  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 a lot of 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 (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; (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.
