Microplastics migration mechanisms in high-erosion watersheds under climate warming

Understanding Microplastics (MPs) migration in small watersheds is crucial for pollution management, but progress has been hindered by limited long-term data and modeling approaches. This study investigated three watersheds on the Qinghai-Xizang Plateau, each with distinct land uses (grassland, cropland, urban). Using 15 years of sediment data, a novel MPs migration model was developed with machine learning (RF, SHAP, DNN), achieving exceptionally high accuracy in source tracing (R² = 0.93) and pathway analysis (R² = 0.97). The results revealed that under conditions of sediment thickness < 6.5 cm (Scenario 1), MPs primarily migrated from cropland to sediment driven by southerly winds and surface runoff, with an MPs migration flux (nMPs) of 2.09 × 10⁴ items/m² and an MPs migration content (ρMPs) of 372.99 items/kg. For sediment thicknesses between 6.5 and 10 cm (Scenario 2), contributions from both cropland and grassland led to a 127.6 % increase in nMPs. When sediment thickness exceeds 10 cm (Scenario 3), grassland contributions become more significant, leading to a 284.52 % increase in nMPs and a 21.31 % reduction in ρMPs. Between 2000 and 2020, climate warming significantly intensified extreme precipitation (p < 0.05), shifting MPs migration patterns toward Scenario 3. Future projections (2030-2100) under a high-emission scenario indicated MPs migration and contents would increase by 111.64 % and 4.29 items/kg per decade, respectively. Under a low-emission scenario, migration would decrease by 1.48 % per decade, while MPs content would slightly increase by 1.05 items/kg per decade. This study provides a robust modeling framework for understanding MPs migration and supporting sustainable pollution management.