What question did this study set out to answer?

This research aims to explore how generative AI can reshape flood management strategies and address existing research gaps.

March 2, 2026Open Access

A Systematic Review of Flood Management Evolution, with Emphasis on How Generative AI Reshapes Prediction-to-Decision Pathways

Key Points

This research aims to explore how generative AI can reshape flood management strategies and address existing research gaps.
Conducted a systematic literature review (SLR) on flood management from 2010 to 2025.
Analyzed 77 peer-reviewed articles using the PRISMA approach.
Identified four applications of generative AI within flood management frameworks.
Generative AI can enhance inclusiveness and real-time sensitivity in flood risk management.
Identified hypothetical applications include knowledge translation and decision-support tools.
Significant issues include algorithm bias and the need for ethical governance in AI applications.

Abstract

Climate change affects flood frequency and intensity throughout the world, leading to a research gap in the traditional management framework. Furthermore, traditional frameworks often rely on complex hydrological patterns and one-way communication, demonstrating urgent needs for adaptive and two-way communication approaches. For this purpose, the current systematic literature review (SLR) fills this gap by analyzing the widely reported literature on the role of an artificial intelligence (AI)-based framework. This SLR provides conceptual and theoretical insight into the potential role of generative AI and an OpenAI-based theoretical framework for effective flood management. Therefore, 77 peer-reviewed articles published between 2010 and 2025 in reputed sources such as ScienceDirect, Springer Nature, MDPI, Wiley, and others were analyzed using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) approach. According to the results of this paper, four hypothetical applications of generative AI are described, namely: (i) a knowledge translator to provide simplified hydrological information, (ii) a decision-support assistant that aids real-time strategic analysis, (iii) a community engagement tool to increase the participation and understanding of people, and (iv) an interface to harmonize and synthesize various sources of information. The discussion indicates that there is a lot of potential in terms of generative AI improving the inclusiveness, real-time sensitivity, and cost-effectiveness of flood risk management practice. Nevertheless, the research also presents significant issues that are connected to data integrity, algorithm bias, digital equity, and ethical governance. The results indicate that generative AI has a significant potential of developing robust, more accessible, and more communicative flood risk management systems, and that additional studies on the responsible and ethical use of the technology are necessary.

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