Microplastic (MP) contamination in groundwater is an emerging environmental concern with implications for human health and agricultural sustainability. Understanding soil hydrology–microplastic interactions is essential for predicting contaminant fate, managing agricultural sustainability, and protecting groundwater and aquatic ecosystems. Unlike previous studies that assess the presence of MPs in groundwater in isolation, this work integrates soil properties, hydrological dynamics, and risk assessment within a unified framework, providing a more comprehensive evaluation of microplastic contamination pathways and potential impacts. Groundwater samples were collected from 48 wells across varied hydrogeological and agricultural zones of Hiriyur Taluk, Karnataka. Soil permeability, porosity, and groundwater recharge rates were measured, and MPs were quantified using density separation and FTIR analysis. Spatial patterns of MP distribution were assessed using GIS mapping, while statistical approaches (i.e., Pearson correlation, Principal Component Analysis (PCA), and regression) and machine learning, i.e., Random Forest (RF), were applied to identify key contamination predictors. MP concentrations ranged from 0.8 to 23.4 particles/L with a standard deviation of 6.75 particles/L. The polymers detected were of the order PE > PP > PET > PS. The Random Forest model achieved an accuracy of 70 %, a precision of 60 %, and an F1-score of 0.63, reflecting balanced performance between correct classification and prediction consistency for microplastic contamination levels. Risk assessment indicated 8 out of 48 wells with greater values of MPs in drinking water, and irrigation-dependent crops exhibited potential for bioaccumulation. The results showed that high-risk zones overlap with areas of intensive farming and irrigation using MP-contaminated surface water. The study provides evidence-based policy recommendations for targeted MP monitoring of high-risk groundwater wells, retrofitting existing wells, promoting sustainable irrigation practices, stakeholders’ collaboration, and the reduction of plastic inputs into agricultural landscapes. These strategies form an integrated framework that can guide monitoring across other semi-arid agricultural settings. The findings highlight that soil permeability and recharge rates are critical drivers of MP mobility, with agricultural hotspots showing elevated contamination. These results underscore the urgent need for integrated groundwater monitoring and plastic-waste management policies in semi-arid agricultural regions.
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