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Earth Surface Dynamics An interactive open-access journal of the European Geosciences Union
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Volume 6, issue 2 | Copyright
Earth Surf. Dynam., 6, 431-450, 2018
https://doi.org/10.5194/esurf-6-431-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 01 Jun 2018

Research article | 01 Jun 2018

Statistical modeling of the long-range-dependent structure of barrier island framework geology and surface geomorphology

Bradley A. Weymer1,a, Phillipe Wernette2, Mark E. Everett1, and Chris Houser3 Bradley A. Weymer et al.
  • 1Department of Geology and Geophysics, Texas A&M University, College Station, Texas 77843, USA
  • 2Department of Geography, Texas A&M University, College Station, Texas 77843, USA
  • 3Department of Earth and Environmental Sciences, University of Windsor, Windsor, Ontario N9B 3P4, Canada
  • anow at: GEOMAR – Helmholtz Center for Ocean Research Kiel, Wischhofstraße 1–3, 24148 Kiel, Germany

Abstract. Shorelines exhibit long-range dependence (LRD) and have been shown in some environments to be described in the wave number domain by a power-law characteristic of scale independence. Recent evidence suggests that the geomorphology of barrier islands can, however, exhibit scale dependence as a result of systematic variations in the underlying framework geology. The LRD of framework geology, which influences island geomorphology and its response to storms and sea level rise, has not been previously examined. Electromagnetic induction (EMI) surveys conducted along Padre Island National Seashore (PAIS), Texas, United States, reveal that the EMI apparent conductivity (σa) signal and, by inference, the framework geology exhibits LRD at scales of up to 101 to 102km. Our study demonstrates the utility of describing EMI σa and lidar spatial series by a fractional autoregressive integrated moving average (ARIMA) process that specifically models LRD. This method offers a robust and compact way of quantifying the geological variations along a barrier island shoreline using three statistical parameters (p, d, q). We discuss how ARIMA models that use a single parameter d provide a quantitative measure for determining free and forced barrier island evolutionary behavior across different scales. Statistical analyses at regional, intermediate, and local scales suggest that the geologic framework within an area of paleo-channels exhibits a first-order control on dune height. The exchange of sediment amongst nearshore, beach, and dune in areas outside this region are scale independent, implying that barrier islands like PAIS exhibit a combination of free and forced behaviors that affect the response of the island to sea level rise.

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This research presents a new method for quantifying the geologic controls on modern barrier island evolution. We used statistical time series analysis to evaluate the scale-dependent vs. scale-independent behavior of a barrier island in southern Texas, USA. By integrating subsurface geophysical with surface geomorphological measurements, we show that the island exhibits both free and forced evolutionary behavior that has important implications for how the island may respond to rising sea levels.
This research presents a new method for quantifying the geologic controls on modern barrier...
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