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

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4. 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 ASERTTI OverviewASERTTI MembersUpcoming Activities

5. 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. 6 NEEA’s Role  Fill the energy efficiency pipeline  Accelerate market adoption  Leverage the power of the region

7. 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. 8 Initiative Goal, Objectives and Deliverables Created by NW growers, utilities and NEEA in partnership with key global suppliers KEY DELIVERABLES THE GOAL Economic enhancement through 20% Agricultural Irrigation energy efficiency by 2020 20% by 2020 DELIVERABLES  Improve yield uniformity  Improve energy intensity  Water goes further  More profit per acre  Decrease energy consumption OBJECTIVES Water and energy savings Irrigation technology + practices Industry- wide data standards

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

10. 10 Today’s Standalone Tools Don’t Integrate LOCALIZED HARDWARE  Weather stations  Moisture sensors  Pumping plants  Smart meters  Flow valves EXTERNAL DATA SOURCES  Soil maps  Weather networks ONLINE ADVISORY SYSTEMS  Crop type  ET  Schedules  Weather  SIS IRRIGATION SCHEDULING TOOLS  VRI  SIS

11. 11 In-Field Equipment: Weather & Moisture 1.Total solar radiation (pyranometer): 2.Soil temperature (thermistor): 3.Air temperature/relative humidity: 4.Wind Vane (Wind Direction) 5.Anemometer (Wind Speed) 6.Tipping-bucket rain gauge 7.12v Solar Panel+battery 8.Telemetry uplink 9.GPS Pivot Location 10.Soil Moisture monitoring: 3x Decagon HS10 11.Soil Moisture Aquacheck probe 12.Irrometer Tensiometer 13.TDR (Time Domain Reflectrometer) 14.Panametrics Flow meters 15.Smart Meters (at pump) Measurement 14 Weather Automated Field Moisture Monitors 13 15 9 1 3 6 4 & 5 101112

12. Integrated Decision Support Solution INPUTS STATIC DATA Soil maps Yield maps ONLINE ADVISORY SYSTEM (ex. AgriMet) Crop type, ET, weather integration, irrigation scheduling, etc. RISK MANAGEMENT ON-FARM INFORMATION Weather Pumping + distribution system Telemetry Moisture sensors OUTPUTS DATA OUTPUT Reports, trends, analysis, etc. DYNAMIC FIXED OPTIMAL IRRIGATION MANAGEMENT Uniform Fields VRI Fields Iterative Feedback Loop DECISION SUPPORT

13. 13 Product: Technology Levels Level 1 Level 2 Level 3  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)  Variable Rate Irrigation (or called VRI Site-Specific or Zone)  Conventional practice  Remote weather station

14. 14 Optimal Irrigation

15. 15 Preliminary Demonstration Results Integration Data and model development Initial performance characterization Demonstrated water savings (informal)

16. 16 Lessons Learned

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

18. 18 Integrated Decision Support Solution INPUTS STATIC DATA Soil maps Yield maps ONLINE ADVISORY SYSTEM (ex. AgriMet) Crop type, ET, weather integration, irrigation scheduling, etc. RISK MANAGEMENT ON-FARM INFORMATION Weather Pumping + distribution system Telemetry Moisture sensors OUTPUTS DATA OUTPUT Reports, trends, analysis, etc. DYNAMIC FIXED OPTIMAL IRRIGATION MANAGEMENT Uniform Fields VRI Fields Iterative Feedback Loop DECISION SUPPORT

19. 19 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. Precision Ag Irrigation Leadership (PAIL) Jointly sponsored  NW Energy Efficiency Alliance  AgGateway Driven by business needs  Voice of the Grower  Manufacturers 20+ partner companies

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

21. 21 Yield Model Calibration

22. 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. 23 Key Modeling Challenges Farm level optimization depends on all fields Optimization implies some level of deficit irrigation Irrigation depends on all farm operations

24. 24 Sites Summary (2013) Field No. Area (Ac) Crop Technology Level Pumping Lift (ft) Location M13124Canola Level 1477 OR M21121.3Canola+FCS Level 3428 M22132.1Canola Level 2515 M10125.5Field Corn Level 1379 M54122.6Field Corn Level 3365 M56123.3Field Corn Level 2360 TR24074.1Sw Corn Sd/SunFlwr Level 3528 WA TR25178.9Sw Corn Sd/SunFlwr Level 2489 TR253119Sw Corn Sd/SunFlwr Level 1509 TD5125Field Corn Level 1239 ID TD7125Field Corn Level 3258 TD11125Field Corn Level 2234 B114125Field Corn Level 3400 WA B116125Field Corn Level 2386 B21197Field Corn Level 1445