Technical Papers
Jul 8, 2020

Evaluation Framework of Landsat 8–Based Actual Evapotranspiration Estimates in Data-Sparse Catchment

Publication: Journal of Hydrologic Engineering
Volume 25, Issue 9

Abstract

Remote sensing has revolutionized the assessment of evapotranspiration by continuous monitoring of the variable at a global scale. However, it is difficult to accurately estimate actual evapotranspiration (AET) in areas with high spatial heterogeneity along with very little ancillary data available. The presence of spatial heterogeneity is observed over India and being a country, whose economy largely depends on agriculture, estimation of AET is crucial for efficient water management. This study proposed a new framework to evaluate AET at a fine spatial scale suitable for such heterogeneous and data-sparse environments, with spatial and temporal validation using global datasets. Landsat 8 data were used to estimate AET for eight cloud-free days of 2014 over the Malaprabha River Basin in India using the modified surface energy balance algorithm for land (M-SEBAL) and two-source energy balance (TSEB) models. These two AET estimates were compared with Moderate resolution Imaging Spectroradiometer (MODIS) and Global Land Evaporation Amsterdam Model (GLEAM) AET for spatial and temporal validation respectively. M-SEBAL outperformed TSEB in capturing the magnitude and spatial variability of AET (e.g., spatial correlation between M-SEBAL and MODIS AET was 0.56 and 0.45 for day of year (DOYs) 040 and 136, respectively, whereas for the same DOYs the correlation between TSEB and MODIS AET was 0.16 and 0.36). The results demonstrate the challenge in AET estimation at a fine spatial resolution and highlight the importance of choosing a suitable algorithm.

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Data Availability Statement

All the remote sensing images used in this study are open source and can be downloaded from http://earthexplorer.usgs.gov/ and https://ladsweb.modaps.eosdis.nasa.gov/search/. The codes used during the study are available from the corresponding author by request.

Acknowledgments

The first author thanks Dr. H. R. Shwetha (Assistant Professor, National Institute of Technology Karnataka, Surathkal, India) for her guidance in learning the basics of evapotranspiration estimation using remote sensing data in energy balance algorithms. The third author acknowledges the funding support provided by the Ministry of Earth Sciences, Government of India, through Project reference number MoES/PAMC/H&C/41/2013-PC-II. The authors thank three anonymous reviewers and the editor of the Journal for their valuable comments that helped to improve the quality of the manuscript.

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Go to Journal of Hydrologic Engineering
Journal of Hydrologic Engineering
Volume 25Issue 9September 2020

History

Received: Dec 21, 2019
Accepted: May 11, 2020
Published online: Jul 8, 2020
Published in print: Sep 1, 2020
Discussion open until: Dec 8, 2020

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Ph.D. Student, Dept. of Civil Engineering, Indian Institute of Science, Bangalore, Karnataka 560012, India. ORCID: https://orcid.org/0000-0001-5651-2775. Email: [email protected]
Divecha Centre for Climate Change, Indian Institute of Science, Bangalore, Karnataka 560012, India. ORCID: https://orcid.org/0000-0003-4878-3836. Email: [email protected]
Professor, Dept. of Civil Engineering and Interdisciplinary Centre for Water Research (ICWaR), Indian Institute of Science, Bangalore, Karnataka 560012, India (corresponding author). ORCID: https://orcid.org/0000-0002-5294-8501. Email: [email protected]; [email protected]

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