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Weeds & Weather: Local to Regional Daily Simulations

Weeds & Weather: Local to Regional Daily Simulations. 7 October 2009 Midwest Weather Network. Aurora, South Dakota (S. Clay, SDSU). 4 wks. Common Ragweed. Sunflower emerges before ragweed. Emergence was earlier in 2007. At 50% emergence, gap between years was substantial.

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Weeds & Weather: Local to Regional Daily Simulations

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  1. Weeds & Weather: Local to Regional Daily Simulations 7 October 2009 Midwest Weather Network

  2. Aurora, South Dakota (S. Clay, SDSU) 4 wks Common Ragweed • Sunflower emerges before ragweed. • Emergence was earlier in 2007. • At 50% emergence, gap between years was substantial. • Why the difference? • What are causes for patterns? • Can patterns be predicted? 2 wks Common Sunflower

  3. 10 20 30 40 50 60 70 80 } • Temperature • Water • O2, CO2, etc. • Seed density • Seedling emergence • potential Soil Microclimate • Many variables change substantially with each cm of depth in the soil profile. • Several of these variables affect weed seeds. • Thus, understanding their dynamics with soil depth is critical.

  4. Kurt Spokas Jim Eklund Curt Bredeson Dean Peterson New Tools • SeedChaser • SolarCalc • SolarCalQ • Global TempSim • STM2 • SeedChaser • WeatherEze Greta Gramig All lead to a new and more universal WeedCast-type software that we tentatively are calling PhenPac (phenology package).

  5. http://www.ars.usda.gov/Services/docs.htm?docid=11787

  6. Insect development Pesticide fate Nematode activity Fertilizer fate Plant uptake Cyst survival

  7. So, what do we need to do?

  8. Simple weather data needed

  9. Organic matter scale In STM2 specify soil type and organic matter, and attach simple weather data file. • Also needed or optional: • More sophisticated soil traits can be entered for site specificity. • Percent shade and water runoff choices are optional. • Geographic location & elevation.

  10. Output from STM2

  11. Manipulated output

  12. Unlikely base T and base ψ

  13. Better base T and base ψ Fit a Weibull or other type of function to data, and that’s the HTT model.

  14. Unlikely base T and base ψ

  15. Better base T and base ψ

  16. Perugia is one of many EWRS sites

  17. EWRS soils were shaded in 2006

  18. Simulated average daily soil temperatures Perugia, Italy (Shaded soil option in STM2)

  19. Rain in Perugia, Italy, 2006

  20. Weed Seed Movement • Largest factor is farming operations - soil tillage: mostly vertical redistribution - combine harvesting: mostly horizontal movement • Excellent data already collected in Europe on this topic

  21. SeedChaser Colored Beads buried at known depths Implement Pass Beads excavated. Depth, color, and horizontal displacement of each bead is recorded Transition matrices Literature data • Availability? Web download • www.ars.usda.gov/mwa/ncscrl • Model is also being used as: • Teaching aid • Extension aid • Research aid

  22. Lambsquarters in Perugia, Italy(Depth distribution of seeds known)

  23. Summary • Predictions are not yet perfect, but they are getting better. • Ability to simulate soil microclimate easily, at several depths, & worldwide, has been a critical achievement for us. • Resulting models (& software) have universal application for helping fine-tune weed management decisions. • The next step is daily automated downloading of data from region-wide weather stations. We do this already with WeatherEze & METAR sites.

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