Evapotranspiration (ET) is pivotal in the terrestrial water cycle in subhumid and tropical regions. In the water cycle, the contribution of plant transpiration can be distinctively more significant than soil evaporation. The seasonal dynamics of plant phenology, commonly represented as the vegetation attribute leaf area index (LAI), closely correlates with actual ET (AET). Hence, addressing the reciprocal LAI–AET interaction is essential for practitioners and researchers to comprehensively quantify the hydrological processes in water resources management, particularly in the perennially vegetated regions of West Africa. However, due to a lack of field measurements, evaluation of the LAI–AET interaction still remains challenging. Hence, our study aims to improve the understanding of the role of the LAI in AET estimation by investigating characteristic regions of West Africa. We set up ecohydrological models (using the Soil and Water Assessment Tool for the tropics – SWAT-T) for two homogeneous land cover types (forest and grassland) to guarantee the representativeness of field measurements for the LAI and AET. We apply different potential ET methods (the Hargreaves; Penman–Monteith – PET-PM; and Priestley–Taylor methods) to evaluate the LAI–AET interaction in SWAT-T. Further, the elementary effects method quantifies the parameter sensitivity for 27 relevant LAI–AET parameters. The comprehensive parameter set is then optimized using the shuffled complex evolution algorithm. Finally, we apply a benchmarking test to assess the performance of SWAT-T with respect to the simulation of AET and to determine the relevance of detailed LAI modeling. The results show that SWAT-T is capable of accurately predicting the LAI and AET at the footprint scale. While all three PET methods facilitate adequate modeling of the LAI and AET, the PET-PM technique outperforms the other methods for AET, independent of the land cover type. Moreover, the benchmarking highlights that, if it only accounts for the LAI but disregards AET data, an optimization process's prediction of AET still yields an adequate performance with SWAT-T for all PET methods and land cover types. Our findings demonstrate that the significance of detailed LAI modeling for the AET estimation is more pronounced in the forested than in the grassland region.

This study evaluates the impact of precipitation ensembles on flood hazards in the Ouémé River Basin by coupling the hydrological HBV and hydrodynamic HEC–RAS model. Both models were calibrated and validated to simulate hydrological and hydraulic processes. Meteorological and hydrometric data from 1994 to 2016, along with flood maps and DEM are used. Evapotranspiration data are calculated using Hargreaves–Samani formula. The coupling HBV–HEC–RAS models enabled the generation of ensemble hydrographs, flood maps, flood probability maps and additional statistics in West Africa for the first time, offering a comprehensive understanding of flood dynamics under uncertainty. Ensemble hydrographs and maps obtained enhance decision-making by showing discharge scenarios, spatial flood variability, prediction reliability, and probabilities, supporting targeted flood management and resource planning under uncertainty. The findings underline the need for a comprehensive strategy to mitigate both common and rare flood events while accounting for spatial uncertainties inherent in hydrological and hydraulic modeling.

Actual evapotranspiration (AET) is a key component of the water cycle and a crucial source of uncertainty in hydrological modeling, particularly for sub-humid and AET-dominant regions such as West Africa. In this region, climate change is projected to be substantial, which will catalyze hydrological changes. In the climate-hydrological modeling chain for impact assessment, multiple sources of uncertainty are embedded. Hence, the present study investigates how different calibration strategies influence simulated future hydrological projections in West Africa. Given the key role of AET in West Africa, the study particularly evaluates how calibration shapes simulated future AET dynamics. In addition, we test whether a specific plant growth modeling, attributed as leaf area index (LAI), can be used as a proxy to predict AET. The Bétérou Catchment in Benin is selected as a demonstration case along hydrological modeling with the eco-hydrological SWAT-T model. To investigate calibration impacts, we apply three strategies, which range from simple (discharge ( Q ) only) to more comprehensive ( Q and LAI; Q , LAI, and AET) approaches. We apply the Robust Parameter Estimation algorithm in each calibration strategy to address parameter equifinality. We use the standardized future climate data from ISIMIP3b (CMIP6) with five GCMs and three emission scenarios and evaluate changes for the near (2031–2050) and far (2070–2099) future periods. The calibration results demonstrate that the combined “ Q + LAI” improves representation of the AET seasonal pattern compared with “ Q only”. From “ Q only” to “ Q + LAI”, the minimum (median) performance increases from EKGE,AET=0.59 (EKGE,AET=0.84) to EKGE,AET=0.81 (EKGE,AET=0.86), respectively. The findings moreover show that projected changes in annual AET depend on the calibration strategy, where all strategies indicate increasing future AET. More precisely, the “ Q + LAI” (886 to 918 mm yr ⁻¹ ) and “ Q + LAI + AET” (904 to 932 mm yr ⁻¹ ) approaches show similar climate sensitivities and project higher future annual AET rates than the “ Q only” approach (846 to 889 mm yr ⁻¹ ). For discharge, contrasting predictions of future changes depending on single GCMs are simulated, mostly indicating decreases across all calibration strategies. The present study provides insights into how calibration choices affect AET simulations for hydrological projections in West Africa. While this study demonstrates that detailed LAI modeling can improve the simulation of seasonal AET dynamics, further research is required to evaluate whether LAI can be used as a reliable proxy for AET in hydrological watershed models.

Evapotranspiration (ET) plays a pivotal role in the terrestrial water cycle in sub-humid and tropical regions. Thereby, the contribution of plant transpiration can be distinctively greater than the soil evaporation. The seasonal dynamics of plant phenology, e.g., commonly represented as the vegetation attribute leaf-area-index (LAI), closely correlates with actual ET (AET). Addressing the reciprocal LAI-AET interaction is hence essential for practitioners and researchers to comprehensively quantify the hydrological processes in water resources management, particularly in the perennially vegetated regions of Western Africa. However due to the lack of field measurements, the evaluation of the LAI-AET interaction still remains challenging. Hence, our study aims to improve the understanding of the role of LAI on the AET estimation with the investigation of characteristic regions of Western Africa. We setup eco-hydrological models (SWAT-T) for two homogeneous land cover types (forest and grassland) to guarantee the representativeness of field measurements for LAI and AET. To evaluate the LAI-AET interaction in SWAT-T, we apply different potential ET methods (Hargreaves, Penman-Monteith (PET-PM), Priestley-Taylor). Further, the parameter sensitivity for 27 relevant LAI-AET parameters is quantified with the elementary effects method. The comprehensive parameter set is then optimized using the Shuffled-Complex-Evolution algorithm. Finally, we apply a benchmark test to assess the performance of SWAT-T to simulate AET and to determine the relevance of a detailed LAI modelling. The results show that SWAT-T is capable to accurately predict LAI and AET on the footprint scale. While all three PET methods facilitate an adequate modelling of LAI and AET, PET-PM outperforms the methods for AET independent of the land cover type. Moreover, the benchmarking highlights that if an optimization process only accounts for LAI but disregards AET data, its prediction of AET still yields an adequate performance with SWAT-T for all PET methods and land cover types. Our findings demonstrate that the significance of a detailed LAI modelling on the AET estimation is more pronounced in the forested than in the grassland region.

Actual evapotranspiration (AET) is pivotal for the assessment of current and future water availability, particularly for sub humid and AET dominant regions such as West Africa. In this region, climate change is projected to be substantial, which will catalyze hydrological changes. In the climate-hydrological modeling chain for impact assessment, multiple sources of uncertainty are embedded. While the uncertainties inherent in general circulation models (GCM) are difficult to reduce, minimizing uncertainties from hydrological modeling remains a critical focus for researchers and practitioners. Hence, the present study investigates the impact calibration strategies can have on future hydrological changes in West Africa. Given the key role of AET in West Africa, the study particularly evaluates how calibration shapes its future dynamics. In addition, we test whether a specific plant growth modeling, attributed as leaf area index (LAI), can be used as a proxy to predict AET. The Bétérou Catchment in Benin is selected as a demonstration case along hydrological modeling with the eco-hydrological SWAT-T model. To investigate calibration impacts, we apply three strategies, which range from simple (discharge (Q) only) to more comprehensive (Q and LAI; Q, LAI, and AET) approaches. We use the Robust Parameter Estimation algorithm in each calibration strategy to address parameter equinfinality. We use the standardized future climate data from ISIMIP3b (CMIP6) with five GCMs and three emission scenarios and evaluate changes for the near (2031–2050) and far (2070–2099) future periods. The findings show that the amount of future annual AET depends on the calibration strategy, where the change signal for all strategies indicates AET increases. The approach including AET calibration (Q, LAI, AET) shows high future changes, with e.g., multi-model mean changes for SSP5–8.5 of ΔE_near = 5.8 % and ΔE_far = 8.4 %. The results moreover demonstrate that the combined "Q + LAI" can be used as a proxy to predict AET rates. For discharge, the change signal mostly indicates future decreases across all calibration strategies with multi-model mean changes for SSP5–8.5 of ∆Q_far = −7.0 % (Q, LAI, AET) to ΔQ_far = −1.6 % (Q only). Yet, contrasting predictions of future changes depending on single GCMs are simulated. The present study under-20 scores the relevance of uncertainty integration in climate-hydrological modeling and contributes to an improved understanding of water availability assessment in West Africa.

Actual evapotranspiration (AET) is pivotal for the assessment of current and future water availability, particularly for sub humid and AET dominant regions such as West Africa. In this region, climate change is projected to be substantial, which will catalyze hydrological changes. In the climate-hydrological modeling chain for impact assessment, multiple sources of uncertainty are embedded. While the uncertainties inherent in general circulation models (GCM) are difficult to reduce, minimizing uncertainties from hydrological modeling remains a critical focus for researchers and practitioners. Hence, the present study investigates the impact calibration strategies can have on future hydrological changes in West Africa. Given the key role of AET in West Africa, the study particularly evaluates how calibration shapes its future dynamics. In addition, we test whether a specific plant growth modeling, attributed as leaf area index (LAI), can be used as a proxy to predict AET. The Bétérou Catchment in Benin is selected as a demonstration case along hydrological modeling with the eco-hydrological SWAT-T model. To investigate calibration impacts, we apply three strategies, which range from simple (discharge (Q) only) to more comprehensive (Q and LAI; Q, LAI, and AET) approaches. We use the Robust Parameter Estimation algorithm in each calibration strategy to address parameter equinfinality. We use the standardized future climate data from ISIMIP3b (CMIP6) with five GCMs and three emission scenarios and evaluate changes for the near (2031–2050) and far (2070–2099) future periods. The findings show that the amount of future annual AET depends on the calibration strategy, where the change signal for all strategies indicates AET increases. The approach including AET calibration (Q, LAI, AET) shows high future changes, with e.g., multi-model mean changes for SSP5–8.5 of ΔE_near = 5.8 % and ΔE_far = 8.4 %. The results moreover demonstrate that the combined "Q + LAI" can be used as a proxy to predict AET rates. For discharge, the change signal mostly indicates future decreases across all calibration strategies with multi-model mean changes for SSP5–8.5 of ∆Q_far = −7.0 % (Q, LAI, AET) to ΔQ_far = −1.6 % (Q only). Yet, contrasting predictions of future changes depending on single GCMs are simulated. The present study under-20 scores the relevance of uncertainty integration in climate-hydrological modeling and contributes to an improved understanding of water availability assessment in West Africa.