Explainable machine learning reveals how thermal stratification and mixing reshape actinobacterial community stability and regulate taste and odor risk in drinking-water source reservoirs

Key Points

• Actinobacterial community stability is significantly impacted by thermal stratification and mixing processes, affecting overall water quality.
• Machine learning techniques highlight specific factors that regulate taste and odor risk in drinking-water reservoirs, aiding in water safety management.
• Observational analysis across various reservoirs indicates a direct relationship between thermal conditions and microbial community dynamics.
• The findings emphasize the need for effective monitoring strategies to ensure water quality standards, especially in warmer climates.