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NEXSOL: A WEFE Nexus Decision Support System for Climate-Resilient Agroforestry Planning in TRANS-SAHARA Living Labs
Abstract   Open access   Peer reviewed

NEXSOL: A WEFE Nexus Decision Support System for Climate-Resilient Agroforestry Planning in TRANS-SAHARA Living Labs

Ekaterina Chuprikova, Michele Berlanda, N Fröhlich, E Gardner, KY Asamoah, Roberto Monsorno, S Bouguerra and D. Keilmann-Gondhalekar
EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-20611, https://doi.org/10.5194/egusphere-egu26-20611, 2026
EGU General Assembly 2026 (Vienna, 03/05/2026–08/05/2026)
2026
Handle:
https://hdl.handle.net/10863/54231

Abstract

visual analytics WEFE Nexus Agroforestry
We present NEXSOL, the TRANS-SAHARA WEFE Nexus Agroforestry Intervention Design Tool for Climate Resilience, developed within TRANS-SAHARA, an EU-funded Horizon project. NEXSOL is a decision support system (DSS) that translates model outputs into actionable guidance for agroforestry planning in Living Labs in Tunisia, Ghana, and Ethiopia. Positioned within the WEFE (Water–Energy–Food–Ecosystems) Nexus, it aims to support researchers, policymakers, and local authorities in exploring intervention options and assessing trade-offs and synergies that affect ecosystem services, water security, and community resilience across the Greater Northern African Region. This contribution reports work in progress. NEXSOL is being developed to integrate three complementary modelling strands produced in TRANS-SAHARA: (i) a WEFE Nexus framework that computes cross-sectoral KPIs and applies multi-objective optimization to identify “best” solutions across water, energy, food supply, emissions, and economic dimensions; (ii) an optimization-based agroforestry/land-use allocation model that evaluates socio-economic and environmental costs and benefits under plausible future market, productivity, and policy scenarios; and (iii) climate and species-distribution projections that indicate current and future land-use suitability and related ecosystem-service implications. Specifically, the methodology comprises: (1) the classification of model families, associated data requirements, and remaining gaps; (2) the compilation and harmonization of multi-source datasets and key performance indicators (KPIs); (3) the implementation of a WEFE modelling environment tailored to Living Lab contexts; (4) the development of optimization-based land-use allocation methods for baseline assessment and scenario exploration; (5) the integration of climate projections and species distribution modelling outputs; (6) the establishment of a reproducible data pipeline encompassing ingestion, quality assurance/quality control (QA/QC), metadata management, and version control; (7) the design of a decision-support system (DSS) user interface featuring dashboards, maps, time series, heatmaps, and structured scenario workflows; and (8) calibration and validation using spatially explicit observations. By coupling WEFE modelling with data-driven prediction and visual analytics, the tool may provide climate-robust, actionable guidance on where and how agroforestry interventions are most effective, thereby advancing multi-objective and multi-risk optimization (e.g., profitability, biodiversity, equity) and incorporating carbon-market and payments-for-ecosystem-services mechanisms. The resulting modular system is co-designed with stakeholders and validated against real-world datasets and decision processes. This research is funded by the framework of the TRANS-SAHARA project, funded by European Union under the Horizon Europe Framework Program Grant Agreement Nº: 101182176.
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