This study presents the calibration and validation of the physically based spatially distributed hydrological and soil erosion model SHETRAN for the Dano catchment, Burkina Faso. A sensitivity analysis of six model parameters was performed to assess the model response and to reduce the number of parameters for calibration. The hydrological component was calibrated and validated using observed discharge data of two years. Statistical quality measures (R 2 , NSE, KGE) ranged from 0.79 to 0.66 during calibration and validation. The calibrated hydrological component was used to feed the erosion modeling. The simulated suspended sediment load (SSL) was compared with turbidity-based measurements of SSL of two years. Achieved quality measures are comparable to other SHETRAN studies. Uncertainties of measured discharge and suspended sediment concentration were determined to assess the propagated uncertainty of SSL. The comparison of measurement uncertainties of discharge and SSL with parameter uncertainty of the corresponding model output showed that simulated discharge and SSL were frequently outside the large measured uncertainty bands. A modified NSE was used to incorporate measurement and parameter uncertainty into the efficiency evaluation of the model. The analyses of simulated erosion sources and spatial patterns showed the importance of river erosion contributing more than 60% to the total simulated sediment loss.
Water scarcity for smallholder farming in West Africa has led to the shift of cultivation from uplands to inland valleys. This study investigates the impacts of climate and land use/land cover (LULC) change on water resources in an intensively instrumented inland valley catchment in Southwestern Burkina Faso. An ensemble of five regional climate models (RCMs) and two climate scenarios (RCP 4.5 and RCP 8.5) was utilized to drive a physically-based hydrological model WaSiM after calibration and validation. The impact of climate change was quantified by comparing the projected period (2021–2050) and a reference period (1971–2000). The result showed a large uncertainty in the future change of runoff between the RCMs. Three models projected an increase in the total runoff from +12% to +95%, whereas two models predicted a decrease from −44% to −24%. Surface runoff was projected to show the highest relative change compared to the other runoff components. The projected LULC 2019, 2025, and 2030 were estimated based on historical LULC change (1990–2013) using the Land Change Modeler (LCM). A gradual conversion of savanna to cropland was shown, with annual rates rom 1 to 3.3%. WaSiM was used to simulate a gradual increase in runoff with time caused by this land use change. The combined climate and land use change was estimated using LULC-2013 in the reference period and LULC-2030 as future land use. The results suggest that land use change exacerbates the increase in total runoff. The increase in runoff was found to be +158% compared to the reference period but only +52% without land use change impacts. This stresses the fact that land use change impact is not negligible in this area, and climate change impact assessments without land use change analysis might be misleading. The results of this study can be used as input to water management models in order to derive strategies to cope with present and future water scarcities for smallholder farming in the investigated area.
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