A classification scheme for Earth’s critical zones and its application in China

As the thin layer at the Earth’s terrestrial surface, the critical zone (CZ) ranges from the vegetation canopy to the aquifer or the interface between saprolite and bedrock and varies greatly in space. In the last decade, much attention has been paid to the establishment of Critical Zone Observatories (CZOs) that focus on various aspects of CZ science over different time scales. However, to the best of our knowledge, few studies have explicitly contributed to CZ classification or regionalization; thus, the spatial patterns of similar CZs have not been clearly identified. This study proposed a three-category CZ classification scheme by integrating environmental factors that greatly affect the transfer of energy and mass in the Earth’s near-surface environment and thus dominate CZ formation and evolution, i.e., climate, parent material, soil type, groundwater table depth, geomorphology and land use. The main goal was to highlight the zonality of these driving forces, of which the high-category classification units were overlaid to delineate the CZ boundaries. The CZ regionalization of China was performed as a case study, resulting in 44 major regions (1st category), 100 submajor regions (2nd category) and 1448 regions (3rd category). The spatial distributions and driving factors of the ten largest regions were identified, followed by a simple comparison of the CZO network. Then, the proposed CZ regionalization was compared with recent studies on regionalization in China to evaluate its successes and weaknesses. By linking together CZ studies from the last decade, we advocate that a theoretical framework integrating the CZ evolution processes with ecological functions acts as one of the frontiers of CZ science. Our study demonstrates that the proposed three-category CZ classification scheme effectively identifies the spatial variations in CZs and could thus be further applied in other areas to advance terrestrial environmental research and provide decision support for the sustainable management of natural resources.