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To improve the efficiency of flood early warning systems (FEWS), it isimportant to understand the interactions between natural and social systems.The high level of trust in authorities and experts is necessary to improve thelikeliness of individuals to take preparedness actions responding to warnings.Despite a lot of efforts to develop the dynamic model of human and water insocio-hydrology, no socio-hydrological models explicitly simulate socialcollective trust in FEWS. Here we develop the stylized model to simulate theinteractions of flood, social collective memory, social collective trust inFEWS, and preparedness actions responding to warnings by extending the existingsocio-hydrological model. We realistically simulate the cry wolf effect, inwhich many false alarms undermine the credibility of the early warning systemsand make it difficult to induce preparedness actions. We found (1) consideringthe dynamics of social collective trust in FEWS is more important in thetechnological society with infrequent flood events than in the green societywith frequent flood events; (2) as the natural scientific skill to predictflood events is improved, the efficiency of FEWS gets more sensitive to thebehavior of social collective trust, so that forecasters need to determinetheir warning threshold by considering the social aspects.

Socio-meteorology: flood prediction, social preparedness, and cry wolf effects