophisticated physical process models into planning-scale physical, ecological, and economic exposure, shoreline change, and impact assessments, all delivered in two simple, user-friendly, online tools. Our results show that by the end of the 21st century, over 250,000 residents and nearly $40 billion in building value across Southern California could be exposed to coastal flooding from storms, sea level rise, and coastal change. Results for the other major population center in California (the greater San Francisco Bay Area) are also available but not explicitly discussed in this report. Together, CoSMoS has now assessed the exposure of 95% of the 26 million coastal residents of the State (17 million in Southern California).

California↗

USGS2017

Doubling of coastal flooding frequency within decades due to sea-level rise

Global climate change drives sea-level rise, increasing the frequency of coastal flooding. In most coastal regions, the amount of sea-level rise occurring over years to decades is significantly smaller than normal ocean-level fluctuations caused by tides, waves, and storm surge. However, even gradual sea-level rise can rapidly increase the frequency and severity of coastal flooding. So far, global-scale estimates of increased coastal flooding due to sea-level rise have not considered elevated water levels due to waves, and thus underestimate the potential impact. Here we use extreme value theory to combine sea-level projections with wave, tide, and storm surge models to estimate increases in coastal flooding on a continuous global scale. We find that regions with limited water-level variability, i.e., short-tailed flood-level distributions, located mainly in the Tropics, will experience the largest increases in flooding frequency. The 10 to 20 cm of sea-level rise expected no later than 2050 will more than double the frequency of extreme water-level events in the Tropics, impairing the developing economies of equatorial coastal cities and the habitability of low-lying Pacific island nations.

Scientific Reports↗

USGS2017

Can beaches survive climate change?

Anthropogenic climate change is driving sea level rise, leading to numerous impacts on the coastal zone, such as increased coastal flooding, beach erosion, cliff failure, saltwater intrusion in aquifers, and groundwater inundation. Many beaches around the world are currently experiencing chronic erosion as a result of gradual, present-day rates of sea level rise (about 3 mm/year) and human-driven restrictions in sand supply (e.g., harbor dredging and river damming). Accelerated sea level rise threatens to worsen coastal erosion and challenge the very existence of natural beaches throughout the world. Understanding and predicting the rates of sea level rise and coastal erosion depends on integrating data on natural systems with computer simulations. Although many computer modeling approaches are available to simulate shoreline change, few are capable of making reliable long-term predictions needed for full adaption or to enhance resilience. Recent advancements have allowed convincing decadal to centennial-scale predictions of shoreline evolution. For example, along 500 km of the Southern California coast, a new model featuring data assimilation predicts that up to 67% of beaches may completely erode by 2100 without large-scale human interventions. In spite of recent advancements, coastal evolution models must continue to improve in their theoretical framework, quantification of accuracy and uncertainty, computational efficiency, predictive capability, and integration with observed data, in order to meet the scientific and engineering challenges produced by a changing climate.

Journal of Geophysical Research F: Earth Surface↗

USGS2017

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

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.

California↗

USGS2017

Climate change-driven cliff and beach evolution at decadal to centennial time scales

Here we develop a computationally efficient method that evolves cross-shore profiles of sand beaches with or without cliffs along natural and urban coastal environments and across expansive geographic areas at decadal to centennial time-scales driven by 21st century climate change projections. The model requires projected sea level rise rates, extrema of nearshore wave conditions, bluff recession and shoreline change rates, and cross-shore profiles representing present-day conditions. The model is applied to the ~470-km long coast of the Southern California Bight, USA, using recently available projected nearshore waves and bluff recession and shoreline change rates. The results indicate that eroded cliff material, from unarmored cliffs, contribute 11% to 26% to the total sediment budget. Historical beach nourishment rates will need to increase by more than 30% for a 0.25 m sea level rise (~2044) and by at least 75% by the year 2100 for a 1 m sea level rise, if evolution of the shoreline is to keep pace with rising sea levels.

Conference Paper↗

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↗

USGS2015

A nonlinear, implicit one-line model to predict long-term shoreline change

We present the formulation, validation, and application of a nonlinear, implicit one-line model to simulate long-term (decadal and longer) shoreline change. The purpose of the implicit numerical method presented here is to allow large time steps without sacrificing model stability compared to explicit approaches, and thereby improve computational efficiency. The model uses a Jacobian-free Newton-Krylov solver to compute the solution to the governing equations, i.e. the shoreline position. The model is validated against an analytical solution for alongshore shoreline diffusion. The model is applied to simulate a decade of observed shoreline change at Ocean Beach (2004-2014). When wave transformation is included (implemented via SWAN and a look-up table) there is a 100% increase in the number of profiles where erosion or accretion is correctly predicted.

Conference Paper↗

USGS2012

Model scenarios of shoreline change at Kaanapali Beach, Maui, Hawaii: Seasonal and extreme events

Kaanapali beach is a well-defined littoral cell of carbonate sand extending 2 km south from Black Rock (a basalt headland) to Hanakao'o Point. The beach experiences dynamic seasonal shoreline change forced by longshore transport from two dominant swell regimes. In summer, south swells (H s = 1–2 m T p = 14–25 s) drive sand to the north, while in winter, north swells (H s = 5–8 m T p = 14–20 s) drive sand to the south where it accumulates on a submerged fossil reef. The Delft3D modeling system accurately predicts directly observed tidal currents and wave heights around West Maui, and is applied to simulate shoreline change. Morphologic simulations qualitatively resolve the observed seasonal behavior.

Hawai'i↗

USGS2012

National assessment of shoreline change: A GIS compilation of vector shorelines and associated shoreline change data for the sandy shorelines of Kauai, Oahu, and Maui, Hawaii

Sandy ocean beaches are a popular recreational destination, and often are surrounded by communities that consist of valuable real estate. Development is increasing despite the fact that coastal infrastructure may be repeatedly subjected to flooding and erosion. As a result, the demand for accurate information regarding past and present shoreline changes is increasing. Working with researchers from the University of Hawaii, investigators with the U.S. Geological Survey's National Assessment of Shoreline Change Project have compiled a comprehensive database of digital vector shorelines and shoreline-change rates for the islands of Kauai, Oahu, and Maui, Hawaii. No widely accepted standard for analyzing shoreline change currently exists. Current measurement and rate-calculation methods vary from study to study, precluding the combination of study results into statewide or regional assessments. The impetus behind the National Assessment was to develop a standardized method for measuring changes in shoreline position that is consistent from coast to coast. The goal was to facilitate the process of periodically and systematically updating the measurements in an internally consistent manner. A detailed report on shoreline change for Kauai, Maui, and Oahu that contains a discussion of the data presented here is available and cited in the Geospatial Data section of this report.

Hawai'i↗

USGS2012

National assessment of shoreline change: Historical shoreline change in the Hawaiian Islands

Sandy beaches of the United States are some of the most popular tourist and recreational destinations. Coastal property constitutes some of the most valuable real estate in the country. Beaches are an ephemeral environment between water and land with unique and fragile natural ecosystems that have evolved in equilibrium with the ever-changing winds, waves, and water levels. Beachfront lands are the site of intense residential and commercial development even though they are highly vulnerable to several natural hazards, including marine inundation, flooding and drainage problems, effects of storms, sea-level rise, and coastal erosion. Because the U.S. population continues to shift toward the coast where valuable coastal property is vulnerable to erosion, the U.S. Geological Survey (USGS) is conducting a national assessment of coastal change. One aspect of this effort, the National Assessment of Shoreline Change, uses shoreline position as a proxy for coastal change because shoreline position is one of the most commonly monitored indicators of environmental change (for example, Fletcher, 1992; Dolan and others, 1991; Douglas and others, 1998; Galgano and others, 1998). Additionally, the National Research Council (1990) recommended the use of historical shoreline analysis in the absence of a widely accepted model of shoreline change. A principal purpose of the USGS shoreline change research is to develop a common methodology so that shoreline change analyses for the continental U.S., portions of Hawaii, and Alaska can be updated periodically in a consistent and systematic manner. The primary objectives of this study were to (1) develop and implement improved methods of assessing and monitoring shoreline movement, and (2) improve current understanding of the processes controlling shoreline movement. Achieving these ongoing long-term objectives requires research that (1) examines the original sources of shoreline data (for example, maps, air photos, global positioning system (GPS), Light Detection and Ranging (lidar)); (2) evaluates the utility of different shoreline proxies (for example, geomorphic feature, water mark, tidal datum, elevation), including the errors associated with each; (3) investigates bias and potential errors associated with integrating different shoreline proxies from different sources; (4) develops standard, uniform methods of shoreline change analysis; (5) examines the effects of human activities on shoreline movement and rates of change; and (6) investigates alternative mathematical methods for calculating historical rates of change and uncertainties associated with them. This report summarizes historical shoreline changes on the three most densely populated islands of the eight main Hawaiian Islands: Kauai, Oahu, and Maui. The report emphasizes the hazard from “chronic” (decades to centuries) erosion at regional scales and strives to relate this hazard to the body of knowledge regarding coastal geology of Hawaii because of its potential impact on natural resources, the economy, and society. Results are organized by coastal regions (island side) and sub-regions (common littoral characteristics). This report of Hawaii coasts is part of a series of reports that include text summarizing methods, results, and implications of the results. In addition, geographic information system (GIS) data used in the analyses are made available for download (Romine and others, 2012). The rates of shoreline change and products presented in this report are not intended for site-specific analysis of shoreline movement, nor are they intended to replace any official source of shoreline change information identified by local or State government agencies, or other Federal entities that are used for regulatory purposes. Rates of shoreline change presented herein may differ from other published rates, and differences do not necessarily indicate that the other rates are inaccurate. Some discrepancies are to be expected, considering the many possible ways of determining shoreline positions and rates of change, and the inherent uncertainty in calculating these rates. Rates of shoreline change presented in this report represent shoreline movement under past conditions and are not intended for use in predicting future shoreline positions or future rates of shoreline change.

Hawai'i↗

USGS2008

Geology of Hawaii reefs

The Hawaii hot spot lies in the mantle under, or just to the south of, the Big Island of Hawaii. Two active subaerial volcanoes and one active submarine volcano reveal its productivity. Centrally located on the Pacific Plate, the hot spot is the source of the Hawaii Island Archipelago and its northern arm, the Emperor Seamount Chain (Fig. 11.1). This system of high volcanic islands and associated reefs, banks, atolls, sandy shoals, and seamounts spans over 30° of latitude across the Central and North Pacific Ocean to the Aleutian Trench, and contains at least 107 separate shield volcanoes (Clague and Dalrymple 1987). The trail of islands increases in age with distance from the hot spot (Fig. 11.2) and reflects the dynamic nature of the Pacific Plate, serving as a record of its speed and direction over the Hawaii hot spot for the last 75–80 MY (Clague and Dalrymple 1987). A major change in plate direction is marked by a northward kink in the chain at the end of the Hawaii Ridge approximately 3,500 km from the site of active volcanism (Moore 1987). On the basis of dredged basalts, Sharp and Clague (2006) assign an age of 50 Ma to this shift from northern to northwestern plate motion, thought to be a result of changes in the movement of neighboring plates to the west. Today the Pacific Plate migrates northwest at a rate of about 10 cm/year (Moore 1987).

Hawaii↗