Increasing the relevance of climate information within the agricultural sector

Host Institution:

African Institute for Mathematical Sciences (AIMS) Rwanda
International Centre for Tropical Agriculture (CIAT), Rwanda

Location:CIAT and AIMS-Rwanda, Kigali, Rwanda

Supervisors:
Dr Rosita Yocgo, ryocgo@nexteinstein.org
Dr Desire Kagabo, D.Kagabo@cgiar.org;

Project Description :

Rwanda has over 100 weather stations, and has made significant efforts to capture and share weather information with all economically important sectors, including the agricultural sector. This provides a solid foundation to model diverse scenarios that are important for increased agricultural productivity.

Crop modelling approaches have been used throughout Africa and globally for research purposes. Integrating crop modelling with weather, soil and farmer profile information provides much more targeted information to farmers. There is therefore a clear opportunity to bring multiple approaches along with remotely sensed and GIS data to create robust predictive models that work together with the weather forecast, soil information, plant disease occurrences, irrigation requirements etc. to: predict yield (the farmer can take the decision if to plant or not to plant); evaluate the aptitude of specific varieties (in order to select the best variety for the next planting season), optimize based on the right amount of fertilizers (to create more productive and climate-smart farms) and more generally, to allow for timely and effective crop monitoring and prediction to increase food security.

In this light, the African Institute for Mathematical Sciences and the International Centre for Tropical Agriculture in Rwanda, aim to develop scientific-based methods/approaches that will make climate information more actionable in the agricultural sector. Candidates are encouraged to propose projects which can support the above aim. Subprojects could include, but are not limited to:

Using climate information to predict crop performance and/or yield.
Modelling soil moisture and yield interaction within a changing climate.
Evaluating irrigation requirements and yield.
Evaluating the impact of climate change on important crops or farming areas.

Candidates should:

have a background in programming,
have an interest to work with climate data, biodiversity and agriculture, and
propose a brief project and approach/method on how they would address one or more of the above subprojects using modelling and related techniques. Candidates may elect to propose new subprojects that are of interest to them.

Results obtained would inform next steps post this internship phase.

Applications for this internship should be submitted via the online application system, stating clearly the title of the internship.

Deadline for applications: March 29th, 2019 – 11:59 PM (EAT).

Any inquiries about these internships should be sent to:
aims-ms4cr.internship@nexteinstein.org.