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Article Dans Une Revue Remote Sensing Année : 2024

Water Footprint of Cereals by Remote Sensing in Kairouan Plain (Tunisia)

Résumé

This article aims to estimate the water footprint (WF) of cereals—specifically, wheat and barley—in the Kairouan plain, located in central Tunisia. To achieve this objective, two components must be determined: actual evapotranspiration (ETa) and crop yield. The study covers three growing seasons from 2010 to 2013. The ETa estimation employed the S-SEBI (simplified surface energy balance index) model, utilizing Landsat 7 and 8 optical and thermal infrared spectral bands. For yield estimation, an empirical model based on the normalized difference vegetation index (NDVI) was applied. Results indicate the effectiveness of the S-SEBI model in estimating ETa, demonstrating an R2 of 0.82 and an RMSE of 0.45 mm/day. Concurrently, yields mapped over the area range between 6 and 77 qx/ha. Globally, cereals’ average WF varied from 1.08 m3/kg to 1.22 m3/kg over the three study years, with the majority below 1 m3/kg. Notably in dry years, the importance of the blue WF is emphasized compared to years with average rainfall (WFb-2013 = 1.04 m3/kg, WFb-2012 = 0.61 m3/kg, WFb-2011 = 0.41 m3/kg). Moreover, based on an in-depth agronomic analysis combining yields and WF, four classes were defined, ranging from the most water efficient to the least, revealing that over 30% of cultivated areas during the study years (approximately 40% in 2011 and 2012 and 29% in 2013) exhibited low water efficiency, characterized by low yields and high WF. A unique index, the WFI, is proposed to assess the spatial variability of green and blue water. Spatial analysis using the WFI highlighted that in 2012, 40% of cereal plots with low yields but high water consumption were irrigated (81% blue water compared to 6% in 2011).
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Dates et versions

hal-04477495 , version 1 (26-02-2024)

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Paternité

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Vetiya Dellaly, Aicha Chahbi Bellakanji, Hedia Chakroun, Sameh Saadi, Gilles Boulet, et al.. Water Footprint of Cereals by Remote Sensing in Kairouan Plain (Tunisia). Remote Sensing, 2024, 16 (3), pp.491. ⟨10.3390/rs16030491⟩. ⟨hal-04477495⟩
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