IFPRI is seeking an individual consultant to develop data and tools aimed at enhancing modeling capacity for assessing the financial feasibility and environmental sustainability of expanding solar irrigation in Sub-Saharan Africa.

Background:

Irrigation is widely perceived as an important means to improve agricultural production in Sub-Saharan Africa (SSA). Ubiquitous energy requirements for water lifting and conveyance may arise from this expansion. The International Food Policy Research Institute, under the CGIAR Initiative on NEXUS Gains, aims to conduct research to identify clean and renewable energy solutions to support irrigation development in SSA.

In recent years, IFPRI has developed an integrated modeling system for assessing the financial feasibility and environmental sustainability of solar irrigation. This modeling system has been applied in several studies in SSA to identify the potential for solar irrigation development and to compare the cost-efficiency of solar irrigation with traditional irrigation systems powered by diesel. However, there are still limitations in the functionality of the modeling system, which hinder its further application. These limitations include, but are not limited to, the large uncertainty associated with input data and the high computational cost of modeling groundwater table variations using currently available process-based groundwater models.

Recent developments in data and machine learning technologies bring new opportunities to enhance the capacity of the modeling system. The successful candidate will work with IFPRI researchers to develop new data and tools, leveraging recent advancements in data and machine learning, to enhance the capacity of IFPRI’s solar irrigation modeling system.

Activities and expected deliverables:

The major activities, along with their specific tasks, and the expected deliverables to be undertaken are as follows:

Model and Data Review:

· Review IFPRI’s previous work on solar irrigation modeling.

· Examine recent advancements in data and machine learning, particularly their applications in Earth science relevant to modeling and designing solar irrigation systems.

· Assess the potential applications of these new data and modeling techniques to enhance IFPRI’s solar irrigation modeling efforts.

· Provide recommendations for enhancing IFPRI’s modeling capacity using the identified new data and modeling technologies.

Deliverable: An interim report presenting findings from the model and data review, along with recommendations for enhancing IFPRI’s solar irrigation model.

Model Enhancement Implementation:

· Develop detailed procedures for model enhancement.

· Acquire and prepare the necessary data and perform programming to build the enhanced model.

· Apply the enhanced model in a case study in the Sub-Saharan African region.

· Prepare documentation to document the model enhancement work.

Deliverables: (1) Solar irrigation model with enhanced functionality or input data. (2) Technical report, potentially to be developed as an IFPRI discussion paper or journal article.

Duration period: 7 months starting from June 1, 2024.

Required qualifications:

· PhD with more than 5 years of postdoctoral experience in a relevant field (such as water resources and hydrological system modeling)

· Demonstrated research expertise in the water-food-energy nexus area

· Proven record of research publication (submission of two sample journal articles in relevant field is required)

· Proven track record of successful project deliveries

Application Criteria: Please upload your CV, one completed software development piece and include your daily rate in the online portal in USD.

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We are unable to respond to every applicant individually, only the selected candidate will be contacted – Thank you!