Skip to main content
U.S. flag

An official website of the United States government

Official websites use .gov
A .gov website belongs to an official government organization in the United States.

Secure .gov websites use HTTPS
A lock ( ) or https:// means you’ve safely connected to the .gov website. Share sensitive information only on official, secure websites.

Skip to content

Sea-level rise and high tide flooding inundation probability and depth statistics at Big Cypress National Preserve, Florida

Metadata Updated: August 8, 2024

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 Big Cypress National Preserve. 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 2050 and 2100 from Sweet and others (2022). Additionally, this data release includes maps of inundation probability under the minor, moderate, and major high tide flooding thresholds defined by the National Oceanic and Atmospheric Administration (NOAA). 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 sea-level rise estimate (Sweet and others, 2022) and tidal datum transformation, respectively. 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.

Access & Use Information

Public: This dataset is intended for public access and use. License: No license information was provided. If this work was prepared by an officer or employee of the United States government as part of that person's official duties it is considered a U.S. Government Work.

Downloads & Resources

Dates

Metadata Created Date April 2, 2024
Metadata Updated Date August 8, 2024

Metadata Source

Harvested from DOI EDI

Additional Metadata

Resource Type Dataset
Metadata Created Date April 2, 2024
Metadata Updated Date August 8, 2024
Publisher U.S. Geological Survey
Maintainer
@Id http://datainventory.doi.gov/id/dataset/3961e5e574091d2f5d1592c09935f12c
Identifier USGS:64fb33add34ed30c2055b04b
Data Last Modified 20240806
Category geospatial
Public Access Level public
Bureau Code 010:12
Metadata Context https://project-open-data.cio.gov/v1.1/schema/catalog.jsonld
Metadata Catalog ID https://datainventory.doi.gov/data.json
Schema Version https://project-open-data.cio.gov/v1.1/schema
Catalog Describedby https://project-open-data.cio.gov/v1.1/schema/catalog.json
Harvest Object Id df1e3b7e-b502-48dc-bc00-2a53529d3c10
Harvest Source Id 52bfcc16-6e15-478f-809a-b1bc76f1aeda
Harvest Source Title DOI EDI
Metadata Type geospatial
Old Spatial -82.0729,24.9424,-80.2081,26.908
Publisher Hierarchy White House > U.S. Department of the Interior > U.S. Geological Survey
Source Datajson Identifier True
Source Hash 2205de0f7b9b77213acd132b0e96dad9644dab898e7b1bf68a67e90cca41228b
Source Schema Version 1.1
Spatial {"type": "Polygon", "coordinates": -82.0729, 24.9424, -82.0729, 26.908, -80.2081, 26.908, -80.2081, 24.9424, -82.0729, 24.9424}

Didn't find what you're looking for? Suggest a dataset here.