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Microplastics migration mechanisms in high-erosion watersheds under climate warming
Summary
Scientists built a machine-learning model using 15 years of sediment data from three different-use watersheds on China's Qinghai-Tibet Plateau — grassland, cropland, and urban — to track how microplastics migrate and where they end up under changing climate conditions. The model achieved very high accuracy in tracing plastic sources and pathways, and found that wind direction and surface runoff are key drivers of transport, with cropland as a major source. The approach offers a practical tool for managing microplastic pollution in remote, high-altitude watersheds where warming is accelerating erosion.
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.
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