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Title: EVAPOTRANSPIRATION ESTIMATES OBTAINED FROM REMOTE SENSING DATA

Author
item Doraiswamy, Paul
item Prueger, John
item Hatfield, Jerry

Submitted to: Remote Sensing in Hydrology Symposium
Publication Type: Proceedings
Publication Acceptance Date: 4/7/2000
Publication Date: N/A
Citation: N/A

Interpretive Summary:

Technical Abstract: Evapotranspiration represents one of the largest components of the energy balance. The amount of available energy used in the evaporation of water from water, soil, and plant surfaces can account for up to 80% of the energy on a weekly average. There is variation among surfaces, natural or cropped, in the partitioning of energy either on a daily or seasonal basis. There have been several attempts at using remotely sensed data from the visible, near-infrared, and thermal regions of the spectrum to estimate energy balance components. We have assembled a data base that includes field scale measurements of the energy balance and evapotranspiration throughout the year and coupled that with data obtained from AVHRR platforms. These data have been combined to estimate evapotranspiration from corn and soybean crops across Iowa. Water use from major crops in Iowa is critical to assess the level of crop stress. The field-based measurements have been used to provide a ground-based measurement of crop water used in order to verify the performance of the model. The model uses the visible and near-infrared wavebands to infer available energy and the thermal bands to measure surface temperature. When combined, these regions of the spectrum provide the critical components of the evapotranspiration model. Using this resolution of data doesn't permit the application of the model to individual fields and is used for large scale assessment of water use and tracking variations across the state. The agreement between the field scale measurements and the model using remotely sensed data was within 10% throughout the growing season. It is possible to apply this form of the model to other areas with little change in the model.