Rainfall variability and rice (Oryza Sativa L.) cultivation in Guyana: A case study
Abstract
Rice (Oryza sativa L.) is one of Guyana’s most important agricultural commodities, with cultivation schedules closely linked to the country’s bimodal rainfall pattern. This study analyses rainfall data obtained from the Ministry of Agriculture’s Hydrometeorological Service of Guyana, Georgetown weather station, for the period 1960-2016. The study aimed to assess rainfall variability relative to the two main rice growing seasons: May to July (MJJ) and November to January (NDJ). The rainfall data was processed using the Python Anaconda Distribution software. Time-series analyses were conducted for the study period, including ten-day running mean graphs and boxplots to represent monthly and seasonal variability under different ENSO phases. The results confirmed a distinct bimodal rainfall distribution driven by the northward and southward migration of the Intertropical Convergence Zone (ITCZ), with peak rainfall occurring in the months of June and December. Further, the results showed that the MJJ season displays higher precipitation (6.2 -11.8 mm ten-day running mean) and greater variability compared to the NDJ season (4.3-9.3 mm), indicating generally wetter conditionsduring the first crop. Further, the MJJ season shows no strong teleconnection to the El Niño Southern Oscillation (ENSO). The NDJ season displays a clear ENSO influence, with El Niño years producing drier conditions and La Niña years producing wetter conditions. These findings highlight the importance of rainfall timing, distribution, and ENSO phase monitoring in planning rice cultivation, particularly for the second crop when ENSO related rainfall deficits are more likely to impact yields.
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