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Arctic shorelines are vulnerable to climate change impacts as sea level rises, permafrost thaws, storms intensify, and sea ice thins. Seventy-five years of aerial and satellite observations have established coastal erosion as an increasing Arctic hazard. However, other hazards at play—for instance, the cumulative impact that sea-level rise and permafrost thaw subsidence will have on permafrost shorelines—have received less attention, preventing assessments of these processes’ impacts compared to and combined with coastal erosion. Alaska’s Arctic Coastal Plain (ACP) is ideal for such assessments because of the high-density observations of topography, coastal retreat rates, and permafrost characteristics, and importance to Indigenous communities and oilfield infrastructure. Here, we produce 21st-century projections of Arctic shoreline position that include erosion, permafrost subsidence, and sea-level rise. Focusing on the ACP, we merge 5 m topography, satellite-derived coastal lake depth estimates, and empirical assessments of land subsidence due to permafrost thaw with projections of coastal erosion and sea-level rise for medium and high emissions scenarios from the Intergovernmental Panel on Climate Change’s AR6 Report. We find that by 2100, erosion and inundation will together transform the ACP, leading to 6-8x more land loss than coastal erosion alone and disturbing 8-11x more organic carbon. Without mitigating measures, by 2100, coastal change could damage 40 to 65% of infrastructure in present-day ACP coastal villages and 10 to 20% of oilfield infrastructure. Our findings highlight the risks that compounding climate hazards pose to coastal communities and underscore the need for adaptive planning for Arctic coastlines in the 21st century.
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Using an urban growth model framework to project the impacts of climate change on coastal populations
Coastal populations are facing increasing environmental stress from coastal hazards including sea level rise, increasing tidal ranges, and storm surges from hurricanes. The East and Gulf Coasts of the United States (U.S.) are projected to face high rates of sea level rise and include many of the U.S.’s largest urban populations. This study proposes modelling land-use change and coastal change between 1996-2019 to project the impacts of intensifying coastal hazards on the U.S. Gulf and East Coast populations and to estimate how coastal populations are growing or retreating from high-risk areas. The primary objective is to develop a multifaceted spatial-temporal (MuST) framework to model coastal change through land-use projections and thorough analysis of the indicators of coastal urban growth or retreat. While urban growth models exist, one that presents an interdisciplinary evaluation of potential growth and retreat due to geographic factors and coastal hazards has not been released. This study proposes modelling urban growth using geospatial metrics including topographic slope, topographic elevation, distance to existing urban areas, distance to existing roads, and distance to the coast. The model will also use historic hurricane data, including storm track and footprint for named storms between 1996-2019 and the associated flood claims data from Federal Emergency Management Agency (FEMA), to account for existing impacts from coastal storms. Additionally, climate change data including sea level rise projections and future tidal ranges will be incorporated to project the impacts of future coastal hazards on urban expansion over the next 30 years (2020-2050). The basis of the urban growth model compares land-use change between 1996-2019 to complete a geospatial analysis of both the areas shifting from rural (agricultural, forest, wetlands) to urban, indicating growth and population data from 2000-2020, to evaluate coastal retreat or abandonment over the next 30 years.
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- PAR ID:
- 10415706
- Date Published:
- Journal Name:
- 2023 World Environmental & Water Resources Congress
- Page Range / eLocation ID:
- 1-8
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.1061/9780784484852.039
