Real Time Monitoring of Water Quality with an Autonomous Surface Vessel in a Coastal Estuary

Ocean and coastal water quality monitoring has become more important in recent decades as onshore anthropogenic activities contribute more pollutants to surface water runoff that flows to offshore systems like the Gulf of Mexico (GOM). Many coastal systems are major sources of income and natural resources for human populations. The Mississippi Sound (MSS) is one such system and can be characterized as a large, nutrient rich, coastal estuary in the Northern GOM. The MSS is bounded by the mainland coast of Mississippi to the north, Mobile Bay to the east, Lake Borgne (Louisiana) to the west, and a series of barrier islands (Cat, Ship, Horn, Petit Bois, and Dauphin Islands) to the south. Major freshwater inputs to the MSS are the Mobile River (via Mobile Bay), the Pascagoula River (via Pascagoula Bay), the Pearl River (via Lake Borgne), and on occasion the Mississippi river (Bonnet Carre spillway openings). Minor inputs are the Biloxi, Tchoutacabuffa, Wolf, and Jourdan, rivers. The barrier islands present an obstacle to water exchange between the MSS and the GOM suggesting prolonged weather or anthropogenic events (i.e., hurricanes or spillway openings, respectively) can greatly impact the biota (e.g., algae) and reliant ecological processes of the MSS due to reduced water exchange with the GOM. Water quality of the MSS is dynamic and can change seasonally, thus, a baseline understanding of water quality and algal density across the MSS can aid resource managers by providing a better understanding of freshwater particulate and solute impacts to the MSS over time. Algae is typically measured via pigments like chlorophyll A (universal algal pigment), phycoerythrin (restricted to saltwater cyanobacteria), or phycocyanin (restricted to freshwater cyanobacteria) which can contribute to water turbidity and therefore affect plant and fish growth. Water quality (DO, CDOM, Temperature, Turbidity, pH, and Salinity) and algal metrics were characterized spatially in the MSS in 2023 after autonomous surface vessel data collection. Data were used to assess water quality and algal metrics from the mainland coast to the offshore barrier islands of the MSS as well as across the MSS from LA to AL. A generalized linear model (GLM) was used to detect differences among transects. Algal metrics were correlated to water quality metrics as well. In general, all metrics were significantly impacted by proximity to the mainland coast and proximity to major freshwater inputs (Pearl and Pascagoula systems). Algal metrics were correlated more strongly with turbidity, CDOM, pH, and salinity than temperature or dissolved oxygen suggesting that these four metrics may have more influence over algal density than the others. Data collected by ASV was positively correlated with data collected by manned vessel. However, not all ASV collected data could be used as a surrogate for data collected from a manned vessel as dissolved oxygen and pH differed among the two datasets while CDOM, temperature, turbidity, and salinity were equivalent among the two. This work highlights the utility of ASV collected data as a viable option for stakeholder decision making purposes and suggests this technology can be effectively utilized to supplement (and possibly replace) existing monitoring techniques. (Abstract)