Rainfall and streamflow variability in North Benin, West Africa, and its multiscale association with climate teleconnections
Study region: Three tributaries of the Niger River, covering 48,000 km² in northern Benin, West Africa. Study focus: Understanding rainfall and streamflow variability in a warming world is crucial for drought-prone West Africa, whose economy relies heavily on rain-fed agriculture. This study explore...
Saved in:
| Main Authors: | , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-06-01
|
| Series: | Journal of Hydrology: Regional Studies |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2214581825001430 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Summary: | Study region: Three tributaries of the Niger River, covering 48,000 km² in northern Benin, West Africa. Study focus: Understanding rainfall and streamflow variability in a warming world is crucial for drought-prone West Africa, whose economy relies heavily on rain-fed agriculture. This study explores past changes (1970–2020) in catchment rainfall and streamflow and their association with climate teleconnections. New hydrological insights for the region: We find consistent rainfall patterns across the three catchments, with a recovery from the 1970s-1980s droughts starting in the 1990s. Total rainfall has increased significantly driven by more rainy days, although the wet day rainfall amount has decreased. These results can be summarized as ‘increased total rainfall, but less intense and more variable in space’. More rain, however, does not mean that the drought situation is alleviated, as high interannual and decadal variability persists. Wavelet coherence reveals that rainfall and streamflow variability are modulated by the climate teleconnections ENSO, AMO, and IOD. For rainfall, we find a tendency of a shift from lower-frequency coherence (4–10 years) in earlier decades to higher-frequency coherence (1–3 years) in recent decades. These patterns are less pronounced for streamflow due to indirect climate influences. Unlike many African studies relying on model simulations, these findings are based on quality-checked, dense station data networks, essential for understanding local climate impacts, water management, and early warning systems. |
|---|---|
| ISSN: | 2214-5818 |