Sectoral interactions and primary drivers in integrated CLEWs modeling: insights from Kenya

Abstract This study applies Global Sensitivity Analysis (GSA) to an optimization model for Kenya based on the Climate, Land, Energy, and Water systems (CLEWs) framework. The model provides insights into the interdependencies among energy, land, and water systems, and the sensitivity analysis allows to evaluate its ability to capture sectoral interactions and trade-offs while identifying key influential parameters shaping the overall system behavior. Using the Morris screening method, the analysis emphasizes the key role of discount rates—both global and technology- specific—influencing the energy sector, biomass use for cooking, renewable energy sources penetration, and forest land cover. The findings also show that all inputs influence forest cover, demonstrating the CLEWs model’s capacity to capture system interactions. By using a fully open methodology, this work enhances CLEWs model transparency and provides actionable insights for policymakers to address trade-offs and support resilient resource management.