1 / 25

RS Requirements for Scheduling Irrigations

RS Requirements for Scheduling Irrigations. Tom Trout USDA-ARS, Ft. Collins, CO. Irrigated Ag 75% of water consumption 18% of cropped land 40%+ Crop Value. San Joaquin Valley. Irrigation Scheduling Approaches. Soil Water Deficit Plant Indicators Estimated Water Use (ET). 800m. 160 ac.

gavivi
Download Presentation

RS Requirements for Scheduling Irrigations

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. RS Requirements for Scheduling Irrigations Tom TroutUSDA-ARS, Ft. Collins, CO

  2. Irrigated Ag • 75% of water consumption • 18% of cropped land • 40%+ Crop Value San Joaquin Valley

  3. Irrigation Scheduling Approaches Soil Water Deficit Plant Indicators Estimated Water Use (ET)

  4. 800m 160 ac 130 ac Spatial Resolution 400m 40 ac 80 ac 200m 10 20 100m 5

  5. Temporal Resolution / Frequency Require Cumulative ETc • Continuous measurement or frequent enough to interpolate with sufficient accurately between measurements.

  6. Temporal Resolution / Frequency

  7. Requirements for Irrigation Scheduling Spatial Resolution • Acceptable – 50m • Preferred – 10m Temporal Resolution • Continuous • Weekly if good interpolation Near Real Time Easy to access and interpret Inexpensive

  8. ApproachesEnergy Balance – Thermal BandTraditional (FAO-56)with Vegetation Indices (Red/NIR)

  9. Reference ET approach(FAO-56)ETc = (kcb*ks+ke)*ETr

  10. ETr Weather Stations/Networks CIMIS – California CoAgMet – Colorado AZMET – Arizona AgriMet – NorthWest AgWeatherNet – Washington MesoNet – Oklahoma AWDN – Nebraska, Dakotas + Weather Data Library – Kansas TXHPET – Texas High Plains

  11. Reference ET approach(FAO-56)ETc = (kcb*ks+ke)*ETr

  12. Kc is related to Light Interception(Ground Cover) Develop Relationship betweenGround Cover and Kcbfor Crops

  13. Development of Reflectance-Based Crop Coefficients for Corn Transactions of the ASABE. 32(6) 1891-1900. @1990 Christopher M. U. Neale, Walter C. Bausch, Dale F. Heermann ABSTRACT Concurrent measurements of reflected canopy radiation and the basal crop coefficient (Kcb) for corn were conducted throughout a season in order to develop a reflectance-based crop coefficient model. Reflectance was measured in Landsat Thematic Mapper bands TM3 (0.63 - 0.69 um) and TM4 (0.76 - 0.90 um) and used in the calculation of a vegetation index called the normalized difference vegetation index (NDVI).

  14. Irrigation Cutoff

  15. Kcb=1.13*fc + 0.14 R2 = 0.99

  16. Kcb min = 0.15 Kcb full = Fr(min(1+0.1h,1.2))+[0.04(u-2)-.004(RH-45]*(h/3)0.3)

  17. NDVI <0.1 0.1-0.2 0.2-0.3 0.3-0.4 >0.4 NDVI Apr 4 Jun 7 Aug 26 Oct 13

  18. fc (%) <10 10-30 30-50 50-70 >70 fc fc=1.26*NDVI - 0.18 Apr 4 Jun 7 Aug 26 Oct 13

  19. <0.2 0.2-0.4 0.4-0.6 0.6-0.8 >0.8 Kcb Kcb=1.13*fc + 0.14 Apr 4 Jun 7 Kcb Aug 26 Oct 13

  20. ET (mm) <2 2-3 3-4 4-5 >5 ETcb ETcb=Kcb*ETo Apr 4 Jun 7 Aug 26 Oct 13

  21. Fractional cover

  22. Comparing years June 2000

  23. NDVI – fc – Kcb – ETcbApproach • Relatively simple, easy to implement, automate • Many RS image options, many resolutions • Fairly easy to interpolate/extrapolate – plant growth • Requires ground-based ETr • Indirect estimate of ETcb • Doesn’t include evaporation • Can’t estimate ETc of stressed crops

  24. Tom TroutUSDA-ARS, Ft. Collins, CO

More Related