1. Irrigation Efficiency: Integrated Data Reporting for Decision Support Solutions Energy Applications and Cloud Computing Webinar Series David Terry ASERTTI Executive Director August 19, 2013

2. ASERTTI ASERTTI Overview ASERTTI Members Upcoming Activities • ASERTTI's mission is to increase the effectiveness of energy research efforts in contributing to economic growth, environmental quality, and energy security. • ASERTTI promotes applied research and technology commercialization in energy efficiency and renewable energy through state, federal, and private collaboration on emerging technologies. ASERTTI works to: • Foster cooperative relationships among its members • Advocate for policies that support clean energy research, development, demonstration, and deployment (RDD&D) www.asertti.org

3. ASERTTI Members ASERTTI Overview ASERTTI Members Upcoming Activities ASERTTI’s membership includes state energy agencies, university energy centers, national laboratories, non-profit organizations, utilities, and other public interest technology organizations. www.asertti.org

4. Upcoming Activities ASERTTI Overview ASERTTI Members Upcoming Activities • ASERTTI Webinar Series: Energy Applications and Cloud Computing • Smart Manufacturing: Cloud Data and Computation Services for Performance Management Modeling (SMLC and EPRI)September 16, 2013 • ASERTTI Fall Meeting: October 2-4, 2013 – Raleigh, NC Integrating Smart Grid Technologies for Buildings, Industry, and Vehicles www.asertti.org

5. Energy and Water Savings from Optimal Irrigation Management and Precision Application Lori Rhodig, Northwest Energy Efficiency Alliance (NEEA) Dr. Charles Hillyer, Oregon State University (OSU)

6. NEEA’s Role • Fill the energy efficiency pipeline • Accelerate market adoption • Leverage the power of the region

7. Impact of Ag Irrigation in the Region ~ 5% or $335M Based on 2007 usage – data from NW Power Conservation Council’s Sixth Power Plan

8. Key Deliverables Initiative Goal, Objectives and Deliverables THE GOAL Economic enhancement through 20% Agricultural Irrigation energy efficiency by 2020 20% by 2020 OBJECTIVES Water and energy savings Irrigation technology + practices Industry-wide data standards • DELIVERABLES • Improve yield uniformity • Improve energy intensity • Water goes further • More profit per acre • Decrease energy consumption Created by NW growers, utilities and NEEA in partnership with key global suppliers

9. Methods Used in Deciding When to Irrigate 2008 – 78% 2008 – 1.4% (Farm And Ranch Irrigation Survey, USDA)

10. Today’s Standalone Tools Don’t Integrate • External data sources • Soil maps • Weather networks • localized Hardware • Weather stations • Moisture sensors • Pumping plants • Smart meters • Flow valves • Online advisory systems • Crop type • ET • Schedules • Weather • SIS • Irrigation • scheduling • Tools • VRI • SIS

11. In-Field Equipment: Weather & Moisture Measurement Total solar radiation (pyranometer): Soil temperature (thermistor): Air temperature/relative humidity: Wind Vane (Wind Direction) Anemometer (Wind Speed) Tipping-bucket rain gauge 12v Solar Panel+battery Telemetry uplink GPS Pivot Location Soil Moisture monitoring: 3x Decagon HS10 Soil Moisture Aquacheck probe IrrometerTensiometer TDR (Time Domain Reflectrometer) Panametrics Flow meters Smart Meters (at pump) 14 15 9 Weather 1 Automated Field Moisture Monitors 10 11 12 13 3 6 4 & 5

12. Integrated Decision Support Solution Iterative Feedback Loop INPUTS OUTPUTS DYNAMIC On-Farm information Optimal Irrigation management Weather Moisture sensors Pumping + distribution system Uniform Fields Telemetry Decision support static Data VRI Fields Yield maps Soil maps Online advisory system (ex. AgriMet) Crop type, ET, weather integration, irrigation scheduling, etc. FIXED data output Reports, trends, analysis, etc. Risk management

13. Product: Technology Levels • Variable Rate Irrigation (or called VRI Site-Specific or Zone) • On-farm weather station with in-field correction • Soil moisture monitoring • Flow monitoring • Energy use monitoring • Optimal Irrigation Scheduling • Soil mapping to calibrate deficit strategies • Yield mapping to verify crop response • VSI ( or VRI-Speed) • Conventional practice • Remote weather station

14. Optimal Irrigation

15. Preliminary Demonstration Results

16. Lessons Learned

17. 2013 Demonstration Sites Key:  = ’12 VRI site  = ‘13 VRI site  = ‘13 VSI site X

18. Integrated Decision Support Solution Iterative Feedback Loop INPUTS OUTPUTS DYNAMIC On-Farm information Optimal Irrigation management Weather Moisture sensors Pumping + distribution system Uniform Fields Telemetry Decision support static Data VRI Fields Yield maps Soil maps Online advisory system (ex. AgriMet) Crop type, ET, weather integration, irrigation scheduling, etc. FIXED data output Reports, trends, analysis, etc. Risk management

19. Precision Ag Irrigation Leadership (PAIL) Jointly sponsored • NW Energy Efficiency Alliance • AgGateway Driven by business needs • Voice of the Grower • Manufacturers 20+ partner companies CHARTER Provide a common set of data standards and formats to convert weather, soil moisture and other relevant data from OEM hardware and software programs to be used by irrigation data analysis and prescription programs.

20. For More Information Telephone or email: Lori Rhodig, LRhodig@neea.org, 503-688-5431 Dr. Charles Hillyer, hillyer@engr.orst.edu, 541-207-2387 Website information: www.neea.org/irrigation (Video on right side)

21. Yield Model Calibration

22. Irrigation Management Online • Web Application for: • Conventional irrigation scheduling • Managing limited water supply • Optimal irrigation • Irrigation optimization The User is the most important part of optimization algorithm

23. Key Modeling Challenges Irrigation depends on all farm operations Optimization implies some level of deficit irrigation Farm level optimization depends on all fields

24. Sites Summary (2013)