Study of a hydrodynamic threshold system for controlling dinoflagellate blooms in reservoirs

Principles and research progress of physical prevention and control technologies for algae in eutrophic water

The abnormal reproduction of algae in water worldwide is prominent in the context of human interference and global climate change. This study first thoroughly analyzed the effects of physical factors, such as light, temperature, hydrodynamics, and operational strategies, on algal growth and their mechanisms. Physical control techniques are safe and have great potential for preventing abnormal algal blooms in the absence of chemical reagents. The focus was on the principles and possible engineering applications of physical shading, ultrasound, micro-current, and ultraviolet (UV) technologies, in controlling abnormal algal reproduction. Physical shading can inhibit or weaken photosynthesis in algae, thereby inhibiting their growth. Ultrasound mainly affects the physiological and biochemical activities of cells by destroying the cell walls, air cells, and active enzymes. Micro-currents destroy the algal cell structure through direct and indirect oxidation, leading to algal cell death. UV irradiation can damage DNA, causing organisms to be unable to reproduce or algal cells to die directly. This article comprehensively summarizes and analyzes the advantages of physical prevention and control technologies for the abnormal reproduction of algae, providing a scientific basis for future research. In the future, attempts will be made toward appropriately and comprehensively utilizing various physical technologies to control algal blooms. The establishment of an intelligent, comprehensive physical prevention and control system to achieve environmentally friendly, economical, and effective physical prevention and control of algae, such as the South-to-North Water Diversion Project in China, is of great importance for specific waters.

Modeling study on oil spill transport in the Great Lakes: The unignorable impact of ice cover

The rise in oil trade and transportation has led to a continuous increase in the risk of oil spills, posing a serious worldwide concern. However, there is a lack of numerical models for predicting oil spill transport in freshwater, especially under icy conditions. To tackle this challenge, we developed a prediction system for oil with ice modeling by coupling the General NOAA Operational Modeling Environment (GNOME) model with the Great Lakes Operational Forecast System (GLOFS) model. Taking Lake Erie as a pilot study, we used observed drifter data to evaluate the performance of the coupled model. Additionally, we developed six hypothetical oil spill cases in Lake Erie, considering both with and without ice conditions during the freezing, stable, and melting seasons spanning from 2018 to 2022, to investigate the impacts of ice cover on oil spill processes. The results showed the effective performance of the coupled model system in capturing the movements of a deployed drifter. Through ensemble simulations, it was observed that the stable season with high-concentration ice had the most significant impact on limiting oil transport compared to the freezing and melting seasons, resulting in an oil-affected open water area of 49 km2 on day 5 with ice cover, while without ice cover it reached 183 km2. The stable season with high-concentration ice showed a notable reduction in the probability of oil presence in the risk map, whereas this reduction effect was less prominent during the freezing and melting seasons. Moreover, negative correlations between initial ice concentration and oil-affected open water area were consistent, especially on day 1 with a linear regression R-squared value of 0.94, potentially enabling rapid prediction. Overall, the coupled model system serves as a useful tool for simulating oil spills in the world's largest freshwater system, particularly under icy conditions, thus enhancing the formulation of effective emergency response strategies.

Phytoplankton species composition as bioindicator in the largest fragmented channel of the Pearl River, China

To test the serial discontinuity concept (SDC) predictions in a regulated river ecosystem, environmental parameters and phytoplankton community structure were determined in a subtropical river (China) which was regulated by 11 cascade dams. Our results showed that total phosphorus (TP) and silicate during the wet period in several dams supported the SDC predictions. Variations of phytoplankton species composition in several cascade dams, such as Datengxia (DTX) and Changzhou (CZ), also supported the SDC predictions. Moreover, the stations near the dams showed the maximum or minimum values of total species numbers in each cascade segment. Predictive model indicated that the types of phytoplankton decreased in the middle reaches, conforming to SDC predictions. In the whole system of cascading dams, an increase in silicate concentration and phytoplankton communities in the downstream was also consistent with SDC predictions. Therefore, these findings aligned with the SDC predictions in the aspects of both single dam and whole cascade dam system to some extent. In future research, our aim is to further investigate the effects of cascade damming on additional phytoplankton-related indices in this aquatic ecosystem. We hope to gather more comprehensive data to fully validate the SDC predictions.

Study on the spatiotemporal distribution of algal blooms and its influencing factors in young reservoirs based on remote sensing interpretation

Algal blooms caused by excessive proliferation of phytoplankton in young reservoirs have been frequently reported, seriously threatening the unstable aquatic ecosystem, water quality safety and public health. Thus, there is an urgent need to investigate the dynamics of phytoplankton in these young reservoirs, and many current studies on phytoplankton in young reservoirs are based on point monitoring information. This study used remote sensing interpretation to invert the chlorophyll-a concentration in 131 images of Zipingpu Reservoir from 2013 to 2021, and analyzed the spatiotemporal characteristics of algal blooms. Partial least squares-structural equation modeling was used to identify the environmental influencing factors of algal blooms. The results showed that the average chlorophyll-a concentration in the reservoir was 4.49 mg/m3, and the frequency of algal blooms was 28%. The maximum area of algal blooms shows a significant increase trend in the interannual (increase by 0.05%/yr in the proportion of water surface area), and the average blooms area shows a weaker increase trend (0.01%/yr). The prone period of algal bloom is from April to August every year. The solar duration and wind speed had significant direct positive effects on the maximum and average algal bloom area, which was the similar effects in different years and months (path coefficient exceeds 0.44). TP also has a significant direct positive effect on the average algal bloom area between different years (path coefficient of 0.30). The suitable meteorological factors level making the bloom-prone period from April to August, the prevailing westerly and southerly winds provide transport for the aggregation of phytoplankton and algal blooms outbreak in the northeastern waters. This study expand the monitoring frequency and spatial information of algal blooms, which provided a reference for young reservoir management and prevention of blooms.

The influence mechanism of water level operation on algal blooms in canyon reservoirs and bloom prevention

The water level operation of reservoirs affects the spatiotemporal patterns of water quality, light-heat, hydrodynamics and phytoplankton, which have implications for algal bloom prevention. However, the theoretical analysis and practical applications of related research are limited. Based on prototype observations and numerical modeling, data on algae, water level operation and environmental factors in the Zipingpu Reservoir from April and September in 2015 to 2017 and 2020 to 2022 were collected. An in-depth analysis of the causal mechanisms between algal blooms and water level operation was performed, and prevention strategies with practical application assessments were developed. Water level operation control in the reservoir from April to September can be divided into five stages (falling-rising-oscillating-falling-rising), with algal blooms occurring only in the second stage. The rising water level with inflow into the middle layers shapes a closed-loop circulation in the surface waters. This distributes the nutrients that were trapped in the surface layer during the first stage, helping algae avoid to phosphorus limitation and thrive in the closed loop circulation, leading to algal blooms (chlorophyll-a exceeding 10 mg/m3). There is a significant positive correlation (p < 0.05) between algal blooms and the rapid rise in water levels in the second stage, occurring within a span of three days. To contain the algal bloom, a water level operation limit of rising waters on the third day after a two-day consecutive rise in water level was examined. This was found to be effective after its practical application to the case reservoir in 2022, with chlorophyll-a concentrations consistently below 10 mg/m3. This study unveils the mechanisms through which water level operation affects algal blooms and presents a successful case of bloom prevention. Furthermore, it serves as a valuable reference for the management of canyon reservoirs.

Multi-objective optimal reservoir operation considering algal bloom control in reservoirs

Reservoir operation strategies (ROSs) are considered an efficient and low-cost method to control algal blooms. However, reservoir operations must consider regular objectives, including flood prevention and power generation. To address this multi-objective optimization problem, we coupled the non-dominated sorting genetic algorithm-II (NSGA-II) model and the General Lake Model-Aquatic EcoDynamics library (GLM-AED) model to optimize reservoir operations. Taking the Zipingpu Reservoir as a case study, we found the peak of outflow discharge (POD) could be reduced from 1059.5 to 861.4 m3 s-1 (19%), the total power generation (TPG) could be increased from 6.6 × 108 to 7.1 × 108 kW h (8%), and the peak of chlorophyll a concentration (PCC) could be decreased from 42.7 to 27.2 μg L-1 (36%) compared with the original reservoir operation in the early flood period. The obtained Pareto frontier revealed the tradeoffs between algal bloom control, flood prevention, and power generation. Reservoir operation schemes that achieved low PCC were typically associated with large POD and moderate TPG. In particular, under fixed start and end water levels, maintaining a higher average water level during May and June could result in larger outflows, effectively inhibiting algal accumulation and bloom development, thereby leading to a lower PCC. Slight variations in average water age were found among the minimum PCC scheme, maximum TPG scheme, and minimum POD scheme, indicating that water exchange varied little and has not been responsible for the differences in PCC. Collectively, enhancing outflow was determined to play a vital role in reducing PCC, particularly when operating under constrained rules. These findings contribute new insights into optimal reservoir operations considering algal bloom control and emphasize the importance of enhancing outflow as a governing mechanism. Furthermore, the coupled model offers a transferable technical framework for reservoir managers to mitigate eutrophication through ROSs.

Key hydrodynamic principles for controlling algal blooms using emergency reservoir operation strategies

Reservoir operation strategies with low cost and high efficiency have been proposed to control algal blooms. However, the key hydrodynamic principle for performing reservoir operation strategies is still unknown, posing an obstacle to practical applications. To address this challenge, we proposed short-term emergency reservoir operation strategies (EROSs), established a three-dimensional (3D) eutrophication model of the Zipingpu Reservoir, and designed six 14-day reservoir operation cases to explore the mechanism of EROSs in controlling algal blooms. Large outflows with rapid water exchange should be adopted early in EROSs to control algal blooms in the reservoir. Small variations in the surface water temperature or the mixed layer depth/euphotic layer depth (Z_mix/Z_eu) ratio were found for different EROSs, indicating that these variations might not have been responsible for the differences in the algal blooms in the reservoir. The EROSs induced high surface flow velocity (V_s) and depth-averaged velocity (V_d) values in the reservoir, thereby controlling algal blooms by inhibiting algal growth and disrupting algal accumulation in the upper water layers. The flow of V_s against the direction of the water intake was detected during the execution of the EROSs, suggesting that increasing V_s might enhance water retention in the reservoir. Increasing V_d not only promoted water exchange to disrupt algal accumulation but also enhanced V_s to inhibit algal growth. Moreover, V_d demonstrated a strong linear relationship with the inhibition ratio of algal blooms. These results demonstrate that V_d is the key hydrodynamic indicator for performing EROSs and that accelerating V_d to exceed 0.039 m s^-1 in the near-dam region can control algal blooms. Overall, in this study, we develop a novel EROS and elucidate corresponding principles for the use of EROSs to control algal blooms in reservoirs.

Controlling spring Dinoflagellate blooms in a stratified drinking water reservoir via artificial mixing: Effects, mechanisms, and operational thresholds

Water-lifting aerators (WLAs) are often applied in stratified reservoirs to activate artificial mixing to inhibit harmful algal blooms (HABs). Here, the effects, mechanisms, and operational thresholds of spring Dinoflagellate control via artificial mixing were studied using a combination of taxonomic and functional groups and boundary line models. Algal cell density at two sampling sites (i.e., S1 and S2) decreased to below 1.0 × 10⁶ cells/L (corresponding chlorophyll-a content under 10 μg/L) during artificial mixing, with a Dinoflagellate removal efficiency of 97.1 % at S1 and 95.5 % at S2, respectively. The succession patterns of main phytoplankton taxonomic and functional groups changed greatly during artificial mixing at the sites: from Dinoflagellate and motile Chlorophyta to Bacillariophyta from groups A/L_O/P to A, respectively. Water temperature (WT), light availability (Z_eu/Z_mix), and mixing depth (Z_mix) were more effective factors influencing phytoplankton dynamics at a short-term scale, followed by total phosphorus (TP). A decrease in surface WT and Z_eu/Z_mix, and increase in Z_mix alongside the improvement of TP levels, which were induced by WLAs, drove the Dinoflagellate bloom control by a shift of phytoplankton structure from large, motile, and low surface to volume ratio (S/V) to small, immobile, and high S/V algae. The operational threshold values of WT, Z_eu/Z_mix, Z_mix and TP concentration for the suppression of Dinoflagellate growth using mixing systems are recommended as 9.6 °C, 0.17, 11.5 m, and 0.020 mg/L, respectively, based on a boundary line analysis. This work can help improve the cognition of mechanisms controlling HABs using mixing and aeration techniques in reservoirs.