Assessment and validation of evapotranspiration using SEBAL algorithm and Lysimeter data of IARI agricultural farm, India. Issue 7 (8th August 2016)

• Record Type: Journal Article
• Authors: Bala, Anju; Rawat, Kishan Singh; Misra, Anil Kumar; Srivastava, Amit
• Is Part Of: Geocarto international. Volume 31:Issue 7(2016)
• Page Start: 739
• Page End: 764
• Publication Date: 2016-08-08
• Subjects: evapotranspiration -- Lysimeter -- remote sensing -- SEBAL -- LANDSAT; Remote sensing -- Periodicals; Geographic information systems -- Periodicals; Geology -- Periodicals; Cartography -- Periodicals; 621.3678
• DOI: 10.1080/10106049.2015.1076062
• Languages: English
• ISSNs: 1010-6049

Abstract

Abstract : Evapotranspiration (ET) is a vital process in land surface atmosphere research. In this study, Surface Energy Balance Algorithm for Land (SEBAL) for the assessment of ET (for 23 December 2010, 8 January 2011, 24 January 2011, 9 February 2011, 25 February 2011, 29 March 2011 and 14 April 2011) from LANDSAT7-ETM+ and validation with Lysimeter data set is illustrated. It is based on the evaporative fraction concept, and it has been applied to LANDSAT7-ETM + (30 m resolution) data acquired over the Indian Agricultural Research Institute's agricultural farm land. The ET from SEBAL was compared with Lysimeter ET using four statistical tests (root-mean-square error (RMSE), relative root-mean-square error (R-RMSE), mean absolute error (MAE), and normalized root-mean square error (NRMSE)), and each test showed a good correlation between the predicted and observed ET values. Results from this study revealed that the RMSE of crop-growing period was 0.51 mm d −1 for ETSEBAL, i.e. ETSEBAL having good accuracy with respect to observed ETLysimeter . Results were also validated using R-RMSE test, which also proved that ETSEBAL data are having good accuracy with respect to observed ETLysimeter as R-RMSE of crop-growing period is 0.19 mm d −1 . MAE (0.19), NRMSE (0.21) and r 2 (0.91) tests indicated that model prediction is significant, and model can be effectively used for the estimation of ET from SEBAL as input of remote sensing data sets. Finally, the SEBAL has been useful for remote agricultural land where ground-based data (Lysimeter data) are not available for daily ET (ET24 h ) estimation. The temporal study of the ET24 h values analysed has revealed that the highest ET24 h values are owing to the higher development (high greenness) of crops, whereas the lower values are related to the lower development (low greenness) or null crop.