Abstract
Abstract Blooming of algae has been a primary issue of concern for heavily polluted aquatic ecosystems. The chlorophyll-a (Chl-a) concentration depends on various hydrological, biochemical and anthropogenic components, which makes prediction of algal blooms complicated. A river regulation project in Yeongsan River, South Korea, involving the construction of a weir, had substantially altered the flow regime. A prewhitened time series analysis is a useful method for delineation of a causal relationship between two environmental variables. This study explores the impact of river regulation on algal blooming using both the prewhitened cross-correlation method and principal factor analysis. Both individual and comprehensive causality structures were configured for the variation in Chl-a concentration. A prewhitened cross-correlation analysis indicates that the water quality response patterns of the river system were changed to those of a reservoir after the river regulation project. A principal factor analysis of correlations indicates that the weir construction had a stronger impact on algal concentration than both the hydro-meteorological factor and difference in sampling location. Variation in stochastic structures from nutrients and water quality factors to algal bloom was substantially reduced by the construction of a weir, which can be explained by the relatively uniform flow pattern throughout the river regulation practice.
Highlights
It is well known that algal blooms result in the decline of specific species, such as invertebrates, and lead to deterioration of fish habitats due to increasing turbidity
This study addresses two issues based on the analysis of measurements of hydro-meteorological, nutrient, and water quality parameters during both pre and post periods of a river regulation project: (i) how a prewhitened relationship (Granger causality) between various environmental parameters and Chl-a concentration can be obtained as a stochastic structure associated with common drivers by eliminating seasonality from each time series; (ii) how multiple relationships between hydro-meteorological, nutrient, and water quality factors and algal bloom can be expressed through factor analysis
Mean concentrations of Chl-a after construction of the Seungchon Weir (KS12 ∼ 14 and NJ12 ∼ 14) were higher than those for the earlier period (KS07 ∼ 09 and NJ07 ∼ 09) and intensity of algal blooming seems higher at the downstream point (NJ) than upstream (KS)
Summary
It is well known that algal blooms result in the decline of specific species, such as invertebrates, and lead to deterioration of fish habitats due to increasing turbidity. When we find a relationship between any environmental variable and chlorophyll-a (Chl-a) concentration, using common index to represent the amount of algal biomass, the conventional cross-correlation function often shows limitations due to the autocorrelation structure of each time series (Kim et al ) This issue can be largely addressed through the introduction of a prewhitening method (Kim ). This study addresses two issues based on the analysis of measurements of hydro-meteorological, nutrient, and water quality parameters during both pre and post periods of a river regulation project: (i) how a prewhitened relationship (Granger causality) between various environmental parameters and Chl-a concentration can be obtained as a stochastic structure associated with common drivers by eliminating seasonality from each time series; (ii) how multiple relationships between hydro-meteorological, nutrient, and water quality factors and algal bloom can be expressed through factor analysis. We analyzed how the construction of the weir changed the algal concentration response pattern in the context of various environmental factors
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