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Greg Easson, H. G. Momm The University of Mississippi Ronald Bingner

Evaluation for the Integration of a Virtual Evapotranspiration Sensor Based on VIIRS and Passive Microwave Sensors into the Annualized Agricultural Non-Point Source (AnnAGNPS) Pollution Model. Greg Easson, H. G. Momm The University of Mississippi Ronald Bingner

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Greg Easson, H. G. Momm The University of Mississippi Ronald Bingner

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  1. Evaluation for the Integration of a Virtual Evapotranspiration Sensor Based on VIIRS and Passive Microwave Sensors into the Annualized Agricultural Non-Point Source (AnnAGNPS) Pollution Model Greg Easson, H. G. Momm The University of Mississippi Ronald Bingner USDA – ARS – National Sedimentation Laboratory

  2. Project Objectives • To investigate the feasibility of using existing NASA results as source of ET estimates for AnnAGNPS pollution model • To evaluate the continuity of the NASA-based remotely sensed ET estimates by the future missions

  3. Project Rationale • Evapotranspiration (ET) plays an important role for modeling surface-lower atmospheric flux processes • ET estimates in a continuous and spatially distributed fashion represents a challenge for scientists • Remote sensing-based techniques are sought as an possible alternative

  4. Background: AnnAGNPS • The Annualized Agricultural Non-Point Source • Pollution model is a continuous watershed-scale computer simulation tool used to generate loading estimates for some constituents of agricultural non-point source pollution

  5. Background: AnnAGNPS (continued) • Developed by USDA-NRCS • Event driven model • Simulates • Surface flow • Sediment • Nutrients • Pesticides • Used to evaluate Best Management Practices

  6. Background: AnnAGNPS (continued) • Watershed is divided into cells • Each of these cells requires 22 parameters • Climate data is derived from field weather stations located within or nearby the watershed • Thiessen polygon method

  7. Background: AnnAGNPS (continued) • Problem when field weather stations are sparse or even non-existing

  8. Project Objectives • To investigate the feasibility of using existing NASA results as source of ET estimates for AnnAGNPS pollution model • To evaluate the continuity of the NASA-based remotely sensed ET estimates by the future missions

  9. Evaluation of the Integration of NASA Results into AnnAGNPS • Modifications to AnnAGNPS • Concept of “Virtual” field weather stations

  10. Evaluation of the Integration of NASA Results into AnnAGNPS (continued) • Modifications to AnnAGNPS

  11. Evaluation of the Integration of NASA Results into AnnAGNPS (continued) • Study Site Long history of hydrologic work Extensive infrastructure USDA-ARS NSL past and ongoing projects

  12. Evaluation of the Integration of NASA Results into AnnAGNPS (continued) • MOD16 daily images for 2004 • Provided by scientists at The University of Montana (Nishida et al., 2003, Cleugh et al., 2007, and Mu et al., 2007). • Ground sampling distance (GSD) of approximately 5,000 meters

  13. Evaluation of the Integration of NASA Results into AnnAGNPS (continued) • Two AnnAGNPS simulations • ET computed using the Penman equation • ET provided proxy-MOD16

  14. Evaluation of the Integration of NASA Results into AnnAGNPS (continued) • Results: • Average watershed ET

  15. Evaluation of the Integration of NASA Results into AnnAGNPS (continued) • Results: • Daily runoff

  16. Evaluation of the Integration of NASA Results into AnnAGNPS (continued) • Results: • Spatial distribution of the 2004 annual percent difference between ET from AnnAGNPS and from MODIS

  17. Evaluation of the Integration of NASA Results into AnnAGNPS (continued) • Results: • Spatial distribution of the 2004 annual percent difference between runoff from AnnAGNPS and from MODIS

  18. Project Objectives • To investigate the feasibility of using existing NASA results as source of ET estimates for AnnAGNPS pollution model • To evaluate the continuity of the NASA-based remotely sensed ET estimates by the future missions

  19. Comparison of Existing and Future NASA Results • Due to the lack of published methodology describing the generation of ET estimates from VIIRS data, a different approach was considered • Using the relationship between ET, VI, and LST, daily ET maps were generated from models created using multivariate linear regression techniques

  20. Comparison of Existing and Future NASA Results (continued) • Lambin and Ehrlich’s feature space

  21. Comparison of Existing and Future NASA Results (continued) • Daily images from April 01, 2004 to July 31, 2004 • Re-sampled to 5,000 GSD 250 meter MODIS NDVI pixels 1,000 meter MODIS LST pixels 400 meter proxy-VIIRS NDVI pixels 750 meter proxy-VIIRS LST pixels

  22. Comparison of Existing and Future NASA Results (continued) • “Virtual” stations “Virtual” Field

  23. Comparison of Existing and Future NASA Results (continued) • Simplified representation DOY 1 DOY 2 DOY 3 DOY 4 5 5 5 5 1 2 1 2 1 2 1 2 3 4 3 4 3 4 3 4 1 2 3 4 5 4 5 2 3 1 DOY 3 4 5 1 2 4 5 1 2 3 Stations

  24. Comparison of Existing and Future NASA Results (continued) • Simplified representation

  25. Comparison of Existing and Future NASA Results (continued) • Model development • Stations 127 to 136 (physical stations) • Stepwise backward elimination (P-value associated with Pearson’s Chi-Squared). • One model per day for each of the sensors considered

  26. Comparison of Existing and Future NASA Results (continued) • Adjusted R2 > 0.25

  27. Comparison of Existing and Future NASA Results (continued) • Results • Variability of models performance • Adjusted R2 • Predictors

  28. Comparison of Existing and Future NASA Results (continued)

  29. Comparison of Existing and Future NASA Results (continued) • Simplified representation

  30. Comparison of Existing and Future NASA Results (continued)

  31. Conclusions • Linking MODIS ET with AnnAGNPS was successfully performed. • The use of MODIS ET can reduce the need to collect/generate dew point, wind speed, and cloud coverage.

  32. Conclusions (continued) • Reducing uncertainty in input parameters will reduce the uncertainty in the model results. • In addition, these values usually have temporal and spatial variability that are not easily taken into consideration when computing ET values.

  33. Conclusions (continued) • MODIS-ET produced 35% less ET then AnnAGNPS-ET and resulted in a 10% increase in runoff. • Large watershed system, climate parameters can be highly variable.

  34. Conclusions (continued) • MODIS-ET provided a more comprehensive spatial variability capability than is not often available from measured climate stations. • Additional remotely sensed data: precipitation and temperature.

  35. Conclusions (continued) • The second objective of this research project was to investigate the continuity of future NASA missions in providing ET estimates to AnnAGNPS simulation model. • Daily NDVI and LST maps from MODIS and proxy-VIIRS data were used to create two sets of daily ET maps.

  36. Conclusions (continued) • Direct comparison between these two sets of daily ET maps indicates that the next generation of moderate resolution sensor will continue to be a potential source of ET estimates to simulation models such as AnnAGNPS. • The VIIRS’s physical design features, such as improved signal to noise ratio and the attenuation of the “bowtie-shaped” footprint at large scan angles were not considered.

  37. Conclusions (continued) • The spatial variability demonstrated by the VIIRS-based LST map can be in part attributed to the downscaling technique used in the simulation process. • Further investigation should be conducted to estimate ET for different land use/land cover classes.

  38. Conclusions (continued) • There are situations were the ET maps generated from VIIRS and from MODIS agreed. • This demonstrates the potential of VIIRS to be used as the continuity mission, in providing ET estimates for AnnAGNPS pollution model.

  39. Acknowledgements • Institute for Technology Development • National Sedimentation Laboratory • The University of Montana • NASA and the University of Southern Mississippi

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