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Title:   Author  item
                                            NEALE, C - Utah State Universityitem
                                            GELI, H - Utah State Universityitem
                                            Kustas, William

                                                         - *Bill*item
                                            Alfieri, Josephitem
                                            Gowda, Prasannaitem
                                            Evett, Steven

                                                         - *Steve*item
                                            Prueger, Johnitem
                                            HIPPS, L - Utah State Universityitem
                                            Dulaney, Wayneitem
                                            CHAVEZ, J - Colorado State Universityitem
                                            French, Andrewitem
                                            Howell, Terry
  Submitted to: Advances in Water Resources
                                    Publication Type: Peer Reviewed Journal
                                    Publication Acceptance Date: 10/13/2012
                                    Publication  Date: 11/30/2012
                                    Citation: Neale, C., Geli, H., Kustas, W.P., Alfieri, J.G., Gowda, P., Evett, S.R., Prueger, J.H., Hipps, L.E., Dulaney, W.P., Chavez, J., French, A.N., Howell, T.A. 2012. Soil water content estimation using a remote sensing based hybrid evapotranspiration modeling approach. Advances in Water Resources. 50:152-161.Interpretive Summary: Remote sensing of evapotranspiration (ET) has evolved over the last 20 years with the development of more robust energy balance approaches and the availability of timely remotely sensed imagery from satellite sensors.  This has allowed the use of remote sensing for near-real time water management of irrigated systems in the Western United States.  A remote sensing-based ET approach is applied to irrigated and non-irrigated cotton fields using airborne remote sensing imagery collected over the strongly advective environment of the Texas Panhandle.  The approach combines the Two-Source-Energy Balance (TSEB) model with the reflectance-based crop coefficient model.  The advantage of combining these two modeling approaches is that the TSEB model provides estimates of actual crop ET while the reflectance-based crop coefficient approach allows updating the basal crop coefficient and the interpolation and extrapolation of ET between the dates of remote sensing inputs.  This facilitates the maintenance of a soil water balance in the root zone of the crop, critical information for irrigation management.  Data assimilation techniques were used to update soil water content values using estimates based on actual ET from the TSEB model, providing feedback information to maintain the soil water balance accuracy. Actual ET estimates from the TSEB model and estimates of the soil water content in the soil profile of both irrigated and rain fed cotton fields were compared with measurements indicating significant improvement in the accuracy of soil water balance by combing these two modeling approaches.  This technique will significantly enhance the capabilities of monitoring crop root zone water content with satellite data resulting in improved water management of large irrigation systems in the Western U.S.
                                Technical Abstract: Remote sensing of evapotranspiration (ET) has evolved over the last 20 years with the development of more robust energy balance approaches and the availability of timely remotely sensed imagery from satellite sensors.  This has allowed the use of remote sensing for near-real time water management in irrigated systems in the western United States.   This paper describes the application of a hybrid ET approach to the irrigated and non-irrigated cotton fields at the BEAREX08 experiment using airborne remote sensing inputs.  The modeling approach is based on the application of the Two-Source-Energy Balance (TSEB) model and the reflectance-based crop coefficient model.   The energy balance model provides estimates of real crop ET while the reflectance -based crop coefficient approach allows for updating the basal crop coefficient and the interpolation and extrapolation of ET between the dates of remote sensing inputs facilitating the maintenance of a soil water balance in the root zone of the crop.  Actual ET estimates from the TSEB were compared with measured ET using eddy covariance systems deployed in four cotton fields during the BEAREX08 experiment. Estimates of soil water content in the soil profile of both irrigated and rain fed cotton fields were compared with measurements at different depths using the neutron probe which occurred during the experiment.  Assimilation techniques were used to update soil water content values using estimates based on actual ET from the TSEB, providing feedback information to maintain the soil water balance accuracy.


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