Develop a Remote Sensing Tool to Estimate Evaporation Loss from Reservoirs

1. Develop a Remote Sensing Tool to Estimate Evaporation Loss from Reservoirs Junming Wang, Ted Sammis, Vince Gutschick Department of Plant and Environmental Sciences New Mexico State University Ramiro Lujan Comisión Internacional de Límites y Aguas (CILA, the Boundary and Water Commission in Mexico) 2008 SCERP Annual Technical Conference, Arizona State University Memorial Union Tempe, Arizona, December 5-6, 2008

2. Introduction A treaty requires that US (Mexico) delivers certain amount water to Mexico (US) each year. However, in some drought years, it may not be followed. Farmers complained. Mexico had amassed a water deficit to the US since 1992 that reached 1.5 million acre-feet at its highest point, costing U.S. agricultural producers in the Rio Grande Valley $1 billion.

3. Evaporation loss • Part of the water delivery problems for both countries was the amount of water being used by reservoir evaporation in the upstream storage reservoirs.

4. Introduction Elephant Butte Lake

5. Introduction Figure 1. Map of Elephant Butte Reservoir and Las Cruces area, NM, USA. From maps.google.com

6. Objective • The general objective of the research was to develop a remote sensing tool to estimate evaporation (E) loss (mm/day or m3) from reservoirs to aid international water delivery management.

7. Ground measurements of evaporation • Inflow–outflow water balance method, pan measurement method, or eddy covariance method are time- and labor-intensive and one point measurement can not integrate the spatial variability of lake evaporation.

8. Remote sensing methods to estimate ET • Surface energy balance algorithm for land (SEBAL) is a residual method of energy budget, developed by [Bastiaanssen et al., 1998] • It is more operational than other models for ET • Need to calibrate the parameters for water body

9. Method • Based on SEBAL, a Remote Sensing ET model was developed and validated for ASTER data for land ET • The model was modified for MODIS input data and was calibrated and validated using a water balance lake evaporation calculation .

10. Build the modelTheory Build the ASTERModel ETins = Rn - G - H R H n ETins G Graph from Allen, et. al., (2002)

11. Start Build the ASTER Model Satellite inputs: surface temperature and reflectance. Local weather inputs: solar radiation, humidity and wind speed Rn=f(Rs, reflectance) General flowchart NDVI=f(reflectance) G=f(NDVI, solar radiation, reflectance) H=f(NDVI, temperature, reflectance, solar radiation, wind speed) ETins=Rn-H-G End

12. Build the ASTER Model Validate the modelMeasurement sites Pecan orchard Alfalfa field

13. Validate the ASTER Model ET measurement Li Cor system

14. Validate the ASTER Model ET map mm/day

15. Validate the ASTER Model The pecan ET of simulation vs. observation.

16. Validate the ASTER Model

17. Calibration for MODIS model • Rn • C (G/Rn)

18. Rn from data in 2005 at Elephant Butte Lake(Almy, 2006)

19. G/Rn • Using Roosevelt lake E data (Water balance) ETins = Rn - G - H

21. mm

22. MODIS model validation Figure 5. Modelled ET from MODIS data taken on June 8, 2005. ET unit: mm/day.

23. ET values obtained from MODIS data compared with the ET values from ASTER data at Las Cruces, NM, USA for June 8, 2005, September 7, 2003, May 18, 2003, and September 4, 2002, .

25. Conclusions • For the summer time E estimate, the accuracy is within 1.5 mm/day. The evapotranspiration accuracy is about 85%. • The model is capable for aiding international water delivery management. • The average evaporation of Elephant Butte Reservoir in summer time was 5.6 mm/day.

26. Publications Referred Journal Paper Wang, J. and T. W. Sammis. 2008. Sensitivity Analysis on Remote Sensing Evapotranspiration Algorithm-Surface Energy Balance Algorithm for Land. ASABE Transaction. Submitted.  Wang, J., T.W. Sammis, and V.P. Gutschick. 2008. Review of Satellite Remote Sensing Use in Forest Health Studies. Applied Remote Sensing. Submitted. Wang, J., T.W. Sammis, and V.P. Gutschick. 2008. Remote Sensing of Water Body Evaporation. Applied Remote Sensing. Submitted. Wang, J. and T. W. Sammis. 2008. New Automatic Band and Point Dendrometers for Measuring Stem Diameter Growth. ASABE Ag. Engineering. In press. Conference Proceedings Wang, J., T.W. Sammis, and V.P. Gutschick. 2008. A Model Estimating Lake Evaporation Using MODIS Data. International Geoscience and Remote Sensing Symposium. 2008 IEEE International Geoscience & Remote Sensing Symposium. July 6-11. 2008. Boston, Massachusetts, U.S.A. Wang, J., T.W. Sammis, and V.P. Gutschick. 2008. A Remote Sensing Model Estimating Water Body Evaporation. 2008 International Workshop on Earth Observation and Remote Sensing Applications. June30-July2. Beijing, China.

27. Evaporation loss at Amistad Reservoir in Mexico

30. Internet Site http://hydrology1.nmsu.edu/

32. Acknowledgements • Dr. Thomas Schmugge at NMSU provided ASTER data • Graduate research assistants. • USGS provided the water balance data. • This publication was made possible by a grant from the Southwest Consortium for Environmental Research and Policy (SCERP).

33. Thank You!