Nathaniel Plant, Ph.D.
I am the Center Director for the Saint Petersburg Coastal and Marine Science Center, where I support scientists working on coastal research topics such as coastal hazards due to storms and sea-level rise; sediment availability and distribution; and response of coastal communities, wetlands, corals, and microbial ecosystems to extreme events and persistent changes to our coastal environment.
I have served in this capacity since October 2018, initially in an acting capacity and permanently since April 2019.
Prior to becoming Center Director, my role with the USGS was as an oceanographer. Past research projects included scientific applications to coastal management, such as assessing storm-induced and long-term coastal erosion or identification of future nesting habitat for endangered shore bird species. Throughout my research career, I have lived in a range of coastal communities in California, Mississippi, and Florida, as well as the Netherlands, and the Washington, DC area. I received my Ph.D. in Marine Geology from Oregon State University’s Oceanography program in 1998.
Science and Products
Appendix D: Use of wave scenarios to assess potential submerged oil mat (SOM) formation along the coast of Florida and Alabama
Extended Kalman Filter framework for forecasting shoreline evolution
Probabilistic prediction of barrier-island response to hurricanes
Natural hazards science strategy
National assessment of hurricane-induced coastal erosion hazards--Gulf of Mexico
Impact assessment of extreme storm events using a Bayesian network
A Bayesian network to predict vulnerability to sea-level rise: data report
Prediction and assimilation of surf-zone processes using a Bayesian network: Part II: Inverse models
Prediction and assimilation of surf-zone processes using a Bayesian network: Part I: Forward models
Process-based model predictions of hurricane induced morphodynamic change on low-lying barrier islands
EAARL Coastal Topography--Cape Canaveral, Florida, 2009: First Surface
A behavior-oriented dynamic model for sandbar migration and 2DH evolution
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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 moviAuthorsP. Soupy Dalyander, Joseph W. Long, Nathaniel G. Plant, David M. ThompsonExtended 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 uncAuthorsJoseph Long, Nathaniel G. PlantProbabilistic 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, inunAuthorsNathaniel G. Plant, Hilary F. StockdonNatural 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 resAuthorsRobert R. Holmes, Lucile M. Jones, Jeffery C. Eidenshink, Jonathan W. Godt, Stephen H. Kirby, Jeffrey J. Love, Christina A. Neal, Nathaniel G. Plant, Michael L. Plunkett, Craig S. Weaver, Anne Wein, Suzanne C. PerryNational 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 riskAuthorsHilary F. Stockdon, Kara S. Doran, David M. Thompson, Kristin L. Sopkin, Nathaniel G. Plant, Asbury H. SallengerImpact 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 duneAuthorsC.(Kees) den Heijer, Dirk T.J.A. Knipping, Nathaniel G. Plant, Jaap S. M. van Thiel de Vries, Fedor Baart, Pieter H. A. J. M. van GelderA Bayesian network to predict vulnerability to sea-level rise: data report
During the 21st century, sea-level rise is projected to have a wide range of effects on coastal environments, development, and infrastructure. Consequently, there has been an increased focus on developing modeling or other analytical approaches to evaluate potential impacts to inform coastal management. This report provides the data that were used to develop and evaluate the performance of a BayesAuthorsBenjamin T. Gutierrez, Nathaniel G. Plant, E. Robert ThielerPrediction and assimilation of surf-zone processes using a Bayesian network: Part II: Inverse models
A Bayesian network model has been developed to simulate a relatively simple problem of wave propagation in the surf zone (detailed in Part I). Here, we demonstrate that this Bayesian model can provide both inverse modeling and data-assimilation solutions for predicting offshore wave heights and depth estimates given limited wave-height and depth information from an onshore location. The inverse meAuthorsNathaniel G. Plant, K. Todd HollandPrediction and assimilation of surf-zone processes using a Bayesian network: Part I: Forward models
Prediction of coastal processes, including waves, currents, and sediment transport, can be obtained from a variety of detailed geophysical-process models with many simulations showing significant skill. This capability supports a wide range of research and applied efforts that can benefit from accurate numerical predictions. However, the predictions are only as accurate as the data used to drive tAuthorsNathaniel G. Plant, K. Todd HollandProcess-based model predictions of hurricane induced morphodynamic change on low-lying barrier islands
Using Delft3D, a Chandeleur Island model was constructed to examine the sediment-transport patterns and morphodynamic change caused by Hurricane Katrina and similar storm events. The model setup included a coarse Gulf of Mexico domain and a nested finer-resolution Chandeleur Island domain. The finer-resolution domain resolved morphodynamic processes driven by storms and tides. A sensitivity analysAuthorsNathaniel G. Plant, David M. Thompson, Edwin EliasEAARL Coastal Topography--Cape Canaveral, Florida, 2009: First Surface
These remotely sensed, geographically referenced elevation measurements of lidar-derived first-surface (FS) topography datasets were produced collaboratively by the U.S. Geological Survey (USGS), St. Petersburg Coastal and Marine Science Center, St. Petersburg, FL, and the National Aeronautics and Space Administration (NASA), Kennedy Space Center, FL. This project provides highly detailed and accuAuthorsJ.M. Bonisteel-Cormier, Amar Nayegandhi, Nathaniel Plant, C. W. Wright, D.B. Nagle, K.S. Serafin, E.S. KlippA behavior-oriented dynamic model for sandbar migration and 2DH evolution
A nonlinear model is developed to study the time‐dependent relationship between the alongshore variability of a sandbar, a(t), and alongshore‐averaged sandbar position, xc(t). Sediment transport equations are derived from energetics‐based formulations. A link between this continuous physical representation and a parametric form describing the migration of sandbars of constant shape is establishedAuthorsK.D. Splinter, R.A. Holman, Nathaniel G. Plant - Software
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