Abstract:
Reducing discrepancies in the simulation of water and energy fluxes remains a key
challenge in accurately representing surface water flux processes, particularly in regions with
limited observational data. This study evaluates the sensitivity of the WRF-Hydro model to three
parameterization schemes - Free Drainage (FD), TOPMODEL, and MMF - over West Africa. The
results show that MMF outperforms the other schemes in representing surface water flux
variables, especially in topographic convergence zones, where soil moisture and
evapotranspiration in riverbeds increase by 20% with respect to FD. At the catchment scale, soil
moisture, evapotranspiration, and groundwater storage are well simulated, with correlation
coefficients reaching 0.9. In addition, model calibration for the Donga River gives reliable
performance with KGE value up to 0.74.
The shrubland, bare soil, and grassland (SBG) in MODIS-IGBP land cover is substituted by the
Evergreen Broadleaf Forest (EBF), Savanna (SAV), and Woody Savanna (WS) to mimic the the
Great Green Wall (GGW) initiative. At basin scale, the seasonal cycle and inter-annual variability
are well captured as there is a strong linear relationship between the observed and simulated
values with correlation coefficients from 0.9 to 0.97. The KGE values reaches respectively 0.72,
0.71, and 0.72 in Oueme, Sissili, and Faga catchments. Compared to the current land use (REF)
scenario, EBF-VC and WS-VC experiments decrease the mean soil moisture (SM) by 0.2 and 0.1
mm, while the SAV-VC increases it by 0.8 mm in drier conditions in Faga. However, the scenarios
reveal a decrease of mean SM by 0.5, 0.6, and 0.1 mm for EBF-VC, SAV-VC, and WS-VC in
higher precipitation areas (Oueme). Remarkably, the average ET is increased whatever the
climatic condition except for SAV-VC in Sissili where a negative effect is recorded. For instance,
EBF-VC, SAV-VC, and WS-VC increases the average ET by 0.25, 0.08, 0.07 mm d-1 in Faga.
EBF-VC, SAV-VC and WS-VC experiments reduce streamflow respectively by 24%, 18%, and
21% in Donga and 31%, 26%, and 28% in Oueme.
The change in the surface fluxes (e.g., LH, SH, GH, RN, ET) and subsurface dynamics (e.g.,
water table depth) in response to the variation of the lineaments permeability (K) is evaluated
with three experiments namely High, Moderate, and Low K (see section 3.4.2.5). Remarkably,
the most significant change in the diurnal cycle of the energy fluxes occurred around noon.
Compared to the reference simulation (without lineament), High and Moderate K experiments
decrease the outgoing longwave (LW) by -2% and -1% in the dry season. Higher permeability in the fractures results in a decrease of the outgoing longwave radiation. An increase of 1.1 and 1.5
W m-2 of sensible heat is associated with Moderate K and Low K experiments from March to
May. The energy balance closure increases significantly by 36.9 and 25.4% for Moderate K and
High K experiments from September to November (SON). The average groundwater storage
(GWS) of the basin increases with High K and Moderate K experiments by 355.8 and 326.8
million m3.
The climate projections of five Global Circulation Models (GCMs) namely GFDL-ESM4,
HadGEM3-GC31-LL, IPSL-CM6A-LR, MIROC6, and NorESM2-MM under two different
Shared Socioeconomic Pathways (SSP1-2.6, SSP5-8.5) are used to assess the subsurface
dynamics’ sensitivity to extreme warming scenarios. Under SSP1-2.6, 3 out the 5 GCMs show
an increase of groundwater storage (GWS) by 0.45 to 30.39 million m3 in Donga basin. All the
GCMs indicate a decrease of mean surface water storage (SWS) under SSP5-8.5 projection
except GFDL-ESM4. According to NorESM2-MM, IPSL-CM6A-LR, MIROC6, and
HadGEM3-GC31-LL projections, a decrease of surface water storage (SWS) will occur whatever
the warming level by the end of the century.
Changes in land use and land management significantly affect the global emissions budget,
influencing the climate through biogeochemical processes. This study provides the assessment of
soil greenhouse gas GHG emissions in the Sudanian savanna region of West Africa using a
chamber-based experimental setup. Our results reveal significant variation in methane (CH₄)
fluxes across the sites. However, nitrous oxide (N₂O) fluxes did not vary significantly, likely due
to uniformly low nitrogen input across all systems. The highest seasonal CH₄ emissions were
recorded in the rainfed rice field (0.69 ± 0.17 and 0.82 ± 0.22 kg C ha-1 season-1, on average),
while the forest reserve acted as a net CH₄ sink (−0.019 ± 0.20 and −0.42 ± 0.13 kg C ha-1 season-
1). In contrast, soils across all sites, both managed and natural, were sources of N₂O, with fluxes
ranging from 0.01 kg N ha⁻¹ season⁻¹ in the forest reserve to 0.16 kg N ha⁻¹ season⁻¹ in the rice
field. This study also analyzed the environmental drivers of GHG fluxes and found that CH₄
variability was significantly influenced by soil water content and soil temperature (partial R²
between 0.21 and 0.42). No significant relationship was observed between these variables and
N₂O emissions. These results highlight that changes in land cover and land management in the
Sudanian can substantially increase CH₄ emissions, while their impact on N₂O fluxes is marginal.