Quantification of Soil Deep Drainage and Aquifer Recharge Dynamics according to Land Use and Land Cover in the Basement Zone of Burkina Faso in West Africa

Abstract

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.

Daily Simulation of the Rainfall–Runoff Relationship in the Sirba River Basin in West Africa: Insights from the HEC-HMS Model

“…This could further be explained by the fact that most hydrological models are rarely sensitive to potential evapotranspiration [4,76,77], which typically affects antecedent soil moisture levels between rainfall events, especially in the case of continuous-based simulations of the water cycle. Also, while intricate relationships in neighboring contexts between surface runoff and groundwater have been reported, such as preferential recharge pathways or groundwater feedback through rising tables [78,79], no such significant control from groundwater to surface runoff was observed in this study. In fact, previous studies highlighted that in the SRB, flood magnitude is largely influenced by surface processes rather than groundwater flow, as the river basin hydrology remains closely dependent on rainfall variability [33].…”

Recharge Estimation Approach in a Data-Scarce Semi-Arid Region, Northern Ethiopian Rift Valley

“…Water scarcity is increasingly becoming a monumental challenge, particularly in arid and semi-arid regions, where the water supply primarily comes from groundwater sources, as surface water sources are inadequate and unreliable [1][2][3][4]. In these areas, especially in rapidly expanding urban and agricultural regions, sustainable groundwater resource development and management rely on reliable estimates of recharge and its variability in time and space [5][6][7][8][9][10]. Accurately estimating recharge is one of the most challenging water-balance components as it is highly spatially and temporally variable and is affected by many factors (e.g., climate, topography, vegetation, soil, and geology) [11][12][13][14][15][16].…”

Unravelling the Impacts of Climate Variability on Surface Runoff in the Mouhoun River Catchment (West Africa)

“…The sedimentary catchment is mainly made of primary and infracambrian formations and clay alluvium of fluvial-lacustrine origin from the terminal continental period. The nature of the topsoil follows closely the geology, geomorphology, and climate patterns, resulting in six major types of soil in the catchment: arenosols, leptosols, lixisols, nitisols, plinthosols, and regosols [33][34][35]. The catchment is mainly dominated by lixisols, with arenosols representing only a tiny fraction of the catchment [36,37], as shown in Figure 2a.…”