Department of Sociology, Florida State University, Tallahassee, FL, 32306, USA.
Center for Demography and Population Health, Florida State University, Tallahassee, FL, 32306, USA.
Nat Commun. 2021 Nov 25;12(1):6900. doi: 10.1038/s41467-021-27260-1.
The exposure of populations to sea-level rise (SLR) is a leading indicator assessing the impact of future climate change on coastal regions. SLR exposes coastal populations to a spectrum of impacts with broad spatial and temporal heterogeneity, but exposure assessments often narrowly define the spatial zone of flooding. Here we show how choice of zone results in differential exposure estimates across space and time. Further, we apply a spatio-temporal flood-modeling approach that integrates across these spatial zones to assess the annual probability of population exposure. We apply our model to the coastal United States to demonstrate a more robust assessment of population exposure to flooding from SLR in any given year. Our results suggest that more explicit decisions regarding spatial zone (and associated temporal implication) will improve adaptation planning and policies by indicating the relative chance and magnitude of coastal populations to be affected by future SLR.
人口暴露于海平面上升（SLR）是评估未来气候变化对沿海地区影响的主要指标。SLR 使沿海人口面临广泛的空间和时间异质性的影响，但暴露评估通常狭义地定义了洪水泛滥的空间范围。在这里，我们展示了选择区域如何导致空间和时间上的差异暴露估计。此外，我们应用一种时空洪水建模方法，将这些空间区域整合在一起，以评估人口暴露的年概率。我们将我们的模型应用于美国沿海地区，以展示对任何给定年份由于 SLR 导致的人口洪水暴露的更稳健评估。我们的研究结果表明，更明确地决策关于空间区域（以及相关的时间影响）将通过指示沿海人口受未来 SLR 影响的相对机会和规模来改善适应规划和政策。
