scholarly journals Assessment of Nakdong River Basin Management: Target Water Quality Achievement and Future Challenges

2020 ◽  
Vol 20 (2) ◽  
pp. 251-263
Author(s):  
Kyeong Hwan Kang ◽  
Junghyeon Kim ◽  
Hyeonjin Jeon ◽  
Kyoungwoo Kim ◽  
Imgyu Byun
Keyword(s):  
Water Quality ◽  
River Basin ◽  
Water Environment ◽  
Quality Data ◽  
Master Plan ◽  
Nakdong River ◽  
Environment Management ◽  
Pollutant Load ◽  
Nakdong River Basin ◽  
Representative Points

In 2006, the Korean Ministry of Environment established <The 1st Water Environment Management Master Plan>. The plan aimed at “Clean Water, Eco River 2015” and guided water quality protection and strengthened water management. This study evaluated the achievement of the target water quality among the 33 mid-level basins in the Nakdong River basin and assessments of the causes of non-achievement of the target water quality by mid-level basins. According to the 2015 water quality data, only 16 of the 33 mid-level basins achieved the target water quality. The low achievement of the target water quality was attributed to the failure to predict the pollutant load at the time of planning, problems with the management of tributaries, implementation of the <Four major river restoration project>, and problems with the representativeness of the water quality representative points. In addition, feasibility studies on the water quality monitoring representative point used in each mid-level basin were also performed; some mid-level basins required improvement or change of the representative points. This study also suggested further research to improve water quality, such as detailed studies of the management of pollutant load, mainstream tributaries, and water quality indicators, for the revision of the current ongoing <The 2nd Water Environment Management Master Plan>.

scholarly journals Prediction of Water Level and Water Quality Using a CNN-LSTM Combined Deep Learning Approach

Water ◽  
2020 ◽  
Vol 12 (12) ◽  
pp. 3399
Author(s):  
Sang-Soo Baek ◽  
Jongcheol Pyo ◽  
Jong Ahn Chun
Keyword(s):  
Water Quality ◽  
Deep Learning ◽  
Water Level ◽  
River Basin ◽  
Short Term Memory ◽  
Quality Data ◽  
Learning Approach ◽  
Nakdong River ◽  
Water Quality Data ◽  
Nakdong River Basin

A Convolutional Neural Network (CNN)-Long Short-Term Memory (LSTM) combined with a deep learning approach was created by combining CNN and LSTM networks simulated water quality including total nitrogen, total phosphorous, and total organic carbon. Water level and water quality data in the Nakdong river basin were collected from the Water Resources Management Information System (WAMIS) and the Real-Time Water Quality Information, respectively. The rainfall radar image and operation information of estuary barrage were also collected from the Korea Meteorological Administration. In this study, CNN was used to simulate the water level and LSTM used for water quality. The entire simulation period was 1 January 2016–16 November 2017 and divided into two parts: (1) calibration (1 January 2016–1 March 2017); and (2) validation (2 March 2017–16 November 2017). This study revealed that the performances of both of the CNN and LSTM models were in the “very good” range with above the Nash–Sutcliffe efficiency value of 0.75 and that those models well represented the temporal variations of the pollutants in Nakdong river basin (NRB). It is concluded that the proposed approach in this study can be useful to accurately simulate the water level and water quality.

scholarly journals Evaluation of Water Quality Interaction by Dam and Weir Operation Using SWAT in the Nakdong River Basin of South Korea

2020 ◽  
Vol 12 (17) ◽  
pp. 6845 ◽  
Author(s):  
Jiwan Lee ◽  
Yonggwan Lee ◽  
Soyoung Woo ◽  
Wonjin Kim ◽  
Seongjoon Kim
Keyword(s):  
Water Quality ◽  
River Basin ◽  
Assessment Tool ◽  
Water Quality Monitoring ◽  
Coefficient Of Determination ◽  
Nakdong River ◽  
Nakdong River Basin ◽  
Gate Control ◽  
The Nakdong River ◽  
Dam Inflow

The purpose of this study was to evaluate the streamflow and water quality (SS, T-N, and T-P) interaction of the Nakdong river basin (23,609.3 km2) by simulating dam and weir operation scenarios using the Soil and Water Assessment Tool (SWAT). The operation scenarios tested were dam control (Scenario 1), dam control and weir gate control (Scenario 2), dam control and sequential release of the weirs with a one-month interval between each weir (Scenario 3), dam control and weir gate full open (Scenario 4), dam control and weir gate sequential full open (Scenario 5), weir gate control (Scenario 6), weir gate full open (Scenario 7), and weir gate sequential full open (Scenario 8). Before evaluation, the SWAT was calibrated and validated using 13 years (2005–2017) of daily multi-purpose dam inflow data from five locations ((Andong Dam (ADD), Imha Dam (IHD), Hapcheon Dam (HCD), Namkang Dam (NKD), and Milyang Dam (MYD))multi-function weir inflow data from seven locations (Sangju Weir (SJW), Gumi Weir (GMW), Chilgok Weir (CGW), Gangjeong-Goryeong Weir (GJW), Dalseong Weir (DSW), Hapcheon-Changnyeong Weir (HCW), and Changnyeong-Haman Weir (HAW)), and monthly water quality monitoring data from six locations (Andong-4 (AD-4), Sangju (SJ-2), Waegwan (WG), Hapcheon (HC), Namkang-4 (NK-4), and Mulgeum (MG). For the dam inflows and dam storage, the Nash-Sutcliffe efficiency (NSE) was 0.59~0.78, and the coefficient of determination (R2) was 0.71~0.90. For water quality, the R2 values of SS, T-N, and T-P were 0.58~0.83, 0.53~0.68, and 0.56~0.79, respectively. For the eight dam and weir release scenarios suggested by the Ministry of Environment, Scenarios 4 and 8 exhibited water quality improvement effects compared to the observed data.

scholarly journals Assessment of Water Quality Target Attainment and Influencing Factors Using the Multivariate Log-Linear Model in the Nakdong River Basin, Republic of Korea

2021 ◽  
Vol 13 (19) ◽  
pp. 11094
Author(s):  
Mi-Ah Kim ◽  
Eunhye Na ◽  
Suyoung Park ◽  
Taegu Kang ◽  
Soyoung Lee
Keyword(s):  
Water Quality ◽  
River Basin ◽  
Mean Squared Error ◽  
Statistical Significance ◽  
Main Stream ◽  
Nakdong River ◽  
Target Attainment ◽  
Nakdong River Basin ◽  
The Nakdong River ◽  
Log Linear

Because identifying the factors affecting water quality is challenging, water quality assessment of an individual component based on the arithmetic mean method cannot adequately support management policies. Therefore, in this study, we assessed the water quality target attainment at 24 sites in the Nakdong River Basin by applying multivariate log-linear models to identify factors influencing water quality, including flow and season. The temporal and seasonal water quality trend and flow were also analyzed using the calculated model coefficients. Specifically, weekly data on biological oxygen demand (BOD), total phosphorous (TP), and flow during 2013–2018 were used to investigate the 2018 water quality target attainment level for this river. The significance and suitability of the models were analyzed using the F-test, root mean squared error (RMSE), mean absolute percent error (MAPE), and adjusted R2 values. All 24 models applied in this study showed statistical significance and suitability for the prediction of BOD and TP concentrations. Moreover, flow was identified as the main factor affecting water quality and had a predominant effect on BOD and TP concentrations in tributaries and the main stream, respectively. Furthermore, among the 24 sites, BOD and TP targets were evidently attained at 18 and 17 sites, respectively.

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