Estimating Regional Evapotranspiration Using Remote Sensing: Application to Sone Low Level Canal System, India

Remote sensing-derived spectral data have been used in the past to partition net radiation, soil heat, and sensible heat fluxes for estimating latent heat flux as a residual of surface energy balance, and thus regional evapotranspiration. Attempts to provide a simplified procedure for estimating sensible heat flux at a regional scale have not been successful because of the relatively strong dependence of the heat transfer coefficient on the land–atmosphere boundary condition. This paper presents a remote sensing-based procedure to estimate the sensible heat flux incorporating the local meteorological conditions, and in turn to determine the regional evapotranspiration. The model utilizes satellite-derived surface albedo, surface temperature, and leaf area index along with a very few agrometeorological data as inputs. The proposed procedure has been tested on a part of the Western Yamuna Canal system, India, and is found to be computationally simple as well as stable. For a well-watered wheat crop, the average evapotranspiration by the proposed model is estimated to be 2.05?mm?d?1 on January 30, 1996, whereas it is estimated to be 1.89?mm?d?1 using the Penman-Monteith equation, indicating a difference of less than 10%. The model is subjected to sensitivity analysis for uncertainties in the observed wind velocity and the computed leaf area index (by ±20%) to estimate sensible heat flux. Results reveal that the percentage change in mean sensible heat flux for the image is less than 5% in all cases, thus indicating the acceptability of the model against the uncertainties. Further, the model has been applied to three sets of Landsat-TM data covering the Sone Low Level Canal system, India, to demonstrate its usefulness in evaluating water delivery performance.