Free & open · v4.5.5

Download CE-QUAL-W2

Get the model executable, the complete source code, the manuals and worked examples. All official packages are distributed free of charge from Portland State University.

Official source. Always download from the Water Quality Research Group at Portland State University to be sure you have the current, unmodified release. Open the official model website ↗

Packages

Choose what you need

The full distribution bundles everything; individual components are listed for reference.

What's inside

What the distribution contains

A complete, self-contained modeling environment.

  • Model executable — the compiled CE-QUAL-W2 solver for Windows.
  • Fortran source code — the full source so you can inspect, audit and recompile.
  • User & theory manuals — PDF documentation of the model and its kinetics.
  • Example data sets — ready-to-run test cases that demonstrate setup and outputs.
  • Utilities — pre- and post-processing helpers and visualization tools.

System requirements

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    CE-QUAL-W2 is a native Windows application. macOS and Linux users typically run it through a virtual machine, compatibility layer, or by recompiling the source with a suitable Fortran compiler.

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    License & cost

    CE-QUAL-W2 is distributed free of charge; its source code is released under the MIT License. Because it was originally developed with public funding, the model and its source are openly available. Please review the license terms included with the distribution and cite the model appropriately in your work.

    How to cite →

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    Verify your download

    Model results can inform high-stakes decisions, so treat your toolchain with care:

    • Download only from the official PSU site.
    • Keep a record of the exact version used for each project.
    • Re-run a known example to confirm a clean install.
    Companion tools

    Pre- and post-processing utilities

    Build inputs faster and turn raw output into figures and animations.

    New to the model? Start with an example.

    Open a worked data set, run it, and compare your output against the bundled results before building your own grid.