Training Workshop 2: Applying the SuPeRBE Tools for Local Risk Assessment

Date: 19.12.2025
By: SuPeRBE
The second SuPeRBE training workshop, jointly organised by the Munich University of Applied Sciences (MUAS) and the Municipality of Schnifis, brought together nearly thirty participants for an in-depth online session dedicated to climate risk assessment. The event focused on teaching professionals and students how to apply the SuPeRBE tools at both the small urban scale and the building scale.

A Focus on Practical Climate Adaptation

The online workshop guided participants through the SuPeRBE Decision Making Model and several key risk assessment modules, including:
•    Extreme heat impacts on buildings and population health
•    Heavy precipitation risks for individual buildings
•    Flood-related transport network vulnerabilities
•    Drought impacts on biodiversity and the environment

Through these modules, attendees learned how to gather relevant data, analyze hazards, and apply risk categories in real-world scenarios. The training strengthened their ability to plan, supervise, and evaluate effective climate adaptation measures.

Most participants were German residents, with additional attendees from Austria. The group consisted of students, professionals from external organizations, and public authorities. This diverse group ensured a productive learning environment enriched by both academic and professional perspectives.

Hands-On Application in Schnifis

In addition to the online content, MUAS students conducted an on-site Risk-Based Evaluation (RBE) exercise in Schnifis. Using the SuPeRBE RB and RN tools, they assessed two selected buildings and the surrounding neighbourhood to test the practical application of the methodology. This field activity provided valuable insight into how digital risk assessment tools translate into concrete local analysis.

Interactive Learning

The workshop format offered opportunities for active engagement, with participants discussing data needs, hazard assessment techniques, and multi-scalar decision-making. No specific improvements were suggested, indicating a smooth and well-structured training experience.