Environmental DNA-informed modeling improves water diversion for cyanobacterial bloom mitigation in urban river-lake networks

Abstract Cyanobacterial blooms in lowland urban river–lake networks are shaped by channel connectivity and sluice operations. In a representative system of the Lower Yangtze region, we combine environmental DNA analysis and microscopic identification with a coupled hydrodynamic–ecological model to identify dominant bloom-forming groups and assess how water diversions and flow regimes control their transport and growth. Quantification of toxin- and odor-related genetic markers, supported by microscopy, shows that toxigenic Microcystis and a dominant filamentous cyanobacterial group account for most bloom biomass, allowing group-specific model parameterization. We then embed these data within an advection–diffusion–reaction framework, using gene copy numbers as proxies for abundance to define boundary conditions and estimate growth, loss, buoyancy, and dispersion parameters. Model results indicate that diversion through a single channel accelerates bloom transport toward the lake, whereas bifurcated diversion improves hydraulic connectivity but can import high cyanobacterial loads when source waters are contaminated. Under observed operational windows, diverting 5 cubic meters per second along the single-river route and 15 cubic meters per second along the bifurcated route reduces bloom risk while improving circulation, with more reaches exceeding target flow velocities. This integrated approach offers transferable guidance for safer diversion strategies and adaptive cyanobacterial management.