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  • 1
    Publication Date: 2019-11-19
    Description: Rip currents and other surf hazards are an emerging public health issue globally. Lifeguards, warning flags, and signs are important, and to varying degrees they are effective strategies to minimize risk to beach users. In the United States and other jurisdictions around the world, lifeguards use coloured flags (green, yellow, and red) to indicate whether the danger posed by the surf and rip hazard is low, moderate, or high respectively. The choice of flag depends on the lifeguard(s) monitoring the changing surf conditions along the beach and over the course of the day using both regional surf forecasts and careful observation. There is a potential that the chosen flag is not consistent with the beach user perception of the risk, which may increase the potential for rescues or drownings. In this study, machine learning is used to determine the potential for error in the flags used at Pensacola Beach and the impact of that error on the number of rescues. Results of a decision tree analysis indicate that the colour flag chosen by the lifeguards was different from what the model predicted for 35 % of days between 2004 and 2008 (n=396/1125). Days when there is a difference between the predicted and posted flag colour represent only 17 % of all rescue days, but those days are associated with ∼60 % of all rescues between 2004 and 2008. Further analysis reveals that the largest number of rescue days and total number of rescues are associated with days where the flag deployed over-estimated the surf and hazard risk, such as a red or yellow flag flying when the model predicted a green flag would be more appropriate based on the wind and wave forcing alone. While it is possible that the lifeguards were overly cautious, it is argued that they most likely identified a rip forced by a transverse-bar and rip morphology common at the study site. Regardless, the results suggest that beach users may be discounting lifeguard warnings if the flag colour is not consistent with how they perceive the surf hazard or the regional forecast. Results suggest that machine learning techniques have the potential to support lifeguards and thereby reduce the number of rescues and drownings.
    Print ISSN: 1561-8633
    Electronic ISSN: 1684-9981
    Topics: Geography , Geosciences
    Published by Copernicus on behalf of European Geosciences Union.
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  • 2
  • 3
    Publication Date: 2019-06-18
    Description: Rips currents and other surf hazards are an emerging public health issue globally. Lifeguards, warning flags and signs are important and to varying degrees they are effective strategies to minimize risk. In the United States and other jurisdictions around the world, lifeguards use coloured flags (green, yellow and red) to indicate whether the danger posed by the surf and rip hazard is low, moderate, or high respectively. The choice of flag depends on the lifeguard monitoring the changing surf conditions along the beach and over the course of the day using both regional surf forecasts and careful observation. There is a potential that the chosen flag does not accurately reflect the potential risk, which may increase the potential for rescues or drownings. In this study, machine learning used to determine the potential for error in the flags used at Pensacola Beach, and the impact of that error on the number of rescues. A decision tree analysis suggests that the wrong flag was flown on ~ 35 % of days between 2004 and 2008 (n = 396/1125), and that those differences account for only 17 % of all rescue days and ~ 60 % of the total number of rescues. Further analysis reveals that the largest number of rescue days and total number of rescues is associated with days where the flag deployed over-estimated the surf and hazard risk, such as a red or yellow flag flying when the model would suggest a green flag would be more appropriate based on the wind and wave forcing. Regardless whether this is a result of the lifeguards being overly cautious or the rip and surf hazard is associated with weak rips forced by a transverse-bar and rip morphology, the results suggest that beach users are discounting the lifeguard warnings if it isn't consistent with how they perceive the surf hazard. Results suggest that machine learning techniques have the potential to support lifeguard and thereby reduce the number of rescues and drownings.
    Electronic ISSN: 2195-9269
    Topics: Geography , Geosciences
    Published by Copernicus on behalf of European Geosciences Union.
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  • 4
    Publication Date: 2019-07-01
    Print ISSN: 0921-030X
    Electronic ISSN: 1573-0840
    Topics: Energy, Environment Protection, Nuclear Power Engineering , Geography , Geosciences
    Published by Springer
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  • 5
    Publication Date: 2018-02-01
    Print ISSN: 0169-555X
    Electronic ISSN: 1872-695X
    Topics: Geography , Geosciences
    Published by Elsevier
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  • 6
    Publication Date: 2015-04-01
    Print ISSN: 0169-555X
    Electronic ISSN: 1872-695X
    Topics: Geography , Geosciences
    Published by Elsevier
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  • 7
    Publication Date: 2017-11-01
    Print ISSN: 0169-555X
    Electronic ISSN: 1872-695X
    Topics: Geography , Geosciences
    Published by Elsevier
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  • 8
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    Springer
    In:  In: Barrier Dynamics and Response to Changing Climate. , ed. by Moore, L. and Murray, A. Springer, Cham, pp. 175-207.
    Publication Date: 2018-01-22
    Description: The height, volume, and alongshore extent of the foredune are primary controls on the response of barrier islands to the elevated storm surge that accompanies hurricanes and extra-tropical storms. In this respect, the ability of the foredune to recover following a storm determines whether a barrier island can maintain elevation as sea level rises and the island migrates landward through the redistribution of sediment to the back of the island through washover and breaching. This chapter provides a review of a body of recent fieldwork on the role of the foredune in controlling island transgression. It is argued that the role of the foredune to control washover and island transgression is analogous to that of a variable resistor in an electrical circuit, with the strength of the resistor dependent on the ability of the dune to recover in height and extent following each storm. Recovery of the foredune requires that sediment removed to the nearshore during a storm be returned to the beachface through the landward migration and welding of the innermost bars where it is eventually transported to the backshore and trapped by vegetation. Field observations from Padre Island in Texas, Santa Rosa Island in Florida, and Assateague Island in Virginia suggest that the recovery of dune height can be modeled using a sigmoidal growth curve, and that recovery can take up to a decade. The slow rate of dune recovery suggests that the resiliency of barrier islands to sea level rise is dependent on whether there is a change in the frequency and magnitude of storm events or an interruption to the exchange of sediment among the nearshore, beach, and dune. Ultimately, the height and volume of the foredune can be controlled by the framework geology (to varying degrees), which determines beach and nearshore state through the availability and texture of sediment and structural controls. In this respect, the response of barrier islands to sea level rise can be expected to vary regionally and alongshore as a reflection of diverse framework geology. The local response to sea level rise depends on the ability of the dune to recover following storms. Assuming no new sediment from alongshore or offshore sources, an increase in the frequency of washover will limit the ability of the dune to recover, and recent field evidence suggests that a change in dune height and volume is self-reinforcing, which suggests a lack of island resiliency. Further testing is required to determine how the field observations and modeling described in this chapter from a select group of barrier islands around the United States are applicable to other islands and consistent throughout the evolution of a barrier island.
    Type: Book chapter , NonPeerReviewed
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  • 9
    Publication Date: 2021-02-08
    Description: The impact of storm surge on a barrier island tends to be considered from a single cross-shore dimension, dependent on the relative elevations of the storm surge and dune crest. However, the foredune is rarely uniform and can exhibit considerable variation in height and width at a range of length scales. In this study, LiDAR data from barrier islands in Texas and Florida are used to explore how shoreline position and dune morphology vary alongshore, and to determine how this variability is altered or reinforced by storms and post-storm recovery. Wavelet analysis reveals that a power law can approximate historical shoreline change across all scales, but that stormscale shoreline change (~10 years) and dune height exhibit similar scale-dependent variations at swash and surf zone scales (〈1000 m). The in-phase nature of the relationship between dune height and storm-scale shoreline change indicates that areas of greater storm-scale shoreline retreat are associated with areas of smaller dunes. It is argued that the decoupling of storm-scale and historical shoreline change at swash and surf zone scales is also associated with the alongshore redistribution of sediment and the tendency of shorelines to evolve to a more diffusive (or straight) pattern with time. The wavelet analysis of the data for post-storm dune recovery is also characterized by red noise at the smallest scales characteristic of diffusive systems, suggesting that it is possible that small-scale variations in dune height can be repaired through alongshore recovery and expansion if there is sufficient time between storms. However, the time required for dune recovery exceeds the time between storms capable of eroding and overwashing the dune. Correlation between historical shoreline retreat and the variance of the dune at swash and surf zone scales suggests that the persistence of the dune is an important control on transgression through island migration or shoreline retreat with relative sea-level rise.
    Type: Article , PeerReviewed
    Format: text
    Format: text
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  • 10
    Publication Date: 2019-02-01
    Description: Electromagnetic induction (EMI) techniques are becoming increasingly popular for near-surface coastal geophysical applications. However, few studies have explored the capabilities and limitations of portable multifrequency EMI profilers for mapping large-scale (101–102 km) barrier island hydrogeology. The purpose of this study is to investigate the influence of groundwater dynamics on apparent conductivity σa to separate the effects of hydrology and geology from the σa signal. Shore-normal and alongshore surveys were performed within a highly conductive barrier island/wind-tidal flat system at Padre Island National Seashore, Texas, USA. Assessments of instrument calibration and signal drift suggest that σa measurements are stable, but vary with height and location across the beach. Repeatability tests confirm σa values using different boom orientations collected during the same day are reproducible. Measurements over a 12 h tidal cycle suggest that there is a tide-dependent step response in σa, complicating data processing and interpretation. Shore-normal surveys across the barrier/wind-tidal flats show that σa is roughly negatively correlated with topography and these relationships can be used for characterizing different coastal habitats. For all surveys, σa increases with decreasing frequency. Alongshore surveys performed during different seasons and beach states reveal a high degree of variability in σa. Here, it is argued that surveys collected during dry conditions characterize the underlying framework geology, whereas these features are somewhat masked during wet conditions. Differences in EMI signals should be viewed in a relative sense rather than as absolute magnitudes. Small-scale heterogeneities are related to changing hydrology, whereas low-frequency signals at the broadest scales reveal variations in framework geology. Multiple surveys should be done at different times of the year and tidal states before geologic interpretations can confidently be made from EMI surveys in coastal environments. This strategy enables the geophysicist to separate the effects of hydrology and geology from the σa signal.
    Type: Article , PeerReviewed
    Format: text
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