On the Use of Decision-Support Tools for Improved Irrigation Management: AquaCrop-Based Applications

Feeding more people with less water is putting efficient irrigation practices worldwide high on the agendas. As a reaction, over the last decades, numerous irrigation decision-support tools have been developed. For several reasons, the gap between farmer and modeler remained in most cases too large. The Food and Agriculture Organization of the United Nations (FAO) contributes to alleviate the encountered adoption limitations with AquaCrop and its stand-alone AquaCrop plug-in. This simple and robust field-crop-water balance has been successfully tested for a wide range of crops and regions, and its database is still expanding through worldwide contributions. The present chapter describes how AquaCrop can help irrigation advisory services draft efficient irrigation calendars that are easily applicable and adoptable: either by the elaboration of site-specific irrigation schedule calendars in chart format when the user has no access to the needed data or by the integration of its plug-in in a server/client ICT application offering centralized data management. As for the irrigation charts, studies prove 10-30% water savings, while maintaining yield and requiring minimum data. The server/client application offers an all-in advice tool, including real-time irrigation advice and yield forecasts. No adoption assessments have yet been carried out, but several ongoing pilot studies are promising

Promouvoir des approches innovantes de recherche-développement en matière de GIRE au Burkina Faso

peer reviewe

Are dynamic vegetation models able to simulate accurately water stress: confronting delta13C predictions of the DVM CARAIB with field values ?

Appui à la politique agricole d'adaptation et résistance au changement climatiqu

Renforcement structurel de la capacité de gestion des ressources en eau pour l'agriculture dans le bassin du Kou (Burkina Faso): Rapport Technique 2 (2005-2006)

Le bassin du Kou, situé dans le sud-ouest du Burkina Faso, est depuis quelques décennies le théâtre de différentes formes de conflits liés à toute une série de problèmes que l’on rencontre généralement dans des zones irriguées. Dans le bassin du Kou, les aménagements hydroagricoles recensés couvrent une superficie totale de près de 3.200 ha. Il s’agit pour l’essentiel de périmètres privés formant la ceinture maraîchère, horticole et fruitière de Bobo-Dioulasso et d’un grand périmètre de 1.200 ha réalisé par l’Etat à Bama et spécialisé dans la production du riz. Outre l’abondance en eau liée à la présence de sources importantes, d’une nappe phréatique facilement exploitable, d’un cours d’eau pérenne et un hivernage à caractère sub-humide, la plupart des utilisateurs d’eau se retrouvent régulièrement en pénurie d’eau à cause d’une augmentation de la population et d’une intensification de l’agriculture irriguée. Ceci conduit les gestionnaires du bassin à rechercher des outils de contrôle et de suivi

Cereal yield forecasting in Morocco using the CARAIB dynamic vegetation model driven by HadGEM2-AO projections

Food security, in Morocco as in many parts of the world, depends heavily on cereal production which fluctuates relying on weather conditions. In fact, Morocco has a production system for cereals which is dominated by rainfed. It is therefore necessary to further develop knowledge about climate change and strengthen forecasting systems for predicting the impacts of climate change. Our research, funded by a bilateral project of Wallonie-Bruxelles International, aims to study the response of cereal production to climate change, using the dynamic vegetation model CARAIB (CARbon Assimilation In the Biosphere) developed within the Unit for Modelling of Climate and Biogeochemical Cycles (UMCCB) of the University of Liège. This spatial model includes crops and natural vegetation and may react dynamically to land use changes. Originally constructed to study vegetation dynamics and carbon cycle, it includes coupled hydrological, biogeochemical, biogeographical and fire modules. These modules respectively describe the exchange of water between the atmosphere, the soil and the vegetation, the photosynthetic production and the evolution of carbon stocks and fluxes in this vegetation-soil system. For crops, a specific module describes basic management parameters (sowing, harvest, rotation) and phenological phases. The simulations are performed across all Morocco using different input data. The three main cereal crops simulated include soft wheat, durum wheat and barley, they are grown in all provinces and all agro-ecological zones. Regarding climatic inputs, we’re using two sets of data: the first one is interpolated and bias-corrected fields from the climate model HadGEM2-AO for the historical period (1990-2005), in addition to three different Representative Concentration Pathway scenarios (RCP2.6, RCP4.5 and RCP8.5) from 2005 to 2100. The second one is high resolution (30 arc sec) gridded climate data derived from WorldClim combined with interpolated anomalies from CRU (Climatic Research Unit) over the historical period 1990 to 2018. After obtaining preliminary results for the past period, and in order to improve the prediction using the field data which are the observed yields, we performed a sensitivity analysis. We used the One-at-a-time (OAT) approach by moving one input variable, keeping others at their baseline (nominal) values, then, returning the variable to its nominal value, then repeating for each of the other inputs in the same way. Sensitivity may then be measured by monitoring changes in the output, using linear regression. The inputs studied are the initial value of carbon pool, leaf C/N ratio, water stress, sowing date, GDD harvest, stomatal conductance parameters, specific leaf area, and rooting depth