Urbanization strongly affects freshwater environments by altering water quality through industrial effluents, agricultural runoff, and land use changes. This study assessed the effect of industrialization on the Fylleån River in Halmstad, Sweden, by comparing an industrial site and an agricultural site using manual and drone-based sampling methods. Five sampling points were selected at each site, and water samples were analyzed for nitrate, nitrite, phosphate, total organic carbon (TOC), total nitrogen (TN), turbidity, and electrical conductivity. Real-time measurements were also recorded using sensor-equipped, AI-powered Aquality drones. Two-way ANOVA statistical tests revealed that nitrate and conductivity were significantly greater in industrial areas, while turbidity and nitrite concentrations were greater in agricultural zones. Drone sensor data also recorded consistently higher nitrate and TOC than manual methods, suggesting greater spatial coverage and sensitivity likely due to a larger spatial coverage and real time in situ sampling that can detect small-scale heterogeneity in water quality that manual sampling can miss and higher sensitivity of drone-mounted sensors to detect the dissolved or particulate fraction not uniformly captured by grab samples. Phosphate and TN did not vary greatly between sites or sampling methods. In this study, “land use type” precisely denotes the differing contexts of the sampling sites, agricultural (Site A) and industrial (Site I). The findings demonstrate that land use significantly affects some water quality indicators, and drone-based approaches offer an effective, efficient solution to environmental monitoring. This study indicates the advantage of merging traditional and novel sampling approaches to enhance spatial resolution, accuracy, and sustainability of freshwater quality monitoring. The results highlight the importance of targeted water management strategies in urban catchments to enable ecosystem health and effective policymaking.