Mapping deep percolation using remote sensing over an irrigated area in the Haouz plain (Marrakech, Morocco)
This study aims to estimate the spatial deep percolation (DP) by combining remote sensing data and SAMIR (SAtellite Monitoring of IRrigation) tool.
In this study, DP was derived as the residual component of water balance in the root zone.
The Indirect computation of water balance requires climate data (reference evapotranspiration (ET0) and rainfall), land cover, crop coefficient derived from normalized difference vegetation index (NDVI), and hydrodynamic soil parameters like soil moisture at field capacity and the wilting point.
The main water balance component is evapotranspiration.
It is spatialized based on the FAO-56 approach and the relationship between crop coefficient and NDVI. This approach was tested over an irrigated area in the Haouz plain during the agricultural period (2011-2012). The results showed that DP followed water supply fluctuations (sum of rainfall and irrigation provided by the manager, ORMVAH). High DP values are observed during heavy rainfall in March (around 36, 27, and 20 mm) for sugar beet, wheat, and olive trees, respectively.
However, from April to June, the vegetation cover was exposed to high water stress for the rest of the season mainly due to the mismatch of water supply.
Nassah, H., Er-Raki, S., Fakir, Y., Simonneaux, V., Diarra, A., Khabba, S. and Chehbouni, A. (2022). Mapping deep percolation using remote sensing over an irrigated area in the Haouz plain (Marrakech, Morocco). Acta Hortic. 1335, 371-380
DOI: 10.17660/ActaHortic.2022.1335.46
https://doi.org/10.17660/ActaHortic.2022.1335.46
DOI: 10.17660/ActaHortic.2022.1335.46
https://doi.org/10.17660/ActaHortic.2022.1335.46
deep percolation, water balance, FAO-56 model, remote sensing, SAMIR
English
1335_46
371-380