Development of a water quality assessment model: a water quality assessment model based on watershed characteristics by non-linear regression

2014 ◽  
Vol 15 (2) ◽  
pp. 236-247 ◽  
Author(s):  
Yongdeok Cho
Keyword(s):  
Water Quality ◽  
Linear Regression ◽  
Quality Assessment ◽  
Watershed Modeling ◽  
Oxygen Demand ◽  
Information Criterion ◽  
Water Quality Assessment ◽  
Assessment Model ◽  
Land Usage ◽  
Non Linear

Here, a water quality assessment model (WQAM) is developed by non-linear regression as an alternative to physical watershed modeling in South Korea. Three cases and 10 scenarios are applied and reviewed to determine the most appropriate WQAM. The three cases are: (1) the area size allocation of sub-watersheds, (2) the watershed imperviousness ratio, and (3) the combination of the area size and imperviousness ratio. The 10 scenarios are: (1) impervious, (2) impervious + pervious, (3) impervious + rainfall, (4) impervious + slope, (5) impervious + rainfall + slope, (6) slope, (7) land usage, (8) land usage + rainfall, (9) land usage + slope, and (10) land usage + rainfall + slope. The best WQAMs are subsequently developed from the generated equations using statistics (R2, Adjusted R2, F-test, the Akaike information criterion and the Shapiro–Wilk test). In addition, the WQAM is verified using the Geum-Sum-Young River watershed. The percentage differences of biochemical oxygen demand (BOD), total nitrogen (T-N), and total phosphorus (T-P) are 31.66%, 8.08%, and 48.94%, respectively. The developed WQAM can be used in place of complex watershed modeling and to aid in the determination of the best restoration locations.

scholarly journals Improving endangered antelope habitat through water quality assessment and collaboration with Kenya Wildlife Service

2020 ◽  
Vol 6 (2) ◽  
pp. 118-122
Author(s):  
Tamie Joy Jovanelly
Keyword(s):  
Water Quality ◽  
Drinking Water ◽  
Quality Assessment ◽  
Animal Health ◽  
Oxygen Demand ◽  
Open Water ◽  
Water Quality Assessment ◽  
Water Sources ◽  
Minimum Criteria ◽  
Physical And Chemical

Background and Aim: A population of endangered sitatunga antelope (Tragelaphus spekii) lives in a free-range environment at Impala Sanctuary in Kisumu, Kenya. Kenya Wildlife Service park officials suspected that increased demands on outdated sewage infrastructure caused animal drinking water sources to become contaminated which resulted in animal sickness and death. In this study, we complete a water quality assessment on open water sources within the park boundaries to determine if water was suitable for animal consumption. Materials and Methods: For the assessment of water, we measure eight physical and chemical parameters (pH, temperature, fecal coliform, dissolved oxygen, biochemical oxygen demand, nitrates, total phosphates, and turbidity). These eight parameters were chosen because they are used to establish a water quality index (WQI) percentage which proved to be useful to communicate conditions to park rangers, stakeholders, and adjacent landowners. Results: Through 6 months of assessments, data collection, and analysis, we determined that most open water sources are severely contaminated, ranking on the WQI from 46% to 58% (bad to medium). In addition, we compared our data to drinking water standards set by the U.S. Department of Agriculture for livestock to find that only two sites met the minimum criteria. The remaining four sites were exponentially contaminated with levels reaching 10× recommended values for animal health. Conclusion: Following these findings, the park was able to attract money for sewage infrastructure rebuilds that resolved the contamination problems. Sickness and death of free-roaming animals, including the antelope, were reduced.

scholarly journals Research on Water Quality Assessment Model Based on Improved Three-Dimensional Nemerow Index Method and Firefly Algorithm

2017 ◽  
Vol 7 (2) ◽  
pp. 47
Author(s):  
Jian Cao ◽  
Zheng-Long Li ◽  
Yuan-Biao Zhang
Keyword(s):  
Water Quality ◽  
Quality Assessment ◽  
Firefly Algorithm ◽  
Human Life ◽  
Three Dimensional ◽  
Water Quality Assessment ◽  
Assessment Model ◽  
Index Method ◽  
Threshold Setting ◽  
Ongoing Concern

Monitoring water quality is a subject of ongoing concern and study since water quality is closely related to human life. Although Nemerow index method is widely used in water quality assessment, the artificial threshold setting may lead to some errors. In this study, we improved the traditional Nemerow index method and built a three-dimensional water quality assessment model combined with the modified firefly algorithm (FA). Then, we applied the improved three-dimensional Nemerow index method to evaluate 100 random water samples. Compared with the traditional method, the improved one proved to be more objective, scientific and practical.

scholarly journals A Multiagent Dynamic Assessment Approach for Water Quality Based on Improved Q-Learning Algorithm

2013 ◽  
Vol 2013 ◽  
pp. 1-7 ◽  
Author(s):  
Jianjun Ni ◽  
Li Ren ◽  
Minghua Liu ◽  
Daqi Zhu
Keyword(s):  
Water Quality ◽  
Quality Assessment ◽  
Water Resource Management ◽  
Learning Algorithm ◽  
Dynamic Assessment ◽  
Water Quality Assessment ◽  
Assessment Model ◽  
Fuzzy Membership Function ◽  
Q Learning ◽  
Interaction Factor

The dynamic water quality assessment is a challenging and critical issue in water resource management systems. To deal with this complex problem, a dynamic water assessment model based on multiagent technology is proposed, and an improved Q-learning algorithm is used in this paper. In the proposed Q-learning algorithm, a fuzzy membership function and a punishment mechanism are introduced to improve the learning speed of Q-learning algorithm. The dynamic water quality assessment for different regions and the prewarning of water pollution are achieved by using an interaction factor in the proposed approach. The proposed approach can deal with various situations, such as static and dynamic water quality assessment. The experimental results show that the water quality assessment based on the proposed approach is more accurate and efficient than the general methods.

Establishment and Application of Water Quality Assessment Model for Jiaozhou Bay Basin

2012 ◽  
Vol 518-523 ◽  
pp. 1165-1170 ◽  
Author(s):  
Chao Liu ◽  
Hui He ◽  
Xiao Hui Tan ◽  
Ai Li Gao ◽  
Song Xue
Keyword(s):  
Water Quality ◽  
Quality Assessment ◽  
Bp Neural Network ◽  
Jiaozhou Bay ◽  
Water Quality Assessment ◽  
Training Sample ◽  
Assessment Method ◽  
Assessment Model ◽  
Water Quality Status ◽  
Effectiveness Of Training

In this paper, a comprehensive water quality assessment model for the seagoing rivers of the Jiaozhou Bay basin was established based on a BP neural network. In the situation investigation, a list of main assessment indexes was selected, comprising COD, permanganate, DO, ammonia, volatile hydroxybenzene and mineral oil. Then Environmental Quality Standards for Surface Water was used as the training sample and comprehensive assessment was conducted for the rivers. In Comparison with results from the conventional single-factor assessment method, this model not only responded to the comprehensive river water quality status, but also improved the speed and effectiveness of training, saving time and increasing accuracy of the assessment model through a series of design optimizations.

Research on the New Assessment Model of Water Source Quality Based on Maximum Entropy Principle

2011 ◽  
Vol 403-408 ◽  
pp. 2123-2126
Author(s):  
Ren Qiang Lu
Keyword(s):  
Water Quality ◽  
Quality Assessment ◽  
Maximum Entropy ◽  
Structural Changes ◽  
Maximum Entropy Principle ◽  
Water Source ◽  
Water Quality Assessment ◽  
Assessment Model ◽  
Lake System ◽  
Entropy Principle

Water source quality is the crucial factor to determine the safety and reliability of urban water supply, and the effective water quality assessment is the premise for water source conservation. Taking a lake system as an example, firstly, the maximum entropy principle was used to analyze the evolution mechanism of the structural changes of lake system. And the nonlinear coupling between the different subsystems of lake system was also analyzed. Secondly, the Self-Organizing feature map neural network was used to simulate the dynamic evolution process of lake system. Finally, a new assessment model for water source quality was established based on the maximum entropy principle. Through application it found that this model achieved the quantitative evaluation of water source quality effectively, and surmounted the inadequate that the precious water quality assessment methods had to determination the weights of the different water quality indicators subjectively.

scholarly journals Zooplankton from can Giuoc River in Southern Vietnam

2016 ◽  
Vol 62 (3) ◽  
pp. 27-33 ◽  
Author(s):  
Pham Anh Duc ◽  
Nguyen Thi Mai Linh ◽  
Dang My Thanh ◽  
Pham Van Mien
Keyword(s):  
Water Quality ◽  
Quality Assessment ◽  
Inorganic Nitrogen ◽  
Oxygen Demand ◽  
Total Suspended Solid ◽  
Water Quality Assessment ◽  
Suspended Solid ◽  
Quality Parameters ◽  
Species Number ◽  
Southern Vietnam

Abstract In this study, the variables of zooplankton and water quality were investigated in the Can Giuoc River, Southern Vietnam. Zooplankton was monitored in April and September 2015 at 5 sampling sites in the river. Some basic water quality parameters were also tested, including pH, total suspended solid (TSS), dissolved oxygen (DO), biological oxygen demand (BOD5), inorganic nitrogen (NH4+), dissolved phosphorus (PO43−), and coliform. The zooplankton biodiversity indices were applied for the water quality assessment. The results showed that pH ranged from 6.7 to 7.6 during the monitoring. The TSSs were between 34–117 mg/L. The DO and BOD5 were from 0.6 to 3.8 mg/L and from 6.3 to 13.2 mg/L, respectively. The NH4+ and PO43− concentrations ranged from 0.44 to 3.23 and from 0.08 to 1.85 mg/L, respectively. The coliform number was between 9.3×103–9.3×104 MPN/100 mL. The zooplankton analyses showed that there were 31 species of coelenterates, rotatoria, oligochaetes, cladocerans, copepods, ostracods, mysidacea, and 8 larval types. Thereof, the species of copepods were dominant in the species number. The zooplankton density ranged from 9 500 to 23 600 individuals/m3 with the main dominant species of Moina dubia (Cladocera), Thermocyclops hyalinus, Acartia clausi, Oithona similis (Copepoda), and nauplius copepods. The biodiversity index values during the monitoring were from 1.47 to 1.79 characteristic of mesotrophic conditions of the aquatic environment. Besides, the species richness positively correlated with pH, TSS, DO, BOD5, NH4+, PO43−, and coliform, while the zooplankton densities got a positive correlation with DO, BOD5, NH4+, PO43−, and coliform. The results confirmed the advantage of using zooplankton and its indices for water quality assessment.

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