Coastal and estuarine water quality monitoring presents a persistent operational challenge in port environments and shallow river delta systems, where the physical constraints of conventional crewed survey vessels — namely draught, maneuverability, and cost — limit achievable spatial resolution. This dissertation investigates the deployment of a shallow-draft Unmanned Surface Vehicle (USV) as a practical data-collection instrument for the assessment of water quality in two ecologically and operationally significant zones within the coastal waters of Batumi, Georgia.

Zone A, the Batumi Port Area, is characterized by a concrete breakwater enclosure that promotes stagnant circulation and the progressive accumulation of pollutants through what is described here in as the Pocket Effect. Zone B, the Chorokhi River Delta, constitutes a dynamic estuarine mixing zone subject to high turbidity loads from mountain silt runoff and rapid lateral gradients in salinity, pH, and redox potential.

The USV platform, guided by a Pixhawk 2.4.8 autopilot and programmed via Mission Planner software, carries a sensor suite comprising a TS-300B turbidity sensor, a glass-electrode pH probe, an Oxidation-Reduction Potential (ORP) sensor, and an Electrical Conductivity (EC) probe. Sensor readings are logged at a frequency of 1.0 Hz and subsequently merged with GPS positional data extracted from the autopilot telemetry logs. The merged dataset is imported into QGIS, where Inverse Distance Weighting (IDW) spatial interpolation is applied to produce continuous, georeferenced water quality heatmaps of each study zone.

The findings demonstrate that the USV-based approach provides substantially greater spatial data density compared to conventional manual grab-sampling, while remaining operable in water depths and restricted geometries inaccessible to standard survey craft. The methodology presents a scalable and replicable model for routine port environmental monitoring.