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SEBAL Expert Training

SEBAL Expert Training. Presented by The University of Idaho and The Idaho Department of Water Resources Aug. 19-23, 2002 Idaho State University Pocatello, ID. The Trainers. Richard G. Allen, University of Idaho, Kimberly Research Station rallen@kimberly.uidaho.edu Wim M. Bastiaanssen

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SEBAL Expert Training

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  1. SEBAL Expert Training Presented by The University of Idaho and The Idaho Department of Water Resources Aug. 19-23, 2002 Idaho State University Pocatello, ID

  2. The Trainers Richard G. Allen,University of Idaho, Kimberly Research Station rallen@kimberly.uidaho.edu Wim M. Bastiaanssen WaterWatch,Wageningen, The Netherlandsw.bastiaanssen@waterwatch.nl Ralf Waters

  3. SEBAL • Surface Energy Balance Algorithm for Land • Developed by • Dr. Wim Bastiaanssen, International Institute for Aerospace Survey and Earth Sciences, The Netherlands • applied in a wide range of international settings • brought to the U.S. by Univ. Idaho in 2000 in cooperation with Idaho Department of Water Resources and NASA/Raytheon

  4. Why Satellites? • Typical method for ET: • weather data are gathered from fixed points -- assumed to extrapolate over large areas • “crop coefficients” assume “well-watered” situation (impacts of stress are difficult to quantify) • Satellite imagery: • energy balance is applied at each “pixel” to map spatial variation • areas where water shortage reduces ET are identified • little or no ground data are required • valid for natural vegetation

  5. Definition of Remote Sensing: The art and science of acquiring information using anon-contact device

  6. SEBAL • UI/IDWR Modifications • digital elevation models for radiation balances in mountains(using slope / aspect / sun angle) • ET at known points tied to alfalfa reference using weather data from Agrimet • testing with lysimeter (ET) data • from Bear River basin (during 2000) • from USDA-ARS at Kimberly (during 2001)

  7. How SEBAL Works SEBAL keys off: • reflectance of light energy • vegetation indices • surface temperature • relative variation in surface temperature • general wind speed (from ground station)

  8. Satellite Compatibility • SEBAL needs both short wave and thermal bands • SEBAL can use images from: • NASA-Landsat (30 m, each 8 or 16 days) - since 1982 • NOAA-AVHRR(advanced very high resolution radiometer) (1 km, daily) - since 1980’s • NASA-MODIS(moderate resolution imaging spectroradiometer) (500 m, daily) - since 1999 • NASA-ASTER(Advanced Spaceborne Thermal Emission and Reflection Radiometer) (15 m, 8 days) - since 1999

  9. Image Processing ERDAS Imagine used to process Landsat images • SEBAL equations programmed and edited in Model Maker function • 20 functions / steps run per image

  10. What Landsat Sees Land Surface Wavelength in Microns Landsat Band 6 is the long-wave “thermal” band and is used for surface temperature

  11. What We Can See With SEBAL Evapotranspiration at time of overpass Oakley Fan, Idaho, July 7, 1989

  12. Uses of ET Maps • Extension / Verification of Pumping or Diversion Records • Recharge to the Snake Plain Aquifer • Feedback to Producers regarding crop health and impacts of irrigation uniformity and adequacy

  13. Why Use SEBAL? • ET via Satellite using SEBAL can provide dependable (i.e. accurate) information • ET can be determined remotely • ET can be determined over large spatial scales • ET can be aggregated over space and time

  14. Future Applications • ET from natural systems • wetlands • rangeland • forests/mountains • use scintillometers and eddy correlation to improve elevation-impacted algorithms in SEBAL • hazardous waste sites • ET from cities • changes in ET as land use changes

  15. Reflected

  16. Net Radiation = radiation in – radiation out

  17. R H n ET ET = R - G - H n G Energy Balance for ET ET is calculated as a “residual” of the energy balance Basic Truth: Evaporation consumes Energy The energy balance includes all major sources (Rn) and consumers (ET, G, H) of energy

  18. Surface Radiation Balance Shortwave Radiation Longwave Radiation (1-eo)RL RL aRS (Incident longwave) (reflected longwave) RS RL (Reflected shortwave) (emitted longwave) (Incident shortwave) VegetationSurface Net Surface Radiation = Gains – Losses Rn = (1-a)RS + RL - RL - (1-eo)RL

  19. Preparing the Image • A layered spectral band image is created from the geo-rectified disk using ERDAS Imagine software. • A subset image is created if a smaller area is to be studied.

  20. Band 6 (low & high) Bands 1-5,7 Layering – Landsat 7

  21. Bands 1-7 in order Layering – Landsat 5

  22. Final Layering Order – Landsat 5

  23. Creating a Subset Image

  24. Creating a Subset Image

  25. Obtaining Header File Information Get the following from the header file: • Overpass date and time • Latitude and Longitude of image center • Sun elevation angle (b) at overpass time • Gain and bias ofr each and (Landsat 7 only)

  26. Method A Applicable for these satellites and formats: • Landsat 5 if original image in NLAPS format • Landsat 7 ETM+ if original image is NLAPS or FAST

  27. Locating the Header File for Landsat 7ETM+

  28. Locating the Header File for Landsat 5TM

  29. GWT Acquiring Header File Information (Landsat 5 - Method A)

  30. Biases Gains Header File for Landsat 7 (bands 1-5,7)

  31. Biases Gains Low gain High gain Header File for Landsat 7 (band 6)

  32. Header File for Landsat 7(latitude and sun elevation)

  33. DOY GWT Acquiring Header File Information (Method B)

  34. Example of Weather Data

  35. Reference ET Definition File of REF-ET Software

  36. Ref-ET Weather Station Data

  37. Ref-ET Output and Equations

  38. Reference ET Results

  39. Calculating the Wind Speed for the Time of the Image For August 22, 2000: image time is 17:57 GMT Apply the correction: timage (Local Time) = 17:57 – 7:00 = 10:57 am Δt = 1 t1 = int 10+57/60 + ½ - 0  (1) + 1 = 12 hours 1

  40. Estimate Wind Speed at 10:57 am Interpolate between the value for 12:00 (1.4 m/s) and the value for 13:00 (1.9 m/s) • U = 1.4+(1.9-1.4)[(10+57/60) – (10+1/2)] = 1.63 m/s • To estimate ETr for 10:57 AM: Interpolate between the values for 12:00 (.59) and for 13:00 (.72) • ETr = .59+(.72-.59) [(10+57/60) – (10+1/2)] = 0.65 mm/hr

  41. Surface Radiation Balance Shortwave Radiation Longwave Radiation RS RL (1-eo)RL RL (Incident shortwave) (Incident longwave) (reflected longwave) (emitted longwave) aRS (Reflected shortwave) VegetationSurface Net Surface Radiation = Gains – Losses Rn = (1-a)RS + RL - RL - (1-eo)RL

  42. a model_04 RS↓ calculator RL↑ model_09 RL↓ calculator atoa model_03 TS model_08 eo model_06 rl model_02 NDVI SAVI LAI model_05 Tbb model_07 Ll model_01 Flow Chart – Net Surface Radiation Rn = (1-a)RS↓ + RL↓ - RL↑ - (1-e0)RL↓

  43. Radiance Equation for Landsat 5

  44. Radiance Equation for Landsat 7 Ll = (Gain × DN) + Bias

  45. Model 01 – Radiance for Landsat 7c

  46. Enter values from Table 6.1 in Appendix 6 Model 01 – Radiance for Landsat 5

  47. Writing the Model for Radiance

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