Risk Perception

Irrigation districts that have long been managed around water scarcity are increasingly confronted with rapid‐onset flooding, creating new challenges for agricultural flood risk management. This study examines how personal disaster experience, village communication, and social media shape farmers’ perceptions of future flood loss and planting intentions in the Hetao Irrigation District of Bayannur City, Inner Mongolia Autonomous Region, China. The case is analytically important because recent flood shocks emerged in a historically drought‐oriented human‐water system. Based on a field survey of 591 farmers and analyzed using linear and generalized linear mixed‐effects models, the results indicate that personal disaster experience is the strongest predictor of future flood loss perception and is also associated with lower willingness to expand cultivated land. Media‐based disaster comparison significantly increases perceived future drought loss but does not further increase perceived flood loss. Community disaster communication does not directly heighten flood risk perception, yet it is positively associated with plans to expand production. The study identifies which information channels make flood loss salient and consequential for farm planning after recent events. The findings show that recent flood memory now dominates local risk cognition in this drought‐oriented irrigation system. Flood risk management in such settings should combine recent lived experience, locally specific guidance on waterlogging and drainage, and community‐based recovery support to strengthen agricultural resilience.

This study investigates the relationship between perceived and actual pollution and mental health, emphasizing how exposure illusion and exposure neglect may contribute to mental health. The research draws on a representative sample of 16,607 Chinese residents, examining the associations between perceived and actual pollution and mental health outcomes, including depression, anxiety, and stress. The study utilizes a generalized linear mixed model, incorporating various pollution conditions, gender, age, education, and urbanization as fixed effects, while the provinces are treated as random effects. The results indicate that even in the absence of high levels of actual pollution, the mere perception of pollution is associated with increased levels of depression (β = 0.51, OR = 1.66, p<.001), anxiety (β = 0.43, OR = 1.54, p<.001), and stress (β=0.30, OR = 1.35, p<.001) among residents. When residents’ perception of pollution aligns with actual pollution levels, the negative effects on mental health appear to be more pronounced (depression: β = 0.90, OR = 2.46, p<.001; anxiety: β = 0.96, OR = 2.60, p<.001; stress: β = 0.56, OR = 1.76, p<.001). These findings demonstrate that perceived pollution may play a primary role in its association with mental health compared to actual pollution. It is important to emphasize that this study is cross-sectional, and thus it cannot establish causal conclusions regarding perceived pollution leading to mental health issues. Furthermore, only air pollution was used as an indicator of actual pollution, which may limit the generalizability of our findings.