Remote Sensing and Internet Data Sources

1. Remote Sensing and Internet Data Sources Unit 3: Module 12, Lecture 2 – Remote Underwater Sampling Stations

2. Overview • Many kinds of remote sensing systems for water science involve sensor systems that remotely operated. These include: • Buoy systems (RUSS units, National Buoy network) • Towed or tethered systems • Sea floor mounted systems • Autonomous underwater vehicles

3. Background: RUSS and WOW • Remote Underwater Sampling Station technology developed at NRRI in mid-1990s • U. of MN creates Apprise Technologies, Inc. to market RUSS units and other sensors • 1996 – NSF Advanced Technology Education grant to create “Water on the Web” • Online curriculum incorporating real-time data from RUSS units into college-level lesson plans • 1999 – 2002 EPA EMPACT program funds Lake Access • Deliver real-time data to public • 2000 – WOW II – Water Science Technician Training • 2001 – DuluthStreams • Real-time stream monitoring

4. Remote monitoring systems for environmental data • RUSS unit – Remote Underwater Sampling Station • Real-time water quality data acquisition • Data transmitted to WOW web site “RUSS” Remote Underwater Sampling Station

5. Solar Panels Triple Hull (with electronics and power supply units) RUSS Design: Platform & Power Supply

6. Solar Panels Triple Hull (with electronics and power supply units) Profiler (Variable-buoyancy device) Multiprobe (sensor package) RUSS Design: Profiler

7. Profiler: Leveling device • Variable buoyancy • Will achieve target depth within 0.2 m • Typically set to collect data at 1 m intervals in water column

8. Profiler: Sensor package • Standard Hydrolab or YSI Sonde attached to Leveler • Measures • Temperature • pH • Dissolved Oxygen • Conductivity • Turbidity • Chl a

9. RUSS deployment Lake Independence, MN

10. RUSS Deployment - Ice Lake, MN

11. The RUSS Fish HouseDecember 1998

13. On-board Data Processing and Storage • Remote Programming, Data Acquisition and Retrieval (RePDAR) unit • CPU • Memory • Telemetry • Data is stored in ring memory on RePDAR • Profiles are stored in a data buffer • Can be downloaded on demand

14. Wireless Communications (cellular/RF/Satellite/900 MHz) Solar Panels Triple Hull (with electronics and power supply units) Profiler (Variable-buoyancy device) Multiprobe (sensor package) RUSS Design: Communications

15. Data Flow: RUSS unit to the WOW web site HTML EXCEL Data Importer Archive DVT

16. RUSS Programming • Sampling timing and frequency can be programmed from the base station computer • Data is broadcast back to the base station at user specified intervals (generally every 4 - 6 hours) • Data is stored in standard ASCII formats for import to spreadsheet or database programs

17. Ice Lake Profile - Sept 5, 2004

18. Data from RUSS units • 5-6 variables per depth • 10-20 depths per profile • 4 profiles per day

19. “Data hose” effect • 5-6 variables per depth • 10-20 depths per profile • 4 profiles per day • ~200 days per season • 96,000 points per lake • 4-6 lakes in WOW • 2-6 years worth of data 2,400,000 data points in archives

20. Online Data Visualization Tools • Profile plotter (parameters vs depth) • Color mapper (parameters vs depth) • DxT (depth vs time)

21. Data Visualization Tools: Profile Plotter • Accesses and plots individual profiles by parameter • Can ‘step through’ or animate time steps

22. Data Visualization Tools: Profile Plotter

23. DVT:Color Mapper

24. Data Visualization Tools: DxT Profiler 2D visualizations: Temperature by Depth and Time

25. Data Visualization Tools: 3D Slicer 2D visualizations: Temperature by Depth and Time

26. Data Visualization Tools: DxT Profiler 2D visualizations: Temperature by Depth and Time Seasonal oxygen patterns Green - > 6 ppm O2 Brown – 3 – 6 ppm O2 – chronic stress Black - < 3 ppm O2 - lethal

27. Seasonal Cycles of Temperature and Oxygen

29. Hardware and management issues

30. Vandalism “I bet you can’t hit that yellow thing out in the water..”

31. Animal Vandals

35. Assuring Data Quality: Sensors • Hydrolab or YSI sondes need to be calibrated biweekly • Biofouling • “Drift” BeforeAfter (1 month)

37. September 30, 2003

38. July 1998 July 2001 Anomalous Conductivity Spike July 4, 1998 Ice Lake, MN “Several truckloads of salt”

39. In-stream sensor package connected to land-based power and data storage units No need for depth profile, but need information on stream flow Similar power and data management issues Stream Monitoring Units

42. SMU deployment • SMUs typically deployed near bridge abutments to allow easy access to stream • Note solar panel on pole • Good climbing skills required WOW staffer Jerry Hennick installing DuluthStreams SMU

44. Baseflow and post-storm differences in stream flow in Chester Creek, Duluth, MN

45. Hardwired SMUs • Ideal situation – obtain power and communications by tying into existing land lines • Duluth ship canal • USGS power supply and office facilities

46. Summary • RUSS and SMUs have formed the basis for the WOW on-line curriculum, as well as projects such as Lake Access and Duluth Streams • As on-line sensors become more widely used, there is a significant potential to use these systems for both public and student education • As a result, we should be more likely to use real data in making land and water management decisions