Rwanda’s Climate Adaptation Monitoring, Evaluation and Learning (MEL) System in the Agriculture Sector: Case studies on the capacity of storage constructed, utilization of surveillance tools, and area of land under erosion control measures and used optimally
Summary
The document evaluates the effectiveness of storage infrastructure, digital pest surveillance tools, and terracing for erosion control in Rwanda. While these initiatives have improved food security and pest management, the report identifies significant gaps, including the underutilization of cold storage, limited digital literacy among rural farmers, and an increase in high-risk erosion areas between 2020 and 2022.
Key insights
- Rwanda's agricultural storage infrastructure is significantly underutilized and poorly maintained. A diagnostic analysis found that 41.4% of storage facilities are not maximally utilized, and 72.2% of cooling and cold rooms are underutilized. Only 51.1% of cold rooms are currently functional, while 25.5% are non-operational.
- Digital surveillance tools, specifically the Fall Armyworm (FAW) database and the Banana Xanthomonas Wilt (BXW) app, have improved pest and disease management. In the Rwamagana District, maize yields recovered from 3.8 tonnes during an FAW infestation to 4.5 tonnes one year later following the use of these tools.
- The adoption of digital tools is hindered by structural and social barriers in rural areas, including limited access to smartphones and internet connectivity, low digital literacy, and resistance to new technology among older farmers.
- Soil erosion risk in Rwanda has increased according to mapping data. In 2020, 33.2% of provincial land (1,402,446 ha) was at high risk for erosion; by 2022, this figure rose to 45% of provincial land (2,385,830 ha).
- Terracing is an effective erosion control method when properly maintained, with some studies showing soil and nutrient loss reductions of up to 90%. However, 74% of land at risk in Rwanda remains unprotected, and 21% of inspected terrace sites are not effectively utilized or maintained.
Cite the original document
- APA
- Tsinda, A., & Ntaganda, B. (2024). Rwanda’s Climate Adaptation Monitoring, Evaluation and Learning (MEL) System in the Agriculture Sector: Case studies on the capacity of storage constructed, utilization of surveillance tools, and area of land under erosion control measures and used optimally. NAP Global Network. https://napglobalnetwork.org/wp-content/uploads/2024/03/rwanda-mel-agriculture-sector-case-studies-v3.pdf
- Chicago
- Tsinda, Aime, and Brenda Ntaganda. Rwanda’s Climate Adaptation Monitoring, Evaluation and Learning (MEL) System in the Agriculture Sector: Case studies on the capacity of storage constructed, utilization of surveillance tools, and area of land under erosion control measures and used optimally. NAP Global Network, 2024. https://napglobalnetwork.org/wp-content/uploads/2024/03/rwanda-mel-agriculture-sector-case-studies-v3.pdf.
- Wikipedia
- {{cite report |last1=Tsinda |first1=Aime |last2=Ntaganda |first2=Brenda |title=Rwanda’s Climate Adaptation Monitoring, Evaluation and Learning (MEL) System in the Agriculture Sector: Case studies on the capacity of storage constructed, utilization of surveillance tools, and area of land under erosion control measures and used optimally |publisher=NAP Global Network |date=February 2024 |url=https://napglobalnetwork.org/wp-content/uploads/2024/03/rwanda-mel-agriculture-sector-case-studies-v3.pdf |access-date=23 October 2026 |via=Climate Insights Directory}}
- BibTeX
- @techreport{tsinda2024rwandas, author = {Tsinda, Aime and Ntaganda, Brenda}, title = {{Rwanda’s Climate Adaptation Monitoring, Evaluation and Learning (MEL) System in the Agriculture Sector: Case studies on the capacity of storage constructed, utilization of surveillance tools, and area of land under erosion control measures and used optimally}}, institution = {NAP Global Network}, year = {2024}, month = feb, url = {https://napglobalnetwork.org/wp-content/uploads/2024/03/rwanda-mel-agriculture-sector-case-studies-v3.pdf}, urldate = {2026-10-23}, note = {Indexed by Climate Insights Directory} }
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