Daily evapotranspiration by combining remote sensing with ground observations: Study from Maricopa,...

Daily evapotranspiration by combining remote sensing with ground

observations: Study from Maricopa, Arizona USA

Andy French and Doug Hunsakerandrew.french@ars.usda.gov

U.S. Arid Land Agricultural Research Center, USDA/ARS, Maricopa, AZ USA

Obtaining Daily ET Estimates Useful for Growers

•Remote sensing provides synoptic views and ways to model instantaneous ET•Obstacles;• Image data too infrequent• Or too coarse• Costly

•Combine remote sensing data with ground observations• Obtain image data as available• Continuous monitoring of meteorology and land surface temperatures• Model spatial LST and vegetation cover • Compute surface energy balance hourly, integrate to daily

Penman-Monteith Equation

DiabaticFlux

AdiabaticFlux

Energy Flux Equations

Surface Flux Modeling Remote Sensing Inputs

NDVI

Temperature

Surface Energy Balance ASTER El Reno, Oklahoma

4 Sep 2000

SensibleHeat

LatentHeat

Daily Evapotranspiration4 Sep 2000

90 m

91 m

64%

4%

FAO Irrigation Scheduling Experiment SiteMaricopa, Arizona

Integrated Monitoring of Crop and Irrigation

Wireless-Based Sensors for Water Management

Maricopa Irrigation Scheduling Experiment 2003Cotton

Simplifying LST to Assist Daily Forecast of ET

Heat Units and Kalman Filtering to Forecast Spatially Distributed Cover & LST

Need Mean & SD Cover Estimates

Daily ET Modeling & Accuracy Assessment

Use parameter uncertainties to model ET uncertaintyCompare ET estimates against P-M and soil moisture

Remote Sensing Resolution and Local Vegetation/Soil Scales

Thermal Imaging & ET: Some Variations Irrelevant for Daily Estimates

Winter Wheat Grazingland

NDVI NDVI

Emissivity

Newer Remote Sensing CapabilitiesMultispectral Thermal Infrared

Emissivity Change at Palo Verde Irrigation District 2007-8

Conclusions

•Combined Remote Sensing & Ground-Based Sensors •Daily ET for Water Management•Reasonable resolution & forecast potential•Reasonable Cost•New satellite sensors will improve ET estimation accuracies•Uncertainty estimation important part of advisory system