Abstract. To improve the efficiency of flood early warning systems (FEWS), it is
important to understand the interactions between natural and social systems.
The high level of trust in authorities and experts is necessary to improve
the likeliness of individuals to take preparedness actions responding to
warnings. Despite many efforts to develop the dynamic model of human and
water in socio-hydrology, no socio-hydrological models explicitly simulate
social collective trust in FEWS. Here, we develop the stylized model to
simulate the interactions of flood, social collective memory, social
collective trust in FEWS, and preparedness actions responding to warnings by
extending the existing socio-hydrological model. We realistically simulate
the cry wolf effect in which many false alarms undermine the credibility of
the early warning systems and make it difficult to induce preparedness
actions. We found that (1) considering the dynamics of social collective trust in
FEWS is more important in the technological society with infrequent flood
events than in the green society with frequent flood events; and (2) as the
natural scientific skill to predict flood events is improved, the efficiency
of FEWS gets more sensitive to the behavior of social collective trust, so
that forecasters need to determine their warning threshold by considering
the social aspects.