Abstract

Author:
Ackim Phiri, Ashish Khanal

Doi: 10.26480/efcc.01.2026.01.07

This is an open access article distributed under the Creative Commons Attribution License CC BY 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited

Lack of reliable localized weather forecasting systems to predict weather patterns is a big challenge to smallholder farmers in Samuel village of Kasenengwa. This hinders effective crop production planning among smallholder farmers. The challenge has increased due to climate variability being experienced in the Saharan region. The increase in temperatures, droughts, and spread of diseases affect crop production. Modern technology provides valuable insights, but its forecasts are often not localized. Also, the challenges of adequate infrastructure, which is expensive to acquire and maintain, have affected the adoption of modern technology. The study focused on smallholder farmers in Samuel village. A total of 100 respondents were selected for the study with the average age being 45 years old, were 65% were female and 35% male. Data was collected using structured questionnaires, interviews, and focus group discussions in April 2023. The collected data was analyzed using Statistical Package for Social Science (SPSS) to understand the relationships. The study revealed various natural and cultural indicators used to predict weather patterns. These include natural-based indicators like plants, insects, and birds. Commonly used plants included Uapaca kirkiana, and Parinari curatelifolia, whose flowering and fruiting ability is key in weather forecasting. This method of forecasting climate change is negatively being impacted due to increasing population causing deforestation, hence affecting prediction accuracy. Smallholder farmers are willing to support government efforts in forest conservation. Therefore, the government must promote extension services to the community and strengthen monitoring mechanisms to reduce high deforestation levels in the area.