Optimal riparian landscape management scale for simultaneous water quality improvement and riverine greenhouse gas emission mitigation

Riverine buffer zones are critical terrestrial-aquatic interfaces for regulating hydrochemistry in watershed landscape management. However, the optimal spatial scale for riverine buffer zone management to synergistically enhance water quality and mitigate greenhouse gas (GHG) emissions remains poorly understood. This study identified a potentially optimal management scale for water quality improvement and GHG mitigation in a river system characterized by landscape patterns. By integrating field-measured water quality and GHG (CO 2 , CH 4 , N 2 O) data with a high-resolution (10 m) land use/land cover (LU/LC) dataset developed from Sentinel-2 imagery using machine learning, we assessed landscape pattern effects across three riverine buffer zone types: riparian strips, circular zones, and sub-basins. The results showed that riparian landscape patterns exhibited stronger correlations with water quality and GHG fluxes than circular zones or sub-basins, and the 300 m buffer width was identified as an optimal management scale in the Yongding River Basin. Within the 300 m riparian strip, dissolved organic carbon and total phosphorus concentrations were negatively correlated with riparian forest coverage ( p < 0.01), highlighting the role of riparian vegetation in intercepting organic matter and nutrient inputs. Furthermore, CH 4 fluxes were strongly related to riparian landscape configuration, with lower edge density (ED) and landscape shape index (LSI), but higher contagion (CONTAG), being associated with reduced CH 4 emissions. Riparian forest shading may indirectly affect CO 2 and N 2 O emissions by regulating water temperature, oxygen conditions, and nitrogen dynamics. These findings emphasize that targeted management of riparian landscape patterns could improve water quality and mitigate riverine GHG emissions.