Comparative Evaluation of Simplified Surface Energy Balance Index-Based Actual ET against Lysimeter Data in a Tropical River Basin

Utkarsh Kumar, Rashmi, Chandranath Chatterjee and Narendra Singh Raghuwanshi
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Utkarsh Kumar: Crop Production Division, ICAR-Vivekananda Parvatiya Krishi Anusandhan Sansthan, Almora 263601, India
Rashmi: Department of Agricultural Economics, Institute of Agricultural Sciences, Banaras Hindu University, Varanasi 221005, India
Chandranath Chatterjee: Agricultural and Food Engineering Department, Indian Institute of Technology Kharagpur, Kharagpur 721302, India
Narendra Singh Raghuwanshi: Agricultural and Food Engineering Department, Indian Institute of Technology Kharagpur, Kharagpur 721302, India

Sustainability, 2021, vol. 13, issue 24, 1-15

Abstract: In the past decades, multispectral and multitemporal remote sensing has been popularly used for estimating actual evapotranspiration ( ET c ) across the globe. It has been proven to be a cost-effective tool for understanding agricultural practices in a region. Today, because of the availability of different onboard sensors on an increasing number of different satellites, land surface activity can be captured at fine spatial and time scales. In the present study, three multi-date satellite imageries were used for the evaluation of remote sensing-based estimation of actual evapotranspiration in paddy in the command area of the tropical Kangsabati river basin. A surface energy balance model, the Simplified-Surface Energy Balance Index (S-SEBI), was applied for all three dates of the Rabi season (2014–2015) for the estimation of actual evapotranspiration. The crop coefficient was calculated using the exhaustive survey data collected from the command area and adjusted to local conditions. The ET c estimated using the S-SEBI-based model was compared with the Food and Agriculture Organization Penman–Monteith (FAO-56 PM) method multiplied by the adjusted local crop coefficient and lysimeter data in the command area. The coefficient of determination ( r 2 ) was applied to examine the accuracy of the S-SEBI model with respect to lysimeter data and the FAO-56 PM-based ET c . The results showed that the S-SEBI model performed well with the lysimeter ( r 2 = 0.90) in comparison with FAO-56 PM, with an r 2 of 0.65. In addition to this, the S-SEBI-based ET estimates correlated well with the FAO-56 PM, with r and RMSE values of 0.06 and 1.13 mm/day (initial stage), 0.85 and 0.48 mm/day (development stage), and 0.77 and 0.52 (maturity stage) for paddy, respectively. The S-SEBI-based ET c estimate varied with different stages of crop growth and successfully captured the spatial heterogeneity within the command area. In general, this study showed that the S-SEBI method has the potential to calculate spatial evapotranspiration and provide useful information for efficient water management. The results revealed the applicability and accuracy of remote sensing-based ET for managing water resources in a command area with scarce data.

Keywords: remote sensing; satellite; image processing; crop identification; land use (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2021
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