• Journal of Environmental Impact Assessment
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• v.28 no.2
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• pp.169-182
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• 2019

This study assessed biological water quality using epilithic diatoms in the Yeong river, Naeseong stream and Wi stream in the upper region of the Nakdong river from May to October 2016. Epilithic diatoms were not mobile, so they could reflect long-term water quality. The sampled epilithic diatoms were identified a total 158 taxa which were composed to 2 orders, 3 suborders, 8 families, 34 genera, 143 species and 15 varieties. Dominant species were Achnanthes convergens and Achnanthes minutissima at Yeong river, Nitzschia inconspicua at Naeseong stream, and Achnanthes minutissima, Cocconeis placentula var. lineata and Navicula minima at Wi stream. As a result of the CCA, Electrical conductivity, total nitrogen and total phosphorus were important factors determining the diatom species composition in the upper region of the Nakdong river. The correlation between diatom indices (DAIpo & TDI) measured to be high in the correlation coefficient (0.87) from the result of correlation analysis. In the result of the assessment of biological water quality using DAIpo and TDI, Yeong river was rated as class A at most sites. Naeseong stream was rated as class C to D at all sites except for N1 which was rated as Class A. Wi stream was rated as class B to C for DAIpo of W1, and TDI was rated as class D. The assessment of biological water quality at this site showed inferior TDI result compared to that of DAIpo. DAIpo and TDI of W2 were rated as class A to D, and the water quality has changed a lot. W3 and W4 were mostly rated as class B and C respectively.

• Journal of the Korean Society of Marine Environment & Safety
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• v.14 no.3
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• pp.189-195
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• 2008

This study analyzed the characteristics of sea water transport between Busan New-port and the Nakdong River estuary. A current meter was placed on a pier bridge and the current velocity was analyzed to determine the flow direction. Water temperature, salinity, turbidity, and tide were also measured to determine the characteristics of sea water and to describe the tidal current between the two regions. The results indicated that the dominant outflow direction of the ebb tidal current was from the Nakdong River estuary to Busan New-port. Conversely, during a flood tide, the dominant direction was from Busan New-port to the Nakdong River estuary. The maximum current speed during the first and second field measurements was about 13.18 and 30.80 cm/ sec, respectively. During the first field measurement, the total volume of sea water transport was $184.71\;m^3/sec$ and the residual volume transport was $+59.74\;m^3/sec$. By contrast, during the second field measurement, the respective values were $331.15\;m^3/sec$ and $28.88\;m^3/sec$.

• Korean Journal of Ichthyology
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• v.18 no.2
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• pp.97-106
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• 2006

In the investigation of geographic variations on the Zacco koreanus distributed widely in southern Korean Peninsula, it was found that there were distinct differences in the nuptial coloration among geographic populations. These color variations were presence of red band on anterior margin of pectoral fin and color patterns of dorsal fin. On the basis of those color variations three color types were recognized in Z. koreanus, that is, HK, NS and NE types. HK types were distributed mainly in Han and Geum River, NS types in Nakdong and Seomjin River, and NE types in Nakdong River and small streams on the east coast. It was noted ecologically and taxonomically that these three types were well separated geographically and two types of them, i.e., NS and NE types cohabit in the Nakdong River and shown a tendency of microhabitat segregation between them.

• Proceedings of the Korean Society of Soil and Groundwater Environment Conference
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• 2000.05a
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• pp.81-81
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• 2000

• Journal of the Korean Society of Marine Environment & Safety
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• v.16 no.2
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• pp.169-174
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• 2010

To obtain more accurate meteorological data for analyzing the river discharge characteristics at the Nakdong River Estuary, we investigated the characteristics of the release barrage discharge observed during the 13-year period from 1996 to 2008 and calculated the differences using meteorological data for the Busan and Gimhae weather stations. The river discharge estimated using a tank model was compared to the real river barrage discharge. We discussed the correlation between the discharge and the meteorological factors that affected the estuary water environment. This study found that total annual discharge from the Nakdong river basin for the 13 years was $272,653.3{\times}10^6\;m^3$/month. The largest monthly mean release discharge occurred in July at $73,212.9{\times}10^6\;m^3$/month (26.9% for the year), followed by August and September in that order with 22.0% and 18.9%, respectively.

• Proceedings of the Korean Society of Coastal and Ocean Engineers Conference
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• 2009.10a
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• pp.109-112
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• 2009

• Journal of Environmental Science International
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• v.9 no.6
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• pp.455-462
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• 2000

This study aims at the development of the model for a forecasting of water quality in river basins using artificial neural network technique. Water quality by Artificial Neural Network Model forecasted and compared with observed values at the Sangju q and Dalsung stations in Nakdong river basin. For it, a multi-layer neural network was constructed to forecast river water quality. The neural network learns continuous-valued input and output data. Input data was selected as BOD, CO discharge and precipitation. As a result, it showed that method III of three methods was suitable more han other methods by statistical test(ME, MSE, Bias and VER). Therefore, it showed that Artificial Neural Network Model was suitable for forecasting river water quality.

• Journal of The Geomorphological Association of Korea
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• v.27 no.3
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• pp.13-24
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• 2020

This study analyzed the characteristics of the grain size distribution of the sediments obtained from the flooding in Ibang-myeon, Changnyeong-gun, which was caused by the collapse of a embarkment on the Nakdong River on August 9, 2020. As a results, it was found that the mean grain size decreases and the sorting becomes poorer as the distance from the embarkment collapse point increases. This is attributed to the fact that the transport energy of the river decreases when flooding occurs, ensuring that coarse-grained sediments are deposited first. Further, as the transport energy further reduces and becomes dispersed, the sorting for the fine-grained sediments becomes poor. Considering the characteristics of spatial distribution, sediments along the farm road showed the properties of floodplain deposits that transport to natural levee and back swamp due to river flooding. On the other hand, sediments along the irrigation ditch exhibited the properties of the deposits that are carried by the flow backward of ditch from the river after the collapse of the embarkment. The results of this study are significant because characteristics of flood sediments were elucidated for major rivers where flooding rarely occurs due to the recently built artificial structures. In addition, by applying the grain size distribution characteristics of present river flood sediments, it will be able to contribute to clarifying the sedimentary environments of the paleo river flood deposits.

• Smart Media Journal
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• v.11 no.2
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• pp.31-38
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• 2022

Promptly predicting changes in the salinity in rivers is an important task to predict the damage to agriculture and ecosystems caused by salinity infiltration and to establish disaster prevention measures. Because machine learning(ML) methods show much less computation cost than physics-based hydraulic models, they can predict the river salinity in a relatively short time. Due to shorter training time, ML methods have been studied as a complementary technique to physics-based hydraulic model. Many studies on salinity prediction based on machine learning have been studied actively around the world, but there are few studies in South Korea. With a massive number of datasets available publicly, we evaluated the performance of various kinds of machine learning techniques that predict the salinity of the Nakdong River Estuary Basin. As a result, LightGBM algorithm shows average 0.37 in RMSE as prediction performance and 2-20 times faster learning speed than other algorithms. This indicates that machine learning techniques can be applied to predict the salinity of rivers in Korea.

• Korean Journal of Ecology and Environment
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• v.51 no.1
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• pp.60-70
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• 2018

The distribution of benthic macroinvertebrates was investigated at 1,157 sites of 7 main water systems in Korea, including 442 sites of Han River system (Namhan River, Bukhan River, Han River main stream, Anseongcheon, etc.), 305 sites of Nakdong River system (Nakdong River, Hyeongsan River, Taehwa River, etc.), 199 sites of Geum River system (Geum River, Sapgyocheon, Mangyeong River, Dongjin River, etc.) 102 sites of Seomjin River system (Seomjin River), 102 sites of Yeongsan River system (Yeongsan River, Tamjin River, etc.), and 7 sites of Jeju stream system. A total of 151 families were found in the whole survey sites, including 141 families in Han River, 122 in Nakdong River, 115 in Geum River, 106 in Seomjin River, 113 in Yeongsan River, and 50 in Jeju. Chironomidae (20.8%) was the most dominant species in Korea, followed by Hydropsychidae (17.1%), Baetidae (12.6%), Tubificidae (10.3%), Heptageniidae (8.6%), Ephemerellidae (6.3%), Asellidae (2.7%), Leptophlebiidae (2.4%), Planariidae (1.7%), and Tipulidae (1.6%). Substrates compositions consisted of large sand (22.6%), large gravel (18.4%), silt (10.5%), and boulder (8.2%). The mean stream width was 133.5 m and the mean watercourse width was 61.7 m. The mean water depth and velocity were 30.2 cm and $33.1cm\;s^{-1}$, respectively. Results of cluster analysis based on distributional characteristics of benthic macroinvertebrates were divided into six groups according to the frequency of benthic macroinvertebrate taxa which appeared in the study area. Finally, altitude, current velocity and substrate composition were the most influencial factors determining the distribution patterns of macroinvertebrate communities.