<![CDATA[Sustainable environmental management faces increasingly complex challenges due to the dynamics of environmental change, uncertainty within social-ecological systems, and the accelerated pace of technological development. These conditions require policy approaches that are no longer static but adaptive and responsive to changing real-world conditions. This study aims to formulate a real-time databased adaptive environmental policy model that can support decision-making in a more effective, transparent, and sustainable manner. The study employs a qualitative-descriptive approach through a systematic literature review and environmental policy analysis, drawing on relevant scientific sources and policy documents published over the past ten years. The results indicate that the integration of adaptive governance and the utilization of real-time data can establish a dynamic policy cycle in which environmental monitoring, data analysis, decision-making, and policy evaluation are interconnected within a mechanism of continuous learning. The resulting policy model consists of four main components, namely technology-based environmental monitoring systems, adaptive analysis and decision-making mechanisms, collaborative institutional frameworks, and policy feedback and learning mechanisms. This model has the potential to enhance policy responsiveness to environmental change, strengthen accountability and transparency, and encourage stakeholder participation. This study is expected to serve as a conceptual reference for policymakers and researchers in developing adaptive, data-driven environmental policies oriented toward long-term sustainability.]]>
