How can we move from traditional hazard forecasts toward impact-based, user-oriented predictions that truly enable early and effective action?
The EGU General Assembly 2026 will address this in the session HS4.5 – “Impact-based forecasting, early warning and early action to reduce disaster risk.”
The conveners invite abstracts related to:
- new modelling approaches for impact-based forecasting (AI-driven, physics-based or hybrid)
- innovative early warning systems and early action strategies
- interdisciplinary work on risk perception and communication
- last-mile challenges in disaster risk management
Submit your abstract here.
Researchers and practitioners working across all relevant fields are warmly invited to contribute.
(image source: AI-generated)