Explainable machine learning algorithms reveal the role of mixing strategies in controlling cyanobacterial overgrowth in a drinking water reservoir

2026-06-15

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Yunhao Bai

Tinglin Huang *

DOI：10.1016/j.jconhyd.2026.105028

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• The three mixing strategies all effectively reduced cyanobacterial overgrowth. • The artificial mixing strategy showed most marked reduction in cyanobacterial abundance. • The mixing process facilitated filamentous cyanobacteria into smaller. • Optimizing machine learning models by comparing ROC curves. • Employing interpretable machine learning algorithms to identify key environmental factors.

Explainable machine learning algorithms reveal the role of mixing strategies in controlling cyanobacterial overgrowth in a drinking water reservoir

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