Agent-based modelling (ABM) is becoming a widely explored method for investigating human–water systems, given its ability to represent heterogeneous actors and their decisions. ABM can simulate how humans interact and co-adapt with their environment, which is beneficial for understanding the effects of humans’ decisions in the face of hazards and climate change. ABMs can serve as tools for examining the effects of current and future hydrological hazard management strategies. However, the implementation of hydrological hazard management in ABMs has not yet been systematically evaluated for floods and droughts. To map the current status of ABMs in hydrological hazard modelling and facilitate a discussion on further potential, we conducted a systematic mapping review based on the ROSES protocol. In this review, we investigate what kinds of hydrological hazards and management strategies that are represented in ABMs. Additionally, we synthesise current practices regarding agent types and their decision-making. A total of 377 articles were screened, and 77 articles were analysed in full text. Our findings indicate that hydrological hazard management strategies in ABMs include both structural and non-structural measures. However, there is an emphasis on the complexity of individual agents’ decision-making in implementing these measures, whereas collective agents (e.g. governments) performing non-individual hazard management are implemented more simplistically, often as static scenarios or collective agents with ad-hoc or rational decision-making. Conversely, individual agents are commonly implemented with human-like behaviour. Our study highlights that the simplicity of hazard management in these models could restrict the potential of ABMs as policy and predictive tools, as the implemented hazard management does not capture the full dynamics of human–water systems. Involving stakeholders, adopting interdisciplinary methods, or incorporating bounded-rational decision-making could represent a significant shift to further enhance the explanatory power of ABM for addressing challenges in hydrological hazard management.

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