Bernard Cappelaere

To project the future of natural resources, the modeling of continental surfaces is identified as a key tool. In this study, an emphasis is given to the modeling of water and vegetal resources, whose interactions cannot be finely apprehended by current models. To this end, an agro-eco-hydrological model is proposed to quantify both the energy, water and carbon exchanges and the plant productivity of natural and agricultural ecosystems encountered in the agropastoral Sahel: millet cultivation and shrub fallow. This model is based on the physically-based SVAT model, SiSPAT (Braud et al., 2005). It mechanistically simulates vertical energy and water transfers in the continuum, and its high capability in the Sahelian zone has been fully demonstrated (Velluet et al., 2014). Processes specific to plant functioning and to carbon cycle were now added to the model: photosynthesis, stomatal regulation, seasonal plant phenology, and organ carbon allocation. This step was carried out for the millet crop using the formalisms described in the agronomic models SARRA-H from CIRAD (Dingkuhn et al., 2003) and STICS from INRAE (Brisson et al., 1998). Similarly, the description of natural ecosystems will soon be drawn from the ecological models STEP (Mougin et al., 1986) and TREEGRASS-2 (Boulain et al., 2014); all these models dedicated to vegetation having successfully been tested in the Sahelian context. The new version of the model has now the ability to simulate the seasonal development of agrosystems as a function of climate and energy and water availability. A first phase of exploitation of the integrated model has just been carried out in order to evaluate the robustness and relevance of the developments. It was conducted at the scale of a millet plot and with the support of multi-year observations acquired at the Wankama site (Cappelaere et al., 2009). The presentation will focus on the results as well as some perspectives of applications in future climatic changes.

West African Sahelian and Sudanian ecosystems provide essential services to people and also play a significant role within the global carbon cycle. However, climate and land use are dynamically changing, and uncertainty remains with respect to how these changes will affect the potential of these regions to provide food and fodder resources or how they will affect the biosphere–atmosphere exchange of CO₂. In this study, we investigate the capacity of a process-based biogeochemical model, LandscapeDNDC, to simulate net ecosystem exchange (NEE) and aboveground biomass of typical managed and natural Sahelian and Sudanian savanna ecosystems. In order to improve the simulation of phenology, we introduced soil-water availability as a common driver of foliage development and productivity for all of these systems. The new approach was tested by using a sample of sites (calibration sites) that provided NEE from flux tower observations as well as leaf area index data from satellite images (MODIS, MODerate resolution Imaging Spectroradiometer). For assessing the simulation accuracy, we applied the calibrated model to 42 additional sites (validation sites) across West Africa for which measured aboveground biomass data were available. The model showed good performance regarding biomass of crops, grass, or trees, yielding correlation coefficients of 0.82, 0.94, and 0.77 and root-mean-square errors of 0.15, 0.22, and 0.12 kg m⁻², respectively. The simulations indicate aboveground carbon stocks of up to 0.17, 0.33, and 0.54 kg C ha⁻¹ m⁻² for agricultural, savanna grasslands, and savanna mixed tree–grassland sites, respectively. Carbon stocks and exchange rates were particularly correlated with the abundance of trees, and grass biomass and crop yields were higher under more humid climatic conditions. Our study shows the capability of LandscapeDNDC to accurately simulate carbon balances in natural and agricultural ecosystems in semiarid West Africa under a wide range of conditions; thus, the model could be used to assess the impact of land-use and climate change on the regional biomass productivity.

West African Sahelian and Sudanian ecosystems are providing essential services to people and also play a significant role within the global carbon cycle. However, climate and land use are dynamically changing and it remains uncertain how these changes will affect the potential of these regions for providing food and fodder resources or the biosphere-atmosphere exchange of CO₂. In this study, we investigate the capacity of a process-based biogeochemical model, LandscapeDNDC, to simulate net ecosystem exchange (NEE) and aboveground biomass of typical managed and natural Sahelian and Sudanian savanna ecosystems. We tested the model for various sites with different proportions of trees and grasses, as well as for the most typical arable cropping systems of the region. In order to describe the phenological development with a common parameterization across all ecosystem types, we introduced soil-water availability in addition to temperature as a driver as seasonal soil water-shortage is a common feature for all these systems. The new approach was tested by using a sample of sites (calibration sites) that provided NEE from flux tower observations and leaf area index data from satellite images (MODIS). For assessing the simulation accuracy, we applied the calibrated model to 42 additional sites (validation sites) across West Africa for which measured aboveground biomass data were available. The model showed a good performance regarding simulated biomass development. Overall, the comparison of simulated and observed biomass at sites with a dominating land cover of crops, grass or trees yielded correlation coefficients of 0.82, 0.94, and 0.77 and the Root Mean Square Error of 0.15, 0.22, and 0.12 kg m⁻², respectively. In absolute terms, the model results indicate above-ground carbon stocks up to 1733, 3291, and 5377 kg C ha⁻¹ yr⁻¹ for agricultural, savanna grasslands, and savanna mixed tree-grassland sites. Carbon stocks as well as exchange rates correlated in particular with the abundance of trees. The simulations indicate higher grass biomass and crop yields under more humid climatic conditions as can be found in the Sudanian savanna region. Our study shows the capability of LandscapeDNDC to accurately simulate carbon balances in natural and agricultural ecosystems in semi-arid West Africa under a wide range of conditions, so that it might be used to assess the impact of land-use and climate change on the regional biomass productivity.

West African Sahelian and Sudanian ecosystems are providing essential services to people and also play a significant role within the global carbon cycle. However, climate and land use are dynamically changing and it remains uncertain how these changes will affect the potential of these regions for providing food and fodder resources or the biosphere-atmosphere exchange of CO₂. In this study, we investigate the capacity of a process-based biogeochemical model, LandscapeDNDC, to simulate net ecosystem exchange (NEE) and aboveground biomass of typical managed and natural Sahelian and Sudanian savanna ecosystems. We tested the model for various sites with different proportions of trees and grasses, as well as for the most typical arable cropping systems of the region. In order to describe the phenological development with a common parameterization across all ecosystem types, we introduced soil-water availability in addition to temperature as a driver as seasonal soil water-shortage is a common feature for all these systems. The new approach was tested by using a sample of sites (calibration sites) that provided NEE from flux tower observations and leaf area index data from satellite images (MODIS). For assessing the simulation accuracy, we applied the calibrated model to 42 additional sites (validation sites) across West Africa for which measured aboveground biomass data were available. The model showed a good performance regarding simulated biomass development. Overall, the comparison of simulated and observed biomass at sites with a dominating land cover of crops, grass or trees yielded correlation coefficients of 0.82, 0.94, and 0.77 and the Root Mean Square Error of 0.15, 0.22, and 0.12 kg m⁻², respectively. In absolute terms, the model results indicate above-ground carbon stocks up to 1733, 3291, and 5377 kg C ha⁻¹ yr⁻¹ for agricultural, savanna grasslands, and savanna mixed tree-grassland sites. Carbon stocks as well as exchange rates correlated in particular with the abundance of trees. The simulations indicate higher grass biomass and crop yields under more humid climatic conditions as can be found in the Sudanian savanna region. Our study shows the capability of LandscapeDNDC to accurately simulate carbon balances in natural and agricultural ecosystems in semi-arid West Africa under a wide range of conditions, so that it might be used to assess the impact of land-use and climate change on the regional biomass productivity.

West African Sahelian and Sudanian ecosystems are providing essential services to people and also play a significant role within the global carbon cycle. However, climate and land use are dynamically changing and it remains uncertain how these changes will affect the potential of these regions for providing food and fodder resources or the biosphere-atmosphere exchange of CO₂. In this study, we investigate the capacity of a process-based biogeochemical model, LandscapeDNDC, to simulate net ecosystem exchange (NEE) and aboveground biomass of typical managed and natural Sahelian and Sudanian savanna ecosystems. We tested the model for various sites with different proportions of trees and grasses, as well as for the most typical arable cropping systems of the region. In order to describe the phenological development with a common parameterization across all ecosystem types, we introduced soil-water availability in addition to temperature as a driver as seasonal soil water-shortage is a common feature for all these systems. The new approach was tested by using a sample of sites (calibration sites) that provided NEE from flux tower observations and leaf area index data from satellite images (MODIS). For assessing the simulation accuracy, we applied the calibrated model to 42 additional sites (validation sites) across West Africa for which measured aboveground biomass data were available. The model showed a good performance regarding simulated biomass development. Overall, the comparison of simulated and observed biomass at sites with a dominating land cover of crops, grass or trees yielded correlation coefficients of 0.82, 0.94, and 0.77 and the Root Mean Square Error of 0.15, 0.22, and 0.12 kg m⁻², respectively. In absolute terms, the model results indicate above-ground carbon stocks up to 1733, 3291, and 5377 kg C ha⁻¹ yr⁻¹ for agricultural, savanna grasslands, and savanna mixed tree-grassland sites. Carbon stocks as well as exchange rates correlated in particular with the abundance of trees. The simulations indicate higher grass biomass and crop yields under more humid climatic conditions as can be found in the Sudanian savanna region. Our study shows the capability of LandscapeDNDC to accurately simulate carbon balances in natural and agricultural ecosystems in semi-arid West Africa under a wide range of conditions, so that it might be used to assess the impact of land-use and climate change on the regional biomass productivity.

West African Sahelian and Sudanian ecosystems are providing essential services to people and also play a significant role within the global carbon cycle. However, climate and land use are dynamically changing and it remains uncertain how these changes will affect the potential of these regions for providing food and fodder resources or the biosphere-atmosphere exchange of CO₂. In this study, we investigate the capacity of a process-based biogeochemical model, LandscapeDNDC, to simulate net ecosystem exchange (NEE) and aboveground biomass of typical managed and natural Sahelian and Sudanian savanna ecosystems. We tested the model for various sites with different proportions of trees and grasses, as well as for the most typical arable cropping systems of the region. In order to describe the phenological development with a common parameterization across all ecosystem types, we introduced soil-water availability in addition to temperature as a driver as seasonal soil water-shortage is a common feature for all these systems. The new approach was tested by using a sample of sites (calibration sites) that provided NEE from flux tower observations and leaf area index data from satellite images (MODIS). For assessing the simulation accuracy, we applied the calibrated model to 42 additional sites (validation sites) across West Africa for which measured aboveground biomass data were available. The model showed a good performance regarding simulated biomass development. Overall, the comparison of simulated and observed biomass at sites with a dominating land cover of crops, grass or trees yielded correlation coefficients of 0.82, 0.94, and 0.77 and the Root Mean Square Error of 0.15, 0.22, and 0.12 kg m⁻², respectively. In absolute terms, the model results indicate above-ground carbon stocks up to 1733, 3291, and 5377 kg C ha⁻¹ yr⁻¹ for agricultural, savanna grasslands, and savanna mixed tree-grassland sites. Carbon stocks as well as exchange rates correlated in particular with the abundance of trees. The simulations indicate higher grass biomass and crop yields under more humid climatic conditions as can be found in the Sudanian savanna region. Our study shows the capability of LandscapeDNDC to accurately simulate carbon balances in natural and agricultural ecosystems in semi-arid West Africa under a wide range of conditions, so that it might be used to assess the impact of land-use and climate change on the regional biomass productivity.

West African Sahelian and Sudanian ecosystems are providing essential services to people and also play a significant role within the global carbon cycle. However, climate and land use are dynamically changing and it remains uncertain how these changes will affect the potential of these regions for providing food and fodder resources or the biosphere-atmosphere exchange of CO₂. In this study, we investigate the capacity of a process-based biogeochemical model, LandscapeDNDC, to simulate net ecosystem exchange (NEE) and aboveground biomass of typical managed and natural Sahelian and Sudanian savanna ecosystems. We tested the model for various sites with different proportions of trees and grasses, as well as for the most typical arable cropping systems of the region. In order to describe the phenological development with a common parameterization across all ecosystem types, we introduced soil-water availability in addition to temperature as a driver as seasonal soil water-shortage is a common feature for all these systems. The new approach was tested by using a sample of sites (calibration sites) that provided NEE from flux tower observations and leaf area index data from satellite images (MODIS). For assessing the simulation accuracy, we applied the calibrated model to 42 additional sites (validation sites) across West Africa for which measured aboveground biomass data were available. The model showed a good performance regarding simulated biomass development. Overall, the comparison of simulated and observed biomass at sites with a dominating land cover of crops, grass or trees yielded correlation coefficients of 0.82, 0.94, and 0.77 and the Root Mean Square Error of 0.15, 0.22, and 0.12 kg m⁻², respectively. In absolute terms, the model results indicate above-ground carbon stocks up to 1733, 3291, and 5377 kg C ha⁻¹ yr⁻¹ for agricultural, savanna grasslands, and savanna mixed tree-grassland sites. Carbon stocks as well as exchange rates correlated in particular with the abundance of trees. The simulations indicate higher grass biomass and crop yields under more humid climatic conditions as can be found in the Sudanian savanna region. Our study shows the capability of LandscapeDNDC to accurately simulate carbon balances in natural and agricultural ecosystems in semi-arid West Africa under a wide range of conditions, so that it might be used to assess the impact of land-use and climate change on the regional biomass productivity.

West African Sahelian and Sudanian ecosystems are providing essential services to people and also play a significant role within the global carbon cycle. However, climate and land use are dynamically changing and it remains uncertain how these changes will affect the potential of these regions for providing food and fodder resources or the biosphere-atmosphere exchange of CO₂. In this study, we investigate the capacity of a process-based biogeochemical model, LandscapeDNDC, to simulate net ecosystem exchange (NEE) and aboveground biomass of typical managed and natural Sahelian and Sudanian savanna ecosystems. We tested the model for various sites with different proportions of trees and grasses, as well as for the most typical arable cropping systems of the region. In order to describe the phenological development with a common parameterization across all ecosystem types, we introduced soil-water availability in addition to temperature as a driver as seasonal soil water-shortage is a common feature for all these systems. The new approach was tested by using a sample of sites (calibration sites) that provided NEE from flux tower observations and leaf area index data from satellite images (MODIS). For assessing the simulation accuracy, we applied the calibrated model to 42 additional sites (validation sites) across West Africa for which measured aboveground biomass data were available. The model showed a good performance regarding simulated biomass development. Overall, the comparison of simulated and observed biomass at sites with a dominating land cover of crops, grass or trees yielded correlation coefficients of 0.82, 0.94, and 0.77 and the Root Mean Square Error of 0.15, 0.22, and 0.12 kg m⁻², respectively. In absolute terms, the model results indicate above-ground carbon stocks up to 1733, 3291, and 5377 kg C ha⁻¹ yr⁻¹ for agricultural, savanna grasslands, and savanna mixed tree-grassland sites. Carbon stocks as well as exchange rates correlated in particular with the abundance of trees. The simulations indicate higher grass biomass and crop yields under more humid climatic conditions as can be found in the Sudanian savanna region. Our study shows the capability of LandscapeDNDC to accurately simulate carbon balances in natural and agricultural ecosystems in semi-arid West Africa under a wide range of conditions, so that it might be used to assess the impact of land-use and climate change on the regional biomass productivity.

West African Sahelian and Sudanian ecosystems are providing essential services to people and also play a significant role within the global carbon cycle. However, climate and land use are dynamically changing and it remains uncertain how these changes will affect the potential of these regions for providing food and fodder resources or the biosphere-atmosphere exchange of CO₂. In this study, we investigate the capacity of a process-based biogeochemical model, LandscapeDNDC, to simulate net ecosystem exchange (NEE) and aboveground biomass of typical managed and natural Sahelian and Sudanian savanna ecosystems. We tested the model for various sites with different proportions of trees and grasses, as well as for the most typical arable cropping systems of the region. In order to describe the phenological development with a common parameterization across all ecosystem types, we introduced soil-water availability in addition to temperature as a driver as seasonal soil water-shortage is a common feature for all these systems. The new approach was tested by using a sample of sites (calibration sites) that provided NEE from flux tower observations and leaf area index data from satellite images (MODIS). For assessing the simulation accuracy, we applied the calibrated model to 42 additional sites (validation sites) across West Africa for which measured aboveground biomass data were available. The model showed a good performance regarding simulated biomass development. Overall, the comparison of simulated and observed biomass at sites with a dominating land cover of crops, grass or trees yielded correlation coefficients of 0.82, 0.94, and 0.77 and the Root Mean Square Error of 0.15, 0.22, and 0.12 kg m⁻², respectively. In absolute terms, the model results indicate above-ground carbon stocks up to 1733, 3291, and 5377 kg C ha⁻¹ yr⁻¹ for agricultural, savanna grasslands, and savanna mixed tree-grassland sites. Carbon stocks as well as exchange rates correlated in particular with the abundance of trees. The simulations indicate higher grass biomass and crop yields under more humid climatic conditions as can be found in the Sudanian savanna region. Our study shows the capability of LandscapeDNDC to accurately simulate carbon balances in natural and agricultural ecosystems in semi-arid West Africa under a wide range of conditions, so that it might be used to assess the impact of land-use and climate change on the regional biomass productivity.

In distributed land surface modeling (LSM) studies, uncertainty in the rainfields that are used to force models is a major source of error in predicted land surface response variables. This is particularly true for applications in the African Sahel region, where weak knowledge of highly time/space-variable convective rainfall in a poorly monitored region is a considerable obstacle to such developments. In this study, we used a field-based stochastic rainfield generator to analyze the propagation of the rainfall uncertainty through a distributed land surface model simulating water and energy fluxes in Sahelian ecosystems. Ensemble time/space rainfields were generated from field observations of the local AMMA-CATCH-Niger recording raingauge network. The rainfields were then used to force the SEtHyS-Savannah LSM, yielding an ensemble of time/space simulated fluxes. Through informative graphical representations and innovative diagnosis metrics, these outputs were analyzed to separate the different components of flux variability, among which was the uncertainty represented by ensemble-wise variability. Scale dependence was analyzed for each flux type in the water and energy budgets, producing a comprehensive picture of uncertainty propagation for the various flux types, with its relationship to intrinsic space/time flux variability. The study was performed over a 2530 km² domain over six months, covering an entire monsoon season and the subsequent dry-down, using a kilometer/daily base resolution of analysis. The newly introduced dimensionless uncertainty measure, called the uncertainty coefficient, proved to be more effective in describing uncertainty patterns and relationships than a more classical measure based on variance fractions. Results show a clear scaling relationship in uncertainty coefficients between rainfall and the dependent fluxes, specific to each flux type. These results suggest a higher sensitivity to rainfall uncertainty for hydrological than for agro-ecological or meteorological applications, even though eddy fluxes do receive a substantial part of that source uncertainty.