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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 (R2 = 0.91). Validation using the PM method also showed high coefficient of correlation (R2 = 0.835). Other statistical parameters (RMSE = 0.583, NRMSE = 0.236) also showed good agreement between actual SEBAL ETc and PM ETc (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.
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