Aquatic macroinvertebrates are key components of freshwater ecosystems and are widely used as indicators of habitat quality, yet the ecological drivers of many protected species remain poorly understood. The diving beetle Graphoderus bilineatus (De Geer, 1774) is a strictly protected Natura 2000 species in Europe, with habitat requirements that vary geographically. While in most of its range the species is associated with standing waters, in Hungary it occurs predominantly in floodplain habitats, suggesting a role for hydrological dynamics on its local populations. Based on long-term field observations, we hypothesized that flood events, particularly spring floods, may influence the occurrence of the species. However, responses to flood events are inherently difficult to study due to their unpredictable distribution in space and time, which may not align with available data from monitoring and faunistic surveys conducted at irregular intervals. In this study, we evaluated whether such data are sufficient to detect relationships between flood dynamics and species occurrence. We analysed presence–absence records collected between 2000 and 2022 across four major river systems (Bodrog, Tisza, Danube and Drava rivers) in Hungary using Bayesian logistic regression models with hydrological predictors derived from water level data. Across all catchments, models including flood variables performed only marginally better than simpler models, and posterior estimates were associated with wide credible intervals. In the Bodrog catchment, higher flood levels were associated with lower predicted occurrence, while results for other rivers remained highly uncertain. Our results provide only weak and inconsistent support for the hypothesized role of floods and demonstrate that opportunistic presence–absence data are insufficient for robust ecological inference in this context. Given the conservation importance of G. bilineatus, we emphasize the need for standardized, hydrology-informed monitoring programmes to better understand its population dynamics and to support effective management.