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Università Ca’ Foscari Venezia (2014)

Sustainability of the innovation in Moroccan agriculture considering future climate change scenarios : The Rabat-Salé-Zemmour-Zaër case study

Volani, Stefania

Titre : Sustainability of the innovation in Moroccan agriculture considering future climate change scenarios : The Rabat-Salé-Zemmour-Zaër case study

Auteur : Volani, Stefania

Université de soutenance : Università Ca’ Foscari Venezia

Grade : Laurea magistrale in Scienze Ambientali Joint Master’s Degree in Sustainable Development 2014

Résumé
Agriculture is of primary importance for Moroccan gross domestic product and for the overall employability of the working population of the country. However, land availability for agricultural purposes is decreasing in Morocco, due to unsustainable farming practices and environmental constraints, such as harsh climatic conditions, soil erosion and water scarcity. Climate change exacerbates risk factors, and thus appropriate adaptation measures should be considered in order to cope with land degradation and depletion of resources in arid and semi-arid areas of Morocco. Only few studies have analyzed Moroccan agriculture constraints and sustainable solutions at a regional scale. Therefore, the aim of the present work is to undertake a land suitability analysis of Rabat-Salé-Zemmour-Zaër region in Central Morocco where cereals, as winter wheat, durum wheat and barley are the main cultivated crops. Conservation agriculture and in particular the practice of no-tillage has been taken as possible measure to overcome land vulnerability and increase socio-economic benefits. Since crop rotation is one of the main pillars of conservation agriculture, it is considered in the analysis as one of the indicators for the identification of lands where no-tillage may be adopted. Wheat (Triticum spp.) and lentil (Lens culinaris Medikus) rotation has been investigated in the implementation of land suitability analysis in a geographic information systems (GIS) context, with the elaboration of spatially distributed and complex land attributes. Classification, overlaying, weighting and other GIS techniques are applied to spatial data, within a multi-criteria decision analysis (MCDA) methodological framework.

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