The effects of climate change-induced flooding on harvest failure in Burkina Faso: case study

Abstract

Background: Climate change leads to more frequent and severe extreme weather events including floods, heatwaves, heavy rainfalls, and droughts. In contrast to the majority of research on weather extremes in sub-Saharan Africa, which focus primarily on how a lack of rainfall causes droughts, this paper aims to elucidate the effect of flooding on harvest failure in rural Burkina Faso. Methods: = 180) on whether any of their fields had been inundated and if so, on harvest loss on these fields; (ii) determining the feasibility of using Sentinel-2 satellite images to validate study participants reports of floods; (iii) characterizing short-term weather including frequency and duration, of extreme rainfall events within the study area, as well as comparing cumulative rainfall (long-term) over the past 50 years; and (v), estimating both the food energy and economic loss of harvest failure due to flooding. Results: = 14, 8%) had lost part of their harvest. Images from the Sentinel-2-Satellite indicated that reported and remotely observed flooding were consistent. According to time series of data from the local weather station, there has been an increase irregular rainfall distribution and at the same time of cumulative annual rainfall in Nouna. Furthermore, a first illustrative calculation allowed us to estimate the amount of energy lost when one hectare of a common crop is flooded. Conclusion: This case study demonstrated that flood-related harvest failures leading to crop losses in sub-Saharan Africa, exemplified by Burkina Faso, are likely to be substantial. This study serves as a proof-of-principle for flooding effects on food security. This could provide more detail for agricultural adaptation and mitigation strategies. Inundation-vulnerable fields need alternative and novel management practices, which may only be effectively implemented if agricultural institutions and national policy-making bodies receive evidence of flooding e.g., from remote sensing.