Model Library

Finite-Volume Community Ocean Model (FVCOM)

Model name: Finite-Volume Community Ocean Model (FVCOM)

Developed by: University of Massachusetts-Dartmouth (UMASS-D) and Woods Hole Oceanographic Institution (WHOI) joint team (Last update: 2023)

Model type: Prognostic, unstructured-grid, finite-volume, free-surface, 3-D primitive equation coastal ocean circulation model
Computational requirements: Linux (recommended), 2-3 cores (recommended); Compilers (required): GFortran, GCC

Software requirements: GIS: optional

Link to download model

Capabilities and Limitations:

Capabilities

  • It has a modular design;
  • The current FVCOM-WRF coupled system includes wave-current interaction and supports hydrostatic or non-hydrostatic conditions. The code is available in FVCOM.
  • It has 4-D nudging and Reduced/Ensemble Kalman Filters for data assimilation.
  • It uses an irregular grid for high-resolution modeling in areas of interest, efficiently handling complex shapes (e.g., coastlines) while minimizing computational costs.
  • It includes non-hydrostatic solvers, ice and surface wave modules, biological and 3 water quality models, a fishery larval life cycle simulator, and a vegetation module accounting for vegetation effects on currents, waves, and sediment.

Limitations

  • Fluid particle trajectories are highly sensitive to local flows (Qu et al., 2016).
  • FVCOM struggles with small-scale local flows, such as those through seamount holes (Qu et al., 2016).
  • Limited resolution and simplifying assumptions reduce its accuracy (Premathilake and Khangaonkar, 2019).
  • FVCOM (version 3.1.6) has flaws in parameterizations, inertial instability, and diffusive behavior, with small stepwise errors accumulating into significant long-term drifts, impacting seasonal, decadal, and climate projections (Wang et al., 2023).
  • This model is restricted to non-commercial purposes only.

Model Inputs and Outputs:

Inputs

Bathymetry data, Grid configuration, Time Configuration, Initial conditions, Boundary conditions, Atmospheric forcing, River discharge, Surface wave data (optional), Water quality data

Outputs

  • Simulation results of sea surface elevation, 3D currents, temperature, salinity, tidal and wave parameters, sediment transport, morpho dynamics, water quality parameters (e.g., dissolved oxygen, nutrients), ecosystem dynamics (e.g., plankton biomass), and fishery larval models.
  • It also models the turbulence metrics, fluxes (heat, freshwater), ice properties, vegetation effects on currents and waves, and user-defined variables, with all data typically stored in NetCDF format.

Examples:

References

Luo, F., Gou, H., Li, R., Wang, H., Chen, Z., Lin, W., & Li, K. (2021). Numerical simulation on marine environmental capacity in the open sea area of Northern Jiangsu Province using a three-dimensional water quality model based on FVCOM. Regional Studies in Marine Science, 45, 101856. https://doi.org/10.1016/j.rsma.2021.101856

Lyu, H., Song, D., Zhang, S., Wu, W., & Bao, X. (2022). Compound effect of land reclamation and land-based pollutant input on water quality in Qinzhou Bay, China. Science of The Total Environment, 826, 154183. https://doi.org/10.1016/j.scitotenv.2022.154183

Objectives

The objectives of the study are to establish a 3D hydrodynamic-water quality coupling model to calculate and evaluate the marine environmental capacity (MEC) and pollutant carrying capacity in the sea area from Dongtai River to Dafeng River. The study aims to provide technical guidance for offshore aquaculture, form a scientific basis for controlling pollutant discharge into the sea, and support marine ecological restoration and sustainable resource utilization.

The objectives of the study are to explore and evaluate the compound effects of land reclamation and land-based pollutant input on water quality in Qinzhou Bay, China, quantify the contributions of each activity to water quality deterioration, improve coastal management, and develop guidelines for coastal environment restoration.