An Integrated Decision Support Framework for Multi-Phase Flood Event Management

Effective flood event management requires coordinated decision-making across preparedness, response, and recovery. Current decision support systems (DSS) handle these phases separately, leaving operational managers without a unified informational picture when it is most needed. This doctoral research develops an integrated DSS framework that unifies heterogeneous data sources - from hydrological models and IoT sensors to satellite imagery and social media - following a Design Science Research (DSR) approach. In this paper, we present the results of a preliminary literature review aimed at identifying the research gap. The review confirms that no published work integrates data across the full risk management cycle - from early warning through response to recovery. Building on this gap, the paper outlines the research design and expected contributions: (1) a DSS framework addressing cross-phase decision support, and (2) a methodology for heterogeneous data integration in flood management. The research addresses both technical and institutional dimensions of fragmentation.