Lentz, E.E., Thieler, E.R., Plant, N.G., Stippa, S.R., Horton, R.M., and Gesch, D.B., 2016, Evaluation of dynamic coastal response to sea-level rise modifies inundation likelihood, Nature Climate Change 6, 696-700, doi: 10.1038/nclimate2957
Predicting how coastal communities will be impacted by sea level rise is not an easy task. A simple strategy for assessing future risk is through inundation modeling. Inundation in sea level studies is the flooding of dry land by the ocean. This type of modeling drapes a future sea level over the existing dry land to determine which areas will become submerged. There are many problems with using this approach, including the uncertainties associated with sea level projections. Additionally, not all coastal landscapes respond in the same way to sea level rise. For example, a rocky shoreline with little to no sediment is more prone to becoming inundated, whereas sandy beaches and marshes can reposition or grow in elevation by the rearrangement of sediment, vegetation and through human mitigation. With sea level projected to rise even with the most drastic reductions in greenhouse gas emissions, it is past due for coastal municipalities to begin planning for future challenges. Imperative to making informed decisions are coastal inundation models that incorporate both inundation and dynamic response of coastal landscapes and the probabilities and uncertainties associated with sea level rise. Erika Lentz, a research geologist at the Unitied States Geological Survey (USGS), and her team, did just this for the densely populated and ecologically diverse northeast United States (from Maine to Virginia).
The Coastal Response Model relies on a Bayesian network, powerful mathematics and statistics that are particularly good at handling the uncertainties associated with sea level rise and landscape response. For the model to have predictive power, the research team needed to establish projections of future sea level rise for the northeast United States. Sea level projections (Figure 1) were constructed by using global sea level rise projections from the latest Intergovernmental Panel on Climate Change Assessment Report (IPCC AR5, 2014), along with regional land movement rates and tide gauge records to develop sea level projections that are more specific to the northeast U.S. These sea level rise projections were separated into future decades, that is, the amount of sea level rise likely to occur by the 2020s, 2030s, 2050s and 2080s. Existing high-resolution digital elevation models (topographic / bathymetric maps) were categorized by land-cover (e.g. beach, rocky, marsh etc.).
A key finding of this study is the disagreement between the Coastal Response Model and simplistic inundation models. In predictions for the year 2020, the inundation model vastly overestimates the amount of inundation in dynamic locations of the northeast U.S., as it fails to consider that the majority of this landscape will respond dynamically.
The Coastal Response Model describes how soon and how likely different areas are to inundate based on predominant land-cover (Figure 2). At the high tide line, developed areas are likely to inundate as soon as 2020. Developed coastal areas that are only several feet above sea level are likely to inundate as soon as 2050. Marshes and forested areas at the same elevation fair slightly better, and do not inundate until 2080. Rocky areas are the most likely to inundate immediately as sea level rises, whereas beaches are very likely to respond dynamically to sea level rise.
The Coastal Response Model truly shines in its ability to inform management strategies for future sea level rise. It is particularly useful in its potential for application to many different regions around the world. Additionally, where probabilities of inundation are low in confidence, more research can be directed to improve predictions. Sea level rise poses a very large challenge to coastal communities; this study provides important tools to decision makers to better inform how likely and how soon different coastal landscapes will inundate so that resources can be more efficiently and intelligently allocated.