Sensitivity of a Sahelian groundwater-based agroforestry system to tree density and water availability using the land surface model ORCHIDEE (r7949) - 2025
Modeling and Simulation; Earth and Planetary Sciences (all)
Abstract :
[en] The Sahel region is characterized by its semi-arid climate and open-canopy agroforestry systems, which play an important role in global carbon dynamics. Parkland agroforestry has the potential to sequester carbon at an average rate of 0.4 tC ha-1 yr-1, which, if expanded to its maximum potential extent, would correspond to an additional carbon stock of approximately 558 TgC compared to treeless croplands. However, land surface models (LSM) used in global climate modeling struggle to represent carbon dynamics in these ecosystems due to the inadequate representation of deep-roots tapping groundwater during dry periods, key environmental control for many agroforestry systems such as the widespread parklands based on the phreatophytic species Faidherbia albida. This study explores the sensitivity of Faidherbia albida parklands to tree density and water availability (rainfall and soil water content in the capillary fringe of the groundwater table) using a new configuration of the ORCHIDEE LSM. To this aim, the ORCHIDEE LSM was modified to simulate the growth of Faidherbia albida by simulating its inverted phenology based on forced temporal series of soil water content of soil layers between 4 and 5 m and water saturation below 5 m and by adjusting the photosynthesis and carbon allocation parameters for Faidherbia albida and associated crops. The model was evaluated against independent eddy covariance and meteorological data from the Niakhar agroforestry site in Senegal. Simulation outputs were analyzed in terms of leaf area index (LAI), gross primary productivity (GPP), latent heat (LE), sensible heat (H) and net radiation (Rn). The model simulated tree GPP of 4.08 ± 0.21 tC ha-1 yr-1 compared to observed GPP of 5.06 ± 0.49 tC ha-1 yr-1. For croplands, the model produced GPP of 7.97 ± 0.89 tC ha-1 yr-1 compared to observed values of 7.78 ± 1.75 tC ha-1 yr-1. Simulations revealed that tree density positively influenced annual carbon uptake but reduced crop harvest at highest tree densities, indicating a trade-off between carbon sequestration and crop yield. Sensitivity analyses showed that interannual variability in soil water content in the capillary fringe of the groundwater table and rainfall influenced differently crop, tree and ecosystem carbon and energy fluxes. Despite its strengths, the model exhibited limited responsiveness of tree productivity to soil water content variability in the capillary fringe of the groundwater table, highlighting the need for enhanced representation of water uptake by tree roots in the model. These findings emphasize the importance of accurately modeling both surface soil water and groundwater dynamics and phenology to predict the responses of semi-arid agroforestry systems to climate variability. This study enhances our understanding of carbon and energy flux partitioning in complex, water-stressed and groundwater dependent agroforestry systems.
Vandewalle, Nadeige ; Université de Liège - ULiège > Département GxABT > Biosystems Dynamics and Exchanges (BIODYNE) ; Earth and Life Institute, Faculty of Bioscience Engineering, Catholic University of Louvain, Louvain-la-Neuve, Belgium
Do, Frédéric C.; LMI IESOL, IRD, ISRA, Bel Air, Dakar, Senegal ; Eco&Sols, University Montpellier, CIRAD, INRAE, Institut Agro, IRD, Montpellier, France ; IRD, UMR Eco & Sols, Univ Montpellier, IRD, CIRAD, INRAE, Montpellier, France
ANR - Agence Nationale de la Recherche DAAD - Deutscher Akademischer Austauschdienst CIRAD - Centre de Coopération Internationale en Recherche Agronomique pour le Développement EU - European Union
Funding text :
This work was publicly funded by the DMTropAFS project through ANR (the French National Research Agency) under the Investissements d'avenir programme with the reference ANR-10-LABX-001-01 Labex Agro and coordinated by Agropolis Fondation. This work was performed using High-Performance Computing (HPC) resources provided by the Grand Equipement National de Calcul Intensif - Tres Grand Centre de Calcul (GENCi-TGCC) under grant 2024-06328. Espoir Gaglo gratefully thanks the German Academic Exchange Service (DAAD) for financial support through a scholarship (In Region Scholarship Programme - CERAAS Senegal/57504744) and CIRAD for providing additional resources to support visits to Eco&Sols through the Action Incitative (AI) Fellowship.This work was publicly funded by the DM-TropAFS project through ANR (the French National Research Agency) under the \u201CInvestissements d'avenir\u201D programme with the reference ANR-10-LABX-001-01 Labex Agro and coordinated by Agropolis Fondation. This work was performed using High-Performance Computing (HPC) resources provided by the Grand \u00C9quipement National de Calcul Intensif \u2013 Tr\u00E8s Grand Centre de Calcul (GENCi\u2013TGCC) under grant 2024-06328. Espoir Gaglo gratefully thanks the German Academic Exchange Service (DAAD) for financial support through a scholarship (In Region Scholarship Programme \u2013 CERAAS Senegal/57504744) and CIRAD for providing additional resources to support visits to Eco&Sols through the Action Incitative (AI) Fellowship.We thank the students and technicians running the \u201CFaidherbia-Flux\u201D platform ( https://lped.info/wikiObsSN/?Faidherbia-Flux , last access: 22 June 2025) and especially Cl\u00E9mence Chenu, Ablaye Diouf, Ibou Diouf, and Robert Diatte. The \u201CFaidherbia-Flux\u201D research infrastructure and platform are funded by CIRAD, IRD, UMR Eco&Sols, LMI IESOL, ISRA, CERAAS. We gratefully acknowledge the use of the Obelix computing cluster from IPSL, France, which provided access to ORCHIDEE and the essential computing infrastructure that enabled the research presented in this paper. Additionally, the authors thank Philippe Peylin, Catherine Ottle, Agn\u00E8s Ducharne and Josefine Ghattas for sharing their knowledge of the model.Several other projects also contributed to supporting the Faidherbia-Flux platform and the PhD of Espoir Koudjo Gaglo, namely: EU Eranet LEAP Agri-215 RAMSES II (EU) grant no. 215; EU DeSIRA CASSECS (grant no. FOOD/2019/410-169); EU H2020 SUSTAIN-SAHEL (grant No. 861974); EU HORIZON EUROPE GALILEO (grant agreement no. 101181623); ANR and France 2030 program PEPR FairCarboN RIFT project (ANR-22-PEXF-0004).
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