Geology topics

Research about Dauphin Island

Source-linked reports with geographic coverage including Dauphin Island.

At least 19 recordsLinked to original sources

USGS2024

Model sensitivity analysis for coastal morphodynamics: Investigating sediment parameters and bed composition in Delft3D

Numerical simulation of sediment transport and subsequent morphological evolution rely on accurate parameterizations of sediment characteristics. However, these data are often not available or are spatially and/or temporally limited. This study approaches the problem of limited sediment grain-size data with a series of simulations assessing model sensitivity to sediment parameters and initial bed composition configurations in Delft3D, leading to improved modeling practices. A previously validated Delft3D sediment transport and morphology model for Dauphin Island, Alabama, USA, is used as the benchmark case. A method for the generation of representative sediment grain sizes and their spatially varying distributions is presented via end-member analysis of in situ surficial sediment samples. Derived sediment classes and their spatial distributions are applied to two sensitivity case simulations with increasing bed composition complexity. First, multiple sediment classes are applied in a single fully mixed layer, regardless of sediment type. Second, multiple sediment classes are applied in a thin, fully mixed transport layer with underlayers containing only the non-cohesive sediment classes below. Simulations were carried out in a probabilistic, Delft3D MorMerge configuration to capture long-term morphology change for 10 years. We found there is sensitivity to the inclusion of additional sediment classes and sediment distribution made evident in bed level and morphology change. Inclusion of highly mobile fine sediments altered model results in each sensitivity case. The model was also found to be sensitive to initial bed composition in terms of bed level and morphology change, with notable differences between sensitivity cases on decadal timescales, indicating an armoring effect in the second sensitivity case, which used the transport and underlayer bed configuration. The results of this study offer guidance for numerical modelers concerned with sediment behavior in coastal and estuarine environments.

Alabama↗

USGS2023

Decision science as a framework for combining geomorphological and ecological modeling for the management of coastal systems

The loss of ecosystem services due to climate change and coastal development is projected to have significant impacts on local economies and conservation of natural resources. Consequently, there has been an increase in coastal management activities such as living shorelines, oyster reef restoration, marsh restoration, beach and dune nourishment, and revegetation projects. Coastal management decisions are complex and include challenging trade-offs. Decision science offers a useful framework to address such complex problems. Here, we provide a synthesis about how decision science can help to integrate research from multiple disciplines (physical and life sciences) with management of coastal and marine systems. Specifically, we discuss the importance of considering concepts and techniques from ecology, coastal geology, geomorphology, climate science, oceanography, and decision analysis when developing conservation plans for coastal restoration. We illustrate the process with several coastal restoration studies. Our capstone example is based on a recent barrier island restoration assessment project at Dauphin Island, Alabama, which included the development of geomorphological and ecological models. We show how decision science can be used as a framework to combine geomorphological and ecological modeling to help inform management decisions while considering uncertainty about system changes and risk tolerance. We also build on our examples through a review of recently developed techniques for spatial conservation planning for land acquisition decisions and the application of adaptive management for sequential decisions.

Alabama↗

USGS2021

Assessing habitat change and migration of barrier islands

Barrier islands are dynamic environments that experience gradual change from waves, tides, and currents, and rapid change from extreme storms. These islands are expected to change drastically over the coming century due to accelerated sea-level rise and changes in frequency and intensity of storm events. The dynamic nature of barrier islands coupled with the importance of these environments make it critical for natural resource managers to understand how habitats on barrier islands are changing or may change over time to determine when and where management actions may be needed. In this study, we applied a habitat change assessment framework, which included exploring areal coverage and distribution changes and change component analysis. Change component analysis, which breaks differences into net gain/loss and allocation difference (i.e., habitat oscillation), has not previously been used to study barrier island habitat evolution. Here, we demonstrate the approach using habitat predictions from a geomorphic modeling effort on Dauphin Island, Alabama (USA). We explored differences of habitat predictions for potential island configurations with and without a beach and dune restoration action under future conditions related to sea level and storminess. We found a potential linkage between landward migration of barrier islands and exchange, an output of change component analysis. The hypothesis may be tested to explore whether this linkage applies over space and time and whether the approach is applicable to monitoring landward migration of coastal wetlands. Collectively, our results highlight the utility of change component analysis for monitoring and quantifying barrier island habitat change and migration.

Alabama↗

USGS2021

Assessing the effectiveness of nourishment in decadal barrier island morphological resilience

Nourishment has shown to be an effective method for short-term storm protection along barrier islands and sandy beaches by reducing flooding, wave attack and erosion. However, the ability of nourishment to mitigate the effects of storms and sea level rise (SLR) and improve coastal resilience over decadal time scales is not well understood. This study uses integrated models of storm-driven hydrodynamics, morphodynamics and post-storm dune recovery to assess the effectiveness of beach and dune nourishment on barrier island morphological resilience over a 30-year period, accounting for storms and a moderate amount of SLR. Results show that at the end of the 30 years, nourishment contributes to maintaining island volumes by increasing barrier height and width compared with a no-action scenario (i.e., no nourishment, only natural recovery). During storms where the collision regime was dominant, higher volumes of sand were lost from the wider beach in the nourishment scenario than in the no-action scenario. During stronger storms, nourishment reduced dune overtopping compared with the no-action scenario, allowing the island to maintain height and width. Additionally, nourishment was particularly effective in reducing breaching during back-to-back storms occurring in the same year.

Mississippi↗

USGS2021

Developing bare-earth digital elevation models from structure-from-motion data on barrier islands

Unoccupied aerial systems can collect aerial imagery that can be used to develop structure-from-motion products with a temporal resolution well-suited to monitoring dynamic barrier island environments. However, topographic data created using photogrammetric techniques such as structure-from-motion represent the surface elevation including the vegetation canopy . Additional processing is required for estimating bare-earth elevation, which is critical for understanding the underlying geomorphology of these islands. In this study, we used a vegetation and elevation survey to produce bare-earth digital elevation models from structure-from-motion-derived elevation products for two sites on Dauphin Island, Alabama (USA). One site was exposed to high wave energy and included a mix of beach, dune, and barrier flat habitats that were dominated by supratidal/upland herbaceous vegetation. The second site was exposed to low wave energy and was dominated by intertidal marsh. Aerial imagery was collected in late fall of 2018 and spring of 2019. We tested several machine learning algorithms for predicting and removing elevation bias for vegetated areas using predictors that included spectral indices from unoccupied aerial systems-based multispectral imagery and landscape position information (e.g., relative topography and distance from shore). Models were developed for each site and season. We also explored how well the model from one season generalized to data from a different season for the same site. For developing initial digital surface models, we found that utilizing a minimum bin algorithm, as opposed to interpolation, led to lower elevation bias. For bias removal, Gaussian process regression performed the best and led to a root mean square error for the bare-earth digital elevation models of around 0.10 m for the high energy site and 0.15 m for the low energy site. Compared to the digital surface models, the root mean square error for the bare-earth digital elevation models was reduced by at least 29 percent for the high energy site and 69 percent for the low energy site. For all models, common predictors included surface elevation, vegetation greenness, and distance from the shoreline. The models produced comparable results when trained using data from a different season. The error estimates for all analyses were within published elevation standards for lidar data for vegetated areas. With calibration, this approach could be portable to other areas or data, such as aerial lidar (conventional or unoccupied), to provide an efficient and repeatable framework for monitoring geomorphology or provide baseline elevations for predicting changes to these environments under future conditions.

Alabama↗

USGS2020

Development and application of an empirical dune growth model for evaluating barrier island recovery from storms

Coastal zone managers require models that predict barrier island change on decadal time scales to estimate coastal vulnerability, and plan habitat restoration and coastal protection projects. To meet these needs, methods must be available for predicting dune recovery as well as dune erosion. In the present study, an empirical dune growth model (EDGR) was developed to predict the evolution of the primary foredune of a barrier island. Within EDGR, an island is represented as a sum of Gaussian shape functions representing dunes, berms, and the underlying island form. The model evolves the foredune based on estimated terminal dune height and location inputs. EDGR was assessed against observed dune evolution along the western end of Dauphin Island, Alabama over the 10 years following Hurricane Katrina (2005). The root mean square error with EDGR (ranging from 0.18 to 0.74 m over the model domain) was reduced compared to an alternate no-change model (0.69–0.96 m). Hindcasting with EDGR also supports the study of dune evolution processes. At Dauphin Island, results suggest that a low-lying portion of the site was dominated by overwash for ~5 years after Katrina, before approaching their terminal height and becoming growth-limited after 2010. EDGR’s computational efficiency allows dune evolution to be rapidly predicted and enables ensemble predictions to constrain the uncertainty that may result if terminal dune characteristics are unknown. In addition, EDGR can be coupled with an external model for estimating dune erosion and/or the long-term evolution of other subaerial features to allow decadal-scale prediction of barrier island evolution.

Alabama↗

USGS2020

Sensitivity of storm response to antecedent topography in the XBeach model

Antecedent topography is an important aspect of coastal morphology when studying and forecasting coastal change hazards. The uncertainty in morphologic response of storm-impact models and their use in short-term hazard forecasting and decadal forecasting is important to account for when considering a coupled model framework. This study provided a methodology to investigate uncertainty of profile response within the storm impact model XBeach related to varying antecedent topographies. A parameterized island Gaussian fit (PIGF) model generated an idealized baseline profile and a suite of idealized profiles that vary specific characteristics based on collated observed LiDAR data from Dauphin Island, AL, USA. Six synthetic storm scenarios were simulated on each of the idealized profiles with XBeach in both 1- and 2-dimensional setups and analyzed to determine the morphological response and uncertainty related to the varied antecedent topographies. Profile morphologic response tends to scale with storm magnitude but among the varied profiles there is greater uncertainty in profile response to the medium range storm scenarios than to the low and high magnitude storm scenarios. XBeach can be highly sensitive to morphologic thresholds, both antecedent and time-varying, especially with regards to beach slope.

Alabama↗

USGS2020

The roles of storminess and sea level rise in decadal barrier island evolution

Models of alongshore sediment transport during quiescent conditions, storm‐driven barrier island morphology, and poststorm dune recovery are integrated to assess decadal barrier island evolution under scenarios of increased sea levels and variability in storminess (intensity and frequency). Model results indicate barrier island response regimes of keeping pace, narrowing, flattening, deflation (narrowing and flattening), and aggradation. Under lower storminess scenarios, more areas of the island experienced narrowing due to collision. Under higher storminess scenarios, more areas experienced flattening due to overwash and inundation. Both increased sea levels and increased storminess resulted in breaching when the majority of the island was not keeping pace and deflation was the dominant regime due to increased overtopping. Under the highest storminess scenario, the island was unable to recover elevation after storms and drowned in just 10 years.

Alabama↗

USGS2020

Predicting barrier island habitats and oyster and seagrass habitat suitability for various restoration measures and future conditions for Dauphin Island, Alabama

Barrier islands, such as Dauphin Island, Alabama, provide numerous invaluable ecosystem services including storm damage reduction and erosion control to the mainland, habitat for fish and wildlife, carbon sequestration in marshes, water catchment and purification, recreation, and tourism. These islands are dynamic environments that are gradually shaped by currents, waves, and tides under quiescent conditions yet can evolve in the time scale of hours to days during hurricanes and other extreme storms. The ecosystems associated with these islands also face numerous other hazards, including accelerated sea-level rise, oil spills, and anthropogenic stressors. Hurricane Katrina in 2005 and the Deepwater Horizon oil spill in 2010 are two major events that have affected habitats and natural resources on Dauphin Island, Ala. The latter event prompted a cooperative effort between the U.S. Geological Survey and the U.S. Army Corps of Engineers to investigate viable, sustainable restoration measures that reduce degradation and enhance the natural resources of Dauphin Island, Ala. In collaboration with the State of Alabama and the National Fish and Wildlife Foundation, the overarching goal of the Alabama Barrier Island Restoration Feasibility Assessment project was to document baseline conditions and forecast potential conditions under varying sea-level change and storm scenarios for a no-action alternative along with a variety of restoration measures including beach and dune restoration, marsh and back-barrier restoration, and placement of sand in the littoral zone. The modeling component of this project used decadal hydrodynamic geomorphic, water quality, and habitat modeling to better understand how the various restoration measures may influence the habitat composition, sustainability, and resiliency of Dauphin Island under potential future conditions, benchmarked against the no-action case. The report covers the habitat modeling efforts associated with the Alabama Barrier Island Restoration Feasibility Assessment project. For various potential future island configurations for Dauphin Island, we predicted coverage of habitat types (for example, beach, dune, intertidal marsh, and woody vegetation) using a spatially explicit habitat model based on landscape-position information (for example, elevation and distance from shore) extracted from the hydrodynamic geomorphic outputs. Similarly, we forecasted habitat suitability for oysters and seagrass using habitat suitability index models. Another component of the Alabama Barrier Island Restoration Feasibility Assessment project, presented separately, integrates these habitat model results into a structured decision-making framework that accounts for competing objectives. Collectively, this information provides insights to natural resource managers and planners on how a restoration measure may maintain or impede natural coastal processes and provide information critical for making future-focused decisions regarding barrier island restoration.

Alabama↗

USGS2020

Application of decadal modeling approach to forecast barrier island evolution, Dauphin Island, Alabama

Forecasting barrier island evolution provides coastal managers and stakeholders the ability to assess the resiliency of these important coastal environments that are home to both established communities and existing natural habitats. This study uses an established coupled model framework to assess how Dauphin Island, Alabama, responds to various storm and sea-level change scenarios, along with a suite of restoration measures, over the course of a decade. The coupled model framework uses validated models for long-term alongshore sediment transport (Delft 3D), short-term storm induced impacts (XBeach), as well as dune building and recovery (empirical dune growth model). This model framework was simulated with the various storm and sea-level change scenarios on a non-restored Dauphin Island, then a subset of the storm and sea-level change scenarios were applied to a suite of seven different restoration measures to determine how they would influence the morphologic evolution over a decadal period. Topographic and bathymetric changes captured in post-simulation digital elevation models were then passed on to partners for various simulations to determine the effects on habitat evolution and water quality as it relates to oyster reef and submerged aquatic vegetation.

Alabama↗

USGS2020

Development of a process-based littoral sediment transport model for Dauphin Island, Alabama

Dauphin Island, Alabama, located in the Northern Gulf of Mexico just outside of Mobile Bay, is Alabama’s only barrier island and provides an array of historical, natural, and economic resources. The dynamic island shoreline of Dauphin Island evolved across time scales while constantly acted upon by waves and currents during both storms and calm periods. Reductions in the vulnerability and enhancements to the resiliency of Dauphin Island—through offshore sand placement, breach closure, berm construction, and other means—have been used to protect the island and its vital resources. Planning for a resilient Dauphin Island requires predicting the long-term evolution of the barrier island system and the dominant, temporally varying processes that influence it, including littoral alongshore sediment transport under typical wave conditions, beach and dune erosion, the island overwash and breaching that occur rapidly during storm events, and the recovery of primary sand dunes through Aeolian transport over decadal time scales. Littoral sediment transport within the Dauphin Island decadal-scale framework was simulated using the Delft-3D modeling software suite. The influences of wind, waves, water levels, and sediment transport are incorporated into the model. Model skill in the prediction of waves, water levels, currents, volumetric flow rates through inlets, and shoreline position was assessed by using a set of deterministic and statistical hindcast simulations. The Delft-3D modeling application described here can be coupled with validated models of storm-response and dune recovery to predict the evolution of Dauphin Island on decadal time scales.

Alabama↗

USGS2020

Final Alabama Barrier Island restoration assessment report, appendix A: Data management plan

The Alabama Barrier Island Restoration Assessment project focused exclusively on Dauphin Island, a significant barrier island along the northern Gulf of Mexico. This restoration feasibility study effort required data collection and analysis of many data types (e.g., hydro, sediment, currents, etc.) through the project’s life cycle to assess restoration measures and their effects on the sustainability of Dauphin Island. As such, the project requires a data management plan (DMP) to address issues such as data delivery format, organizational strategies, internal data sharing, archival processes, and product dissemination.

Alabama↗

USGS2020

Decision analysis of restoration actions for faunal conservation and other stakeholder values: Dauphin Island, Alabama

Dauphin Island is a barrier island located in the northern Gulf of Mexico and serves as the only barrier island providing protection to much of the State of Alabama’s coastal natural resources. The ecosystem spans over 3,500 acres of barrier island habitat including, beach, dune, overwash fans, intertidal wetlands, maritime forest and freshwater ponds. In addition, Dauphin Island provides protection to approximately one-third of the Mississippi Sound estuarine habitats in its lee including oyster reefs, mainland marshes and seagrasses. The habitat supports a variety of species including at least 347 species of birds, some of which are Federally or State listed species that either pass through or reside on the island. The island enhances the region’s recreational and commercial fishery habitat through maintenance and protection of water quality in the sound and adjacent nearshore habitats. Dauphin Island also serves as the location for cultural resources, the United States Air Force’s (USAF) early warning radar station, the State’s marine education facilities, infrastructure for the oil and gas industry, and a vibrant tourism economy. Consequently, anthropogenic actions (e.g., structural changes) and externally driven natural factors (e.g., storms and sea level rise) that impact Dauphin Island could affect both the conservation and economic value of the island.

Alabama↗

USGS2019

Combining numerical and statistical models to predict storm-induced dune erosion

Dune erosion is an important aspect to consider when assessing coastal flood risk, as dune elevation loss makes the protected areas more susceptible to flooding. However, most advanced dune erosion numerical models are computationally expensive, which hinders their application in early-warning systems. Based on a combination of probabilistic and process-based numerical modeling, we develop an efficient statistical tool to predict dune erosion during storms. The analysis focuses on Dauphin Island, AL in the northern Gulf of Mexico, where we combine synthetic sea storms with a calibrated and validated XBeach model to develop and test a range of different surrogate models for their ability to predict barrier-island geometric parameters under storm conditions. Surrogate models are developed by combining the oceanographic forcing from 100 optimally sampled sea-storm events covering the entire multivariate parameter space (used as XBeach input) and associated changes in the dune system (XBeach output). We test four surrogate models using a k-fold approach for validation. All models perform well in predicting changes in dune elevation, barrier-island area, and width, but are less accurate in predicting alterations in the cross-shore locations of dune morphological features. Multivariate adaptive regression splines are identified as the best surrogate model based on their fast development and good performance, attaining a modified Mielke index of 0.81 for dune crest height. As demonstrated at Dauphin Island, our approach shows potential to be used in an operational framework to predict dune response (in particular crest elevation change) when water level and wave forecasts are available.

Alabama↗

USGS2019

Surrogate model development for coastal dune erosion under storm conditions

Early coastal dune erosion predictions are essential to avoid potential flood consequences but most dune erosion numerical models are computationally expensive, hence their application in Early Warning Systems is limited. Here, based on a combination of optimally sampled synthetic sea storms with a calibrated and validated XBeach model, we develop a surrogate model capable of producing fast and accurate dune erosion predictions under storm conditions when water level and wave forecasts are available. The analysis is performed on Dauphin Island, AL, where we train Multiple Linear Regression Models with oceanographic forcing from the selected sea storms (i.e., XBeach input) and predicted changes in the dune system (i.e., XBeach output). Surrogate model performance is assessed with a rigorous k-fold cross validation. Although changes in the location of dune features are not well predicted, the model attains good performance when predicting changes in dune elevation, barrier-island width and volume.

Alabama↗

USGS2019

Advancing barrier island habitat mapping using landscape position information

Barrier islands are dynamic ecosystems that change gradually from coastal processes, including currents and tides, and rapidly from episodic events, such as storms. These islands provide many important ecosystem services, including storm protection and erosion control to the mainland, habitat for fish and wildlife, and tourism. Habitat maps, developed by scientists, provide a critical tool for monitoring changes to these dynamic ecosystems. Barrier island monitoring often requires custom habitat maps due to several factors, including island size and the classification of unique geomorphology-based habitats, such as beach, dune, and barrier flats. In this study, we reviewed barrier-island-specific habitat mapping efforts and highlighted common habitat class types, source data, and mapping approaches. We also developed a framework for mapping geomorphology-based barrier island habitats using a rule-based, geographic object-based image analysis approach, which included the use of field data, tide data, high-resolution orthophotography, and lidar data. This framework integrates several barrier island mapping advancements with regard to the use of landscape position information for automated dune extraction and the use of Monte Carlo analyses for the treatment of elevation uncertainty for elevation-dependent habitats. Specifically, we used the uncertainty analyses to refine automated dune delineation based on elevation relative to extreme storm water levels and to increase the accuracy of intertidal and supratidal/upland habitat delineation. We found that dune extraction results were enhanced when elevation relative to storm water levels and visual interpretation were also applied. This framework could also be applied to beach–dune systems found along a mainland.

Alabama↗

USGS2018

Assessing the impact of open-ocean and back-barrier shoreline change on Dauphin Island, Alabama, at multiple time scales over the last 75 years

Dauphin Island and Little Dauphin Island, collectively, make up a geomorphically complex barrier island system located along Alabama’s southern coast, separating Mississippi Sound from the Gulf of Mexico and Mobile Bay. The barrier island system provides numerous economical (tourism, fisheries) and natural (habitat for migratory birds, natural protection of inland and coastal areas from storms) benefits to the State of Alabama. The complex geomorphology of Dauphin Island is partly a response to temporal variations in the direction and magnitude of sediment transport along and across the barrier island system. In this report, we present open-ocean and back-barrier shoreline change rates at different time scales to evaluate the island’s dominant behavior (expansion or widening and contraction or narrowing) over the last 75 years. The spatial and temporal variability of barrier island width provides baseline and historical context for potential restoration alternatives being considered as part of the Alabama Barrier Island Restoration Feasibility Study. Open-ocean shorelines have eroded continuously over the last 75 years, with rates ranging from 1.5 to 4 meters per year. Back-barrier shorelines are less uniform than open-ocean shorelines, but are, on average, also eroding over the same period. Periods of back-barrier progradation are observed but generally occur during discrete, large altering events like hurricanes that overwash or breach narrow sections of the barrier island. Because both shorelines are eroding, the width of the island has decreased during the last 75 years. The section to the west of a breach that opened during Hurricanes Ivan and Katrina (known as Katrina Cut) exhibits a steady, rapid decrease in width while the section to the east of the breach has gone through periods of expansion and contraction and has only recently begun slowly narrowing. Although the recent trends indicate declining widths, the back-barrier progradation rates in this area were the highest compared to other time periods, which abated extreme narrowing caused by increased open-ocean shoreline erosion. These data and the interpreted results indicate that both short-term (annual) and long-term (decadal) cross-barrier sediment exchange is a key component of sustaining barrier island width. Therefore, any mechanisms that influence this exchange, whether from natural processes (overwash, breaching, or inlet dynamics) or human activities (development, post-storm recovery, restoration), should be considered when evaluating the long-term sustainability of barrier island systems.

Alabama↗

USGS2018

Nearshore single-beam bathymetry data collected in 2015, Dauphin Island, Alabama

Dauphin Island, Alabama, is a barrier island located in the northern Gulf of Mexico that supports local residences, tourism, commercial infrastructure, and historic Fort Gaines. During the past decade, Dauphin Island was affected by several major hurricanes—Hurricanes Ivan (2004), Katrina (2005), and Isaac (2012)—and storms, along with sea-level rise, continue to present a threat to island stability. State and Federal managers are using a scientific approach to identify, formulate, and implement a long-term plan to provide restoration options for Dauphin Island, thereby helping increase its resilience against future storms and sea-level rise. Island morphology, including current bathymetry and shoreline data, is one scientific domain being investigated in an effort to produce a comprehensive restoration plan funded by an interagency grant from the National Fish and Wildlife Foundation Gulf Environmental Benefit Fund . In August 2015, the U.S. Geological Survey ( USGS ) St. Petersburg Coastal and Marine Science Center ( SPCMSC ), in cooperation with the U.S. Army Corps of Engineers at the U.S. Army Engineer Research and Development Center, Mobile District, and the State of Alabama, conducted bathymetric surveys of the nearshore waters surrounding Dauphin Island. This report provides a detailed methodology for the data acquisition and post-processing of 1,165-line kilometers (km) of single-beam bathymetry data collected under the USGS–SPCMSC Alabama Barrier Island Restoration Study . These data were acquired and processed under USGS field activity number 2015–326–FA . Data are provided in three datums: (1) the International Terrestrial Reference Frame of 2000, ellipsoid height (from –47.04 meters (m) to –29.36 m); (2) the North American Datum of 1983, CORS96 realization (NAD83 (CORS96)) horizontal, and the North American Vertical Datum 1988 GEOID12A vertical (from –0.24 m to –17.33 m); and (3) NAD83 (CORS96) horizontal, and mean lower low water vertical (from –0.12 m to –17.93 m). The x,y,z point datasets, trackline shapefiles, digital and handwritten Field Activity Collection Systems logs, one 50-m digital elevation model, and formal Federal Geographic Data Committee metadata are obtainable from the Data Downloads page or the associated USGS data release .

Alabama↗