Multidimensional Analysis of Meteorological Information as a Lever for Adoption of Climate-Smart Agricultural Practices: a Case Study in Senegal

The effects of climate change significantly impact critical sectors, such as agriculture, which threaten food security for smallholder farmers in Senegal. In response to this challenge, climate-smart agricultural practices and the utilization of climate information are essential for building resilience. However, the factors influencing the adoption of these practices are not well understood, which limits the effectiveness of adaptation policies. This study aimed to identify the factors that influence the adoption of climate-smart agricultural practices among smallholder farmers in Senegal. A total of 341 households were surveyed, with data collected through questionnaires and interviews. The data were analyzed using Epi-Data and SPSS software. Univariate and bivariate analyses were conducted, and a multivariate binary regression model was developed to identify the factors affecting the adoption of these agricultural practices. The results indicate that practices such as harvest timing, land preparation, sowing or planting timing, post-harvest treatments, and intercropping have an adoption rate of 60%. Notably, the timing of forecast communication emerged as the most significant factor, with an adoption rate of 57.2%. The study also reveals a significant direct relationship between the use of meteorological information and the adoption of climate-smart agricultural practices, with a regression coefficient (B) of 0.498 and a t-value of 8.396. Furthermore, confidence in meteorological information plays a crucial mediating role in this relationship (Z = 6.454, p < 0.000001). Despite this mediation, the direct link remains significant. These findings offer valuable insights into promoting climate-smart practices among smallholder farmers and can inform policies aimed at enhancing agricultural resilience in the face of climate change.