FastFlood and the Use of Digital Elevation Models:

FastFlood is an advanced flood simulation tool that uses various global datasets, including high-quality Digital Elevation Models (DEMs). These models are essential for determining how water flows and accumulates in the terrain, as the landscape directly influences flood dynamics. The tool currently includes two global-scale digital elevation models:

- Copernicus 30m Digital Elevation Model (DEM), also known as Copernicus GLO-30 DEM.

- Shuttle Radar Topography Mission (SRTM) DEM.

In addition to these global models, FastFlood also uses two national-level elevation datasets:

- AHN DEM (Actueel Hoogtebestand Nederland) for the Netherlands.

- US National Elevation Dataset (USNED) for the United States.

These datasets are used within the system to calculate the topography of the areas being modeled and simulate how water would flow through them during a flood event.

The Copernicus 30m Digital Elevation Model (DEM), also known as Copernicus GLO-30 DEM, is a high-resolution global elevation dataset developed as part of the European Union’s Copernicus Programme and produced by the European Space Agency (ESA). This elevation model was released in 2020 and has a spatial resolution of 30 meters. It is considered one of the most accurate and detailed models available globally.

Main Features:

- Near-Global Coverage: The model covers nearly the entire planet, providing consistent, high-quality data.

- Improvements over Previous Models: Compared to the SRTM model, the Copernicus DEM offers significant improvements in accuracy, coverage, and the reduction of data voids and artifacts, making it ideal for flood simulations.

- Data Source: The elevation data is primarily derived from radar data collected by the TanDEM-X mission.

 

SRTM DEM (Shuttle Radar Topography Mission)

The SRTM DEM is a widely used global dataset in geospatial sciences. It was collected by the Space Shuttle Endeavour during an 11-day mission in February 2000 using radar instruments. The SRTM DEM offers near-global coverage, from latitudes 60°N to 56°S.

Main Features:

- Near-Global Coverage: The model covers a vast portion of the planet, from 60°N to 56°S.

- Resolution: The data is available with a resolution of 30 meters in areas of global coverage.

- Historical Database: SRTM was one of the first large efforts to obtain global elevation data and remains a valuable source for research worldwide.

The SRTM DEM is used in the FastFlood model to detail the terrain in many regions, particularly in areas where the Copernicus model is not yet implemented or unavailable. While Copernicus DEM is preferred for its higher quality, the SRTM DEM remains useful for areas requiring global elevation data.

The AHN DEM (Actueel Hoogtebestand Nederland) is a highly detailed elevation dataset for the Netherlands, obtained through LiDAR (Light Detection and Ranging) surveys, which provides exceptional accuracy.

Main Features:

- High Resolution: AHN provides elevation data with resolutions as fine as 0.5 meters, making it one of the most accurate elevation datasets available at the national level.

- Developed by Government Institutions: This dataset is managed by a consortium of Dutch governmental organizations.

The AHN DEM is used to model the terrain of the Netherlands with high precision, which is essential for performing detailed flood simulations in specific regions.

US National Elevation Dataset (USNED)

The USNED is a national-level elevation dataset for the United States, developed and maintained by the U.S. Geological Survey (USGS). This dataset integrates the best available elevation data from multiple sources and offers several resolution options ranging from 3m to 30m.

Main Features:

- Coverage of the United States: The model covers the entire territory of the United States.

- Variable Resolution: The data is available in resolutions ranging from 3m to 30m.

- Consolidated Database: It integrates data from multiple sources into a unified framework.

The system uses the 10m and 20m resolution versions of this dataset to simulate floods in the United States. These resolutions allow for adequate terrain modeling without overly taxing computational resources.

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