In this study, the Soil and Water Assessment Tool (SWAT) model is used to assess changes in surface runoff between the baseline (1995–2014) and future (2031–2050) periods in the Tougou watershed ( 37 km 2 ) in Burkina Faso. The study uses a combination of land use maps (for current and future periods) and a bias-corrected ensemble of 9 CMIP6 climate models, under two warming scenarios. An increase in rainfall (13.7% to 18.8%) is projected, which is the major contributor to the increase in surface runoff (24.2% to 34.3%). The land use change narrative (i.e. conversion of bare areas to croplands) is expected to decrease in surface runoff, albeit minor in comparison to the effect of future climate change. Similar findings are observed for annual maximum surface runoff. This study sheds light on the need to consider simultaneously future climate and land use in framing water management policies.

In Burkina Faso, the basement aquifers represent a major asset in terms of quantity and quality, for both drinking and irrigation purposes for rural populations. They provide water resources that can guarantee the long-term needs of the populations, provided that a sustainable management policy for these resources is adopted. Yet, any groundwater resource management policy is necessarily linked to a better knowledge of aquifer recharge mechanisms, which is yet to be fully assessed in the Sahelian basement area. The objective of this study was to characterize the recharge mechanism within the experimental site of Sanon, located in the basement zone in Burkina Faso, using a coupling of hydrodynamic and chemical approaches. The hydrodynamic approach consisted of monitoring the spatial and temporal distribution of the piezometric levels of the aquifers along a north–south and east–west transect and determining soil infiltration capacity. The hydrochemical characterization of the aquifers was carried out through an analysis of groundwater samples from the concerned aquifers and daily tracing of the electrical conductivity of the aquifer water. The cross-analysis from the results of the implemented approaches shows a direct recharge mechanism through rainwater infiltration in the central valley, an indirect recharge mechanism in the lowlands, and a recharge mechanism by lateral transfers in the peripheral aquifers of the Sanon experimental catchment. The existence of a piezometric dome reveals in the central valley a zone of preferential recharge and water movement. The water of the central valley is the least mineralized with electrical conductivities below 100 µS/cm. This mineralization follows the direction of the water flow.

Groundwater is a vital water supply for local populations and ecosystems globally. With the continuous population growth, the anthropic pressure on groundwater is ever increasing, thus reducing the amount of available water resource. Yet, estimating the impact of anthropogenic activities on aquifer recharge is still a significant challenge for research, especially in basement aquifers. This study aims to improve the actual knowledge of deep drainage and deep aquifer recharge pathways and dynamics in the basement as affected by land use/land cover (LULC). The methodology used in this study accounted for hydraulic processes in soil layers within both unsaturated and saturated zones in an integrated approach. An experimental setup consisting of three (3) experimental plots, respectively under natural vegetation (NV), cropped millet (CM) and cropped groundnut (CG) on which deep drainage was monitored during the years 2020 and 2021. The results show significant differences between the LULC types after two years of implementation. Deep drainage is improved under CM and CG plots located in the central valley, as compared to the NV plot located in the ridge zone. Deep drainage is estimated at 8%, 24% and 25% of the annual rainfall, respectively for NV, CM and CG. The ratio between the recharge value obtained by the water table fluctuation (WTF) method and the deep drainage tends to 1 for the CM and CG plots, highlighting a rapid water transfer between unsaturated and saturated zones. The central valley, which seems to be a preferential recharge pathway, provides promising insights under specific conditions for the implementation of artificial recharge infrastructures.

This study aims to estimate the groundwater storage change of hard rock aquifers in the face of change. For this, the approach developed consisted initially in the implementation of 5 Magnetic Resonance Soundings (MRS) around the observation wells realized and monitored from 2014 to 2015 in the Sanon experimental site. In a second step, we determined the storage change using the MRS data and the water table fluctuation method. The MRS data show that the water content varies spatially from 4.5 to 1.3%. The maximum value is recorded at the central valley where a piezometric dome is observed. The specific yield varies from 2.4% in the central valley to 1.3% at the outlet. The renewed water resource is estimated at 116 mm in the central valley and 32 mm at the outlet, which corresponds respectively to 13 and 3% of the annual rainfall. The renewed water resource is consistent with the annual recharge. Thus, the combination of the MRS geophysical approach and water table fluctuation method is an efficient, fast and cheaper (compared with long-term pumping test) tool for the estimation of groundwater storage changes.

This study evaluates the impact of sub-daily bias correction of gridded rainfall products (RPs) on the estimation rainfall erosivity in Burkina Faso (West African Sahel). Selected RPs, offering half-hourly to hourly rainfall, are assessed against 10 synoptic stations over the period 2001–2020 to appraise their accuracy. The optimal product (the integrated multi-satellite retrievals for GPM, IMERG) is further used as a reference for bias correction, to adjust the rainfall distribution in the remaining RPs. RPs-derived rainfall erosivity is compared to the global rainfall erosivity database (GloREDa) estimates. The findings indicate that bias correction improves the rainfall accuracy estimation for all RPs, in terms of quantitative, categorial metrics and spatial patterns. It also improved the distributions of rainfall event intensities and duration across all products, which further significantly improved the annual rainfall erosivity estimates at various timescales along with spatial patterns across the country, as compared to raw RPs. The study also highlights that bias correction is effective at aligning annual trends in rainfall with those in rainfall erosivity derived from RPs. The study therefore underscores the added value of bias correction as a practice for improving the rainfall representation in high-resolution RPs before long-term rainfall erosivity assessment, particularly in data-scarce regions vulnerable to land degradation.