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- W4200380453 abstract "Abstract A better understanding of rainfall variability and trends is vital for agricultural production systems. This study evaluates the spatio-temporal variability and trends in annual, seasonal and daily rainfall in Benin. Daily rainfall data for the 1970-2016 period measured at three weather stations (Savè, Malanville, and Tanguiéta) were obtained from the Benin National Weather Agency. Descriptive statistics, standardized anomaly of rainfall (SAR) and rainfall intensity were used to analyze rainfall variability. For rainfall trends analysis, we tested for auto-correlation and used the Mann-Kendall and Modified Mann-Kendall tests for non-auto-correlated and auto-correlated data, respectively. Trend magnitude was estimated using Sen’s slope. Globally a moderate-to-high seasonal rainfall and low variability of yearly rainfall were observed. The SAR indicated more than 50% of the years in the studies period experienced dry years. Between 1970 and 2016, a significant 20 % increase was observed in the yearly rainfall in Tanguiéta whereas no significant trends were observed in Malanville (10% increase) and Savè (0.6% decrease). The general rainfall increase observed during the post-monsoon season (October to November) in the three weather stations potentially increases flood frequencies during the harvest period of some crops, which can reduce crop yields. The changes in the pre-monsoon season (March to May) and monsoon season (June to September) were not globally uniform and can have positive/negative impact on agriculture, certainly when no adaptation strategies are applied. These findings are essential to the resilience building and climate risk management in agriculture which is largely dependent on weather conditions." @default.
- W4200380453 created "2021-12-31" @default.
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- W4200380453 date "2021-12-30" @default.
- W4200380453 modified "2023-09-26" @default.
- W4200380453 title "Characterization of Spatio-temporal Trends in Long-term Rainfall of Three Weather Stations in Benin: Implications for Agricultural Decision Making." @default.
- W4200380453 doi "https://doi.org/10.21203/rs.3.rs-1140845/v1" @default.
- W4200380453 hasPublicationYear "2021" @default.
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