Midterm change in rainfall distribution in north and central Benin: implications for agricultural decision making

• Published in: Environment, development and sustainability Vol. 26; no. 11; pp. 27431 - 27456
• Main Authors: Wabi, Moudjahid Akorédé, Vanhove, Wouter, Idohou, Rodrigue, Hounkpèvi, Achille, Kakaï, Romain Lucas Glèlè, Van Damme, Patrick
• Format: Journal Article
• Language: English
• Published: Dordrecht Springer Netherlands 17.08.2023; Springer Nature B.V
• Subjects: Agricultural management; Agricultural production; Agriculture; Autocorrelation; Climate change; Climate effects; Crop production; Crop yield; Crops; Decision making; Earth and Environmental Science; Ecology; Economic Geology; Economic Growth; Environment; Environmental Economics; Environmental Management; Environmental risk; Flood frequency; Flood management; Hydrologic data; Process engineering; Rain; Rainfall; Rainfall distribution; Rainfall intensity; Resilience; Risk management; Seasonal distribution; Statistical analysis; Sustainable Development; Trends; Variability; Weather; Weather stations; Benin; Rainfall; Climate change; National adaptation plan (NAP); Agriculture; Risk management; Cropping seasons
• ISSN: 1573-2975; 1387-585X; 1573-2975
• DOI: 10.1007/s10668-023-03766-0

A better understanding of rainfall variability and trends is vital for agricultural production systems which are largely dependent on climate. This study aims to analyze and to quantify the significance of change on annual, seasonal and daily rainfall in North and Central Benin, and to infer future challenges for crop production. 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–November) in the three weather stations potentially increases flood frequencies during the harvest period of some crops, which can reduce crop yields. Adaptation strategies are needed which can mitigate the effects of climate change on agriculture. These findings are essential to the climate risk management in agriculture and to target appropriate adaptive measures for resilience building in the sector.