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Conference Paper

Comparison of Remote Sensing based Evapotranspiration models for Indian region

Authors

Athira,  K. V.
IUGG 2023, General Assemblies, 1 General, International Union of Geodesy and Geophysics (IUGG), External Organizations;

Rajasekaran,  Eswar
IUGG 2023, General Assemblies, 1 General, International Union of Geodesy and Geophysics (IUGG), External Organizations;

Boulet,  Gilles
IUGG 2023, General Assemblies, 1 General, International Union of Geodesy and Geophysics (IUGG), External Organizations;

Nigam,  Rahul
IUGG 2023, General Assemblies, 1 General, International Union of Geodesy and Geophysics (IUGG), External Organizations;

Bhattacharya,  Bimal K.
IUGG 2023, General Assemblies, 1 General, International Union of Geodesy and Geophysics (IUGG), External Organizations;

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Citation

Athira, K. V., Rajasekaran, E., Boulet, G., Nigam, R., Bhattacharya, B. K. (2023): Comparison of Remote Sensing based Evapotranspiration models for Indian region, XXVIII General Assembly of the International Union of Geodesy and Geophysics (IUGG) (Berlin 2023).
https://doi.org/10.57757/IUGG23-4746


Cite as: https://gfzpublic.gfz-potsdam.de/pubman/item/item_5021154
Abstract
Evapotranspiration is a key process in Earth’s land surface -atmospheric interactions and the accurate estimation of ET is essential for understanding the carbon and water cycles. Multiple remote sensing based ET models are developed all over the world. The regionality of models demands an intercomparison study over different areas. This study compares three ET models: Priestley Taylor – Jet Propulsion Lab (PT-JPL), Soil Plant Atmosphere and Remote Sensing Evapotranspiration (SPARSE – Layer and Patch), and Surface Temperature Initiated Closure (STIC) belonging to different categories of ET models, over the Indian region. The models are tested using in-situ data and then further compared using multi-scale satellite data (1km and 30m). MODIS data was used to estimate 1km ET and Landsat was used to estimate 30m ET. IMDAA reanalysis data was used for meteorological data and was resampled to MODIS/Landsat scale. The results indicate the performance of models varies with respect to the scale. At the field scale PT-JPL model performed the best with RMSE of 62.89 Wm-2, followed by the SPARSE Layer with RMSE of 75.23 Wm-2, STIC with RMSE of 79.15 Wm-2 and SPARSE Patch with RMSE of 82.95 Wm-2. But when the satellite data were used SPARSE models performed the best with RMSE of 25.33 Wm-2 and 26.65 Wm-2, followed by STIC with RMSE of 31.75 Wm-2 and PT-JPL with RMSE of 37.28 Wm-2. Also the ET at 1km and 30m performed differently with 30m ET having high error due to the unavailability of high resolution meteorological data.