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Alfredo Aretxabaleta

Publications and source records attributed to Alfredo Aretxabaleta.

At least 19 recordsLinked to original sources
USGS2026

Artificial intelligence strategy for the U.S. Geological Survey

Artificial intelligence (AI) can offer opportunities to enhance the science, science delivery, and business operations of the U.S. Geological Survey (USGS). Although USGS staff have proactively adopted AI into our workflows for many years, a comprehensive USGS strategy for AI has not previously been developed. The strategy described here is motivated by the acceleration of AI technological development, the benefits of increased AI adoption to USGS mission delivery as anticipated by USGS staff, rising public concern about the implications and trustworthiness of AI, and emerging Federal directives and guidance about AI. The USGS vision is to continue integrating AI to deliver valuable science for the public good while maintaining high ethical standards, scientific quality and integrity, and compliance with Federal and U.S. Department of the Interior requirements. To realize this vision, the USGS can take steps to (1) develop a strong AI workforce, (2) adapt our organizational approaches to include AI governance and communication, (3) ensure responsible and trustworthy use of AI, (4) modernize our computing and data infrastructure to support AI, and (5) accelerate AI adoption and innovation in the Bureau.

Circular↗
USGS2024

Sensitivity analysis of a dynamic vegetation-sediment transport model using equadratures: Exploring inorganic accretion on a marsh platform

Salt marsh systems require a net import of inorganic sediment to maintain their structure in response to sea‐level rise. Marshes are affected by physical processes including tides, waves, sediment transport, and the influence of vegetation, and these processes interact in complex ways leading to sediment accretion or erosion. We implement a 3‐D hydrodynamic sediment transport model in an idealized marsh‐bay complex with a gently sloping edge, and use it as a laboratory to explore the processes leading to bed elevation change through the bay‐marsh continuum. We use the novel equadratures method for efficient sensitivity analysis to test the roles of wave, vegetation, and sediment parameters on wave dissipation, bed shear stress, sediment fluxes, and deposition and erosion across a transect spanning bay shallows to the marsh. Within the explored bounds of parameter uncertainty, significant wave height ( H sig ), settling velocity ( w s ), and critical shear stress (τ crit ) most strongly affect accretion on the marsh platform. Deposition is affected more by parameter‐parameter interactions, that is, both τ crit and w s or both H sig and w s , than by a single parameter varying alone. The sediment that accretes on the marsh platform originates beyond the marsh edge, indicating that the dynamics of the adjacent mudflat are important for predicting the fate of the marsh. Applying efficient sensitivity analysis techniques can empower process‐based models to test more parameters, larger ranges, and longer timeframes, enabling future predictions of marsh response to sea‐level rise based on physical processes

California↗
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↗
USGS2023

Processes controlling coastal erosion along Cape Cod Bay, MA

Cape Cod Bay, MA, is a semi-enclosed embayment in the northeastern United States, open on the north to the Gulf of Maine. The coastline experiences impacts typically from strong Nor’easter storms that occur in the late fall or winter months, with some sections of this coastline being affected more severely than others. We investigate the processes that cause spatial variability in storm impacts by using geophysical surveys, shoreline-change analysis, and numerical modeling. We simulated the Gulf of Maine and Cape Cod Bay from Jan–April, 2021, using the COAWST modeling system, including ocean, wave, infragravity wave, and sediment transport models. Results identify bay-scale circulation of alongshore sediment fluxes and convergences at regional shoals. Nearshore modeling also revealed zones of increased wave heights that correlate with regions of increased erosion and coastal angle orientation. Modeled and computed shoreline-change have some correlation but the model does not capture all the variability. This overall approach can potentially be used for other coastal locations to identify regions of storm impacts and to manage coastal resources.

Massachusetts↗
USGS2023

Sound-side inundation and seaward erosion of a barrier island during hurricane landfall

Barrier islands are especially vulnerable to hurricanes and other large storms, owing to their mobile composition, low elevations, and detachment from the mainland. Conceptual models of barrier-island evolution emphasize ocean-side processes that drive landward migration through overwash, inlet migration, and aeolian transport. In contrast, we found that the impact of Hurricane Dorian (2019) on North Core Banks, a 36-km barrier island on the Outer Banks of North Carolina, was primarily driven by inundation of the island from Pamlico Sound, as evidenced by storm-surge model results and observations of high-water marks and wrack lines. Analysis of photogrammetry products from aerial imagery collected before and after the storm indicate the loss of about 18% of the subaerial volume of the island through the formation of over 80 erosional washout channels extending from the marsh and washover platform, through gaps in the foredunes, to the shoreline. The washout channels were largely co-located with washover fans deposited by earlier events. Net seaward export of sediment resulted in the formation of deltaic bars offshore of the channels, which became part of the post-storm berm recovery by onshore bar migration and partial filling of the washouts with washover deposits within 2 months. This event represents a volumetric setback in the overwash/rollover behavior required for barrier transgression, but the new ponds and lowland habitats may provide beneficial habit for endangered species and will likely persist for years.

North Carolina↗
USGS2022

Shoaling wave shape estimates from field observations and derived bedload sediment rates

The shoaling transformation from generally linear deep-water waves to asymmetric shallow-water waves modifies wave shapes and causes near-bed orbital velocities to become asymmetrical, contributing to net sediment transport. In this work, we used two methods to estimate the asymmetric wave shape from data at three sites. The first method converted wave measurements made at the surface to idealized near-bottom wave-orbital velocities using a set of empirical equations: the “parameterized” waveforms. The second method involved direct measurements of velocities and pressure made near the seabed: the “direct” waveforms. Estimates from the two methods were well correlated at all three sites (Pearson’s correlation coefficient greater than 0.85). Both methods were used to drive bedload-transport calculations that accounted for asymmetric waves, and the results were compared with a traditional excess-stress formulation and field estimates of bedload transport derived from ripple migration rates based on sonar imagery. The cumulative bedload transport from the parameterized waveform was 25% greater than the direct waveform, mainly because the parameterized waveform did not account for negative skewness. Calculated transport rates were comparable to rates estimated from ripple migration except during the largest event, when calculated rates were as much as 100 times greater, which occurred during high period waves.

Florida, Massachusetts, New York↗
USGS2021

Modeling marsh dynamics using a 3-D coupled wave-flow-sediment model

Salt marshes are dynamic biogeomorphic systems that respond to external physical factors, including tides, sediment transport, and waves, as well as internal processes such as autochthonous soil formation. Predicting the fate of marshes requires a modeling framework that accounts for these processes in a coupled fashion. In this study, we implement two new marsh dynamic processes in the 3-D COAWST (coupled-ocean-atmosphere-wave sediment transport) model. The processes added are the erosion of the marsh edge scarp caused by lateral wave thrust from surface waves and vertical accretion driven by organic growth on the marsh platform. The sediment released from the marsh causes a change in bathymetry, thereby modifying the wave-energy reaching the marsh edge. Marsh vertical accretion due to biomass production is considered for a single vegetation species and is determined by the hydroperiod parameters (tidal datums) and the elevation of the marsh cells. Tidal datums are stored at user-defined intervals as a hindcast (on the order of days) and used to update the vertical growth formulation. Idealized domains are utilized to verify the lateral wave thrust formulation and show the dynamics of lateral wave erosion leading to horizontal retreat of marsh edge. The simulations of Reedy and Dinner Creeks within the Barnegat Bay estuary system demonstrate the model capability to account for both lateral wave erosion and vertical accretion due to organic growth in a realistic marsh complex. The simulations show that majority of accretion over the marsh complex occurs due to organic production while most estuarine sediment deposition occurs along the channel edges. The ability of the model to capture the fate of the sediment can be extended to model future storm and relative sea level rise (RSLR) scenarios.

Frontiers in Marine Science↗
USGS2021

Quantifying slopes as a driver of forest to marsh conversion using geospatial techniques: Application to Chesapeake Bay coastal-plain, USA

Coastal salt marshes, which provide valuable ecosystem services such as flood mitigation and carbon sequestration, are threatened by rising sea level. In response, these ecosystems migrate landward, converting available upland into salt marsh. In the coastal-plain surrounding Chesapeake Bay, United States, conversion of coastal forest to salt marsh is well-documented and may offset salt marsh loss due to sea level rise, sediment deficits, and wave erosion. Land slope at the marsh-forest boundary is an important factor determining migration likelihood, however, the standard method of using field measurements to assess slope across the marsh-forest boundary is impractical on the scale of an estuary. Therefore, we developed a general slope quantification method that uses high resolution elevation data and a repurposed shoreline analysis tool to determine slope along the marsh-forest boundary for the entire Chesapeake Bay coastal-plain and find that less than 3% of transects have a slope value less than 1%; these low slope environments offer more favorable conditions for forest to marsh conversion. Then, we combine the bay-wide slope and elevation data with inundation modeling from Hurricane Isabel to determine likelihood of coastal forest conversion to salt marsh. This method can be applied to local and estuary-scale research to support management decisions regarding which upland forested areas are more critical to preserve as available space for marsh migration.

Delaware, Maryland, Virginia↗
USGS2020

A non-linear relationship between marsh size and sediment trapping capacity compromises salt marshes’ resilience to sea-level rise

Global assessments predict the impact of sea-level rise on salt marshes with present-day levels of sediment supply from rivers and the coastal ocean. However, these assessments do not consider that variations in marsh extent and the related reconfiguration of intertidal area affect local sediment dynamics, ultimately controlling the fate of the marshes themselves. We conducted a meta-analysis of six bays along the United States East Coast to show that a reduction in the current salt marsh area decreases the sediment availability in estuarine systems through changes in regional-scale hydrodynamics. This positive feedback between marsh disappearance and the ability of coastal bays to retain sediments reduces the trapping capacity of the whole tidal system and jeopardizes the survival of the remaining marshes. We show that on marsh platforms, the sediment deposition per unit area decreases exponentially with marsh loss. Marsh erosion enlarges tidal prism values and enhances the tendency toward ebb dominance, thus decreasing the overall sediment availability of the system. Our findings highlight that marsh deterioration reduces the sediment stock in back-barrier basins and therefore compromises the resilience of salt marshes.

Massachusetts, New York, New Jersey, Maryland, Vir↗
USGS2020

Spatiotemporal variability of light attenuation and net ecosystem metabolism in a back-barrier estuary

Quantifying system-wide biogeochemical dynamics and ecosystem metabolism in estuaries is often attempted using a long-term continuous record at a single site or short-term records at multiple sites due to sampling limitations that preclude long-term monitoring. However, differences in the dominant primary producer at a given location (e.g., phytoplankton versus benthic producers) control diel variations in dissolved oxygen and associated ecosystem metabolism, and they may confound metabolic estimates that do not account for this variability. We hypothesize that even in shallow, well-mixed estuaries there is strong spatiotemporal variability in ecosystem metabolism due to benthic and water-column properties, as well as ensuing feedbacks to sediment resuspension, light attenuation, and primary production. We tested this hypothesis by measuring hydrodynamic properties, biogeochemical variables (fluorescent dissolved organic matter – fDOM, turbidity, chlorophyll a fluorescence, dissolved oxygen), and photosynthetically active radiation (PAR) over 1 year at 15 min intervals at paired channel (unvegetated) and shoal (vegetated by eelgrass) sites in Chincoteague Bay, Maryland–Virginia, USA, a shallow back-barrier estuary. Light attenuation ( K dPAR ) at all sites was dominated by turbidity from suspended sediment, with lower contributions from fDOM and chlorophyll a . However, there was significant seasonal variability in the resuspension–shear stress relationship on the vegetated shoals, but not in adjacent unvegetated channels. This indicated that K dPAR on the shoals was mediated by submerged aquatic vegetation (SAV) and possibly microphytobenthos presence in the summer, which reduced resuspension and therefore K dPAR . We also found that gross primary production ( P g ) and K dPAR were significantly negatively correlated on the shoals and uncorrelated in the channels, indicating that P g over the vegetated shoals is controlled by a feedback loop between benthic stabilization by SAV and/or microphytobenthos, sediment resuspension, and light availability. Metabolic estimates indicated substantial differences in net ecosystem metabolism between vegetated and unvegetated sites, with the former tending towards net autotrophy in the summer. Ongoing trends of SAV loss in this and other back-barrier estuaries suggest that these systems may also shift towards net heterotrophy, reducing their effectiveness as long-term carbon sinks. With regards to temporal variability, we found that varying sampling frequency between 15 min and 1 d resulted in comparable mean values of biogeochemical variables, but extreme values were missed by daily sampling. In fact, daily resampling minimized the variability between sites and falsely suggested spatial homogeneity in biogeochemistry, emphasizing the need for high-frequency sampling. This study confirms that properly quantifying ecosystem metabolism and associated biogeochemical variability requires characterization of the diverse estuarine environments, even in well-mixed systems, and demonstrates the deficiencies introduced by infrequent sampling to the interpretation of spatial variability.

Maryland, Virginia↗
USGS2020

A geospatially resolved wetland vulnerability index: Synthesis of physical drivers

Assessing wetland vulnerability to chronic and episodic physical drivers is fundamental for establishing restoration priorities. We synthesized multiple data sets from E.B Forsythe National Wildlife Refuge, New Jersey, to establish a wetland vulnerability metric that integrates a range of physical processes, regulatory information and physical/biophysical features. The geospatial data are based on aerial imagery, remote sensing, regulatory information, and hydrodynamic modeling, and include elevation, tidal range, unvegetated to vegetated marsh ratio (UVVR), shoreline erosion, potential exposure to contaminants, residence time, marsh condition change, change in salinity and salinity exposure, and sediment concentration. First, we delineated the wetland complex into individual marsh units based on surface contours and then defined a wetland vulnerability index that combined contributions from all parameters. We applied principal component and cluster analyses to explore the interrelations between the data layers and separate regions that exhibited common characteristics. Our analysis shows that the spatial variation of vulnerability in this domain cannot be explained satisfactorily by a smaller subset of the variables. The most influential factor on the vulnerability index was the combined effect of elevation, tide range, residence time, and UVVR. Tide range and residence time had the highest correlation, and similar bay-wide spatial variation. Some variables (e.g., shoreline erosion) had no significant correlation with the rest of the variables. The aggregated index based on the complete dataset allows us to assess the overall state of a given marsh unit and quickly locate the most vulnerable units in a larger marsh complex. The application of geospatially complete datasets and consideration of chronic and episodic physical drivers represents an advance over traditional point-based methods for wetland assessment.

New Jersey↗
USGS2020

Using the Lomb-Scargle method for wave statistics from gappy time series

Sandwich Town Neck Beach in Sandwich, MA, has experienced substantial erosion and has been the subject of efforts by the town and private landowners to limit the sand loss. Erosion has been particularly dramatic in the past five years with the loss of dwellings. Sandwich's nourishment efforts presented a unique opportunity for scientists at the U.S. Geological Survey Woods Hole Coastal and Marine Science Center to monitor beach morphology and to test new technologies and techniques such as geo-referenced drone imaging. Two bottom lander deployments were performed in Cape Cod Bay at a location that was key to model the fate of waves at Sandwich Town Neck Beach and to support the study of beach morphological evolution. The study period was after the town nourished the beach and during a time when several intense winter storms reshaped the beach and removed much of the nourished sand. A TRDI Workhorse Sentinel V ADCP was used for both deployments. For wave bursts, the instruments collected 2048 samples at 2 Hz every hour. The first deployment during the winter of 2016 returned good quality data. The second deployment during the following winter had gaps throughout the time series from a wiring problem in the external battery pack. The timing of the gaps was random, the duration approximately 100 s. While most of the bursts started at the top of each hour, many had 1-3 gaps within. Time series data with random gaps are problematic for computing spectral density, and thus, wave statistics. This kind of situation is familiar in other scientific disciplines such as astrophysics [1], where techniques exist to find stationary signals in sparse data. One of these methods is the Lomb-Scargle technique for computing periodograms. The most useful feature of the Lomb-Scargle (LS) method is that it allows the spectral analysis of incomplete records, without having to manipulate the record to extrapolate from or replace missing data. We compared the effectiveness of LS against common methods of averaging Fourier transforms such as a simple un-windowed Fast Fourier transform (FFT), Welch's method, and TRDI's Wavesmon software; methods that are commonly used in oceanography for non-gappy data. Synthetic data series that have been artificially modified to introduce gaps were used to evaluate the performance of each method. The LS approach was able to recover spectral density even with several 100-s gaps present. The method was applied here to the gappy and non-gappy data from both Sandwich deployments, and wave statistics were obtained and compared to the wave-buoy data. LS was used to process data that contains gaps that was rejected by Wavesmon, which was approximately 39% of the dataset. Significant wave height and peak period from LS compared well with buoy data. Mean period computed on gappy data using LS produced values biased low, compared with other methods when gaps were filled with the mean value. The LS technique has potential to uncover low-frequency signals such as infragravity waves from gappy records where the non-gappy segments are not long enough to resolve them. It has potential to unlock new information from older data sets.

Massachusetts↗
USGS2019

Spatial distribution of water level impact to back-barrier bays

Water level in semi-enclosed bays, landward of barrier islands, is mainly driven by offshore sea level fluctuations that are modulated by bay geometry and bathymetry, causing spatial variability in the ensuing response (transfer). Local wind setup can have a secondary role that depends on wind speed, fetch, and relative orientation of the wind direction and the bay. Inlet geometry and bathymetry primarily regulate the magnitude of the transfer between open ocean and bay. Tides and short-period offshore oscillations are more damped in the bays than longer-lasting offshore fluctuations, such as storm surge and sea level rise. We compare observed and modeled water levels at stations in a mid-Atlantic bay (Barnegat Bay) with offshore water level proxies. Observed water levels in Barnegat Bay are compared and combined with model results from the Coupled Ocean-Atmosphere-Wave-Sediment Transport (COAWST) modeling system to evaluate the spatial structure of the water level transfer. Analytical models based on the dimensional characteristics of the bay are used to combine the observed data and the numerical model results in a physically consistent approach. Model water level transfers match observed values at locations inside the Bay in the storm frequency band (transfers ranging from 70-100%) and tidal frequencies (10-55%). The contribution of frequency-dependent local setup caused by wind acting along the bay is also considered. The approach provides transfer estimates for locations inside the Bay where observations were not available resulting in a complete spatial characterization. The approach allows for the study of the Bay response to alternative forcing scenarios (landscape changes, future storms, and rising sea level). Detailed spatial estimates of water level transfer can inform decisions on inlet management and contribute to the assessment of current and future flooding hazard in back-barrier bays and along mainland shorelines.

Natural Hazards and Earth System Sciences↗
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↗
USGS2017

Physical response of a back-barrier estuary to a post-tropical cyclone

This paper presents a modeling investigation of the hydrodynamic and sediment transport response of Chincoteague Bay (VA/MD, USA) to Hurricane Sandy using the Coupled Ocean-Atmosphere-Wave-Sediment-Transport (COAWST) modeling system. Several simulation scenarios with different combinations of remote and local forces were conducted to identify the dominant physical processes. While 80% of the water level increase in the bay was due to coastal sea level at the peak of the storm, a rich spatial and temporal variability in water surface slope was induced by local winds and waves. Local wind increased vertical mixing, horizontal exchanges, and flushing through the inlets. Remote waves (swell) enhanced southward flow through wave setup gradients between the inlets, and increased locally generated wave heights. Locally generated waves had a negligible effect on water level but reduced the residual flow up to 70% due to enhanced apparent roughness and breaking-induced forces. Locally generated waves dominated bed shear stress and sediment resuspension in the bay. Sediment transport patterns mirrored the interior coastline shape and generated deposition on inundated areas. The bay served as a source of fine sediment to the inner shelf, and the ocean-facing barrier island accumulated sand from landward-directed overwash. Despite the intensity of the storm forcing, the bathymetric changes in the bay were on the order of centimeters. This work demonstrates the spectrum of responses to storm forcing, and highlights the importance of local and remote processes on back-barrier estuarine function.

Chincoteague Bay↗