Signals without action: a value chain analysis of Luxembourg's 2021 flood disaster

This study uses a value chain approach to examine how forecast information, institutional responsibilities, and communication processes interacted during the July 2021 floods in Luxembourg. Using a structured database questionnaire alongside hydrometeorological data, official documentation, and public communications, the analysis identifies points where early signals did not lead to anticipatory action.

The findings show that warning performance was shaped less by technical limitations than by procedural thresholds, institutional fragmentation and timing mismatches across the chain. A new conceptual model, the Waterdrop Model, is introduced to show how forecast signals can be filtered or delayed within systems not designed to process uncertainty collectively. The results demonstrate that forecasting capacity alone is insufficient. Effective early warning depends on integrated procedures, shared interpretation, and governance arrangements that support timely response under uncertainty.