Welcome to RA2CE’s documentation!#

Resilience Assessment and Adaptation for Critical infrastructurE

Quantify network vulnerability, prioritize interventions, and support adaptation decisions. For transport infrastructure exposed to natural hazards and future climate conditions. Built by Deltares.

🚀 Get Started 📓 Browse tutorials ⭐ GitHub
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Assess hazard exposure
Overlay flood depths and other hazard maps onto networks to identify exposed segments across return periods.
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Quantify criticality
Identify critical links, measure redundancy, and compute detour costs under single- or multi-link failure scenarios.
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Estimate economic risk
Compute direct damages (EAD) and indirect economic losses (EAL), and compare adaptation strategies side-by-side.

About RA2CE#

RA2CE (just say “race”!) is an open-source Python package developed by Deltares for assessing the resilience of critical infrastructure networks under natural hazard conditions.

Given a network sourced from OpenStreetMap or a shapefile, and one or more hazard maps (e.g. flood depth rasters), RA2CE lets you:

  • Overlay hazard data onto network edges to identify exposed segments across multiple return periods.

  • Quantify criticality by measuring redundancy, computing detour lengths, and identifying links whose failure would most disrupt connectivity.

  • Estimate economic risk through direct damage functions (EAD) and indirect loss models (EAL).

  • Compare adaptation strategies side-by-side to support investment and policy decisions under present and future climate conditions.

The package is fully scriptable via Python and ships with a suite of Jupyter Notebook tutorials. It is available on PyPI and licensed under GPL-3.0.

Who uses RA2CE#

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Consultants
Run flood impact analyses and generate risk metrics for infrastructure projects. Plug RA2CE into your workflow without proprietary tooling or licensing costs.
Start with the tutorials →
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Researchers
Extend the methodology, integrate custom damage curves, and contribute back. Full API reference and modular architecture included alongside peer-reviewed publications.
Browse the API reference →
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Decision makers
Review real case studies with interpretable outputs before asking your team to adopt the tool. Understand what RA2CE produces and what data inputs it needs.
View showcases →

💡 New to RA2CE?

Start with the Getting Started guide, then work through the Tutorials to run your first analysis step-by-step using Jupyter Notebooks.

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