9 March 2021 Spatial variability of evapotranspiration and pressure on groundwater resources: remote sensing monitoring by crop type in the Bekaa plain, Lebanon
Arnaud Caiserman, Ghaleb Faour
Author Affiliations +
Abstract

The lack of data on water consumption by agriculture in the context of climate change led the authors to estimate the water balance of the Bekaa Valley. Plots were mapped according to the normalized difference vegetation index profiles of spring and summer crop with the Sentinels-2 images. Surface energy balance model python (PYSEBAL) estimated the seasonal evapotranspiration (ETseason) and net irrigation requirements (NIRseason). Spring and summer crop maps were accurate: 90% and 93%. The results of PYSEBAL were validated by the comparison between averaged daily ET of PYSEBAL and FAO-56 method (root mean square error from 0.38 to 1.93 and the mean average error from 0.33 to 1.64  mm  /  day). The water balance was negative: 0.16  km3 of groundwater was extracted against 0.10  km3 of rainfall available for aquifer recharge in 2017. This is explained by ET/ha/season (alfalfa: 1094  mm  /  ha  /  season, orchards 881, corn 719, tobacco 606, cucumber 558, late potatoes 487, summer vegetables 483, early potatoes 467, vineyard 390, spring vegetables 237, and wheat 313). ETseason varies according to temperature (strong correlation between daily ET and temperature, Pearson: 0.74), relative humidity (Pearson: −0.65), surface radiation (Pearson: 0.75), and percentage of sand in the soil and its depth (strong negative Pearson: −0.62 and −0.57).

© 2021 Society of Photo-Optical Instrumentation Engineers (SPIE) 1931-3195/2021/$28.00 © 2021 SPIE
Arnaud Caiserman and Ghaleb Faour "Spatial variability of evapotranspiration and pressure on groundwater resources: remote sensing monitoring by crop type in the Bekaa plain, Lebanon," Journal of Applied Remote Sensing 15(1), 014517 (9 March 2021). https://doi.org/10.1117/1.JRS.15.014517
Received: 2 September 2020; Accepted: 15 February 2021; Published: 9 March 2021
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CITATIONS
Cited by 2 scholarly publications.
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KEYWORDS
Near infrared

Agriculture

Climatology

Soil science

Remote sensing

Earth observing sensors

Landsat

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