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Alaskan Limnological Surveys Using Autonomous Sensor Platforms
Low-Cost Autonomous and Automated Platform Prototypes Conduct Bathymetric and Hydrographic Surveys on the North Slope of Alaska

AUTHORS:

Hunter C. Brown
Ocean Engineer
Department of Naval Architecture
and Marine Engineering
University of Michigan
Ann Arbor, Michigan

Liza K. Jenkins
Research Scientist
Michigan Tech Research Institute
Michigan Technological University
Ann Arbor, Michigan

On March 12, 1968, the largest oil field in North America was discovered at Prudhoe Bay on the North Slope of Alaska. Oil companies quickly descended on the region, building airfields, supply roads and facilities to extract the oil from 9,000 feet below the surface. Environmental data gaps and public concern about how drilling would affect the environment led to the creation of an organization focused on providing scientific and regulatory understanding of existing and future ecological conditions of the region. The North Slope Science Initiative (NSSI) was established in 2003 as an intergovernmental endeavor to provide the critical information requirements needed for sound resource management and decision-making.

The NSSI created the North Slope Water Characterization Project to support the development of innovative and cost-effective methods to collect essential data required to make informed decisions. The initiative partnered with the University of Michiganís (UM) Marine Hydrodynamics Laboratory (MHL) and the Michigan Tech Research Institute (MTRI) to provide high-resolution bathymetric and hydrographic data collections at remote North Slope locations, many accessible only by helicopter.

The project began with engineering tests of Lagrangian data-collection buoys during the 2006 summer field season and has evolved to include autonomous sensor platforms in 2009, including a new autonomous surface vessel (ASV), BathyBoat. Over the course of the program, remote-sensing-based algorithms have also been developed to extend in-situ measurements and provide insight into the processes occurring in the region.


Research Goals
Extensive water depth information is needed to help identify and map habitats for a variety of North Slope organisms, including fish overwintering sites and nursery areas. One species of interest is the yellow-billed loon, a candidate for the federal endangered species list that nests in freshwater lakes in the Arctic tundra. Water-quality and water-depth data are needed to help determine yellow-billed loon lake preference and thus identify critical lakes for conservation efforts.

Better bathymetric data is also necessary to help maintain water access throughout the Alaskan winter, when most lakes freeze completely to the lakebed.

To retrieve water for building winter ice roads and ice infrastructure that support the oil and gas community, teams must drill through thick ice to reach liquid water, if water is available at all. It is both costly and time-consuming to deploy and position equipment and personnel at a lake to attempt water withdrawal without the guarantee of success.

Bathymetric information is sparse on the North Slope, and more data is needed.

Sensors included on the BathyBoat.
BathyBoat
Bathymetric surveys for a single lake on the North Slope typically cost between $10,000 and $25,000 using industry standard techniques. In an effort to reduce these costs, UM, MTRI and NSSI collaborated to design and build a low-cost ASV sensor platform that can survey, log and transmit real-time data in a fully autonomous mode of operation at a fraction of the cost (a full order of magnitude). The prototype vehicle, known as the BathyBoat, also serves as a development platform for remote sensing algorithms and auto-nomous navigation schemes.

To meet real-time data collection and transmission objectives, collaborators integrated a suite of hydrographic sensors into a UM-designed hull. These sensors included an electronic compass, a global positioning system (GPS) receiver, an acoustic depth sensor, a conductivity sensor, a temperature sensor and a wireless fish-finder. A Digi International Inc. (Minnetonka, Minne-sota) XTend radio modem was also installed. A custom deck and passive directional indicator were added using special composite/aluminum fabrication techniques.

The BathyBoatís hull is only 38 inches in length, with a draft of five inches, making it possible to be transported by helicopter (allowing access to remote lakes deep in the Arctic Circle). The interior cavity is lined with foam to provide emergency buoyancy in case of flooding. The minimal draft, in combination with a recessed propeller, allows the vehicle to operate in extremely shallow environments. Fully loaded with batteries, the vehicle weighs 32 pounds and can easily be unloaded, ported and launched by a single person.

The BathyBoat is operated in two control modes: autonomous and manual. In autonomous mode, the vehicle will follow a heading or perform GPS waypoint navigation. In manual mode, the operator still has real-time access to the full suite of sensors through the radio modem. Both manual control and radio modem control were demonstrated from an airborne helicopter during the most recent missions in Alaska.

Heading, GPS waypoints and sensor options can be modified in real time through a long-distance radio modem with a range of up to 14 miles. At any time, a field operator can assume manual control by powering a hand-held radio control transmitter.


ALWAS
While the BathyBoat is designed for targeted in-situ water-depth data collections, the Automated Lagrangian Water Quality Assessment System (ALWAS) is designed to collect broad-spectrum water-quality parameter data via a drifter buoy platform.

Each ALWAS buoy can be easily deployed by helicopter and is portable by one person. The buoys contain state-of-the-art water-quality sensors that measure temperature, conductivity, pH, oxidation-reduction potential, turbidity, dissolved oxygen, total dissolved solids, salinity, nitrate, ammonium, chloride, chlorophyll a, blue-green algae and water depth. The buoy also records GPS information, including geographic location (latitude and longitude), speed and heading, quality metric, the number of visible satellites, time and date. Data is stored on board and transmitted in real-time via a spread-spectrum radio link. MTRI built custom software so that data can be imported directly into geographic information system computer applications, such as Desktop ArcGIS and QGIS and Web-based OpenLayers and Google Earth for visual displays.


Results
The baseline characterization data set was collected during four field deployments in July 2006, August 2008, September 2008 and July 2009. This sampling has provided data from a variety of tundra lakes spanning a large geographic area, with some repeat sampling and specific targeted scientific investigations such as saltwater intrusion, yellow-billed loon habitat assessments and temporal lake dynamics. The full data set, including summary statistics, data maps, presentations, posters and reports, is available on the Tundra Lake Studies website.

The field measurements have been used in combination with electro-optical and synthetic aperture radar satellite data to create new computer algorithms that map and help predict which lakes are deep enough to harvest water for winter ice road and ice infrastructure construction, among other needs. The new satellite algorithms are an attempt to provide detailed locations and overall descriptions of lakes that will provide liquid water on the first drilling attempt.


Future Work
The latest North Slope deployment exposed features of the BathyBoat prototype that need to be modified. The hull form, autonomous navigation control system and power system are the focus of current upgrade efforts by the MHL. The BathyBoat is currently slated for return to the North Slope this summer.


Acknowledgments
The North Slope Water Characterization project is ongoing with contributions from the NSSI. The authors would like to thank Dr. John Payne, Dr. Guy Meadows and Dr. Robert Shuchman for technical guidance; Nick Wild and Joe Wild for support in machining, fabrication and paint; Edward Celkis for electronics support; Chuck Hatt for software development; Kris Owens for administrative services; and Scott Guyer for field logistics and data-collection assistance.



Hunter C. Brown, an ocean engineer and Ph.D. student, leads the Autonomous Systems Group at the University of Michiganís Marine Hydro-dynamics Laboratory. His current research focuses on autonomous vehicles, machine vision and military systems.

Liza K. Jenkins, a research scientist at Michigan Technological Universityís Michigan Tech Research Institute, earned her bachelorís and masterís of science in natural resource management at the University of Michigan. She specializes in hydrological application of remote sensing data.



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