Abstract
Cotton yields in the Sudano-Sahelian region contribute to food security through their role in agricultural productivity. Daily precipitation data and cotton yield data were synthesized from nine agricultural regions obtained from the “Société de Développement du Coton (SODECOTON)”. The following seasonal rainfall indices—from Cameroon’s cotton zone—were mapped with geographic information systems for spatial analysis: wet season onset and retreat date, rainfall amount, number of rainy days, rainfall intensity (SDII), heavy-rainfall events (R95p), consecutive dry days (CDD), annual highest daily precipitation (Rx1day) and number of very heavy precipitation days (R20mm). Linear regressions were used as statistical tools for analysis. The strongest relationships were observed between cotton yields and the heavy-rainfall events, closely followed by seasonal rainfall amount. An increase in consecutive dry days (CDD) and heavy events, and a decreased seasonal rainfall amount, have a negative impact on cotton yield trends. Overall, the critical breakpoint analysis between cotton yields and all rainfall indices showed that the cotton yield was particularly negatively impacted before a 251 retreat date, 591 mm seasonal rainfall amount and 33 rainy days. By contrast, an onset date, rainfall intensity, heavy rainfall, CDD, Rx1day and R20mm of 127, 12.5 mm·day−1, 405 mm, 27 days, 67 mm and 22 days, respectively, were identified for an optimum cotton yield. These results can be used as information for agricultural activity and management, civil planning of economic activities and can also contribute to furthering our understanding of the management impacts on future food security.
Highlights
Introduction iationsCotton production is a vital source of food and income for millions of people in developing countries, including West Africa
We analyzed the spatiotemporal impact of the following seasonal rainfall indices on the cotton yield in the Sudano-Sahelian zone of Cameroon: onset and retreat of the rainy season, number of rainy days, rainfall amount and rainfall intensity, number of Consecutive Dry Days (CDD), highest daily precipitation and frequency and heavyrainfall events
Our results demonstrated the strongest relationship between cotton yields and heavy-rainfall events closely followed by a relationship between cotton yields and seasonal rainfall amount
Summary
Cotton production is a vital source of food and income for millions of people in developing countries, including West Africa. It is commonly presented as a positive economic indicator in West Africa [1]. Cotton yields have been increasing continually since the 1960s, while in West Africa, they stagnated since the 1980s, with a decline in some countries such as Cameroon (Statistics of the Food and Agriculture Organization of the United Nations (FAO): http://faostat.fao.org, accessed on 20 October 2021). The aim of this study is to contribute to furthering our understanding of this decline by examining the effects of climate, focusing mainly on how the seasonal distribution of rainfall on cotton productivity could increase farmers’ yields. Cotton is the major cash crop of Cameroon and represents the major
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