The deployment of green hydrogen production is increasingly considered a strategic opportunity for energy-exporting countries. However, beyond technological and environmental aspects, large-scale industrial projects may generate complex and uncertain social and economic impacts at the regional level. This study investigates the potential social implications of introducing a green hydrogen production plant in the Department of Paysandú, Uruguay, using a System Dynamics modeling approach. It proposes an initial system model designed to establish a foundational Modeling and Simulation framework. The model explicitly represents feedback mechanisms linking public finance, education, labor competencies, productivity, and social behavior impact, allowing the exploration of long-term socio-economic trajectories under alternative institutional and policy conditions. It is used as an exploratory decision-support tool to assess conditional pathways, trade-offs, and risks. Results indicate that positive social outcomes, such as human capital accumulation and regional income growth, are possible but not automatic; they depend critically on governance capacity, fiscal sustainability, labor market coordination, and social acceptance, and may be attenuated or delayed under adverse scenarios. While this framework provides a strategic engineering lens on the social dimension, it represents a first step toward a comprehensive decision-making tool. The study analyzes a complex system by integrating energy, production, economic, social, and environmental aspects from strategic engineering lens and contributes to the literature by integrating social dimension and institutional constraints into a Modeling and Simulation framework applied to green hydrogen industrialization, offering insights into policy design under uncertainty in emerging energy-export contexts.

Uruguay’s largest green-hydrogen initiative—an integrated e-fuels complex proposed for the Department of Paysandú—is approaching its final investment decision amid a public debate centered on water use, land occupation and community acceptance. Building on a peer-reviewed formulation in which social acceptance acts as an operational moderator of the local economy, this article reports the experimental, uncertainty and corroboration program of a hybrid System Dynamics and agent-based territorial impact model: a replicated factorial design, two global sensitivity campaigns, a 1000-replication Monte Carlo campaign, policy isolation studies, a feasibility assessment under editable thresholds, and a 2010–2022 historical backcast. In the simulations, capacity raises income only jointly with external demand (interaction: 21.2% of variance), while employment responds primarily to the public-investment rate (55.1%). Two behavioral parameters—the rates at which community trust builds and erodes—rank highest for every output (PRCC 0.74–0.96); as these are judgment parameters, the quantitative conclusions are conditional on their declared ranges, and their empirical calibration through a longitudinal design is identified as the priority. Acceptance declines monotonically across the sampled capacity range and the outcome distribution is bimodal, so policy is read as shifting the probability of the favorable branch. The backcast reproduces observed income conservatively and the official human-development index to half a percent. A model-conditional feasible configuration emerges—one train, phased construction, labor peace, early cost decline—delivered as a decision tool with editable thresholds.