Green hydrogen site selection is a complex multi-criteria decision-making problem involving renewable-energy availability, water access, grid connectivity, industrial demand, land-use constraints, ecological risk, and social-permitting feasibility. Because these criteria are conflicting, heterogeneous, and often judged under uncertainty, this study proposes an explainable q-rung orthopair fuzzy Entropy-COPRAS framework for robust site evaluation. q-rung orthopair fuzzy sets are employed to represent positive, negative, and hesitant expert assessments within a flexible mathematical structure suitable for generalized uncertainty modelling. An entropy-based weighting procedure is developed to derive objective criterion weights from the dispersion of q-rung orthopair fuzzy score information, reflecting information-theoretic uncertainty. The COPRAS method is extended to rank candidate sites by separately considering benefit-type and cost-type criteria according to the complex proportional assessment principle. To improve transparency, the framework incorporates sensitivity analysis through q-parameter variation, weight perturbation, criterion ablation, and criterion-level contribution diagnosis. A reproducible benchmark with five candidate green hydrogen sites and seven criteria demonstrates the approach. Results show that the industrial port brownfield achieves the highest utility score, followed by the coastal renewable hub and inland solar belt. The framework supports transparent, interpretable, and sustainable hydrogen infrastructure planning under uncertain decision environments for planners, investors, regulators, and energy-system decision makers globally.