Antibiotic use in aquaculture has become widespread to sustain production and control bacterial diseases, but it poses significant ecological and human health risks due to residue accumulation and resistance development. This study investigated the occurrence, dominance, and combined use of sulfonamide and fluoroquinolone antibiotics in freshwater fish aquaculture ponds around Wuxi, China. Here, the term aquaculture refers specifically to the controlled farming of freshwater fish species such as carp and crucian carp in managed pond systems. A total of 80 water samples (collected exclusively from pond waters) were obtained from 40 ponds during the high intensity rearing and harvest stage of fish. Residues of enrofloxacin and sulfonamide antibiotics were analyzed using a validated LC–MS/MS method with detection limits in the low nanogram-per-liter range. Results revealed that antibiotics were ubiquitous in pond waters, with enrofloxacin emerging as the dominant compound in August, reaching concentrations of up to 2.36 µg/L. By October, sulfonamides, particularly sulfamethoxazole and sulfadiazine, became more prevalent, with a maximum sulfadiazine concentration exceeding 4 µg/L. Multivariate analyses demonstrated a clear seasonal shift in antibiotic profiles, while correlation analyses indicated limited combined use in summer but notable co-occurrence of sulfonamides in autumn. These findings underscore that antibiotic application patterns in aquaculture are strongly linked to production stages, with potential consequences for environmental safety, resistance development, and food security. Effective monitoring, stricter regulation, and alternative disease management strategies are urgently required to mitigate risks and promote sustainable aquaculture practices.

Quick Quantitative (QQ) immunoassays have been increasingly applied for the measurement of enrofloxacin (ENR) and ciprofloxacin (CIP) residues in aquaculture due to their speed and convenience. However, their quantitative reliability remains limited because measurement uncertainty (MU) is rarely considered during field testing. To enhance the metrological reliability of QQ-based residue analysis, we developed AquaUncertainty Pal, a mobile application that embeds real-time MU computation into the QQ workflow. The software automatically evaluates uncertainty sources during sampling and pipetting, visualizes the uncertainty budget, and guides users through optimized operations. The framework was validated against ISO/IEC 17025–accredited LC–MS/MS and assessed through a user study involving 20 frontline technicians. With the integrated software, pipetting precision (RSD) at 100 μL improved from 4.1% to 1.79%, the inter-operator variability (CV) decreased by 52%, and conformity assessment accuracy for samples near the maximum residue limit (MRL) increased from 25% to 70%. This suggests that real-time MU visualization effectively guided technicians toward consistent pipetting and interpretation behavior. These results demonstrate that integrating MU into the QQ workflow is both feasible and effective, substantially improving reliability and providing a replicable digital framework for uncertainty-informed residue monitoring in aquaculture.