Abstract This qualitative review examines recent developments in impact-based decision making in flood risk management, with a particular focus on bridging behavioral and engineering sciences. Floods pose a significant global threat, with increasing importance under climate change, but also with challenges in operational decision making, as needed to control structures and warn the population before and during an event. The review examines factors influencing decision makers, such as cognitive biases and bounded rationality, and evaluates interdisciplinary approaches to modeling these factors. It highlights advances in seamless weather forecasting and real-time impact assessment, emphasizing their integration into operational flood management to improve decision accuracy and trust in warning systems. Techniques such as ensemble forecasts and impact libraries are assessed for their potential to address uncertainties and improve risk communication. While many studies do not yet leverage theoretical foundations, this review highlights the potentials of prospect theory, regret theory, robust decision making, fuzzy set theory, and Bayesian decision theory in advancing flood management practices. Highlighting these theoretical applications reveals a gap in current flood management research, urging scholars and practitioners to explore how incorporating social science insights can better inform and enhance existing systems.
Bovermann et al. (Wed,) studied this question.