James Partan

and 3 more

The advocacy activities necessary to sustain healthy watersheds and improve impaired ones ultimately rely on the democratic process, and therefore depend on a public that values our coastal resources and understands the role that water quality plays in maintaining that value. We contend that an opportunity exists to improve the temporal and spatial density of monitoring by reducing the cost of collecting measurements, while simultaneously fostering an informed and invested public. We envision a distributed water quality monitoring sensor network, composed of low-cost ($1000-$2000) profiling devices we call TideRiders, built and operated by private citizens and local educational organizations and supported by an institution-hosted centralized data and control portal. The TideRider concept engages the public not just in the collection of data but also in the building, deployment, operation, and recovery of these robot sensors. TideRiders will carry a suite of basic water quality instrumentation (temperature, conductivity, and dissolved oxygen), transmit data and accept commands over the cellular network, and can sample surface and bottom waters by surfacing and submerging on a programmable schedule. Operators will harness tidal currents to move their TideRiders deliberately around an embayment, essentially by surfacing in a favorable tide and anchoring on the bottom in an adverse tide. A network of TideRiders deployed in tidally-dominated estuaries like Buzzards Bay and Narragansett Bay could provide basic water quality data at several-hour intervals for weeks at a time by “virtually mooring” in center-bay locations that are otherwise only accessible by boat and therefore typically sampled less frequently than shore stations. We present preliminary field results from a series of prototypes designed and built by students. The prototype devices utilize a novel low-cost semi-passive shallow-water buoyancy engine and were constructed for less than $1000 in parts.

Michael Jakuba

and 3 more

We report the design and results from a series of recent cruises using a fast vertical profiling autonomous underwater vehicle called Clio. Clio has been designed specifically to complement conventional wire-based sampling techniques—to improve ship-time utilization by operating simultaneously and independently of conventional techniques, and thereby to cost-effectively improve the understanding of marine microorganism ecosystem dynamics on a global scale. Life processes and ocean chemistry are linked: ocean chemistry places constraints on marine metabolic processes, and life processes alter the speciation, chemical associations, and water-column residence time of seawater constituents. Advances in sequencing technology and in situ preservation have made it possible to study the genomics (DNA), transcriptomics (RNA), proteomics (proteins and enzymes), metabolomics (lipids and other metabolites), and metallomics (metals), associated with marine microorganisms; however, at present these techniques require sample collection. For this purpose, Clio’s primary payload consists of two Suspended-Particle Rosette (SUPR) multi-samplers capable of returning up to 20 sets of filtered samples and filtrate per dive, and filtering up to 280 L of water per sample. Clio hosts additional profiling sensors consisting presently of a Seabird Electronics CTD, WET Labs combined chlorophyll and backscatter fluorimeter, and C-Star transmissometer. Since sea trials in 2017 Clio has participated in 5 cruises including most recently a section cruise between Bermuda and Woods Hole in June of 2019. On that cruise Clio executed a total of 9 nightly dives 12-16 hours in length and filtered a total of 20,878 L of seawater. The vehicle holds depth to a precision of better than 5 cm, is rated to 6000 m (4100 m maximum depth to date) and transits the water column at 45 m/min. Clio has demonstrated consistent reliable performance in its intended role; however, opportunities exist to further exploit its capabilities. Clio’s last two dives included autonomous data-driven selection of sample depths to better capture the deep chlorophyll maximum. Clio’s large payload capacity (10s W, 10s kg) could host novel samplers as well as in situ sample processors and other profiling instruments.