Abstract :
[en] Small-scale irrigation initiatives are expanding rapidly in Burkina Faso. However, in many cases optimal yields are not being obtained despite the available water and the required nutrient applications. Local stakeholders need an easy-to-use decision-support tool to assess irrigation water use and its impact on yield. In this study, a water-driven crop model, AquaCrop, developed by FAO, was adapted for cabbage (Brassica oleracea L.) using a limited dataset and leave-one-out cross-validation (LOOCV). The experiment was conducted in south-western Burkina Faso on small irrigated farmer plots, where optimal managerial conditions could not always be guaranteed. Statistical indicators – normalized root mean square error (nRMSE) and index of agreement (d) – suggested that the model is very reliable for simulating cabbage biomass yield and soil water content (low nRMSE and d-index near 1). The relationship between observed and simulated yield produced a d-index of 0.99 and an nRMSE of 1.39% (or 0.59 ton/ha). The comparison between observed and modeled soil water content gave a d-index of 0.90 and an nRMSE of 4.38% (or 9.13 mm). Also of interest was the indirect link between plant density and yield via maximum canopy cover, which can considerably simplify yield estimation. It was concluded that AquaCrop was a very useful tool for enabling local end-users to evaluate and optimize cabbage yield and irrigation water use.
Research Center/Unit :
Université de Liège, Département Sciences et Gestion de l’Environnement, Arlon, Belgium
Name of the research project :
GEeau - Renforcement des capacités à concevoir et à mettre en oeuvre des outils de gestion de l'eau à usage agricole - Burkina Faso
Scopus citations®
without self-citations
48