Optimizing water resources management in rainfed agricultural production systems requires the reasonable choice of crops. The adoption of crops diversification is promoted to increase the agricultural production. 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.

In this study case, water scarcity resulted from increasing water demand on the irrigation system, since groundwater became saline, and farmers were not able to adapt the cropping system in the case of perennial citrus orchards. A learning approach was developed to change the perception of local actors of the current situation of water scarcity and to reflect on the construction of collective actions for the improvement of the quality of irrigation service.

Accurate monitoring of surface water extent is essential for hydrological investigation of small lakes (1–10 ha), which supports millions of smallholder farmers. Landsat monitoring of long-term surface water dynamics is shown to be suited to lakes over 3 ha based on extensive hydrometric data from seven field sites over 15 years. MNDWI water classification optimized here for the specificities of small water bodies reduced mean surface area errors by 57 % compared to published global datasets.