抄録
The Critical Zone (CZ), as an integrated interface connecting the lithosphere, hydrosphere, biosphere, and atmosphere, represents a core scientific unit for understanding the coupled structure and function of Earth’s surface systems. In recent years, Critical Zone science has developed rapidly worldwide, emerging as a frontier field for exploring multi-sphere interactions and environmental sustainability within the Earth system. This study systematically reviews the theoretical evolution and research progress of CZ science, outlining its disciplinary trajectory and future development trends. Through bibliometric analysis and theoretical synthesis, it first reveals the conceptual evolution of the CZ from the “Earth’s living skin” to the “Earth’s reactor,” highlighting its theoretical significance in surface system coupling studies. It then comprehensively summarizes recent advances in CZ research from the perspectives of hydrological processes, biogeochemical cycling, and multi-sphere matter–energy exchanges, comparing different research paradigms regarding deep weathering, interface reactions, and feedback mechanisms. Furthermore, it examines the applications and limitations of Critical Zone Observatories (CZOs), multi-scale monitoring technologies, and numerical simulations in promoting the integration and prediction of surface processes. The findings indicate that model complexity, data uncertainty, and cross-scale integration remain key bottlenecks constraining the systematization of CZ research. Finally, under the context of global change, this paper proposes future directions for CZ science: strengthening process modeling driven by artificial intelligence and big data, deepening the study of deep biosphere–rhizosphere interactions, and constructing a digital twin of the Critical Zone to achieve dynamic perception and predictive simulation of Earth surface systems. Through theoretical integration and forward-looking analysis, this work aims to promote the development of Critical Zone science toward greater predictability, sustainability, and systematization.
