scholarly journals Identification of High-Priority Tributaries for Water Quality Management in Nakdong River Using Neural Networks and Grade Classification

2020 ◽  
Vol 12 (21) ◽  
pp. 9149
Author(s):  
Kang-Young Jung ◽  
Sohyun Cho ◽  
Seong-Yun Hwang ◽  
Yeongjae Lee ◽  
Kyunghyun Kim ◽  
...  
Keyword(s):  
Neural Network ◽  
Water Quality ◽  
Quality Management ◽  
Water Quality Management ◽  
Oxygen Demand ◽  
Principal Component ◽  
Pollution Load ◽  
Nakdong River ◽  
Neural Network Models ◽  
Grade Classification

To determine the high-priority tributaries that require water quality improvement in the Nakdong River, which is an important drinking water resource for southeastern Korea, data collected at 28 tributaries between 2013 and 2017 were analyzed. To analyze the water quality characteristics of the tributary streams, principal component analysis and factor analysis were performed. COD (chemical oxygen demand), TOC (total organic carbon), TP (total phosphorus), SS (suspended solids), and BOD (biochemical oxygen demand) were classified as the primary factors. In the self-organizing maps analysis using the unsupervised learning neural network model, the first factor showed a highly relevant pattern. To perform the grade classification, 11 parameters were selected. Six parameters are concentrations of the main parameters for the water quality standard assessment in South Korea. We added the pollution load densities for the selected five primary factors. Joochungang showed the highest pollution load density despite its small watershed area. According to the results of the grade classification method, Joochungang, Topyeongcheon, Hwapocheon, Chacheon, Gwangyeocheon, and Geumhogang were selected as tributaries requiring high-priority water quality management measures. From this study, it was concluded that neural network models and grade classification methods could be utilized to identify the high-priority tributaries for more directed and effective water quality management.

scholarly journals A Multivariate and Spatiotemporal Analysis of Water Quality in Code River, Indonesia

2020 ◽  
Vol 2020 ◽  
pp. 1-11
Author(s):  
Mochamad A. Pratama ◽  
Yan D. Immanuel ◽  
Dwinanti R. Marthanty
Keyword(s):  
Water Quality ◽  
Land Cover ◽  
Agricultural Land ◽  
Water Quality Management ◽  
Temporal Trends ◽  
Oxygen Demand ◽  
Principal Component ◽  
Water Quality Monitoring ◽  
Quality Data ◽  
Water Quality Data

The efficacy of a water quality management strategy highly depends on the analysis of water quality data, which must be intensively analyzed from both spatial and temporal perspectives. This study aims to analyze spatial and temporal trends in water quality in Code River in Indonesia and correlate these with land use and land cover changes over a particular period. Water quality data consisting of 15 parameters and Landsat image data taken from 2011 to 2017 were collected and analyzed. We found that the concentrations of total dissolved solid, nitrite, nitrate, and zinc had increasing trends from upstream to downstream over time, whereas concentrations of parameter biological oxygen demand, cuprum, and fecal coliform consistently undermined water quality standards. This study also found that the proportion of natural vegetation land cover had a positive correlation with the quality of Code River’s water, whereas agricultural land and built-up areas were the most sensitive to water pollution in the river. Moreover, the principal component analysis of water quality data suggested that organic matter, metals, and domestic wastewater were the most important factors for explaining the total variability of water quality in Code River. This study demonstrates the application of a GIS-based multivariate analysis to the interpretation of water quality monitoring data, which could aid watershed stakeholders in developing data-driven intervention strategies for improving the water quality in rivers and streams.

scholarly journals Mathematical Modeling for Water Quality Management under Interval and Fuzzy Uncertainties

2013 ◽  
Vol 2013 ◽  
pp. 1-14 ◽  
Author(s):  
J. Liu ◽  
Y. P. Li ◽  
G. H. Huang
Keyword(s):  
Water Quality ◽  
Quality Management ◽  
Water Quality Management ◽  
Treatment Plant ◽  
Oxygen Demand ◽  
Interval Numbers ◽  
Nonpoint Sources ◽  
Xiangxi River ◽  
Constrained Programming ◽  
System Benefit

In this study, an interval fuzzy credibility-constrained programming (IFCP) method is developed for river water quality management. IFCP is derived from incorporating techniques of fuzzy credibility-constrained programming (FCP) and interval-parameter programming (IPP) within a general optimization framework. IFCP is capable of tackling uncertainties presented as interval numbers and possibility distributions as well as analyzing the reliability of satisfying (or the risk of violating) system’s constraints. A real-world case for water quality management planning of the Xiangxi River in the Three Gorges Reservoir Region (which faces severe water quality problems due to pollution from point and nonpoint sources) is then conducted for demonstrating the applicability of the developed method. The results demonstrate that high biological oxygen demand (BOD) discharge is observed at the Baishahe chemical plant and Gufu wastewater treatment plant. For nonpoint sources, crop farming generates large amounts of total phosphorus (TP) and total nitrogen (TN). The results are helpful for managers in not only making decisions of effluent discharges from point and nonpoint sources but also gaining insight into the tradeoff between system benefit and environmental requirement.

Analisis Kualitas Air dan Daya Tampung Sungai dengan Metode Qual2Kw (Studi Kasus: Sungai Code, Yogyakarta)

2020 ◽  
Vol 5 (4) ◽  
Author(s):  
Nelly Marlina ◽  
Widodo Brontowiyono ◽  
Rosida Chasna
Keyword(s):  
Water Quality ◽  
Quality Management ◽  
Water Quality Management ◽  
Quality Standards ◽  
Class I ◽  
Water Sampling ◽  
Pollution Load ◽  
Administrative Region ◽  
Yogyakarta City

Code River is one of the rivers in the D.I Province Yogyakarta that crosses the administrative areas of Sleman Regency, Bantul Regency and Yogyakarta City. Each administrative region provides input of waste with various contents and affects the capacity of the pollution load with the study area along ± 21 km. The study was conducted at the point of Ngentak, Gondolayu, Sayidan, Keparakan, Tungkak, Ngoto and Wonokromo. The study area is divided into 6 segments for water sampling. In the study conducted with 4 scenario simulations based on existing conditions, prediction of population in the next 5 years, conformity of class I quality standards without pollutant burden and trial error. The method used to analyze water quality is the QUAL2Kw method. By using this software, it can be easier to simulate changes in the upstream to downstream areas. This study aims to analyze the capacity of the pollution load on the concentration of Ammonia, Phosphate and TSS in order to determine the strategy of water quality management in the Code River

scholarly journals Assessment of Lake Water Quality and Eutrophication Risk in an Agricultural Irrigation Area: A Case Study of the Chagan Lake in Northeast China

Water ◽  
2019 ◽  
Vol 11 (11) ◽  
pp. 2380 ◽  
Author(s):  
Xuemei Liu ◽  
Guangxin Zhang ◽  
Guangzhi Sun ◽  
Yao Wu ◽  
Yueqing Chen
Keyword(s):  
Water Quality ◽  
Quality Management ◽  
Lake Water ◽  
Northeast China ◽  
Water Quality Management ◽  
Chemical Properties ◽  
Principal Component ◽  
Trophic State Index ◽  
Lake Water Quality ◽  
Chagan Lake

Water quality safety is the key factor to maintain the ecosystem service functions of lakes. Field investigations and statistical analyses were carried out to study the water quality of a large, agriculture-stressed lakes (e.g., Chagan Lake) in Northeast China. The hydro-chemical properties of the Chagan Lake are HCO3·CO3-Na. Nutrient (N and P) and non-nutrient (pH and F−) were found to be the major factors that threaten water quality safety of the lake. The concentration of total nitrogen (TN) and total phosphorus (TP) was found to vary seasonally and at different locations. The overall lake water had mean TN and TP values of 2.19 mg/L and 0.49 mg/L, respectively, in summer. TN was the major factor for water quality deterioration in the western region of the lake, while TP was the principal factor in the other regions, as determined by a principal component analysis (PCA). Fluoride (F−) concentration in the lake water were related to the values of total dissolved solid (TDS), pH, and electrical conductivity (EC). In addition, eutrophication is a fundamental index that has been affecting the ecological evaluation of water quality. The results showed that trophic level index (TLI), trophic state index (TSI), and eutrophication index (EI) were evaluated to quantify the risk of eutrophication. However, TLI and TSI can better describe the purification effect of the wetland. These indices showed that the lake water was hyper-eutrophic in summer, with TLI, TSI, and EI values of 60.1, 63.0, and 66.6, respectively. Disparities in water quality were observed among whole areas of the lake. Overall, this study revealed that controlling agriculture drainage is crucial for lake water quality management. The study generated critical data for making water quality management plans to control the risk.

scholarly journals Development of two-dimensional water quality management model using the reliability analysis method

2011 ◽  
Vol 14 (2) ◽  
pp. 412-423
Author(s):  
Sang-Ho Kim ◽  
Kun-Yeun Han ◽  
Ji-Sung Kim ◽  
Joonwoo Noh
Keyword(s):  
Water Quality ◽  
Quality Management ◽  
Water Quality Management ◽  
Management Model ◽  
Two Dimensional ◽  
Nakdong River ◽  
Input Parameters ◽  
Quality Management Model ◽  
The Nakdong River ◽  
Mcs Method

A two-dimensional water quality management model, the unsteady/uncertainty water quality model (UUWQM), is developed for three kinds of analysis: hydrodynamic and advection–diffusion analyses by using the Petrov–Galerkin finite element method, and a reliability analysis by using uncertainty techniques. This model is then applied to a 35 km reach of the Nakdong River in Korea. Two-dimensional hydrodynamic and deterministic water quality analyses were performed in this reach. The Monte Carlo simulation (MCS) method was used to decide and verify 14 key input parameters among 80 total input parameters. These key input parameters were incorporated to compute exceedance probabilities and frequency distributions using the mean first-order second-moment (MFOSM) and MCS methods at several locations along this reach of the Nakdong River. From the results of the probable risk for water quality standard, it shows that the outputs from the MFOSM method were similar to those from the MCS method. In practical usage, the MFOSM method is more attractive in terms of its computational simplicity and shorter execution time. Therefore, the UUWQM can be applied efficiently and accurately to estimate the water quality distribution and the risk assessment for the specified water quality in any river.

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