Submitted to: Irrigation Science
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 7/16/2007
Publication Date: 3/1/2008
Citation: Gowda, P., Chavez Eguez, J.L., Colaizzi, P.D., Evett, S.R., Howell, T.A., Tolk, J.A. 2008. ET mapping for agricultural water management: Present status and challenges. Irrigation Science. 26:223-237.
Interpretive Summary: Evapotranspiration (ET) is an essential component of the water balance and a major consumptive use of irrigation water and precipitation on crop land. In this paper, a brief review of numerous remote sensing based models was made to assess the current status of research, underlying principle for each method, data requirements, and their strengths and weaknesses. Although the remote sensing based ET models have been shown to have the potential to accurately estimate regional ET, opportunities exist to further improve these models. Further, the existing set of earth observing satellite platforms are not sufficient enough to be used in the estimation of spatially distributed ET for on-farm irrigation management purposes.
Technical Abstract: Evapotranspiration (ET) is an essential component of the water balance. Remote sensing based agrometeorological models are presently most suited for estimating crop water use at both field and regional scales. Numerous ET algorithms have been developed to make use of remote sensing data acquired by sensors on airborne and satellite platforms. In this paper, a literature review was done to evaluate numerous commonly used remote sensing based algorithms for their ability to accurately estimate regional ET. The reported ET estimation accuracy varied from 67 to 97% for daily ET and above 94% for seasonal ET, indicating that they have the potential to accurately estimate regional ET. However, there are opportunities to further improve these models through developing methods to accurately estimate surface aerodynamic temperature. The spatial and temporal remote sensing data from the existing set of earth observing satellite platforms are not sufficient enough to be used in the estimation of spatially distributed ET for on-farm irrigation management purposes, especially at a field scale level (~10-200 ha). This will be constrained further if the thermal sensors on future Landsat satellites are abandoned. However, research opportunities exist to improve the spatial and temporal resolution of ET by developing algorithms to increase the spatial resolution of surface temperature data derived from Landsat/ASTER/MODIS thermal images using same/other-sensor high resolution multi-spectral images.