Climate variability poses significant risks to agricultural productivity, particularly for smallholder farmers in Rwanda. This paper presents the Dfarmer Mobile Application, a digital tool designed to enhance climate risk management by providing real-time weather updates, early warning notifications, and climate-smart agricultural advisories. The system was tested in Musanze District, a region with a high dependency on agriculture, to assess its feasibility, usability, and effectiveness in improving farmers’ decision-making. The study highlights the strengths of the application, including its scalability, ease of use, and potential to improve farm resilience. However, challenges such as mobile network dependency, digital literacy barriers, and the need for long-term sustainability strategies were identified. Findings suggest that the Dfarmer Mobile Application has the potential to support climate adaptation efforts among Rwandan farmers but requires further refinement to optimize accessibility and effectiveness. Future work will focus on expanding the system’s functionality, integrating machine learning for predictive analytics, and conducting broader evaluations across diverse agricultural regions.

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Development of a Mobile-Based Climate Information System for Farmers’s Climate Risk Management: A Case Study of Musanze District, Rwanda

  • Mukaneza Angelique,
  • Neema Mduma,
  • Kisangiri Michael

摘要

Climate variability poses significant risks to agricultural productivity, particularly for smallholder farmers in Rwanda. This paper presents the Dfarmer Mobile Application, a digital tool designed to enhance climate risk management by providing real-time weather updates, early warning notifications, and climate-smart agricultural advisories. The system was tested in Musanze District, a region with a high dependency on agriculture, to assess its feasibility, usability, and effectiveness in improving farmers’ decision-making. The study highlights the strengths of the application, including its scalability, ease of use, and potential to improve farm resilience. However, challenges such as mobile network dependency, digital literacy barriers, and the need for long-term sustainability strategies were identified. Findings suggest that the Dfarmer Mobile Application has the potential to support climate adaptation efforts among Rwandan farmers but requires further refinement to optimize accessibility and effectiveness. Future work will focus on expanding the system’s functionality, integrating machine learning for predictive analytics, and conducting broader evaluations across diverse agricultural regions.