Geology topics

Nathaniel G. Plant

Publications and source records attributed to Nathaniel G. Plant.

At least 73 records · Page 4Linked to original sources

USGS2014

Hurricane Sandy: observations and analysis of coastal change

Hurricane Sandy, the largest Atlantic hurricane on record, made landfall on October 29, 2012, and impacted a long swath of the U.S. Atlantic coastline. The barrier islands were breached in a number of places and beach and dune erosion occurred along most of the Mid-Atlantic coast. As a part of the National Assessment of Coastal Change Hazards project, the U.S. Geological Survey collected post-Hurricane Sandy oblique aerial photography and lidar topographic surveys to document the changes that occurred as a result of the storm. Comparisons of post-storm photographs to those collected prior to Sandy’s landfall were used to characterize the nature, magnitude, and spatial variability of hurricane-induced coastal changes. Analysis of pre- and post-storm lidar elevations was used to quantify magnitudes of change in shoreline position, dune elevation, and beach width. Erosion was observed along the coast from North Carolina to New York; however, as would be expected over such a large region, extensive spatial variability in storm response was observed.

Open-File Report↗

USGS2014

Probabilistic estimation of dune retreat on the Gold Coast, Australia

Sand dunes are an important natural buffer between storm impacts and development backing the beach on the Gold Coast of Queensland, Australia. The ability to forecast dune erosion at a prediction horizon of days to a week would allow efficient and timely response to dune erosion in this highly populated area. Towards this goal, we modified an existing probabilistic dune erosion model for use on the Gold Coast. The original model was trained using observations of dune response from Hurricane Ivan on Santa Rosa Island, Florida, USA (Plant and Stockdon 2012. Probabilistic prediction of barrier-island response to hurricanes, Journal of Geophysical Research, 117(F3), F03015). The model relates dune position change to pre-storm dune elevations, dune widths, and beach widths, along with storm surge and run-up using a Bayesian network. The Bayesian approach captures the uncertainty of inputs and predictions through the conditional probabilities between variables. Three versions of the barrier island response Bayesian network were tested for use on the Gold Coast. One network has the same structure as the original and was trained with the Santa Rosa Island data. The second network has a modified design and was trained using only pre- and post-storm data from 1988-2009 for the Gold Coast. The third version of the network has the same design as the second version of the network and was trained with the combined data from the Gold Coast and Santa Rosa Island. The two networks modified for use on the Gold Coast hindcast dune retreat with equal accuracy. Both networks explained 60% of the observed dune retreat variance, which is comparable to the skill observed by Plant and Stockdon (2012) in the initial Bayesian network application at Santa Rosa Island. The new networks improved predictions relative to application of the original network on the Gold Coast. Dune width was the most important morphologic variable in hindcasting dune retreat, while hydrodynamic variables, surge and run-up elevation, were also important

Queensland↗

USGS2013

Effects of sea-level rise on barrier island groundwater system dynamics: ecohydrological implications

We used a numerical model to investigate how a barrier island groundwater system responds to increases of up to 60 cm in sea level. We found that a sea-level rise of 20 cm leads to substantial changes in the depth of the water table and the extent and depth of saltwater intrusion, which are key determinants in the establishment, distribution and succession of vegetation assemblages and habitat suitability in barrier islands ecosystems. In our simulations, increases in water-table height in areas with a shallow depth to water (or thin vadose zone) resulted in extensive groundwater inundation of land surface and a thinning of the underlying freshwater lens. We demonstrated the interdependence of the groundwater response to island morphology by evaluating changes at three sites. This interdependence can have a profound effect on ecosystem composition in these fragile coastal landscapes under long-term changing climatic conditions.

Maryl;Virginia↗

USGS2013

Bridging groundwater models and decision support with a Bayesian network

Resource managers need to make decisions to plan for future environmental conditions, particularly sea level rise, in the face of substantial uncertainty. Many interacting processes factor in to the decisions they face. Advances in process models and the quantification of uncertainty have made models a valuable tool for this purpose. Long-simulation runtimes and, often, numerical instability make linking process models impractical in many cases. A method for emulating the important connections between model input and forecasts, while propagating uncertainty, has the potential to provide a bridge between complicated numerical process models and the efficiency and stability needed for decision making. We explore this using a Bayesian network (BN) to emulate a groundwater flow model. We expand on previous approaches to validating a BN by calculating forecasting skill using cross validation of a groundwater model of Assateague Island in Virginia and Maryland, USA. This BN emulation was shown to capture the important groundwater-flow characteristics and uncertainty of the groundwater system because of its connection to island morphology and sea level. Forecast power metrics associated with the validation of multiple alternative BN designs guided the selection of an optimal level of BN complexity. Assateague island is an ideal test case for exploring a forecasting tool based on current conditions because the unique hydrogeomorphological variability of the island includes a range of settings indicative of past, current, and future conditions. The resulting BN is a valuable tool for exploring the response of groundwater conditions to sea level rise in decision support.

Water Resources Research↗

USGS2013

cBathy: A robust algorithm for estimating nearshore bathymetry

A three-part algorithm is described and tested to provide robust bathymetry maps based solely on long time series observations of surface wave motions. The first phase consists of frequency-dependent characterization of the wave field in which dominant frequencies are estimated by Fourier transform while corresponding wave numbers are derived from spatial gradients in cross-spectral phase over analysis tiles that can be small, allowing high-spatial resolution. Coherent spatial structures at each frequency are extracted by frequency-dependent empirical orthogonal function (EOF). In phase two, depths are found that best fit weighted sets of frequency-wave number pairs. These are subsequently smoothed in time in phase 3 using a Kalman filter that fills gaps in coverage and objectively averages new estimates of variable quality with prior estimates. Objective confidence intervals are returned. Tests at Duck, NC, using 16 surveys collected over 2 years showed a bias and root-mean-square (RMS) error of 0.19 and 0.51 m, respectively but were largest near the offshore limits of analysis (roughly 500 m from the camera) and near the steep shoreline where analysis tiles mix information from waves, swash and static dry sand. Performance was excellent for small waves but degraded somewhat with increasing wave height. Sand bars and their small-scale alongshore variability were well resolved. A single ground truth survey from a dissipative, low-sloping beach (Agate Beach, OR) showed similar errors over a region that extended several kilometers from the camera and reached depths of 14 m. Vector wave number estimates can also be incorporated into data assimilation models of nearshore dynamics.

North Carolina↗

USGS2013

U.S. Geological Survey natural hazards science strategy— Promoting the safety, security, and economic well-being of the Nation

Executive Summary The mission of the U.S. Geological Survey (USGS) in natural hazards is to develop and apply hazard science to help protect the safety, security, and economic well-being of the Nation. The costs and consequences of natural hazards can be enormous, and each year more people and infrastructure are at risk. USGS scientific research—founded on detailed observations and improved understanding of the responsible physical processes—can help to understand and reduce natural hazard risks and to make and effectively communicate reliable statements about hazard characteristics, such as frequency, magnitude, extent, onset, consequences, and where possible, the time of future events. To accomplish its broad hazard mission, the USGS maintains an expert workforce of scientists and technicians in the earth sciences, hydrology, biology, geography, social and behavioral sciences, and other fields, and engages cooperatively with numerous agencies, research institutions, and organizations in the public and private sectors, across the Nation and around the world. The scientific expertise required to accomplish the USGS mission in natural hazards includes a wide range of disciplines that this report refers to, in aggregate, as hazard science. In October 2010, the Natural Hazards Science Strategy Planning Team (H–SSPT) was charged with developing a long-term (10-year) Science Strategy for the USGS mission in natural hazards. This report fulfills that charge, with a document hereinafter referred to as the Strategy, to provide scientific observations, analyses, and research that are critical for the Nation to become more resilient to natural hazards. Science provides the information that decisionmakers need to determine whether risk management activities are worthwhile. Moreover, as the agency with the perspective of geologic time, the USGS is uniquely positioned to extend the collective experience of society to prepare for events outside current memory. The USGS has critical statutory and nonstatutory roles regarding floods, earthquakes, tsunamis, landslides, coastal erosion, volcanic eruptions, wildfires, and magnetic storms—the hazards considered in this plan. There are numerous other hazards of societal importance that are considered either only peripherally or not at all in this Strategy because they are either in another of the USGS strategic science plans (such as drought) or not in the overall mission of the USGS (such as tornados).

Circular↗

USGS2013

Assessing hazards along our Nation's coasts

Coastal areas are essential to the economic, cultural, and environmental health of the Nation, yet by nature coastal areas are constantly changing due to a variety of events and processes. Extreme storms can cause dramatic changes to our shorelines in a matter of hours, while sea-level rise can profoundly alter coastal environments over decades. These changes can have a devastating impact on coastal communities, such as the loss of homes built on retreating sea cliffs or protective dunes eroded by storm waves. Sometimes, however, the changes can be positive, such as new habitat created by storm deposits. The U.S. Geological Survey (USGS) is meeting the need for scientific understanding of how our coasts respond to different hazards with continued assessments of current and future changes along U.S. coastlines. Through the National Assessment of Coastal Change Hazards (NACCH), the USGS carries out the unique task of quantifying coastal change hazards along open-ocean coasts in the United States and its territories. Residents of coastal communities, emergency managers, and other stakeholders can use science-based data, tools, models, and other products to improve planning and enhance resilience.

Fact Sheet↗

USGS2013

Application of a hydrodynamic and sediment transport model for guidance of response efforts related to the Deepwater Horizon oil spill in the Northern Gulf of Mexico along the coast of Alabama and Florida

U.S. Geological Survey (USGS) scientists have provided a model-based assessment of transport and deposition of residual Deepwater Horizon oil along the shoreline within the northern Gulf of Mexico in the form of mixtures of sand and weathered oil, known as surface residual balls (SRBs). The results of this USGS research, in combination with results from other components of the overall study, will inform operational decisionmaking. The results will provide guidance for response activities and data collection needs during future oil spills. In May 2012 the U.S. Coast Guard, acting as the Deepwater Horizon Federal on-scene coordinator, chartered an operational science advisory team to provide a science-based review of data collected and to conduct additional directed studies and sampling. The goal was to characterize typical shoreline profiles and morphology in the northern Gulf of Mexico to identify likely sources of residual oil and to evaluate mechanisms whereby reoiling phenomena may be occurring (for example, burial and exhumation and alongshore transport). A steering committee cochaired by British Petroleum Corporation (BP) and the National Oceanic and Atmospheric Administration (NOAA) is overseeing the project and includes State on-scene coordinators from four States (Alabama, Florida, Louisiana, and Mississippi), trustees of the U.S. Department of the Interior (DOI), and representatives from the U.S. Coast Guard. This report presents the results of hydrodynamic and sediment transport models and developed techniques for analyzing potential SRB movement and burial and exhumation along the coastline of Alabama and Florida. Results from these modeling efforts are being used to explain the complexity of reoiling in the nearshore environment and to broaden consideration of the different scenarios and difficulties that are being faced in identifying and removing residual oil. For instance, modeling results suggest that larger SRBs are not, under the most commonly observed low-energy wave conditions, likely to move very far alongshore. This finding suggests that SRBs from one source location may not (outside of storm conditions) be redistributed to other up or down coast locations. This information can guide operational response decisions. In addition, because SRBs are less mobile compared with sand, they are likely to become buried and unburied under normal sand transport processes thereby lengthening the time SRBs may take to move onshore. The rate of onshore movement was not specifically addressed by this study, yet the results resolve the cross-shore domain and cross-shore variations in alongshore transport that are relevant to achieving the primary objectives. Furthermore, during infrequent events (for example, winter storms and severe meteorological events such as Hurricane Isaac of August 2012), energy is shown to be sufficient to move a greater range of SRB sizes and potentially expose and break up submerged oil mats. When SRBs do move alongshore, the models indicate that there are regions that are more conducive to accumulation of SRB material than others. Accumulation can occur where there are reversals and decelerations in alongshore currents and where forces created by shear stress drops below critical thresholds to maintain or initiate SRB movement. In addition, flow and SRB mobility patterns around inlets indicate patterns in hydrodynamic forces that influence redistribution of SRBs and the surface oil that mixed with sediment to form oil mats in the first place.

Alabama;Florida↗

USGS2013

National assessment of hurricane-induced coastal erosion hazards: Southeast Atlantic Coast

Beaches serve as a natural barrier between the ocean and inland communities, ecosystems, and natural resources. However, these dynamic environments move and change in response to winds, waves, and currents. During extreme storms, changes to beaches can be large, and the results are sometimes catastrophic. Lives may be lost, communities destroyed, and millions of dollars spent on rebuilding. During storms, large waves may erode beaches, and high storm surge shifts the erosive force of the waves higher on the beach. In some cases, the combined effects of waves and surge may cause overwash or flooding. Building and infrastructure on or near a dune can be undermined during wave attack and subsequent erosion. During Hurricane Ivan in 2004, a five-story condominium in Orange Beach, Alabama, collapsed after the sand dune supporting the foundation eroded. The September 1999 landfall of Hurricane Dennis caused erosion and undermining that destroyed roads, foundations, and septic systems. Waves overtopping a dune can transport sand inland, covering roads and blocking evacuation routes or emergency relief. If storm surge inundates barrier island dunes, currents flowing across the island can create a breach, or new inlet, completely severing evacuation routes. Waves and surge during the 2003 landfall of Hurricane Isabel left a 200-meter (m) wide breach that cut the only road to and from the village of Hatteras, N.C. Extreme coastal changes caused by hurricanes may increase the vulnerability of communities both during a storm and to future storms. For example, when sand dunes on a barrier island are eroded substantially, inland structures are exposed to storm surge and waves. Absent or low dunes also allow water to flow inland across the island, potentially increasing storm surge in the back bay, on the soundside of the barrier, and on the mainland. During Hurricane Isabel the protective sand dunes near the breach were completely eroded, increasing vulnerability to future storms.

North Carolina;South Carolina;Georgia;Florida↗

USGS2013

National assessment of hurricane-induced coastal erosion hazards: Mid-Atlantic Coast

Beaches serve as a natural buffer between the ocean and inland communities, ecosystems, and natural resources. However, these dynamic environments move and change in response to winds, waves, and currents. During extreme storms, changes to beaches can be large, and the results are sometimes catastrophic. Lives may be lost, communities destroyed, and millions of dollars spent on rebuilding. During storms, large waves may erode beaches, and high storm surge shifts the erosive force of the waves higher on the beach. In some cases, the combined effects of waves and surge may cause overwash (when waves and surge overtop the dune, transporting sand inland) or flooding. Building and infrastructure on or near a dune can be undermined during wave attack and subsequent erosion. During Hurricane Ivan in 2004, a five-story condominium in Orange Beach, Alabama, collapsed after the sand dune supporting the foundation eroded. Hurricane Sandy, which made landfall as an extra-tropical cyclone on October 29, 2012, caused erosion and undermining that destroyed roads, boardwalks, and foundations in Seaside Heights, New Jersey. Waves overtopping a dune can transport sand inland, covering roads and blocking evacuation routes or emergency relief. If storm surge inundates barrier island dunes, currents flowing across the island can create a breach, or a new inlet, completely severing evacuation routes. Waves and surge during Hurricane Sandy, which made landfall on October 29, 2012, left a breach that cut the road and bridge to Mantoloking, N.J. Extreme coastal changes caused by hurricanes may increase the vulnerability of communities both during a storm and to future storms. For example, when sand dunes on a barrier island are eroded substantially, inland structures are exposed to storm surge and waves. Absent or low dunes also allow water to flow inland across the island, potentially increasing storm surge in the back bay, on the soundside of the barrier, and on the mainland.

New York;New Jersey;Delaware;Maryl;Virginia↗

USGS2013

Hurricane Isaac: observations and analysis of coastal change

Understanding storm-induced coastal change and forecasting these changes require knowledge of the physical processes associated with a storm and the geomorphology of the impacted coastline. The primary physical process of interest is sediment transport that is driven by waves, currents, and storm surge associated with storms. Storm surge, which is the rise in water level due to the wind, barometric pressure, and other factors, allows both waves and currents to impact parts of the coast not normally exposed to these processes. Coastal geomorphology reflects the coastal changes associated with extreme-storm processes. Relevant geomorphic variables that are observable before and after storms include sand dune elevation, beach width, shoreline position, sediment grain size, and foreshore beach slope. These variables, in addition to hydrodynamic processes, can be used to quantify coastal change and are used to predict coastal vulnerability to storms (Stockdon and others, 2007). The U.S. Geological Survey (USGS) National Assessment of Coastal Change Hazards (NACCH) project ( http://coastal.er.usgs.gov/national-assessment/ ) provides hazard information to those concerned about the Nation’s coastlines, including residents of coastal areas, government agencies responsible for coastal management, and coastal researchers. Extreme-storm research is a component of the NACCH project ( http://coastal.er.usgs.gov/hurricanes/ ) that includes development of predictive understanding, vulnerability assessments using models, and updated observations in response to specific storm events. In particular, observations were made to determine morphological changes associated with Hurricane Isaac, which made landfall in the United States first at Southwest Pass, at the mouth of the Mississippi River, at 0000 August 29, 2012 UTC (Coordinated Universal Time) and again, 8 hours later, west of Port Fourchon, Louisiana (Berg, 2013). Methods of observation included oblique aerial photography, airborne light detection and ranging (lidar) topographic surveys, and ground-based topographic surveys. This report documents data-collection efforts and presents qualitative and quantitative descriptions of hurricane-induced changes to the shoreline, beaches, dunes, and infrastructure in the region that was heavily impacted by Hurricane Isaac. The report is divided into the following sections: Section 1: Introduction Section 2: Storm Overview, presents a synopsis of the storm, including meteorological evolution, wind speed impact area, wind-wave generation, and storm-surge extent and magnitudes. Section 3: Coastal-Change Observations, describes data-collection missions, including acquisition of oblique aerial photography and airborne lidar topographic surveys, in response to Hurricane Isaac. Section 4: Coastal-Change Analysis, describes data-analysis methods and observations of coastal change.

Atlantic Ocean;Caribbean Sea;Gulf Of Mexico;Missis↗

USGS2013

Appendix D: Use of wave scenarios to assess potential submerged oil mat (SOM) formation along the coast of Florida and Alabama

During the Deepwater Horizon oil spill, oil in the surf zone mixed with sediment in the surf zone to form heavier-than-water sediment oil agglomerates of various size, ranging from small (cm-scale) pieces (surface residual balls, SRBs) to large mats (100-m scale, surface residue mats, SR mats). Once SR mats formed in the nearshore or in the intertidal zone, they may have become buried by sand moving onshore or alongshore. To assist in locating possible sites of buried oil, wave scenarios previously developed by the U.S. Geological Survey (USGS) were used to determine the depths at which surface oil had the potential to mix with suspended sediment. For sediment to mix with floating oil and form an agglomerate of sufficient density to sink to the seafloor, either the water must be very shallow (e.g., within the swash zone) or sediment must be suspended to the water surface in sufficient concentrations to create a denser-than-sea water agglomerate. The focus of this study is to analyze suspended sediment mixing with surface oil in depths beyond the swash zone, in order to define the seaward limit of mat formation. A theoretical investigation of sediment dynamics in the nearshore zone revealed that non-breaking waves do not suspend enough sediment to the surface to form sinking sand/oil agglomerates. For this study, it was assumed that the cross-shore distribution of potential agglomerate formation is associated with the primary breaker line, and the presence of plunging breakers, over the time frame of oiling. The potential locations of submerged oil mats (SOMs) are sites where (1) possible agglomerate formation occurred, where (2) sediment accreted post-oiling and buried the SOM, and where (3) the bathymetry has not subsequently eroded to re-expose any mat that may have formed at that site. To facilitate identification of these locations, the range of water level variation over the time frame of oiling was also prescribed, which combined with the wave-breaking depth analysis and pre-oiling bathymetry would identify the potential geographic locations of SOMs.

Operational Science Advisory Team Report↗

USGS2012

Impact assessment of extreme storm events using a Bayesian network

This paper describes an investigation on the usefulness of Bayesian Networks in the safety assessment of dune coasts. A network has been created that predicts the erosion volume based on hydraulic boundary conditions and a number of cross-shore profile indicators. Field measurement data along a large part of the Dutch coast has been used to train the network. Corresponding storm impact on the dunes was calculated with an empirical dune erosion model named duros+. Comparison between the Bayesian Network predictions and the original duros+ results, here considered as observations, results in a skill up to 0.88, provided that the training data covers the range of predictions. Hence, the predictions from a deterministic model (duros+) can be captured in a probabilistic model (Bayesian Network) such that both the process knowledge and uncertainties can be included in impact and vulnerability assessments.

Conference Paper↗

USGS2012

Probabilistic prediction of barrier-island response to hurricanes

Prediction of barrier-island response to hurricane attack is important for assessing the vulnerability of communities, infrastructure, habitat, and recreational assets to the impacts of storm surge, waves, and erosion. We have demonstrated that a conceptual model intended to make qualitative predictions of the type of beach response to storms (e.g., beach erosion, dune erosion, dune overwash, inundation) can be reformulated in a Bayesian network to make quantitative predictions of the morphologic response. In an application of this approach at Santa Rosa Island, FL, predicted dune-crest elevation changes in response to Hurricane Ivan explained about 20% to 30% of the observed variance. An extended Bayesian network based on the original conceptual model, which included dune elevations, storm surge, and swash, but with the addition of beach and dune widths as input variables, showed improved skill compared to the original model, explaining 70% of dune elevation change variance and about 60% of dune and shoreline position change variance. This probabilistic approach accurately represented prediction uncertainty (measured with the log likelihood ratio), and it outperformed the baseline prediction (i.e., the prior distribution based on the observations). Finally, sensitivity studies demonstrated that degrading the resolution of the Bayesian network or removing data from the calibration process reduced the skill of the predictions by 30% to 40%. The reduction in skill did not change conclusions regarding the relative importance of the input variables, and the extended model's skill always outperformed the original model.

Florida↗

USGS2012

Extended Kalman Filter framework for forecasting shoreline evolution

A shoreline change model incorporating both long- and short-term evolution is integrated into a data assimilation framework that uses sparse observations to generate an updated forecast of shoreline position and to estimate unobserved geophysical variables and model parameters. Application of the assimilation algorithm provides quantitative statistical estimates of combined model-data forecast uncertainty which is crucial for developing hazard vulnerability assessments, evaluation of prediction skill, and identifying future data collection needs. Significant attention is given to the estimation of four non-observable parameter values and separating two scales of shoreline evolution using only one observable morphological quantity (i.e. shoreline position).

Geophysical Research Letters↗

USGS2012

National assessment of hurricane-induced coastal erosion hazards--Gulf of Mexico

Sandy beaches provide a natural barrier between the ocean and inland communities, ecosystems, and resources. However, these dynamic environments move and change in response to winds, waves, and currents. During a hurricane, these changes can be large and sometimes catastrophic. High waves and storm surge act together to erode beaches and inundate low-lying lands, putting inland communities at risk. A decade of USGS research on storm-driven coastal change hazards has provided the data and modeling capabilities to identify areas of our coastline that are likely to experience extreme and potentially hazardous erosion during a hurricane. This report defines hurricane-induced coastal erosion hazards for sandy beaches along the U.S. Gulf of Mexico coastline. The analysis is based on a storm-impact scaling model that uses observations of beach morphology combined with sophisticated hydrodynamic models to predict how the coast will respond to the direct landfall of category 1-5 hurricanes. Hurricane-induced water levels, due to both surge and waves, are compared to beach and dune elevations to determine the probabilities of three types of coastal change: collision (dune erosion), overwash, and inundation. As new beach morphology observations and storm predictions become available, this analysis will be updated to describe how coastal vulnerability to storms will vary in the future.

Open-File Report↗

USGS2012

Natural hazards science strategy

The mission of the U.S. Geological Survey (USGS) in natural hazards is to develop and apply hazard science to help protect the safety, security, and economic well-being of the Nation. The costs and consequences of natural hazards can be enormous, and each year more people and infrastructure are at risk. USGS scientific research—founded on detailed observations and improved understanding of the responsible physical processes—can help to understand and reduce natural hazard risks and to make and effectively communicate reliable statements about hazard characteristics, such as frequency, magnitude, extent, onset, consequences, and where possible, the time of future events. To accomplish its broad hazard mission, the USGS maintains an expert workforce of scientists and technicians in the earth sciences, hydrology, biology, geography, social and behavioral sciences, and other fields, and engages cooperatively with numerous agencies, research institutions, and organizations in the public and private sectors, across the Nation and around the world. The scientific expertise required to accomplish the USGS mission in natural hazards includes a wide range of disciplines that this report refers to, in aggregate, as hazard science. In October 2010, the Natural Hazards Science Strategy Planning Team (H–SSPT) was charged with developing a long-term (10-year) Science Strategy for the USGS mission in natural hazards. This report fulfills that charge, with a document hereinafter referred to as the Strategy, to provide scientific observations, analyses, and research that are critical for the Nation to become more resilient to natural hazards. Science provides the information that decisionmakers need to determine whether risk management activities are worthwhile. Moreover, as the agency with the perspective of geologic time, the USGS is uniquely positioned to extend the collective experience of society to prepare for events outside current memory. The USGS has critical statutory and nonstatutory roles regarding floods, earthquakes, tsunamis, landslides, coastal erosion, volcanic eruptions, wildfires, and magnetic storms—the hazards considered in this plan. There are numerous other hazards of societal importance that are considered either only peripherally or not at all in this Strategy because they are either in another of the USGS strategic science plans (such as drought) or not in the overall mission of the USGS (such as tornados).

Open-File Report↗

USGS2011

Forecasting hurricane impact on coastal topography: Hurricane Ike

Extreme storms can have a profound impact on coastal topography and thus on ecosystems and human-built structures within coastal regions. For instance, landfalls of several recent major hurricanes have caused significant changes to the U.S. coastline, particularly along the Gulf of Mexico. Some of these hurricanes (e.g., Ivan in 2004, Katrina and Rita in 2005, and Gustav and Ike in 2008) led to shoreline position changes of about 100 meters. Sand dunes, which protect the coast from waves and surge, eroded, losing several meters of elevation in the course of a single storm. Observations during these events raise the question of how storm-related changes affect the future vulnerability of a coast.

Eos, Transactions, American Geophysical Union↗