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Abstract. The quantification of evapotranspiration from irrigated areas is important for agriculture water management, especially in arid and semi-arid regions where water deficiency is becoming a major constraint in economic welfare and sustainable development. Conventional methods that use point measurements to estimate evapotranspiration are representative only of local areas and cannot be extended to large areas because of landscape heterogeneity. Remote sensing-based energy balance models are presently most suited for estimating evapotranspiration at both field and regional scales. In this study, we aim to develop a methodology based on the triangle concept, allowing estimation of evapotranspiration through the classical equation of Priestley and Taylor (1972) where the proportional coefficient α in this equation is ranged using a linear interpolation between surface temperature and Normalized Difference Vegetation Index (NDVI) values. Preliminary results using remotely sensed data sets from Landsat ETM+ over the Habra Plains in west Algeria are in good agreement with ground measurements. The proposed approach appears to be more reliable and easily applicable for operational estimation of evapotranspiration over large areas.

4559 ABSTRACTThe quantification of evapotranspiration from irrigated areas is important for agriculture water management, especially in arid and semiarid regions where water deficiency is becoming a major constraint in economic welfare and sustainable development. Conventional methods that use point measurements to estimate evapotranspiration are representative only of local areas and cannot be extended to large areas because of heterogeneity of landscape. Remote sensing based energy balance models are presently most suited for estimating evapotranspiration at both field and regional scales. In this study, SEBAL (Surface Energy Balance Algorithm for Land), a remote sensing based evapotranspiration model, has been applied with Landsat ETM+ sensor for the estimation of actual evapotranspiration in the Habra plain, a semiarid region in west Algeria with heterogeneous surface conditions. This model followed an energy balance approach, where evapotranspiration is estimated as the residual when the net radiation, sensible heat flux and soil heat flux are known. It involves in the input the remote sensing land surface parameters such as surface temperature, NDVI and albedo. Different moisture indicators derived from the evapotranspiration were then calculated: evaporative fraction, Priestley-Taylor parameter and surface resistance to evaporation. These calculated indicators facilitate the quantitative diagnosis of moisture stress status in pixel basis. The study area contains extremes in surface albedo, vegetation cover and surface temperature. The land uses in this study area consists of irrigated agriculture, rain-fed agriculture and livestock grazing. The obtained results concern the validation of the used model for spatial distribution analysis of evapotranspiration and moisture indicators. The evaluation of daily evapotranspiration and moisture indicators are accurate enough for the spatial variations of evapotranspiration rather satisfactory than sophisticated models without having to introduce an important number of parameters in input with difficult accessibility in routine. In conclusion, the results suggest that SEBAL can be considered as an operational method to predict actual evapotranspiration from irrigated areas having limited amount of ground information.

Accurate spatio-temporal estimation of evapotranspiration (ET) and surface energy fluxes is crucial for many agro-environmental applications, including the determination of water balance, irrigation scheduling, agro-ecological zoning, simulation of global changes in land use and forecasting crop yields. Remote sensing based energy balance models are presently most suitable for estimating ET at both temporal and spatial scales. This study presents an intercomparison of ET maps over the Habra plain in western Algeria obtained with two different models: Ts/VI trapezoid (Surface temperature/Vegetation Index Trapezoid Model) and SEBAL (Surface Energy Balance Algorithm for Land). Ts/VI trapezoid is the most used model, due to its simplicity, ease of use, few data input requirements and relatively high accuracy. It allows estimating ET directly by using the Priestley-Taylor equation. Whereas SEBAL allows estimating ET as the residual term of the energy balance equation, by using a rather complex hot and cold pixel based contextual approach to internally calibrate sensible heat flux through an iterative approach. The data set consists of four Landsat-8 OLI/TIRS images acquired on 2018-2019 and some ground measurements. In conclusion, the results show that SEBAL and Ts/VI trapezoid models provide comparable outputs and suggest that both the two models are suitable approaches for ET mapping over agricultural areas where ground measurements are scarce or difficult to collect.

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