<p>Facing the dual pressures of climate change and rapid urbanization, regional ecosystems are experiencing unprecedented stress. Developing advanced decision-support technologies to assess ecological vulnerability is crucial for developing effective climate adaptation and mitigation strategies. This study couples the Ordered Weighted Averaging (OWA) operator with the Sensitivity–Resilience–Pressure (SRP) model to evaluate spatiotemporal dynamics and simulate adaptive management scenarios in Zhejiang Province. The objective is to elucidate the mechanisms of climate–human–environment interactions and provide a foundation for targeted spatial governance. Based on the SRP conceptual model, the temporal and spatial evolution of ecological vulnerability from 2000 to 2020 was analyzed. Using 2020 data, the OWA operator was introduced as a scenario simulation technology to assess vulnerability under multiple decision-making preferences (ranging from risk-averse to risk-seeking). Spatial autocorrelation results were integrated to delineate four types of adaptive functional zones under three representative scenarios. Furthermore, the geographical detector model was applied to identify the driving mechanisms and synergistic effects among influencing factors. Results show that ecological vulnerability in Zhejiang Province first decreases and then increases, with significant spatial heterogeneity characterized by lower vulnerability in the southwest and higher vulnerability in the northeast. Multi-scenario simulations indicate that decision preferences regarding climate risks markedly influence vulnerability distribution. Land-use intensity, biological abundance, and vegetation coverage are identified as the main driving factors. These findings provide critical insights for future ecological zoning and the development of resilient, climate-adaptive governance in Zhejiang Province.</p>