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Updated: Jan 11, 2026

Watershed Planning within a Quantitative Scenario Analysis Framework
Published on: July 24, 2016
Comprehensive Assessment of Vulnerability and Mitigation Opportunities for River Antibiotic Risk via Intelligent
Qian Qu1, Shuting Wang2, Xiangang Hu1
1Key Laboratory of Pollution Processes and Environmental Criteria (Ministry of Education), Tianjin Key Laboratory of Environmental Remediation and Pollution Control, College of Environmental Science and Engineering, Nankai University, Tianjin 300350, China.
Abstract:
Riverine antibiotic pollution has gained significant attention owing to its negative impacts on the environment and human health. Although previous studies have revealed the spatial distribution of antibiotics in local regions, their vulnerability to antibiotic risks, environmental drivers, policy intervention effectiveness, and potential opportunities for mitigation remain unknown. Here, we constructed a random-forest-algorithm-assisted risk assessment framework and intelligent watershed management to capture the temporal and spatial variations in global river antibiotic risks. The interaction between precipitation and livestock density as a key driver explained ∼43% of the antibiotic risk variance. Rivers in Africa are highly vulnerable to antibiotic pollution. We provide empirical evidence supporting the effectiveness of antibiotic use control policies, identifying more than 15 successful interventions that significantly reduce risks. Notably, policy instruments demonstrate greater effects when implemented as a mix rather than in isolation. Optimization analysis demonstrated that reducing wastewater discharge (4.82 ± 0.04%) and livestock density (10.23 ± 0.05%) would alleviate antibiotic risk by 10.22 ± 0.08%, which would benefit ecological functions (e.g., water purification, gross primary productivity, and leaf litter decomposition) in rivers. These findings provide novel insights for advancing global antibiotic mitigation and strengthening integrated watershed management.
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