ET mapping for agricultural water management: present status and challenges

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 estimate regional ET accurately. The reported estimation accuracy varied from 67 to 97% for daily ET and above 94% for seasonal ET indicating that they have the potential to estimate regional ET accurately. However, there are opportunities to further improving these models for accurately estimating all energy balance components. 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 to 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 reflectance and surface temperature data derived from Landsat/ ASTER/MODIS images using same/other-sensor high resolution multi-spectral images.

SEBAL-A: A Remote Sensing ET Algorithm that Accounts for Advection with Limited Data. Part II: Test for Transferability

“…Generally, researchers report SEBAL errors on daily ET estimation to range between 2% and about 35%. Gowda et al [25] reported an average accuracy of 85%, while Trezza [26] found the error to range from 2.7% to 35%, with 18.2% being the average error. Singh et al [9] found that ETc estimated using SEBAL could be within 5% of measured ETc.…”

Evapotranspiration Estimation with Remote Sensing and Various Surface Energy Balance Algorithms—A Review

“…The performance of the METRIC model has been tested by Gowda et al [60] in the Texas High Plains on two different days in 2005 using Landsat 5 TM data by comparison of resultant daily ET estimates with measured values derived from soil moisture budget. Integration of water balance model with METRIC estimated ET could provide significant improvements in the irrigation schedules as found in Spain by Santos et al [101].…”

“…Remote sensing based evapotranspiration estimation and its development has been reviewed from time to time [40,47,55]. This issue has been addressed from a hydrological perspective by Overgaard et al [58] with particular emphasis to plant sciences, agronomy, and irrigation applications [59,60]. Farahani et al [61] provide a focused survey of progress in crop evapotranspiration measurement and modeling with particular emphasis on the aspects of irrigational interest.…”

Mapping reference evapotranspiration from meteorological satellite data and applications

“…On global basis, the mean ET accounts for more than half of the total precipitation fallen on land surfaces (Chahine 1992;Oki and Kanae 2006). ET is also the major irrigation water and precipitation use on agricultural lands (Gowda et al 2008). ET rates are affected by many factors, such as ground solar radiation (GSR), wind speed, air temperature and humidity, soil water content, vegetation type, growth stage, planting density, and management practices, etc.…”

“…A substantial number of remote sensing algorithms, varied greatly in main assumptions and input requirements, have been proposed over the past few decades to provide ET mapping at different time and spatial scales (Jiang and Islam 2003;Gowda et al 2008;Kalma et al 2008;Li et al 2009;Jiménez et al 2011;Liou and Kar 2014). Remote sensed land surface temperature (LST) is the most critical input for many of those proposed algorithms.…”