Geology topics

Peter N. Adams

Publications and source records attributed to Peter N. Adams.

5 recordsLinked to original sources

USGS2022

On the potential for remote observations of coastal morphodynamics from surf-cameras

Recreational surf-cameras (surfcams) are ubiquitous along many coastlines, and yet are a largely untapped source of coastal morphodynamic observations. Surfcams offer broad spatial coverage and flexibility in data collection, but a method to remotely acquire ground control points (GCPs) and initial camera parameter approximations is necessary to better leverage this existing infrastructure to make quantitative measurements. This study examines the efficacy of remotely monitoring coastal morphodynamics from surfcams at two sites on the Atlantic coast of Florida, U.S.A., by leveraging freely available airborne lidar observations to acquire remote-GCPs and open-source web tools for camera parameter approximations, ignoring lens distortion. Intrinsic and extrinsic camera parameters are determined using a modified space resection procedure, wherein parameters are determined using iterative adjustment while fitting to remote-GCPs and initial camera parameter approximations derived from justified assumptions and Google Earth. This procedure is completed using the open-source Surf-Camera Remote Calibration Tool (SurfRCaT). The results indicate root mean squared horizontal reprojection errors at the two cameras of 3.43 m and 6.48 m. Only immobile hard structures such as piers, jetties, and boulders are suitable as remote-GCPs, and the spatial distribution of available points is a likely reason for the higher accuracy at one camera relative to the other. Additionally, lens distortion is not considered in this work. This is another important source of error and including it in the methodology is highlighted as a useful avenue for future work. Additional factors, such as initial camera parameter approximation accuracy, likely play a role as well. This work illustrates that, provided there is sufficient remote-GCP availability and small lens distortion, remote video monitoring of coastal areas with existing surfcams could provide a usable source of coastal morphodynamic observations. This is further explored with a shoreline change analysis from the higher-accuracy camera. It was found that only the largest (>6 m) magnitude shoreline changes exceed the observational uncertainty driven by shoreline mapping error and reprojection error, indicating that remotely calibrated surfcams can provide observations of seasonal or storm-driven signals.

Florida↗

USGS2019

Daily to decadal variability of beach morphology at NASA-Kennedy Space Center: Storm influences across timescales

Shoreline variability over timescales ranging from days to decades is examined at NASA-Kennedy Space Center on the Atlantic coast of Florida. Three sources of shoreline position data are utilized to complete this analysis: hourly video-image observations, monthly Real Time Kinematic GPS observations, and historical aerial imagery dating back to 1943. We find that shoreline positions tend to respond coherently to monthly variations in wave energy, except during storm-driven shoreline change. A seasonal signal in shoreline behavior is also evident, however this signal becomes indiscernible after a rapid change in morphologic behavior following Hurricane Sandy’s impact in October 2012. Further, the spatial pattern of shoreline change following Sandy’s impact mimics decadal-scale trends, suggesting that response to large storms may be controlling decadal shoreline change behavior at this site.

Florida↗

USGS2015

Application of Bayesian Networks to hindcast barrier island morphodynamics

Prediction of coastal vulnerability is of increasing concern to policy makers, coastal managers and other stakeholders. Coastal regions and barrier islands along the Atlantic and Gulf coasts are subject to frequent, large storms, whose waves and storm surge can dramatically alter beach morphology, threaten infrastructure, and impact local economies. Given that precise forecasts of regional hazards are challenging, because of the complex interactions between processes on many scales, a range of probable geomorphic change in response to storm conditions is often more helpful than deterministic predictions. Site-specific probabilistic models of coastal change are reliable because they are formulated with observations so that local factors, of potentially high influence, are inherent in the model. The development and use of predictive tools such as Bayesian Networks in response to future storms has the potential to better inform management decisions and hazard preparation in coastal communities. We present several Bayesian Networks designed to hindcast distinct morphologic changes attributable to the Nor'Ida storm of 2009, at Fire Island, New York. Model predictions are informed with historical system behavior, initial morphologic conditions, and a parameterized treatment of wave climate. We refine a preliminary Bayesian Network by 1) increasing model experience through additional observations, 2) including anthropogenic modification history, and 3) replacing parameterized wave impact values with maximum run-up elevation. Further, we develop and train a pair of generalized models with an additional dataset encompassing a different storm event, which expands the observations beyond our hindcast objective. We compare the skill of the generalized models against the Nor'Ida specific model formulation, balancing the reduced skill with an expectation of increased transferability. Results of Nor'Ida hindcasts ranged in skill from 0.37 to 0.51 and accuracy of 65.0 to 81.9%.

New York↗

USGS2014

The rock coast of the USA

The coastline of the USA is vast and comprises a variety of landform types including barrier islands, mainland beaches, soft bluffed coastlines and hard rocky coasts. The majority of the bluffed and rocky coasts are found in the northeastern part of the country (New England) and along the Pacific coast. Rocky and bluffed landform types are commonly interspersed along the coastline and occur as a result of relative lowering of sea level from tectonic or isostatic forcing, which can occur on timescales ranging from instantaneous to millenia. Recent research on sea cliffs in the contiguous USA has focused on a broad range of topics from documenting erosion rates to identifying processes and controls on morphology to prediction modelling. This chapter provides a detailed synthesis of recent and seminal research on rocky coast geomorphology along open-ocean coasts of the continental United States (USA).

Book chapter↗

USGS2009

The framework of a coastal hazards model: A tool for predicting the impact of severe storms

The U.S. Geological Survey (USGS) Multi-Hazards Demonstration Project in Southern California (Jones and others, 2007) is a five-year project (FY2007-FY2011) integrating multiple USGS research activities with the needs of external partners, such as emergency managers and land-use planners, to produce products and information that can be used to create more disaster-resilient communities. The hazards being evaluated include earthquakes, landslides, floods, tsunamis, wildfires, and coastal hazards. For the Coastal Hazards Task of the Multi-Hazards Demonstration Project in Southern California, the USGS is leading the development of a modeling system for forecasting the impact of winter storms threatening the entire Southern California shoreline from Pt. Conception to the Mexican border. The modeling system, run in real-time or with prescribed scenarios, will incorporate atmospheric information (that is, wind and pressure fields) with a suite of state-of-the-art physical process models (that is, tide, surge, and wave) to enable detailed prediction of currents, wave height, wave runup, and total water levels. Additional research-grade predictions of coastal flooding, inundation, erosion, and cliff failure will also be performed. Initial model testing, performance evaluation, and product development will be focused on a severe winter-storm scenario developed in collaboration with the Winter Storm Working Group of the USGS Multi-Hazards Demonstration Project in Southern California. Additional offline model runs and products will include coastal-hazard hindcasts of selected historical winter storms, as well as additional severe winter-storm simulations based on statistical analyses of historical wave and water-level data. The coastal-hazards model design will also be appropriate for simulating the impact of storms under various sea level rise and climate-change scenarios. The operational capabilities of this modeling system are designed to provide emergency planners with the critical information they need to respond quickly and efficiently and to increase public safety and mitigate damage associated with powerful coastal storms. For instance, high resolution local models will predict detailed wave heights, breaking patterns, and current strengths for use in warning systems for harbor-mouth navigation and densely populated coastal regions where beach safety is threatened. The offline applications are intended to equip coastal managers with the information needed to manage and allocate their resources effectively to protect sections of coast that may be most vulnerable to future severe storms.

California↗