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Management and Sustainable Control of Harmful Algal Blooms
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Management and Sustainable Control of Harmful Algal Blooms

A special issue of Water (ISSN 2073-4441). This special issue belongs to the section "Water Quality and Contamination".

Deadline for manuscript submissions: 30 August 2026 | Viewed by 1092

Special Issue Editors

Dr. Ofir Tal

E-Mail Website
Guest Editor
Israel Oceanographic & Limnological Research Ltd., Haifa, Israel
Interests: harmful algal blooms; cyanoHABs; freshwater ecosystems; ecology; bioinformatics
Dr. Yael Amitai

E-Mail Website
Guest Editor
Israel Oceanographic & Limnological Research Ltd., Haifa, Israel
Interests: chlorophyll; oceanography numerical modeling; physical oceanography; ocean currents and circulation; satellite coastal oceanography

Special Issue Information

Dear Colleagues,

This Special Issue aims to promote a multidisciplinary framework for the sustainable management and control of harmful algal blooms (HABs) in ocean and freshwater environments. HABs, largely driven by eutrophication, climate variability, and hydrological alterations, are a growing threat to water quality, biodiversity, and public health. The Special Issue will welcome contributions that span from computational and modeling-based approaches, such as early warning systems, predictive models, data-driven causal inference, and decision support tools, to in situ strategies involving nutrient manipulation, chemical additions, or biological control agents. Field and mesocosm studies exploring the effectiveness, sustainability, and ecological safety of such interventions are especially encouraged. Submissions may also address climate-related vulnerability, system resilience, and long-term control strategies under realistic environmental constraints. It is hoped that this Special Issue will serve as a reference point for researchers, water authorities, and lake managers seeking integrative, science-based solutions to mitigate the impacts of HABs and promote ecosystem stability.

Dr. Ofir Tal
Dr. Yael Amitai
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Water is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • cyanoHABs
  • harmful algal blooms (HABs)
  • modeling
  • causal inference
  • monitoring
  • ecological restoration
  • sus-tainable control
  • climate change
  • decision–support
  • remote sensing

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Published Papers (2 papers)

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Research

16 pages, 1657 KB  
Article
Application of Clay–Polymer Nanocomposites for the Removal of Toxic Cyanobacteria and Other Phytoplankton from Water—A Laboratory Scale Study
by Giora Rytwo, Yehezkel Tsveher, Yehudith Viner-Mozzini and Assaf Sukenik
Water 2026, 18(11), 1301; https://doi.org/10.3390/w18111301 - 27 May 2026
Viewed by 110
Abstract
The increasing global frequency of harmful cyanobacterial blooms (CyanoHABs), driven by nutrient enrichment and climate change, poses a severe threat to aquatic ecosystems and public health. This study evaluates the effectiveness of novel clay–polymer nanocomposites (CPCs) that combine the charge-neutralizing capabilities of polydiallyldimethylammonium [...] Read more.
The increasing global frequency of harmful cyanobacterial blooms (CyanoHABs), driven by nutrient enrichment and climate change, poses a severe threat to aquatic ecosystems and public health. This study evaluates the effectiveness of novel clay–polymer nanocomposites (CPCs) that combine the charge-neutralizing capabilities of polydiallyldimethylammonium chloride (polyDADMAC) with the high clay mineral density (kaolinite and sepiolite) for rapid removal of toxic cyanobacteria from water. Laboratory experiments were performed using Microcystis aeruginosa, Aphanizomenon ovalisporum, and Chlorella sp., with treatment doses determined by particle charge detector (PCD) measurements to identify the “nominal dose” required for full charge neutralization. Results show that clay–polymer nanocomposites achieve over 95% removal of turbidity and chlorophyll in M. aeruginosa at doses significantly lower (15–20%) than the calculated nominal dose, likely due to specific physical bridging interactions with the cyanobacteria’s external exopolysaccharide fibers. In contrast, A. ovalisporum and Chlorella sp. required doses closer to full charge neutralization for optimal removal. Among the materials tested, kaolinite-based nanocomposites (DKG24) showed slightly superior, more stable performance than sepiolite-based nanocomposites. Notably, application at or above the nominal dose was associated with increased soluble microcystin levels, suggesting that excessive polymer concentrations may compromise cell integrity and lead to toxin leakage. These findings suggest that engineered nanocomposites offer highly efficient, scalable technology for CyanoHAB management, provided that operational doses are carefully optimized to maximize biomass removal while minimizing toxin release. Full article
(This article belongs to the Special Issue Management and Sustainable Control of Harmful Algal Blooms)
33 pages, 3319 KB  
Article
From Monitoring Data to Management Decisions: Causal Network Analysis of Water Quality Dynamics Using CEcBaN
by Sabrin Hilau, Yael Amitai and Ofir Tal
Water 2026, 18(6), 764; https://doi.org/10.3390/w18060764 - 23 Mar 2026
Viewed by 610
Abstract
Effective water resource management requires understanding the causal mechanisms driving water quality dynamics, yet extracting actionable insights from complex multivariate monitoring data remains a persistent challenge. This study presents CEcBaN (CCM-ECCM-Bayesian Networks), a decision-support tool that integrates Convergent Cross Mapping (CCM) for detecting [...] Read more.
Effective water resource management requires understanding the causal mechanisms driving water quality dynamics, yet extracting actionable insights from complex multivariate monitoring data remains a persistent challenge. This study presents CEcBaN (CCM-ECCM-Bayesian Networks), a decision-support tool that integrates Convergent Cross Mapping (CCM) for detecting dynamical coupling, Extended CCM (ECCM) for identifying temporal lags and causal directionality, and Bayesian network (BN) modeling for probabilistic scenario-based inference. The tool was designed to enable managers and researchers without programming expertise to reconstruct causal networks from routine monitoring data, distinguish direct from indirect effects, and evaluate intervention scenarios. CEcBaN was validated using four synthetic datasets with known causal structures, achieving superior specificity (0.83) and edge count accuracy (25% error) compared to Transfer Entropy (0.47 specificity, 139% error), Granger causality (0.82, 39% error), and the PC algorithm (0.83, 46% error). Application to Lake Kinneret, Israel, demonstrated the tool’s utility across three water quality challenges: (1) nitrogen cycling, where the nitrification pathway was reconstructed and seasonal stratification was identified as a key modulator (accuracy 0.931); (2) thermal dynamics, where a transition from atmosphere-driven to internally regulated heat transfer during stratification was revealed (2.1-fold increase in coupling strength); and (3) cyanobacterial bloom prediction, where prior phytoplankton community composition provided a 4–6-week early warning window (accuracy 0.846). CEcBaN advances causal inference in water resource management by making these analytical methods accessible through an intuitive interface. Full article
(This article belongs to the Special Issue Management and Sustainable Control of Harmful Algal Blooms)
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