Abstract
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.
Highlights
River Algal Blooms analysis and driving mechanism of algal blooms in large hydrological-regulated rivers have become a major concern, as the algal blooms in these rivers lead to deteriorating water quality and aquatic ecosystems and restrict socioeconomic developments and threaten public health with a greater sphere of influence
We conduct following studies including 1) determining the key driving factors regulating the algal blooms in the lower Hanjiang River (HR). 2) evaluating the time-lag effect of influencing factors by analyzing data collected from field surveys with principal component analysis (PCA), Almon Distributed Lag Model and curve fitting
We used a variety of statistical analysis methods and the Almon Time Lag Model to investigate the algal blooms during a decade (2003–2014) in the lower HR, which is the largest tributary of the Yangtze River (YR) of China
Summary
River Algal Blooms analysis and driving mechanism of algal blooms in large hydrological-regulated rivers have become a major concern, as the algal blooms in these rivers lead to deteriorating water quality and aquatic ecosystems and restrict socioeconomic developments and threaten public health with a greater sphere of influence. All of the above studies show that the hydrologic regime is an important driving factor for river-type algal blooms (Mitrovic et al, 2007; Cheng et al, 2019; Xia et al, 2020). It is necessary to carry out a quantitative analysis of the time-lag effect between river algal blooms and its multiple driving factors, in order to reveal the mechanism of river water ecological degradation. This study aims to reveal the response mechanism of river algal blooms based on the analysis of interactions of those influencing factors, by quantitatively determining the time-lag response of algal bloom to multiple driving factors. We expect to propose a method for predicting river water ecological degradation in advance
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