| Dates | 2009-10-01 to 2022-09-30 |
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| Description | The long-term objectives of this effort are to provide an improved capability to predict coastal vulnerability to hazards associated with sea level rise. We expect to improve fundamental understanding of the sensitivity of sediment transport, ecosystem dynamics, and hydrology to SLR understanding of the interactions between these processes and the sensitivity of those interactions to SLR observation-based assessments of actual SLR related coastal vulnerabilities models that incorporate fundamental understanding and observations and to make accurate predictions applied decision support tools based on existing and improved understanding of the coastal vulnerability to SLR.An existing framework for this problem has been developed using a Bayesian network approach to characterize the correlations between physical settings and processes involved in coastal response to SLR. This framework has been developed using several large data sets spanning a wide range of environments. It has not be evaluated against independent data sets (nor even rigorously tested against a hindcast). Broader testing and understanding of its abilities (and shortcomings) is required.Near-term objectives are to Evaluate the capability of the existing decision support modeling framework against available data sets. Identify knowledge gaps that can be filled with a focused research effort and identify study sites that would support this effort Apply the existing capability to suitable trial coastal management problems where forecasts of vulnerability to SLR are critical to making management decisions. Develop a strategy for expanding the effort on a national scale.The research focus is expected to provide response to specific questions, such as: What locations will experience a simple inundation in response to SLR, and what locations will have a more complex response? What processes will be most important, and what is our ability to parameterize those processes in order to provide a useful assessment of potential outcomes? What is the ability of coastal wetlands to keep pace with future SLR? What is the spatial variability of this response, and what impact will changes in wetland extent have on geologic and hydrologic systems? What are the potential effects of SLR on the depth to ground water and the position of the freshwater/saltwater interface in coastal aquifers? Which aquifers may be most affected? What are the sources of uncertainty in SLR vulnerability assessments? What aspects of our fundamental understanding of SLR impacts, if improved, would contribute most to our assessment uncertainty? |
| Keywords | Bayesian networks, sea-level rise, coastal erosion, decision support, coastal ecosystems, wetlands, barrier islands, coastal aquifers, beach erosion |
| Status | Active |
| Center | USGS, Woods Hole Coastal and Marine Science Center |
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