1 / 41

Development of a Procedure for Estimating Crop Evapotranspiration over Short Periods

Development of a Procedure for Estimating Crop Evapotranspiration over Short Periods. Dr. Jorge Gonzalez, Professor Dept. of Mechanical Engineering Santa Clara University. Eric Harmsen, Associate Professor Richard Diaz, Research Assist.

chico
Download Presentation

Development of a Procedure for Estimating Crop Evapotranspiration over Short Periods

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. Development of a Procedure for Estimating Crop Evapotranspiration over Short Periods Dr. Jorge Gonzalez, Professor Dept. of Mechanical Engineering Santa Clara University. Eric Harmsen, Associate Professor Richard Diaz, Research Assist. Dept. of Agr. and Biosystems Eng. Civil Engineering Department University of Puerto Rico University of Puerto Rico

  2. Acknowledgements • NASA-EPSCoR (NCC5-595), NOAA-CREST, USDA-TSTAR, NASA-URC, and UPRM-TCESS. • Individuals: Javier Chaparro, Antonio Gonzalez, Jose Paulino-Paulino, and Dr. Ricardo Goanaga of the USDA Tropical Agricultural Research Station in Mayaguez, PR. • The ATLAS Sensor was provided by NASA Stennis Space Center and the Lear Jet Plane was provided by NASA Glenn Research Center.

  3. Water Use • Agriculture is the greatest consumer of water in society. • It is estimated that 69% of all water withdrawn on a global basis is used for agriculture.

  4. Water Losses • Large losses of irrigation water are common. • Irrigation efficiencies on the order of 50% are typical.

  5. The ability to estimate short-term latent heat fluxes (i.e., crop water use) from remotely sensed data is an essential tool for managing the worlds future water supply. • However, validation of these sensors is necessary.

  6. Objective • To describe a relatively inexpensive method for estimating short-term (e.g., hourly) actual evapotranspiration. • Present validation results for the method • Present application example results from two field studies conducted in Puerto Rico.

  7. Methodology Combine Humidity Gradient and Generalized Penman-Monteith Methods

  8. Generalized Penman-Monteith Method (GPM) ET = evapotranspiration Δ = slope of the vapor pressure curve Rn = net radiation G = soil heat flux density ρa = air density cp = heat capacity of air λ = psychrometric constant T = mean daily air temperature at 2 m height u2 = wind speed at 2-m height es = saturated vapor pressure and ea is the actual vapor pressure rs and ra = bulk surface resistance and aerodynamic resistance, respectively.

  9. Simplified representation of the (bulk) surface resistance and aerodynamic resistances for water vapor flow (from Allen et al., 1989).

  10. Aerodynamic Resistance (ra) ra = aerodynamic resistance zm = height of wind measurement zh = height of the humidity measurement d = zero plane displacement h = crop height k = von Karman’s constant uz = wind speed at height z

  11. Humidity Gradient Method (HGM) ET = evapotranspiration ρa = density of air cp = heat capacity of air ρw = density of water ρvL = water vapor density at height L ρvH = water vapor density at height H rs = bulk surface resistance ra = aerodynamic resistance = ζ/ u2 u2 = wind velocity at 2 m

  12. Elevator Device

  13. Method Validation

  14. Eddy Covariance System Eddy-Covariance System

  15. Eddy Covariance System

  16. ET Station

  17. ET Results - UF Agr. Experiment Station - April 6th, 2005

  18. RH results over a 15-minute periodUF Agr. Experiment Station April 6th, 2005

  19. Actual Vapor Pressures and Actual Vapor Pressure DifferencesUF Agr. Experiment Station - April 6th, 2005

  20. Comparison: eddy covariance system and ET station U of F Agr. Experiment Station April 5th and 6th, 2005

  21. Comparison: eddy covariance system and ET station U of F Agr. Experiment Station April 5th, 2005

  22. Comparison: eddy covariance system and ET station U of F Agr. Experiment Station April 6th, 2005

  23. Vapor Pressure Monteith and Unsworth, 1990

  24. Monteith and Unsworth, 1990 Temperature

  25. Application Example No. 1 Estimation of ET and aerodynamic resistance for sugarcane, Lajas, PR

  26. Estimated ET for a sugarcane plot November 9, 2004, Lajas, PR ET = 1.3 mm/day and ζ = 305

  27. Estimated surface and aerodynamic resistances for a sugarcane plot November 9, 2004, Lajas, PR

  28. Measured Net Radiation for a sugarcane plot Oct. 31st and Nov. 9, 2004 Lajas, PR

  29. Application Example No. 2The ATLAS Mission • On February 11th, 2004, the ATLAS was used to evaluate the Urban Heat Island Effect within the San Juan Metropolitan area. • A ground-based study was conducted at the University of Puerto Rico Agricultural Experiment Station in Rio Píedras.

  30. The ATLAS Mission

  31. Estimated ET for a grass-covered field Nov. 11, 2004, Rio Piedras, PR ET = 3.7 mm/day and ζ = 208 and rs = 90 sm-1 0.53 mm/hr Time of fly-over 2:25 PM

  32. Remote Sensing ET Equation ρv is the vapor density of the air measured at the ground surface. ρvs is the actual vapor pressure based on the corrected remotely sensed surface temperature

  33. ATLAS-Estimated Surface Temperature for a grass-covered field Nov. 11, 2004, Rio Piedras, PR ATLAS surface temperature correction: 33.0 oC – 29.8 oC= 4.2 oC

  34. Areal Photo Surface Temperature

  35. 31.78 oC 4 33.95 oC 5

  36. Temperature and ET variation with distance from the ocean The estimated ET varied 0.1 mm/hr over the 20 km transect.

  37. Relative Cost Comparison of Direct ET Methods

  38. Future Work • Additional method validation. • Utilize the ET station to estimate evapotranspiration rates and factors (ra, rs, Kc, Ks). • Deploy numerous stations around Puerto Rico to validate/calibrate remote sensing estimates of surface temperature, ET and the surface energy balance.

More Related