Evapotranspiration (ET) is one of the complex, but essential components of the hydrologic cycle. Advances in remote sensing (RS) and geographical information systems (GIS) have enabled us to estimate ET spatially. In the present study, both, RS and GIS tools have been utilized to estimate the actual crop ET by surface energy balance algorithm for land (SEBAL) model using high spatial resolution satellite image Landsat7 ETM+ for Hisar district, Haryana in north India. Previously calibrated and validated SEBAL model with lysimeter data within the same agroclimatic zone were used in the study. Derived actual ET from lysimeter data validated SEBAL method was again validated using Penman-Montieth (PM) method for the study area located in the same agro-climatic zone. Based on the primary and secondary data analysis, it can be inferred that SEBAL ET is the best spatial ET estimation model for Hisar district or regions having similar agro-climatic conditions. Validation of SEBAL ET with ground-observed lysimeter data showed high coefficient of correlation (R 2 = 0.91). Validation using the PM method also showed high coefficient of correlation (R 2 = 0.835). Other statistical parameters (RMSE = 0.583, NRMSE = 0.236) also showed good agreement between actual SEBAL ET c and PM ET c (crop evapotranspiration). It was also found that any prior knowledge about the crops, their types and cropping seasons is not required for the estimation of actual ET by SEBAL model. Keywords: Energy balance algorithm, evapotranspiration, ground truthing, remote sensing, wheat.OVER the last few decades with the reduction of water resources, India is facing critical problems with industrial and agricultural growth being impacted 1 . In agriculture, water requirements are associated with irrigation water use. Prediction of irrigation water demand involves computation of many water balance factors, and evapotranspiration (ET) is one of its major components. ET is the combined loss of water from the soil as well as plants and it is a crucial component of the hydrologic cycle. At the same time, ET depends upon several factors and is difficult to calculate precisely. Remote sensing (RS) techniques are emerging to solve this problem by providing reliable algorithms. Several models have been developed to derive ET fluxes like surface energy balance algorithm for land (SEBAL) 2 , simplified surface energy balance index (S-SEBI) 3 , two-source energy balance (TSEB) 4 and surface energy balance system (SEBS) 5 . SEBAL is one of the best models to estimate spatial ET because it calculates the fluxes independently from land cover and can handle thermal infrared images at resolutions between a few metres and several kilometres 6 . Due to these major advantages of this surface energy balance model, it was adopted for the spatial estimation of ET in Hisar district, Haryana, India. SEBAL model was used in the present study which was already validated using lysimeter data from a nearby location, i.e. Water Technology Centre, Indian Agricultural Research Instit...

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