Gridded population and flood hazard data are crucial for flood exposure assessments. However, current assessments incorporate uncertainties related to data selection, yet the mechanisms through which subjective data selection propagate uncertainties in exposure models remain poorly understood. To address this gap, this study conducted a comparative assessment of flood exposure in China using five population datasets and five flood hazard datasets. Furthermore, it explored the absolute and relative impacts of data uncertainties on 100 year return period flood exposure and discussed the underlying causes. Results exhibit substantial variations in flood exposure when different data combinations are employed. Specifically, there is a significant difference of 333 million individuals within the exposure range, with the highest estimate being 2.82 times the lowest one. Overall, the exposure variation was primarily from differences in flood hazards rather than population patterns, but their relative importance differed spatially depending on factors of slope, altitude, and artificial surface coverage. Despite the differences, all 25 data combinations revealed a disproportional larger share of population in floodplains, which was 2.28–3.49 times the share of floodplains. These findings are significant for understanding the uncertainties of flood exposure and can shed lights on informed policies for risk management.

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