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Estimating Hydrological Connectivity in Coastal Wetlands using UAVSAR and Numerical Modeling
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  • Kyle Wright,
  • Paola Passalacqua,
  • Cathleen Jones,
  • Marc Simard,
  • Michael Lamb
Kyle Wright
University of Texas at Austin

Corresponding Author:[email protected]

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Paola Passalacqua
University of Texas at Austin
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Cathleen Jones
Jet Propulsion Laboratory
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Marc Simard
Jet Propulsion Laboratory
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Michael Lamb
California Institute of Technology
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Abstract

In response to a growing number of natural and anthropogenic threats, the long-term sustainability of coastal river deltas and wetlands has come into question worldwide. Tools such as remote sensing and numerical modeling have been implemented in an effort to monitor and predict the hydro-geomorphological evolution of our coasts. Hydrological connectivity is known to play an important role in deltaic evolution by delivering flow, sediment, and nutrients to the interior of deltaic islands/wetlands. However, estimating connectivity typically requires detailed field work or numerical modeling, which is difficult to implement over broad spatial and temporal scales. In the present work, we investigate the potential of using remote sensing to estimate hydrological connectivity in the Wax Lake Delta (WLD) and Atchafalaya Delta region of the Louisiana coast. During a three-hour window, five difference maps of water level in the WLD and surrounding wetlands were collected using UAVSAR L-band radar in repeat-pass interferometric mode. We then modeled the WLD subsection of the domain using a 2D shallow-water hydrodynamic model configured to run on the same discharge, tide, and wind conditions as recorded at nearby monitoring stations during the observational window, with vegetation parameterized as a source of additional drag in the deltaic islands. Modeling allowed us to determine the relative influence of tides, vegetation, and wind on WLD water levels, which could then be extrapolated to infer the behavior throughout the rest of the domain. Over the observational window, UAVSAR measured a cumulative loss of over 22 megatons of water from non-channelized wetlands as tides fell. We find that the model tends to under-predict the observed water level draw-down, as well as the degree of hydrological activity in proximal islands that we observe in the UAVSAR data. Models that neglect the influence of wind underestimate the volume of water leaving the islands by up to two-thirds, suggesting the importance of wind on deltaic hydrodynamics during the observational window. With the information gained from the numerical modeling, as well as the computation of information theory statistics, we extend the WLD results to analyze and quantify the water level behavior in the surrounding wetlands and Atchafalaya delta.