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Operational Evapotranspiration Algorithms for LDCM

Operational Evapotranspiration Algorithms for LDCM. Rick Allen, University of Idaho. LDCM Science Team Meeting, Jan. 10, 2007. Primary Objectives. Continue development work in surface energy balance for ET mapping (METRIC) at Landsat scale resolution

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Operational Evapotranspiration Algorithms for LDCM

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  1. Operational Evapotranspiration Algorithms for LDCM Rick Allen, University of Idaho LDCM Science Team Meeting, Jan. 10, 2007

  2. Primary Objectives • Continue development work in surface energy balance for ET mapping (METRIC) at Landsat scale resolution • Interoperability of Landsat data and ET with other satellite system data and resolutions • Use ET from energy balance to calibrate vegetation-based (reflectance-based) procedures LDCM Science Team Meeting, Jan. 10, 2007 Operational Evapotranspiration Algorithms for LDCM

  3. ET “mapping” with METRICtm • Mapping EvapoTranspiration with high Resolution and Internalized Calibration Developed by Allen, Tasumi and Trezza University of Idaho, Kimberly– development began in 2000 – rooted in the Dutch SEBAL2000 algorithms by Bastiaanssen Principle applications have been: Irrigated Agriculture Riparian Vegetation Desert Systems Wetlands LDCM Science Team Meeting, Jan. 10, 2007 Operational Evapotranspiration Algorithms for LDCM METRICtm and SEBAL are, in general, complementary processes

  4. Vegetation, water availability and thus evapotranspiration are variable in space and time LDCM Science Team Meeting, Jan. 10, 2007 Operational Evapotranspiration Algorithms for LDCM

  5. Annual Evapotranspiration by Water Source Type and by Common Land Unit Field Ground Water Mixed Water LDCM Science Team Meeting, Jan. 10, 2007 Operational Evapotranspiration Algorithms for LDCM Surface Water

  6. Applications for Endangered Species • Better ET information can Reduce Diversions by Irrigation for Endangered Salmon dewatered stream segment excess return diversion historical irrigation LDCM Science Team Meeting, Jan. 10, 2007 Operational Evapotranspiration Algorithms for LDCM

  7. (radiation from sun and sky) R n ET H (heat to air) ET = R - G - H n G (heat to ground) Why Energy balance? • ET is calculated as a “residual” of the energy balance Basic Truth: Evaporation consumes Energy LDCM Science Team Meeting, Jan. 10, 2007 Operational Evapotranspiration Algorithms for LDCM

  8. Energy balance gives us “actual” ET We can ‘see’ impacts on ET caused by: • water shortage • disease • crop variety • planting density • cropping dates • salinity • management • Energy balance requires THERMAL information • Many of these effects can be ‘missed’ by vegetation index based methods • ET reduction effects can be converted directly into an evapotranspiration coefficient LDCM Science Team Meeting, Jan. 10, 2007 Operational Evapotranspiration Algorithms for LDCM

  9. Class Name ET in mm Petroleum Tank Yards 237 Rangeland 242 Unclassified 298 Barren 335 Commercial / Industrial 380 Transportation 420 Idle Agriculture 436 Abandoned Agriculture 459 Junk Yard 467 Feedlot 479 Dairy 524 Other Agriculture 536 Public 548 Sewage Treatment Facility 552 New Subdivision 606 Farmstead 609 Rural Residential 657 Urban Residential 684 Canal 731 Irrigated Crops 812 Perennial 820 Recreation 826 Water 924 Wetland 1,025 ET BY LAND USE CLASS Boise River Valley, Idaho Benefit: New Information Cost: + $70,000 LDCM Science Team Meeting, Jan. 10, 2007 Operational Evapotranspiration Algorithms for LDCM

  10. Path 35 Path 34 METRIC applications Middle Rio Grande of New Mexico Issues: --Riparian Vegetation, --Endangered Species, --500 year old (Pueblo) Native-American Water Rights Imperial Valley, CA via Landsat 7 LDCM Science Team Meeting, Jan. 10, 2007 Operational Evapotranspiration Algorithms for LDCM

  11. Middle Rio Grande Region of New Mexico Range in ActualET from Riparian Systems LDCM Science Team Meeting, Jan. 10, 2007 Operational Evapotranspiration Algorithms for LDCM

  12. Frequency Distribution of ET 15,000 acres of cottonwood and salt cedar June Annual LDCM Science Team Meeting, Jan. 10, 2007 Operational Evapotranspiration Algorithms for LDCM

  13. Why use High Resolution Imagery? Kc 0.00 0.3 0.6 0.9 1.2 1.4 ET from individual Fields is Critical for: • Water Rights, • Water Transfers, • Farm Water Management METRIC application in La Mancha, Spain, 2003 LDCM Science Team Meeting, Jan. 10, 2007 Operational Evapotranspiration Algorithms for LDCM (Kc based on ETo)

  14. Sharpening of Thermal Band of Landsat 5 from 120 m to 30 m using NDVI Landsat 5 -- Albacete, Spain, 07/15/2003 ET ratio before sharpening ET ratio after sharpening LDCM Science Team Meeting, Jan. 10, 2007 Operational Evapotranspiration Algorithms for LDCM

  15. Why use High Resolution Imagery? Landsat vs MODIS Landsat False Color (MRG) 8/26/2002 10:33am MODIS False Color (MRG) 8/26/2002 11:02am LDCM Science Team Meeting, Jan. 10, 2007 Operational Evapotranspiration Algorithms for LDCM

  16. Why use High Resolution Imagery? Landsat 7 ET of Idaho by AVHRR-ALEXI (Anderson et al.) MODIS –near nadir scan angle MODIS -same day, large scan angle LDCM Science Team Meeting, Jan. 10, 2007 Operational Evapotranspiration Algorithms for LDCM

  17. Linear “dT” vs. Ts function Ta H ra (Tns - Ta ) Tns Surface Temperature ‘Calibration’ of METRIC • Sensible Heat Flux by ‘near surface’ dT:H = ( ρ cp)(Tns - Ta ) / ra = ( ρ cp)(dT) / ra unknown air temperatures Tns= Near Surface Temperature (floats above ‘zoh’) LDCM Science Team Meeting, Jan. 10, 2007 Operational Evapotranspiration Algorithms for LDCM

  18. How METRIC is “Trained” • At a“cold” pixel:Hcold = Rn – G - lEcold • where lEcold = 1.05 × ETr • Then, dTcold = Hcold × rah / (r × cp) • At a “hot” pixel:Hhot = Rn – G - lEhot • where lEhot ~ 0 • dThot = Hhot × rah / (r × cp) Reference ET from weather data (Penman-Monteith) LDCM Science Team Meeting, Jan. 10, 2007 Operational Evapotranspiration Algorithms for LDCM

  19. z z 2 2 H H H r r r dT dT ah ah ah z 1 z 1 Near Surface Temperature Difference (dT) • SEBAL/METRIC: dT = Tz1 – Tz2 • Tair is unknown and unneeded • SEBAL and METRICtm assume a linear relationship between Ts and dT: dT = b + aTs Bastiaanssen ingenuity • Important: Ts is used primarily as an index and can have large bias and does not need to represent aerodynamic surface temperature LDCM Science Team Meeting, Jan. 10, 2007 Operational Evapotranspiration Algorithms for LDCM

  20. Interpolation to the rest of the day (and month) (and year) LDCM Science Team Meeting, Jan. 10, 2007 Operational Evapotranspiration Algorithms for LDCM

  21. ETr F = Fraction of ETr = KcAssumption: ETr F is consistent through the day LDCM Science Team Meeting, Jan. 10, 2007 Operational Evapotranspiration Algorithms for LDCM

  22. Interpolation for Monthly or Seasonal ET LDCM Science Team Meeting, Jan. 10, 2007 Operational Evapotranspiration Algorithms for LDCM

  23. Seasonal ET LDCM Science Team Meeting, Jan. 10, 2007 Operational Evapotranspiration Algorithms for LDCM

  24. Comparison with Lysimeter Measurements: 1968-1991 Lysimeter at Kimberly (Wright) 12/17/01 LDCM Science Team Meeting, Jan. 10, 2007 Operational Evapotranspiration Algorithms for LDCM

  25. METRIC ET for period Kimberly, Idaho – Periods between Satellites Sugar Beets, 1989 Kimberly, Idaho Lysimeter data by Dr. J.L. Wright, USDA-ARS LDCM Science Team Meeting, Jan. 10, 2007 Operational Evapotranspiration Algorithms for LDCM

  26. METRIC Comparison of Seasonal ET by METRICtm with Lysimeter Sugar Beets ET (mm) - April-Sept., Kimberly, 1989 METRIC 714 mm Lysimeter718 mm LDCM Science Team Meeting, Jan. 10, 2007 Operational Evapotranspiration Algorithms for LDCM

  27. wet fields Variation in ET Each point represents one field ETrF = Fraction of Reference ET =  from weather data NDVI = Normalized Difference Vegetation Index LDCM Science Team Meeting, Jan. 10, 2007 Operational Evapotranspiration Algorithms for LDCM

  28. “mean” Kc vs. NDVI Well-watered fields Kc ~ 1.18 NDVI + 0.04 LDCM Science Team Meeting, Jan. 10, 2007 Operational Evapotranspiration Algorithms for LDCM

  29. ETc from NDVI vs. from METRIC (Averages for 100’s of fields and Kc vs. NDVI is calibrated from METRIC) LDCM Science Team Meeting, Jan. 10, 2007 Operational Evapotranspiration Algorithms for LDCM

  30. Conclusions • ET maps are valuable for: • Determining Actual ET • Water Transfers • Water Rights Conflicts • Diversion Management for Endangered Species • Ground-water Management • Consumption by Riparian Vegetation • ET maps by METRICtm(and SEBAL) have good accuracy and consistency • A single, high resolution thermal band is adequate and essential LDCM Science Team Meeting, Jan. 10, 2007 Operational Evapotranspiration Algorithms for LDCM

  31. More information at: www.kimberly.uidaho.edu/water/ (METRICtm) http://www.idwr.idaho.gov/gisdata/et.htm http://maps.idwr.idaho.gov/et/ LDCM Science Team Meeting, Jan. 10, 2007 Operational Evapotranspiration Algorithms for LDCM

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