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Evaluation of dynamic coastal response to sea-level rise modifies inundation likelihood
- Source :
- Nature Climate Change. 6:696-700
- Publication Year :
- 2016
- Publisher :
- Springer Science and Business Media LLC, 2016.
-
Abstract
- A model that evaluates the likelihood of coastal inundation (flooding) and dynamical response (adaptation) as sea levels rise shows that, for the northeastern US, about 70% of the coast has some capacity to respond dynamically and alter inundation risk. Sea-level rise (SLR) poses a range of threats to natural and built environments1,2, making assessments of SLR-induced hazards essential for informed decision making3. We develop a probabilistic model that evaluates the likelihood that an area will inundate (flood) or dynamically respond (adapt) to SLR. The broad-area applicability of the approach is demonstrated by producing 30 × 30 m resolution predictions for more than 38,000 km2 of diverse coastal landscape in the northeastern United States. Probabilistic SLR projections, coastal elevation and vertical land movement are used to estimate likely future inundation levels. Then, conditioned on future inundation levels and the current land-cover type, we evaluate the likelihood of dynamic response versus inundation. We find that nearly 70% of this coastal landscape has some capacity to respond dynamically to SLR, and we show that inundation models over-predict land likely to submerge. This approach is well suited to guiding coastal resource management decisions that weigh future SLR impacts and uncertainty against ecological targets and economic constraints.
- Subjects :
- 010504 meteorology & atmospheric sciences
Flood myth
business.industry
Flooding (psychology)
Environmental resource management
Probabilistic logic
Elevation
Climate change
Terrain
010501 environmental sciences
Environmental Science (miscellaneous)
01 natural sciences
Climatology
Environmental science
Resource management
business
Social Sciences (miscellaneous)
Sea level
0105 earth and related environmental sciences
Subjects
Details
- ISSN :
- 17586798 and 1758678X
- Volume :
- 6
- Database :
- OpenAIRE
- Journal :
- Nature Climate Change
- Accession number :
- edsair.doi...........e984e4e2c016b07756a2688f219464c1