Analysis of Environmental Factors Associated with Cyanobacteria Dominance in Baekje Weir and Juksan Weir

백제보와 죽산보에서 남조류 우점 환경요인 분석

  • Received : 2019.03.03
  • Accepted : 2019.05.22
  • Published : 2019.05.30


Followingthe Four Rivers Project, cyanobacterial blooms have been frequently observed in the upstream of the installed weirs. The aim of this study was to characterize the major environmental factors that are associated with the cyanobacteria dominance in Baekje Weir (Geum River) and Juksan Weir (Youngsan River) based on intensive experiments and systematic data mining methods. The factors related to the cyanobacteria dominance include7-days cumulative rainfall (APRCP7), 7-days averaged flow (Q7day), water temperature (Temp), stratification strength (${\Delta}T$), electronic conductivity (EC), DO, pH, $NO_3-N$, $NH_3-N$, TN, TP, $PO_4-P$, Chl-a, Fe, BOD, COD, TOC, and $SiO_2$. The most highly correlatedfactors to the dominant cyanobacteria were found to be EC, Temp, Q7day, $PO_4-P$ in theBaekje Weir. On the other hand, those dominant in the Juksan Weir were ${\Delta}T$, TOC, Temp, EC and TN. The EC showed a strong correlation with cyanobacteria dominance in both weirs because a high EC represents a persisted low flow condition. The cyanobacteria dominance was as high as 56 % when the EC was equal or greater than $418{\mu}S/cm$ in Baekje Weir. It was as high as 63% when the ${\Delta}T{\geq}2.1^{\circ}C$ in the Juksan Weir. However, nutrients showed a minor correlation with cyanobacteria dominance in both weirs. The results suggest that the cyanobacteria dominate in astate where the water flow rate is low, water temperature is high and thermal stratification is strengthened. Therefore, the improvement of flow regimes is the most important to prevent persistent thermal stratification and formation of cyanobacteria bloom in theBaekje and JuksanWeirs.

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Fig. 1. Locations of study sites and monitoring stations in BJW and JSW.

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Fig. 2. The overall processes of this study.

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Fig. 3. Temporal variations of precipitation and cell density of each algae group(surface layer) in (a) BJW and (b) JSW Weirs

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Fig. 4. The correlation between TP-Chl-a and TN-Chl-a at each weir.

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Fig. 5. The comparison of measured cyanobacteria dominance with simulated results using SMLR and RF models

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Fig. 6. Partial dependence plots of the RF models, showing the marginal effects of a single variable on cyanobacteria dominance

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Fig. 7. Evaluation of environmental conditions that have influence on the cyanobacteria dominance by using a decision tree.

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Fig. 8. The correlation between EC (µS/cm) and flow (m3/s) ((a): BJW, (b): JSW).

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Fig. 9. Bi-plots of PCA results grouped by season and HAB level.

Table 1. Descriptive statistics of data used in this study

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Table 2. Bi-variables correlation analysis between variables observed in BJW (right-gray) and JSW (left-white) weir.

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Table 3. Correlation analysis between nutrients and Chl-a at each weir,

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Table 4. Subset regression variables that best matched the performance criterion.

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Table 5. Integration of study results for comprehensive interpretation.

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Supported by : 국토교통과학기술진흥원


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