Model Library

Delft3D Flexible Mesh Suite (Delft3D FM)

Model name: Delft3D Flexible Mesh Suite (Delft3D FM)

Developed by: Deltares (Last update: 2024)

Model type: 1D/2D/3D distributed, deterministic, process-based hydrodynamic, water quality, and morphodynamic, waterbody model

History: Delft3D FM is the successor of Delft3D 4 Suite

Computational requirements: Windows 10 64bits or Alma Linux 8 and computational core only, Single Core 1.0 GHz - Intel i7Quad Core > 2 GHz, Minimum 1-4 GB of RAM depending on model sizes, 1-100 GB of free storage, minimum 1024x768 and recommended 1920 x 1080 of screen resolution, 4k Monitor is not supported;

Software requirements: Microsoft .NET Framework 4.8 or later.

Link to download model: Upon request

Capabilities and Limitations:

Capabilities

  • Delft3D FM has D-Hydrology module that integrates watershed processes with downstream waterbody dynamics;
  • It features one of the most user-friendly GUI in the market;
  • It is a robust and advanced computational model with multiple modules and tools (Muñoz et al., 2021);
  • It supports both triangulation and averaging methods for generating roughness maps (Muñoz et al., 2021);
  • It uses unstructured grids (Deltares, n.d.);
  • It can simulate extreme storm impacts, including hurricane-induced storm surges over short time scales (Zhu et al., 2023);
  • It allows variable resolutions within one model domain to optimize computational efficiency (Symonds et al., 2016);
  • It is 6 to 10 times faster than 2D HEC-RAS (Muñoz et al., 2021).
  • It is constantly supported by the developers.

Limitations 

  • Open-source code upon request, excluding GUI;
  • It requires high computational resources (Muñoz et al., 2021);
  • It relies on historical storm records, which may limit comprehensive analysis (Zhu et al., 2023).

Model Inputs and Outputs: 

Inputs

Computational grids, Bathymetry data, Topography data, Boundary conditions, Initial conditions, Meteorological data, Hydrological data, Water quality data.

Outputs

It simulates hydrodynamics, salinity, temperature and sediment dynamics, phytoplankton and water-quality coupling infrastructure, and linkage to a habitat suitability model, wave module, and sediment transport module.

Examples:

References

Lee, W., Sun, A. Y., Scanlon, B. R., et al. 
(2024). Hindcasting compound pluvial, fluvial, and coastal flooding during Hurricane Harvey (2017) using Delft3D-FM. Natural Hazards, 120, 851–880. 
https://doi.org/10.1007/s11069-023-06247-9

Dang, T. D., Arias, M. E., Tarabih, O., Phlips, E. J., Ergas, S. J., Rains, M. C., & Zhang, Q. (2023). Modeling temporal and spatial variations of biogeochemical processes in a large subtropical lake: Assessing alternative solutions to algal blooms in Lake Okeechobee, Florida. Journal of Hydrology: Regional Studies, 47, 101441. https://doi.org/10.1016/j.ejrh.2023.101441

Objectives

The objective of this study was to better quantify the impacts of compound flooding and to assess the relative contributions of storm surge, pluvial (rainfall) and fluvial (riverine) flooding using Hurricane Harvey as a case study.

This study aimed to answer the following questions: (1) What are the main factors causing ABs in Lake Okeechobee? (2) How much of a reduction in nutrient imports and/or legacy sediments is needed to reduce the occurrence of ABs? (3) What magnitude of nutrient input reduction would be required to reduce ABs?