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C. G. Karishma Balaji Kannan K. Nagarajan S. Panneerselvam S. Pazhanivelan

Abstract

Estimating evapotranspiration's spatiotemporal variance is critical for regional water resource management and allocation, including irrigation scheduling, drought monitoring, and forecasting. The Surface Energy Balance Algorithm for Land (SEBAL) method can be used to estimate spatio-temporal variations in evapotranspiration (ET) using remote sensing-based variables like Land Surface Temperature (LST), Normalized Difference Vegetation Index (NDVI), surface albedo, transmittance, and surface emissivity. The main aim of the study was to evaluate the actual evapotranspiration for the lower Bhavani basin, Tamil Nadu based on remote sensing methods using Landsat 8 data for the years 2018 to 2020. The actual evapotranspiration was estimated using SEBAL model and its spatial variation was compared over different land covers. The estimated values of daily actual evapotranspiration in the lower Bhavani basin ranged from 0 to 4.72 mm day-1. Thus it is evident that SEBAL model can be used to predict ET with limited ground base hydrological data. The spatially estimated ET values will help in managing the crop water requirement at each stage of crop and irrigation scheduling, which will ensure the efficient use of available water resources.

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Keywords

Actual evapotranspiration, Remote sensing, Spatio-temporal, Surface Energy Balance Algorithm for Land

References
Bastiaanssen, W. G. M. et al. 共2005兲. “SEBAL model with remotely sensed data to improve water-resources management under actual field conditions.” J. Irrig. Drain. Eng., 131共1兲, 85–93
Bastiaanssen, W. G. M. et al. 共2005兲. “SEBAL model with remotely sensed data to improve water-resources management under actual field conditions.” J. Irrig. Drain. Eng., 131共1兲, 85–93
Allen, R. G., Tasumi, M. & Trezza, R. (2007). Satellite-based energy balance for mapping evapotranspiration with internalized calibration (METRIC)—Model. Journal of irrigation and drainage engineering, 133(4), 380-394.
Bala, A., Pawar, P. S., Misra, A. K. & Rawat, K. S. (2017). Estimation and validation of actual evapotranspiration for wheat crop using SEBAL model over Hisar District, Haryana, India. Current Science, 134-141.
Bashir, M. A., Hata, T., Tanakamaru, H., Abdelhadi, A. W. & Tada, A. (2008). Satellite-based energy balance model to estimate seasonal evapotranspiration for irrigated sorghum: a case study from the Gezira scheme, Sudan. Hydrology and Earth System Sciences, 12(4), 1129-1139.
Bastiaanssen, W. G. M., Noordman, E. J. M., Pelgrum, H., Davids, G., Thoreson, B. P. & Allen, R. G. (2005). SEBAL model with remotely sensed data to improve water-resources management under actual field conditions. Journal of irrigation and drainage engineering, 131(1), 85-93.
Bastiaanssen, W. G., Pelgrum, H., Wang, J., Ma, Y., Moreno, J. F., Roerink, G. J. & Van der Wal, T. (1998a). A remote sensing surface energy balance algorithm for land (SEBAL).: Part 2: Validation. Journal of Hydrology, 212, 213-229.
Bastiaanssen, W. G., Menenti, M., Feddes, R. A. & Holtslag, A. A. M. (1998b). A remote sensing surface energy balance algorithm for land (SEBAL). 1. Formulation. Journal of hydrology, 212, 198-212.
Fawzy, H. E. D., Sakr, A., El-Enany, M. & Moghazy, H. M. (2021). Spatiotemporal assessment of actual evapotranspiration using satellite remote sensing technique in the Nile Delta,Egypt. Alexandria Engineering Journal, 60(1), 1421-1432.
Firozjaei, M. K., Kiavarz, M., Nematollahi, O., Karimpour Reihan, M. & Alavipanah, S. K. (2019). An evaluation of energy balance parameters, and the relations between topographical and biophysical characteristics using the mountainous surface energy balance algorithm for land (SEBAL). International Journal of Remote Sensing, 40(13), 5230-5260.
Lian, J. & Huang, M. (2016). Comparison of three remote sensing based models to estimate evapotranspiration in an oasis-desert region. Agricultural Water Management, 165, 153-162.
Liou, Y. A. & Kar, S. K. (2014). Evapotranspiration estimation with remote sensing and various surface energy balance algorithms—A review. Energies, 7(5), 2821-2849.
Mao, Y. & Wang, K. (2017). Comparison of evapotranspiration estimates based on the surface water balance, modified Penman‐Monteith model, and reanalysis data sets for continental China. Journal of Geophysical Research: Atmospheres, 122(6), 3228-3244.
Mohamed, E. S., Ali, A., El-Shirbeny, M., Abutaleb, K. & Shaddad, S. M. (2020). Mapping soil moisture and their correlation with crop pattern using remotely sensed data in arid region. The Egyptian Journal of Remote Sensing and Space Science, 23(3), 347-353.
Rawat, K. S., Singh, S. K., Bala, A. & Szabo, S. (2019). Estimation of crop evapotranspiration through spatial distributed crop coefficient in a semi-arid environment. Agricultural Water Management, 213, 922-933.
Seneviratne, S. I., Koster, R. D., Guo, Z., Dirmeyer, P. A., Kowalczyk, E., Lawrence, D.& Verseghy, D. (2006). Soil moisture memory in AGCM simulations: analysis of global land–atmosphere coupling experiment (GLACE) data. Journal of Hydrometeorology, 7(5), 1090-1112.
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Karishma, C. G., Kannan, B., Nagarajan, K., Panneerselvam, S., & Pazhanivelan, S. (2022). Spatial and temporal estimation of actual evapotranspiration of lower Bhavani basin, Tamil Nadu using Surface Energy Balance Algorithm for Land Model. Journal of Applied and Natural Science, 14(2), 566–574. https://doi.org/10.31018/jans.v14i2.3412
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