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Sea-level rise and high tide flooding inundation probability and depth statistics at Biscayne National Park, Florida

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DataCite Commons2024-09-03 更新2026-05-07 收录
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https://www.sciencebase.gov/catalog/item/64fb3180d34ed30c2055b036
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This dataset includes elevation-based probability and depth statistics for estimating inundation under various sea-level rise and high tide flooding scenarios in and around the National Park Service’s Biscayne National Park. For information on the digital elevation model (DEM) source used to develop these datasets refer to the corresponding spatial metadata file (Danielson and others, 2023). This data release includes results from analyses of two local sea-level rise scenarios for two-time steps — the Intermediate-Low and Intermediate-High for 2040 and 2080 from Sweet and others (2022). Additionally, this data release includes maps of inundation probability under the minor, moderate, and major hight tide flooding thresholds. We estimated the probability of an area being inundated under a given scenario using Monte Carlo simulations with 1,000 iterations. For an individual iteration, each pixel of the DEM was randomly propagated based on the lidar data uncertainty, while the sea-level rise and high tide flooding water level estimates were also propagated based on uncertainty in the estimate (Sweet and others, 2022) and tidal datum transformation. Moreover, the probability of a pixel being inundated was calculated by summing the binary simulation outputs and dividing by 1,000. Following, probability was binned into the following classes: 1) Unlikely, probability ≤0.33; 2) Likely as not, probability >0.33 and ≤0.66; and 3) Likely, probability >0.66. Finally, depth statistics were only recorded when depth was equal to or greater than 0. We calculated the median depth, 25th percentile, 75th percentile, and interquartile range using all the pixels that met this criterion. When utilizing the depth statistics, it is important to also consider the probability of this pixel being flooded. In other words, the depth layers may show some depth returns, but the pixel may have rarely been inundated for the 1,000 iterations.
提供机构:
U.S. Geological Survey
创建时间:
2024-01-05
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