Geology topics

Li H. Erikson

Publications and source records attributed to Li H. Erikson.

At least 55 records · Page 3Linked to original sources

USGS2021

Drivers of extreme water levels in a large, urban, high-energy coastal estuary – A case study of the San Francisco Bay

Reliable and long-term hindcast data of water levels are essential in quantifying return period and values of extreme water levels. In order to inform design decisions on a local flood control district level, process-based numerical modeling has proven an essential tool to provide the needed temporal and spatial coverage for different extreme value analysis methods. To determine the importance of different physical processes to the extreme water levels we developed a process-based numerical model (Delft3D Flexible Mesh) and applied it to simulate a large, urban, high-energy coastal estuary (the San Francisco Bay). The unstructured grid with 1D/2DH model elements, allows for efficient model simulations and therefore it was possible to simulate over 70 years between 1950 and 2019. Results show significant skill in reproducing observations for the entire modeled time period with an average root-mean-square error of 8.0 cm. A process-based modeling approach allows for the explicit in- and exclusion of different physical processes to quantify their importance to the extremes. For the 100-year still water level (SWL), tide (70%) and non-tidal residual (NTR) (25%) explain the majority of the simulated high water levels in the Bay relative to Mean Higher High Water (MHHW). However, closer to the Delta, local fluvial inflow increases in importance. For longer return periods, the importance of tide decreases and the importance of remote NTRs and fluvial inflow increases.

California↗

USGS2020

Changing storm conditions in response to projected 21st century climate change and the potential impact on an arctic barrier island–lagoon system—A pilot study for Arey Island and Lagoon, eastern Arctic Alaska

Executive Summary Arey Lagoon, located in eastern Arctic Alaska, supports a highly productive ecosystem, where soft substrate and coastal wet sedge fringing the shores are feeding grounds and nurseries for a variety of marine fish and waterfowl. The lagoon is partially protected from the direct onslaught of Arctic Ocean waves by a barrier island chain (Arey Island) which in itself provides important habitat for migratory shorebirds and waterfowl. In this work, numerically modeled waves and water levels are computed under the provision of sea-level rise and changing conditions brought about by 21st century climate variability. Model results, supported by observations, are used to assess the stability of the barrier chain and spatiotemporal changes in flood patterns across fringing coastal wet sedge areas. The results aim to support studies that investigate the possibility of new biological succession trajectories and loss or increase of habitat areas.

Alaska↗

USGS2020

Effect of fluvial discharges and remote non-tidal residuals on compound flood forecasting in San Francisco Bay

Accurate and timely flood forecasts are critical for making emergency-response decisions regarding public safety, infrastructure operations, and resource allocation. One of the main challenges for coastal flood forecasting systems is a lack of reliable forecast data of large-scale oceanic and watershed processes and the combined effects of multiple hazards, such as compound flooding at river mouths. Offshore water level anomalies, known as remote Non-Tidal Residuals (NTRs), are caused by processes such as downwelling, offshore wind setup, and also driven by ocean-basin salinity and temperature changes, common along the west coast during El Niño events. Similarly, fluvial discharges can contribute to extreme water levels in the coastal area, while they are dominated by large-scale watershed hydraulics. However, with the recent emergence of reliable large-scale forecast systems, coastal models now import the essential input data to forecast extreme water levels in the nearshore. Accordingly, we have developed Hydro-CoSMoS, a new coastal forecast model based on the USGS Coastal Storm Modeling System (CoSMoS) powered by the Delft3D San Francisco Bay and Delta community model. In this work, we studied the role of fluvial discharges and remote NTRs on extreme water levels during a February 2019 storm by using Hydro-CoSMoS in hindcast mode. We simulated the storm with and without real-time fluvial discharge data to study their effect on coastal water levels and flooding extent, and highlight the importance of watershed forecast systems such as NOAA’s National Water Model (NWM). We also studied the effect of remote NTRs on coastal water levels in San Francisco Bay during the 2019 February storm by utilizing the data from a global ocean model (HYCOM). Our results showed that accurate forecasts of remote NTRs and fluvial discharges can play a significant role in predicting extreme water levels in San Francisco Bay. This pilot application in San Francisco Bay can serve as a basis for integrated coastal flood modeling systems in complex coastal settings worldwide.

California↗

USGS2020

Impacts of sea-level rise on the tidal reach of California coastal rivers using the Coastal Storm Modeling System (CoSMoS)

In coastal rivers, the interactions between tides and fluvial discharge affect local ecology, sedimentation, river dynamics, river mouth configuration, and the flooding potential in adjacent wetlands and low-lying areas. With sea-level rise, the tidal reach within coastal rivers can expand upstream, impacting river dynamics and increasing flood risk across a much greater area. Rivers along the Pacific coast of California are constrained by coastal mountain ranges, in contrast to the typical large and low-gradient river deltas and estuaries often used in tidal reach studies. Yet, the impacts of tides are ever-present and considerable to these rivers' habitats and neighboring communities. The impacts of a range of sea-level rise, discharge, and coastal storm conditions on the upstream extent of a spring tidal influence and the associated flood potential are assessed for several coastal rivers across California using coupled Delft3D FLOW-WAVE hydrodynamic simulations that explicitly account for the interactions between waves, currents, surge, and water levels in this study. Projected changes in tidal reach among the various rivers are characterized and implications for adjacent communities and stakeholders are discussed.

California↗

USGS2019

Toward a national coastal hazard forecast of total water levels

Storm surge and large waves combine to erode beaches, cause marsh and coral decay, and inundate low-elevation areas, resulting in hazards to coastal communities and loss of natural resources. The USGS, in collaboration with NOAA, is developing a real-time system to provide ∼ 6-day forecasts of total water levels (TWLs) combining tides, storm surge, and wave runup. TWL is compared with dune elevations along sandy coastlines to obtain regional flood and coastal hazard forecasts. The predictions are available online (https://coastal.er.usgs.gov/hurricanes/research/twlviewer/) and provide intuitive representations of regional coastal risk. Current efforts include 1) assessing skill by comparing forecasts with observations along sandy coastlines and 2) developing methods more appropriate for non-sandy coastlines (e.g., rocky, reef, marsh, cliff, and built shorelines). The vision of this work is to provide a tool for short- to medium-term coastal hazard forecasts to inform planners and emergency responders along nearly the entire US coastline.

Conference Paper↗

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↗

USGS2019

Towards determining spatial methane distribution on Arctic permafrost bluffs with an unmanned aerial system

Arctic permafrost stores vast amounts of methane (CH 4 ) in subsurface reservoirs. Thawing permafrost creates areas for this potent greenhouse gas to be released to the atmosphere. Identifying ‘hot spots’ of methane flux on a local scale has been limited by the spatial scales of traditional ground-based or satellite-based methane-sampling methods. Here we present a reliable and an easily replicable design using only off-the-shelf, cost-effective methane sensor components and an Unmanned Aerial System (UAS). Our results demonstrate the high efficiency of the design and the advantages of this methodology for environmental methane studies that are subjected to the high spatial variability of methane levels. On Barter Island, NE Alaska, we noted spikes in CH 4 concentrations coincident with topographic features or anomalies. Such spikes may be attributed to enhanced land/air transfer and may reveal zones of high methane production and/or minimal oxidation in areas of thermoerosional gullies along thawing coastal zones. Thermoerosional gullies represent hotspots that release significantly higher levels of methane than the surrounding areas, thus suggesting that point sampling is inadequate in characterizing methane releases and that increasing rates of permafrost thaw may result in increasing point sources of high CH 4 emissions.

SN Applied Sciences↗

USGS2019

Modeling sediment bypassing around idealized rocky headlands

Alongshore sediment bypassing rocky headlands remains understudied despite the importance of characterizing littoral processes for erosion abatement, beach management, and climate change adaptation. To address this gap, a numerical model sediment transport study was developed to identify controlling factors and mechanisms for sediment headland bypassing potential. Four idealized headlands were designed to investigate sediment flux around the headlands using the process-based hydrodynamic model Delft-3D and spectral wave model SWAN. The 120 simulations explored morphologies, substrate compositions, sediment grain sizes, and physical forcings (i.e., tides, currents, and waves) commonly observed in natural settings. A generalized analytical framework based on flow disruption and sediment volume was used to refine which factors and conditions were more useful to address sediment bypassing. A bypassing parameter was developed for alongshore sediment flux between upstream and downstream cross-shore transects to determine the degree of blockage by a headland. The shape of the headland heavily influenced the fate of the sediment by changing the local angle between the shore and the incident waves, with oblique large waves generating the most flux. All headlands may allow sediment flux, although larger ones blocked sediment more effectively, promoting their ability to be littoral cell boundaries. The controlling factors on sediment bypassing were determined to be wave angle, size, and shape of the headland, and sediment grain size.

Journal of Marine Science and Engineering↗

USGS2018

Storm surge propagation and flooding in small tidal rivers during events of mixed coastal and fluvial influence

The highly urbanized estuary of San Francisco Bay is an excellent example of a location susceptible to flooding from both coastal and fluvial influences. As part of developing a forecast model that integrates fluvial and oceanic drivers, a case study of the Napa River and its interactions with the San Francisco Bay was performed. For this application we utilize Delft3D-FM, a hydrodynamic model that computes conservation of mass and momentum on a flexible mesh grid, to calculate water levels that account for tidal forcing, storm surge generated by wind and pressure fields, and river flows. We simulated storms with realistic atmospheric pressure, river discharge, and tidal forcing to represent a realistic joint fluvial and coastal storm event. Storm conditions were applied to both a realistic field-scale Napa river drainage as well as an idealized geometry. With these scenarios, we determine how the extent, level, and duration of flooding is dependent on these atmospheric and hydrologic parameters. Unsurprisingly, the model indicates that maximal water levels will occur in a tidal river when high tides, storm surge, and large fluvial discharge events are coincident. Model results also show that large tidal amplitudes diminish storm surge propagation upstream and that phasing between peak fluvial discharges and high tide is important for predicting when and where the highest water levels will occur. The interactions between tides, river discharge, and storm surge are not simple, indicating the need for more integrated flood forecasting models in the future.

California↗

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

The influence of sea level rise on the regional interdependence of coastal infrastructure

Sea level rise (SLR) is placing both immediate and long‐term pressures on coastal communities to take protective actions. Projects in the United States, and in many locations throughout the world, generally involve local jurisdictions raising the elevation of shoreline protection elements, with limited or no analysis of the feedback between shoreline management decisions and the impacts to water levels regionally. Our study examines the impact of local shoreline development on regional flood risk and considers SLR scenarios up to 1.5 m using a large‐scale numerical model, as an example, for San Francisco Bay. Here we show that measures to prevent flooding along an embayment shoreline in one location or subregion may increase inundation elsewhere in the system. The network of interactions occurs not only within subbasins of the Bay but also across the greater geographic extent from one end of the Bay to the other, and local jurisdiction may have either reciprocal relationships with or asymmetric impacts on one other. Importantly, the nature of the interaction network is seen to evolve with SLR: interactions are purely subregional at current sea level but with higher sea level (e.g., 1 m of SLR), not only do the subregional interdependencies strengthen but also regional interdependences emerge.

California↗

USGS2018

Identification of storm events and contiguous coastal sections for deterministic modeling of extreme coastal flood events in response to climate change

Deterministic dynamical modeling of future climate conditions and associated hazards, such as flooding, can be computationally-expensive if century-long time-series of waves, sea level variations, and overland flow patterns are simulated. To alleviate some of the computational costs, local impacts of individual coastal storms can be explored by first identifying particular events or scenarios of interest and dynamically modeling those events in detail. In this study, an efficient approach to selecting storm events for subsequent deterministic detailed modeling of coastal flooding is presented. The approach identifies locally relevant scenarios derived from regional datasets spanning long time-periods and covering large geographic areas. This is done by identifying storm events from global climate models using a robust, yet computationally simple approach for calculating total water level proxies at the shore, assuming a linear superposition of the important processes contributing to the overall total water level. Clustering of the total water level time-series is used to define coherent coastal cells where similar return period water level extrema occur in response to region-wide storms. Results show that the more severe but rare coastal flood events (e.g., the 100-year (yr) event) typically occur from the same storm across the region, but that a number of different storms are responsible for the less severe but more frequent local extreme water levels (e.g., the 1-yr event). This new ‘storm selection’ approach is applied to the Southern California Bight, a region of varying shoreline orientations that is subject to wave refraction across complex bathymetry, and shadowing, focusing, diffraction, and dissipation of wave energy by islands. Results indicate that wave runup dominates total water level extremes at this study site, highlighting the importance of downscaling global-scale models to nearshore waves when seeking accurate projections of local coastal hazards in response to climate change.

California↗

USGS2018

Estimating fluvial discharges coincident with 21st century coastal storms modeled with CoSMoS

On the open coast, flooding is largely driven by tides, storm surge, waves, and in areas near coastal inlets, the magnitude and co-occurrence of high fluvial discharges. Statistical methods are typically used to estimate the individual probability of coastal storm and fluvial discharge occurrences for use in sophisticated flood hazard models. A challenge arises when considering possible future climate changes and the relation between the intensity of extreme coastal water levels and high fluvial discharges. In this study, the Coastal Storm Modeling System (CoSMoS) is used to dynamically downscale global climate projections to local-scale storm-driven coastal water levels, including associated fluvial discharges. An efficient approach to derive 21st century projected fluvial discharges for rivers within San Francisco Bay was developed, leveraging a readily-available time-series of projected (2010 – 2100) discharge rates of the predominant river system (the “Delta”). Delta projections were used to estimate flow rates of 8 Bay rivers for the IPCC's CMIP5 RCP4.5 climate scenario. Relationships describing discharge rates, normalized by respective watershed areas, were developed and applied to projected data to generate 21st century fluvial discharge time-series for each river. Results indicate decreasing discharge rates throughout the 21 st century with the exception of extreme flows.

California↗

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

Controls of multi-modal wave conditions in a complex coastal setting

Coastal hazards emerge from the combined effect of wave conditions and sea level anomalies associated with storms or low-frequency atmosphere-ocean oscillations. Rigorous characterization of wave climate is limited by the availability of spectral wave observations, the computational cost of dynamical simulations, and the ability to link wave-generating atmospheric patterns with coastal conditions. We present a hybrid statistical-dynamical approach to simulating nearshore wave climate in complex coastal settings, demonstrated in the Southern California Bight, where waves arriving from distant, disparate locations are refracted over complex bathymetry and shadowed by offshore islands. Contributions of wave families and large-scale atmospheric drivers to nearshore wave energy flux are analyzed. Results highlight the variability of influences controlling wave conditions along neighboring coastlines. The universal method demonstrated here can be applied to complex coastal settings worldwide, facilitating analysis of the effects of climate change on nearshore wave climate.

California↗

USGS2017

Interactions of estuarine shoreline infrastructure with multiscale sea level variability

Sea level rise increases the risk of storms and other short‐term water‐rise events, because it sets a higher water level such that coastal surges become more likely to overtop protections and cause floods. To protect coastal communities, it is necessary to understand the interaction among multiday and tidal sea level variabilities, coastal infrastructure, and sea level rise. We performed a series of numerical simulations for San Francisco Bay to examine two shoreline scenarios and a series of short‐term and long‐term sea level variations. The two shoreline configurations include the existing topography and a coherent full‐bay containment that follows the existing land boundary with an impermeable wall. The sea level variability consists of a half‐meter perturbation, with duration ranging from 2 days to permanent (i.e., sea level rise). The extent of coastal flooding was found to increase with the duration of the high‐water‐level event. The nonlinear interaction between these intermediate scale events and astronomical tidal forcing only contributes ∼1% of the tidal heights; at the same time, the tides are found to be a dominant factor in establishing the evolution and diffusion of multiday high water events. Establishing containment at existing shorelines can change the tidal height spectrum up to 5%, and the impact of this shoreline structure appears stronger in the low‐frequency range. To interpret the spatial and temporal variability at a wide range of frequencies, Optimal Dynamic Mode Decomposition is introduced to analyze the coastal processes and an inverse method is applied to determine the coefficients of a 1‐D diffusion wave model that quantify the impact of bottom roughness, tidal basin geometry, and shoreline configuration on the high water events

Journal of Geophysical Research: Oceans↗