Harmful algal blooms pose growing risks to freshwater ecosystems, drinking water security, and public health. Yet despite their dramatic appearance at the water surface, the earliest stages of these events often unfold quietly and invisibly below. This study shows that algal blooms can begin days earlier than previously recognized, originating from chlorophyll-rich plumes rising from lake sediments before any surface discoloration appears. Using ultrahigh-resolution three-dimensional monitoring, researchers observed how these hidden subsurface plumes move upward through the water column and later spread horizontally, ultimately seeding surface blooms. The findings reveal that bloom formation follows a structured bottom-up process rather than a sudden surface accumulation, offering new opportunities for early detection and prevention.
Globally, harmful algal blooms have intensified over recent decades as a result of nutrient enrichment, climate warming, and increasingly variable hydrological conditions. While surface blooms are easily detected by satellites or visual surveys, their subsurface precursors remain poorly understood. Lake sediments are known to store both nutrients and dormant algal cells, but conventional monitoring tools lack the spatial and temporal resolution needed to track how these benthic reservoirs contribute to bloom initiation. Satellite observations cannot penetrate deep waters, and routine sampling often misses rapid, localized events occurring near the lakebed. As a result, the physical mechanisms linking sediment disturbance to surface bloom outbreaks have remained largely speculative. Based on these challenges, it is essential to conduct in-depth research to uncover subsurface bloom precursors and the pathways by which they are transported upward.
Researchers from Harbin Institute of Technology and collaborating institutions reported their findings (DOI: 10.1016/j.ese.2025.100652) on December 25, 2025, in Environmental Science and Ecotechnology. The study introduces an ultrahigh-resolution three-dimensional monitoring framework that uses an autonomous underwater drone to observe algal dynamics in a freshwater reservoir. Over a four-month period, the system collected more than 2.8 million data points, allowing researchers to track how rainfall-driven disturbances at the sediment–water interface generate chlorophyll-rich plumes that rise through the water column and ultimately fuel surface algal blooms.
The team deployed a remotely operated underwater vehicle equipped with multiparameter sensors and samplers to map the reservoir at an unprecedented resolution—five meters horizontally and one meter vertically. This level of detail enabled continuous, volumetric monitoring of chlorophyll-a concentrations throughout the entire water column. In effect, the researchers could observe the lake as a dynamic three-dimensional system rather than a flat surface snapshot. During heavy rainfall events, the data consistently revealed a three-stage process. First, chlorophyll anomalies appeared near the lakebed as rainfall-induced turbulence resuspended sediment and dormant algal cells. Next, instead of dispersing immediately, these anomalies formed coherent plumes that ascended vertically while maintaining high biomass concentrations. Finally, after a delay of approximately one to two days, the plumes reached surface waters and expanded laterally, triggering visible algal blooms.
Statistical analyses showed that deep-water chlorophyll peaks systematically preceded surface blooms, providing direct evidence for a bottom-up initiation mechanism. Spatial comparisons further demonstrated strong correlations between surface bloom hotspots and areas with high benthic algal stocks combined with strong wind–rain forcing. In contrast, simulations based on conventional monitoring approaches often failed to detect these short-lived subsurface signals, identifying blooms only after surface concentrations had already peaked. Together, these results indicate that sediment-derived plumes act as reliable early indicators of impending algal blooms, but only when monitoring systems are capable of resolving fine-scale, three-dimensional processes.
“This study fundamentally changes how we understand algal bloom initiation,” said Prof. Troy Yu Tao from Harbin Institute of Technology, the leading author of the work. “For a long time, blooms were treated as sudden surface events. Our results show that they are actually the final stage of an organized process that begins near the sediment days earlier. By detecting these hidden subsurface dynamics, we gain a valuable time window for intervention.”
The findings highlight the potential of ultrahigh-resolution underwater monitoring as an early-warning tool for harmful algal blooms. By identifying sediment-derived precursors before surface proliferation occurs, water managers could shift from reactive responses to proactive prevention. Targeted interventions—such as localized sediment management in high-risk zones—may reduce bloom severity while minimizing ecological disruption. As climate change intensifies rainfall and hydrodynamic disturbances in freshwater systems, process-based monitoring approaches like this will become increasingly important for safeguarding ecosystems, protecting drinking water supplies, and improving the resilience of aquatic environments worldwide.
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References
DOI
https://doi.org/10.1016/j.ese.2025.100652
Original Source URL
https://doi.org/10.1016/j.ese.2025.100652
Funding information
This work was supported by the National Natural Science Foundation of China (No. 52321005, No. 52293443, and No. 52230004), Shenzhen Science and Technology Program (No. KQTD20190929172630447), Shenzhen Key Research Project (No. GXWD20220817145054002), Shenzhen Natural Science Foundation (No. JCYJ20240813104812017), and Talent Recruitment Project of Guangdong (No. 2021QN020106).
About Environmental Science and Ecotechnology
Environmental Science and Ecotechnology (ISSN 2666-4984) is an international, peer-reviewed, and open-access journal published by Elsevier. The journal publishes significant views and research across the full spectrum of ecology and environmental sciences, such as climate change, sustainability, biodiversity conservation, environment & health, green catalysis/processing for pollution control, and AI-driven environmental engineering. The latest impact factor of ESE is 14.3, according to the Journal Citation ReportsTM 2024.