SeaTrac Missions

SeaTrac Supports Environmental Agencies with Water-Quality Monitoring

SeaTrac Systems partnered with Massachusetts environmental agencies to advance continuous water-quality monitoring in Salem Sound and the Danvers River. This case study underscores how our autonomous platform enables remote, high-resolution data collection that supports understanding of eelgrass decline and pollution dynamics.

  • Year: 2020
  • Operational Area: Danvers River and Salem Sound, Massachusetts
  • Advantage: USV Offered Route Repeatability, Enabling Consistent Long-Term Observations

Key Benefits

Purpose

Eelgrass loss in Salem Sound has reached alarming levels, with reports showing an 81% decline in some areas since 1995. Scientists from the Massachusetts Office of Coastal Zone Management and the MassBays National Estuary Program, supported by EPA funding, turned to SeaTrac for a more effective way to link water quality and eelgrass health. Multiple missions were run to establish a baseline and timeline for understanding nutrient dynamics across spatial and temporal variables (vs. fixed buoys).

Method + Equipment

Base Platform and Equipment 

SeaTrac’s USV was outfitted with a multi-parameter YSI sonde to sample temperature, conductivity (salinity), turbidity, dissolved oxygen, pH, and chlorophyll. 

Autonomous Sampling Strategy

The USV was programmed to run two transects twice per month during July–September: one along the Danvers River toward the sewer outfall, and one over eelgrass beds off the Manchester coast. The USV’s navigational programming feature allowed it to follow nearly identical courses each mission, enabling consistent long-term observations.

“Collecting data with unmanned systems such as SeaTrac’s increases the quality and timeliness of our efforts to understand and protect our water resources, which is very good news. We would like to see this mission continued and replicated along all of our coastlines.”

Todd Callaghan, Massachusetts Office of Coastal Zone Management

Results

The USV successfully handled currents and variable conditions in both riverine and coastal settings. The team was particularly impressed with how reliably the vehicle retraced its path—enabling repeatable sampling. As noted by a data scientist, “the ability to loiter over outflows was incredibly helpful.” 

Continuous data revealed clear discrepancies between traditional spot sampling and mobile sampling: for example, chlorophyll trends varied more dynamically than they would appear in fixed-sample approaches. Ultimately, the mission delivered a robust baseline dataset, better informing how urban runoff and wastewater discharge affect eelgrass ecosystems, and demonstrated the power of autonomous systems to inform coastal management and policy.

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