Farmers Adaptation Strategies to Drought and Their Adoption Determinants in Northwestern Parts of Bangladesh
Background: Drought-induced substantial production decline in agricultural sectors results in a seasonal food crisis in Bangladesh. Nevertheless, the farmers in Bangladesh have not yet adequately adopted adaptation strategies to address the detrimental effects of drought, especially in agriculture. The study was conducted to identify the farmers’ current adaptation strategies to drought and their adoption determinants in northwestern parts of Bangladesh. Methods: A total of 150 farmers were selected through simple random sampling from two drought affected districts of Bangladesh. The collected data were then analyzed by using the descriptive statistics and Poisson regression model. Result: The results indicated that approximately 38% of farmers adopted three out of the 9 strategies for adaptation to address the drought scenario. The Poisson regression suggested that the gender of the primary farmer, education, training and agriculture credit positively influence the adoption of adaptation strategies. For example, positive and significant coefficient of training suggests that farmers who have undergone training exhibit a 0.21 unit greater difference in the logs of expected counts compared to farmers who have not received any training. Farmers identified several obstacles to adoption, including insufficient knowledge about suitable adaptation, limited access to financing facilities and inadequate level of extension services.
Authors
- Mst Shopna Akter (ORCID: https://orcid.org/0009-0006-1691-1898)
- W. Mohammad
- S. M. Mustafizur Rahman (ORCID: https://orcid.org/0000-0001-9693-5529)
- Gazi M. A. Jalil
- Md. Sadique Rahman (ORCID: https://orcid.org/0000-0001-8175-2164)
Publication Details
- Journal
- Agricultural Science Digest - A Research Journal
- Published
- 2025-06-30
- DOI
- https://doi.org/10.18805/ag.df-691
- Primary Topic
- Agricultural Economics and Practices
- Type
- article
- Field-Weighted Citation Impact
- 0.00