IAHS2022-680, updated on 23 Sep 2022
https://doi.org/10.5194/iahs2022-680
IAHS-AISH Scientific Assembly 2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.

Analysis of rainfed cereal-legume mixture cropping water productivity in Lebna catchment, Cap-Bon, Tunisia.

Insaf Mekki1, Rim Zitouna-Chebbi1, Salah Benyoussef2, Aya Abdelghaffar1, Frederic Jacob3, and Jean Albergel3
Insaf Mekki et al.
  • 1National Research Institute for Rural Engineering, Water and Forestry, Université de Carthage, Ariana, Tunisia (insaf.mekki.im@gmail.com)
  • 2National Agricultural Research Institute of Tunisia, Université de Carthage, Ariana, Tunisia
  • 3Research Institute for Development/UMR LISAH, France

Under climate change conditions, optimizing water resources management in rainfed agricultural production systerms requires the reasonable choice of crops. In this context, the adoption of crops diversification is promoted to increase the agricultural production and the added value per cubic meter of rain water (green water) used by crops. Contributing, therefore, to increase agricultural production and to preserve soil and water resources. The objective of this study is : i) to identify mixed crops within agricultural fields and, ii) to evaluate the biomass production and the water productivity in the Lebna watershed (Cap-Bon, Tunisia) using remote sensing and field measurements. The study area, covering 210 km2, is characterized by a semi-arid Mediterranean climate, the predominant of cereals, legumes and fodder cropping systems, and the degradation of soil resources. The field investigation and experiments allowed the quantification of crop evapotranspiration and the observed biomass production at the agricultural field plots. The use of the sentinel images and the observations at different agricultural fields allowed to produce NDVI maps. The results first confirmed a good correlation between biomass production and NDVI vlaues. The linear relationships showed a values of R² greater than 0.9 and  values of RMSE less than 0.35. The use of sentinel images and GIS allowed to compute water productivity from field to watershed scale.  The results revealed a considerable spatial variation in water productivity values  for different crops. Compared to a single crops, the cereal-legume mixture cropping improved the water productivity. Theses results help to recommed adaptation measures in agricultural production systems to climate change. Ongoing work coupling field experiments, remote sensing and agro-hydrological model aim to develop simulation and evaluate the agri-environmental impacts from field to regional scale.

How to cite: Mekki, I., Zitouna-Chebbi, R., Benyoussef, S., Abdelghaffar, A., Jacob, F., and Albergel, J.: Analysis of rainfed cereal-legume mixture cropping water productivity in Lebna catchment, Cap-Bon, Tunisia., IAHS-AISH Scientific Assembly 2022, Montpellier, France, 29 May–3 Jun 2022, IAHS2022-680, https://doi.org/10.5194/iahs2022-680, 2022.