# Case Studies

This section translates the ARCADIA methodological framework into **operational practice**. It collects the **Climate Risk Assessment (CRA) workflows** co-designed and technically validated within the Regional Innovation Labs.

Unlike static case studies, these tutorials are structured as **replicable technical workflows**. They demonstrate how to apply the Hazard–Exposure–Vulnerability logic to specific regional challenges (e.g., landslides, urban heat, flooding) and, crucially, how to quantify the performance of **Nature-based Solutions (NbS)** by comparing a *Baseline Scenario* against an *Adaptation Scenario*.

## Tutorial Structure

To ensure consistency and transferability, each tutorial follows the harmonised **4-step methodology** defined in the [Risk Assessment Methodology](/cra_toolbox_2026/ctb-riskassessmentmethodology-risk-assessment-methodology.md) section:

> • **Context & Objectives:** Definition of the hazard, the affected sector, and the specific NbS/BGI intervention being tested.
>
> • **Step 1 – Data Acquisition:** Identification of minimum required datasets (local high-resolution vs. EU open data) and pre-processing steps.
>
> • **Step 2 – Model Setup:** Configuration of the specific tools (from GIS-based screening to physical models like SWAT+ or CRITERIA-3D).
>
> • **Step 3 – Analysis:** Characterisation of the current risk and baseline indicators.
>
> • **Step 4 – NbS Scenario Testing:** Implementation of the NbS in the model and comparison of results (performance indicators).

## A Living Resource

The tutorials listed below represent the workflows currently validated by the Innovation Labs. As the project progresses, new tutorials and updates will be added to reflect additional hazards, refined datasets, and lessons learned from the Fellow Regions.


---

# Agent Instructions: Querying This Documentation

If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://arcadia-15.gitbook.io/cra_toolbox_2026/ctb-casestudies-readme-arcadia-regions-guidelines-tutorials.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.