• Journal of Environmental Science International
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• v.23 no.8
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• pp.1513-1522
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• 2014

Fish passage asssessments were conducted in the fishway at Juksan Weir, which was constructed as a four-major rivers project in the downstream area of Youngsan-River Watershed. For the research, fish-movements/migrations were analyzed for seven times from April ~ October, 2013 using an approach of fish trap-setting. Fish fauna and compositions were analyzed in the fishway, and seasonal- and diel-movement patterns were analyzed in relation to current velocity in the fishway. Also, abundances of exotic fishes such as bluegill sunfish (Lepomis macrochirus), large-mouth bass (Micropterus salmoides), and white curcian carp (Carassius cuvieri) were monitored in the fishway. Current velocity(n = 18) in the fishway showed large variations ($0.82{\pm}0.63m/s$) depending on the location of the fish trap-setting and this physical factor influenced the fish movements. Fish movements, based on the CPUE of individuals, in the fishway was greater in slower velocity (mean: 0.36 m/s, range: 0.10~1.54 m/s) than faster velocity (mean: 1.51 m/s, range: 0.90~1.90 m/s). Seasonal analysis of fish movements showed that most frequent uses (8 speices and 591 individuals, 66.2% of the total) of the fishway occurred in spring period(i.e., June). Diel movement analysis, in the mean time, showed highest in the time period of 00:00 ~ 3:00 am (7 species and 281 individuals, 20.9% of the total). The efficient managements in the fishway at Juksan Weir are required in relation to the hydrological regime.

• Journal of Environmental Science International
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• v.19 no.11
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• pp.1323-1336
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• 2010

This study was carried out to determine marine environments and phytoplankton community around Mokpo harbour on March to November during the period of 2004-2009. The remarkable fluctuations of marine environments were shown around Mokpo harbour depending on monthly and yearly. Among seasons, summer was a great that was associated with extremely releasing the freshwater from Youngsan River Weir, contributing to effect the fluctuations of water quality. Nevertheless of monthly and yearly, the molecular ratio of N:P was always shown in above 16 that was mainly attributed to freshwater discharge on March to November. This indicates that phosphorus playes an important role in limiting factor as growth in phytoplankton. During this study, Skeletonema costatum was found to be richer than the other groups of diatoms in terms of abundance and species number. Mokpo harbour, with the presence of a narrow avenue for exchange with offshore waters, has limited growth in phytoplankton, but this species is able to well adapt and fast grow under even high level of suspended solid and low intensity of light compared with other species. The discharge of freshwater is associated with significantly fluctuation of marine environments in this region, but it does not affect the quantitative and qualitative distribution of phytoplankton. It is necessary to persistently monitor based on water quality and phytoplankton community.

• Journal of Korean Society on Water Environment
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• v.35 no.3
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• pp.257-270
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• 2019

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.

• Journal of Korea Water Resources Association
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• v.49 no.9
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• pp.789-798
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• 2016

Frequent algal blooms at major river systems in Korea have been serious social and environmental problems. Especially, the appearance of cyanobacteria with toxic materials is a threat to secure a safe drinking water. In order to model the behaviour of cyanobacteria cell number, an exclusive causality analysis using prewhitening technique was introduced to delineate effective parameters to predict the cell numbers of cyanobacteria in Seungchon Weir and Juksan Weir along Youngsan river system. Both input and output transfer function models were obtained to explain temporal variation of cyanobacteria cell number. A threshold behaviour of water temperature was implemented into the model development to consider winter characteristic of cyanobacteria. The implementation of water temperature threshold into the model structure improves the predictability in simulation. Even though the input output transfer model cannot completely explained all blooms of cyanobacteria, the simple structure of model provide a feasibility in application which can be important in practical aspect.

• Korean Journal of Ecology and Environment
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• v.48 no.4
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• pp.238-252
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• 2015

The effect of weir construction (2009~2011) was investigated on algal bloom dynamics and surrounding conditions in the Youngsan River by analyzing the long-term (2001~2014) data provided by the Water Information System, Ministry of Environment. The data include chlorophyll a and water properties such as total suspended solids (TSS), ammonium ($NH_4{^+}$), nitrate ($NO_3{^-}$), orthophosphate ($PO{_4}^{3-}$), total nitrogen (TN), total phosphorus (TP) and DIN/DIP molar ratio collected from 12 stations along the channel of the river. Temporal variations were examined using data collected monthly from 2001~2014 and Box-Whisker plot was used to examine the difference in algal bloom dynamics between before (2006~2008) and after (2012~2014) the weir construction. Pearson's correlation analysis was also used to analyze the correlation of parameters. The results showed that TSS affecting water turbidity increased during the construction but decreased especially at the stations located in the upper and middle regions of the river after the construction. Ammonium concentrations increased whereas the concentrations of other nutrients decreased after the construction inducing an increase in N:P molar ratio. Chlorophyll a decreased suddenly during the construction but increased clearly after the construction at the stations where TSS decreased. This indicates that algal blooms can develop in the Youngsan River due to a decrease in turbidity that increases light penetration in water column although the concentrations of nutrients such as orthophosphate were reduced after the weir construction.

• Environmental Engineering Research
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• v.24 no.3
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• pp.404-411
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• 2019

In this study, we designed a data-driven model to predict chlorophyll-a using M5P model tree and extreme learning machine (ELM). The Juksan weir in the Youngsan River has high chlorophyll-a, which is the primary indicator of algal bloom every year. Short-term algal bloom prediction is important for environmental management and ecological assessment. Two models were developed and evaluated for short-term algal bloom prediction. M5P is a classification and regression-analysis-based method, and ELM is a feed-forward neural network with fast learning using the least square estimate for regression. The dataset used in this study includes water temperature, rainfall, solar radiation, total nitrogen, total phosphorus, N/P ratio, and chlorophyll-a, which were collected on a daily basis from January 2013 to December 2016. The M5P model showed that the prediction model after one day had the highest performance power and dropped off rapidly starting with predictions after three days. Comparing the performance power of the ELM model with the M5P model, it was found that the performance power of the 1-7 d chlorophyll-a prediction model was higher. Moreover, in a period of rapidly increasing algal blooms, the ELM model showed higher accuracy than the M5P model.