Multi-factor identification and modelling analyses for managing large river algal blooms

Xia, Rui; Zhang, Yuan; Wang, Gangsheng; Zhang, Yongyong; Dou, Ming; Hou, Xueling; Qiao, Yunfeng; Wang, Qiang; Yang, Zhongwen

doi:10.1016/j.envpol.2019.113056

Cited by 53 publications

(17 citation statements)

References 77 publications

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“…The variations in river hydrodynamic conditions under natural and artificial regulation have certain similarities. These special hydrological and hydraulic conditions provide a direct driving force for the proliferation of planktonic algae and algal bloom outbreaks in eutrophic lowland rivers, which in turn gives ecological significance to the special hydrodynamic conditions (Everbecq et al, 2001; Reynolds, 2000; Xia et al, 2019; Yu et al, 2015). For example, the variations in hydrological and hydraulic conditions have an important impact on the competitive evolution of different algal communities, resulting in diatoms with a certain resistance to the impact of water velocity becoming the dominant species for river algal blooms (Lind et al, 2007; Pathak et al, 2021; Poff & Zimmerman, 2010).…”

Section: Discussionmentioning

confidence: 99%

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Hydrological management strategies for the control of algal blooms in regulated lowland rivers

Yin

Jia

et al. 2021

Hydrological Processes

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Reservoirs of lowland floodplain rivers with eutrophic backgrounds cause variations in the hydrological and hydraulic conditions of estuaries and low‐dam reservoir areas, which can promote planktonic algae to proliferate and algal bloom outbreaks. Understanding the ecological effects of variations in hydrological and hydraulic processes in lowland rivers is important for algal bloom control. In this study, the middle and lower reaches of the Han River, China, a typical regulated lowland river with a eutrophic background, are selected. Based on the effect of hydrological and hydraulic variability on algal blooms, a hydrological management strategy for river algal bloom control is proposed. The results showed that (a) differences in river morphology and background nutrient levels cause significant differences in the critical threshold flow velocities for algal bloom outbreaks between natural river and low‐dam reservoir sections; there is no uniform threshold flow velocity for algal bloom control. (b) There are significant differences in the river hydrological/hydraulic conditions between years with and without algal blooms. The average river flow, water level and velocity in years with algal blooms are significantly lower than those in years without algal blooms. (c) For different river sections where algal blooms occur and to meet the threshold flow velocities, the joint operation of cascade reservoirs and diversion projects is an effective method to prevent and control algal blooms in regulated lowland rivers. This study is expected to deepen our understanding of the ecological significance of special hydrological processes and guide algal bloom management in regulated lowland rivers.

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Section: Discussionmentioning

confidence: 99%

“…A high nutrient load is a necessary condition for the occurrence of river algal blooms (Hilton et al, 2006; Xia et al, 2019). The concentrations of nutrients, such as nitrogen, phosphorus and silicon, can affect the dominant phytoplankton species.…”

Section: Introductionmentioning

confidence: 99%

Hydrological management strategies for the control of algal blooms in regulated lowland rivers

Yin

Jia

et al. 2021

Hydrological Processes

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“…Our analysis also show that, ΔH is closely related to the algal blooms in the lower HR as a variable that comprehensively expresses the hydrological situation of the HR and the YR. Many researchers have also proposed that the hydrological regime is the most important driving factor for the outbreak of river algal blooms (Yang et al, 2011;Kim et al, 2019;Xia et al, 2019;Xia et al, 2020). A lower water level difference indicates a smaller flow rate.…”

Section: Driving Factors Algal Blooms In the Lower Hanjiang Rivermentioning

confidence: 99%

Time-Lag Effect: River Algal Blooms on Multiple Driving Factors

et al. 2022

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Compared to the eutrophication of lakes and reservoirs, the mechanism of river algal blooms in a flowing water body are more complicated, and often lead to serious consequence in catchment scale. Due to the simultaneous impact of a variety of environmental pressures, the water ecosystem integrity state often shows a response characteristic of accumulation, complexity and time lag, therefore it is difficult to use conventional hydrodynamic and water quality models to scientifically characterize and analyze. The lower Hanjiang River (HR) is an important influence area of the middle route of the South-to-North Water Diversion Project (SNWDP) in China, continuous river blooms issue has become a major national concern. In this study, a time-lag analysis approach was developed to identify the causes of algal blooms formation and the time-lag response law in the lower HR, including principal component analysis (PCA), grey relation analysis (GRA), and Almon Distributed Lag Model. Results found that, the hydrological regime (ΔH) contributes the most to the river bloom, especially due to the flow hindrance of the Yangtze River (YR) and the water project upstream. It is also found that the algal bloom outbreak in the lower HR is not an immediate response to the driving factors. It has a time lag of about 1 period (10 days) in the response with antecedent driving factors. Finally, we discussed the influence and its responding mechanism of ΔH on the growth of phytoplankton. The research can provide early warning for the prevention and control of algal blooms in the large river system.

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“…Nutrient concentrations are extremely important for the formation of algal blooms, although local meteorological conditions also influence the outbreak of algal blooms [107,108]. When the nutrient concentrations in the lake are relatively high, the algal bloom frequency will certainly increase as the climate warms.…”

Section: Implications and Prospectsmentioning

confidence: 99%

Monitoring the Spatial and Temporal Variations in The Water Surface and Floating Algal Bloom Areas in Dongting Lake Using a Long-Term MODIS Image Time Series

et al. 2020

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Significant water quality changes have been observed in the Dongting Lake region due to environmental changes and the strong influence of human activities. To protect and manage Dongting Lake, the long-term dynamics of the water surface and algal bloom areas were systematically analyzed and quantified for the first time based on 17 years of Moderate Resolution Imaging Spectroradiometer (MODIS) observations. The traditional methods (index-based threshold algorithms) were optimized by a dynamic learning neural network (DL-NN) to extract and identify the water surface area and algal bloom area while reducing the extraction complexity and improving the extraction accuracy. The extraction accuracy exceeded 94.5% for the water and algal bloom areas, and the analysis showed decreases in the algal bloom and water surface areas from 2001–2017. Additionally, the variations in the water surface and algal bloom areas are greatly affected by human activities and climatic factors. The results of these analyses can help us better monitor human contamination in Dongting Lake and take measures to control the water quality during certain periods, which is crucial for future management. Moreover, the traditional methods optimized by the DL-NN used in this study can be extended to other inland lakes to assess and monitor long-term temporal and spatial variations in algal bloom areas and can also be used to acquire baseline information for future assessments of the water quality of lakes.

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Multi-factor identification and modelling analyses for managing large river algal blooms

Cited by 53 publications

References 77 publications

Hydrological management strategies for the control of algal blooms in regulated lowland rivers

Hydrological management strategies for the control of algal blooms in regulated lowland rivers

Time-Lag Effect: River Algal Blooms on Multiple Driving Factors

Monitoring the Spatial and Temporal Variations in The Water Surface and Floating Algal Bloom Areas in Dongting Lake Using a Long-Term MODIS Image Time Series

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