scholarly journals River water quality management using a fuzzy optimization model and the NSFWQI Index

Water SA ◽  
2021 ◽  
Vol 47 (1 January) ◽  
Author(s):  
Mohammad Kazem Ghorbani ◽  
Abbas Afshar ◽  
Hossein Hamidifar
Keyword(s):  
Water Quality ◽  
Objective Function ◽  
Quality Index ◽  
Water Quality Management ◽  
Fuzzy Optimization ◽  
Model Performance ◽  
River System ◽  
Proposed Model ◽  
Artificial Ants ◽  
Waste Load

In this study, a novel multiple-pollutant waste load allocation (WLA) model for a river system is presented based on the National Sanitation Foundation Water Quality Index (NSFWQI). This study aims to determine the value of the quality index as the objective function integrated into the fuzzy set theory so that it could decrease the uncertainties associated with water quality goals as well as specify the river's water quality status rapidly. The simulation-optimization (S-O) approach is used for solving the proposed model. The QUAL2K model is used for simulating water quality in different parts of the river system and ant colony optimization (ACO) algorithm is applied as an optimizer of the model. The model performance was examined on a hypothetical river system with a length of 30 km and 17 checkpoints. The results show that for a given number of both the simulator model runs and the artificial ants, the maximum objective function will be obtained when the regulatory parameter of the ACO algorithm (i.e., q0) is considered equal to 0.6 and 0.7 (instead of 0.8 and 0.9). Also, the results do not depend on the exponent of the membership function (i.e., γ). Furthermore, the proposed methodology can find optimum solutions in a shorter time.

scholarly journals Fuzzy Optimization Model for Waste Load Allocation in a River with Total Maximum Daily Load (TMDL) Planning

Water ◽  
2020 ◽  
Vol 12 (9) ◽  
pp. 2618
Author(s):  
Jae Heon Cho ◽  
Jong Ho Lee
Keyword(s):  
Water Quality ◽  
Wastewater Treatment ◽  
Water Quality Management ◽  
Fuzzy Optimization ◽  
Fuzzy Model ◽  
Low Flow ◽  
Satisfaction Level ◽  
Waste Load Allocation ◽  
Pollutant Load ◽  
Waste Load

In traditional waste load allocation (WLA) decision making, water quality-related constraints must be satisfied. Fuzzy models, however, can be useful for policy makers to make the most reasonable decisions in an ambiguous environment, considering various surrounding environments. We developed a fuzzy WLA model that optimizes the satisfaction level by using fuzzy membership functions and minimizes the water quality management cost for policy decision makers considering given environmental and socioeconomic conditions. The fuzzy optimization problem was formulated using a max–min operator. The fuzzy WLA model was applied to the Yeongsan River basin, which is located in the southwestern part of the Korean Peninsula and Korean TMDLs were applied. The results of the fuzzy model show that the pollutant load reduction should be increased in the Gwangju 1 and Gwangju 2 wastewater treatment plants (WWTPs) and in subcatchments with high pollutant load. In particular, it is necessary to perform advanced wastewater treatment to decrease the load of 932 kg ultimate biochemical oxygen demand (BODu)/day in the large-capacity Gwangju 1 WWTP and reduce the BODu emission concentration from 4.3 to 2.7 mg/L during the low-flow season. The satisfaction level of the fuzzy model is a relatively high at 0.81.

scholarly journals Assessment of Water Quality of Major Tributaries in Seoul using Water Quality Index and Cluster Analysis

2020 ◽  
Vol 42 (10) ◽  
pp. 452-462
Author(s):  
Jinhyo Lee ◽  
Hyunju Ha ◽  
Manho Lee ◽  
Mokyoung Lee ◽  
Taeho Kim ◽  
...  
Keyword(s):  
Water Quality ◽  
Cluster Analysis ◽  
River Water ◽  
Quality Index ◽  
Water Quality Management ◽  
River Water Quality ◽  
Quality Information ◽  
Linkage Method ◽  
And Cluster Analysis

Objectives : 17 water quality measurement networks (WQMNs, tributaries) in Seoul were analyzed by using NSFWQI and cluster analysis to provide basic data for future river water quality management so that citizens could easily and comprehensively understand the water quality information on the rivers in Seoul.Methods : For the past 3 years (2015~2017), in order to estimate WQI, 9 items, DO (% sat), Fecal coliform, pH, BOD, Temperature change (TC), TP, NO3-, Turbidity and Total solids, were selected from among the 19 water quality data measurement items produced monthly from 17 WQMNs in Seoul. WQI was derived and graded using NSFWQI and cluster analysis was performed using Ward Linkage Method, SOM (Self Organizing Map).Results and Discussion : Water quality of most water quality monitoring networks was BOD Ⅱ grade (slightly good) or higher and TP Ⅲ grade (normal) or higher according to the standard of water quality and water ecosystem river living environment, and NSFWQI was also 64 (Medium)~89 (Good). All showed good water quality. NSFWQI does not show a significant difference by season, so it is believed that it is affected by anthropogenic sources rather than seasonal effects. As a result of examining the correlation between NSFWQI and water quality level according to environmental standards, it was confirmed that R2 has a relatively good correlation with 0.78, and there is no clear difference between the two groups, and through this, it was found that the currently implemented water quality rating system and NSFWQI are well matched. As a result of cluster analysis using ward linkage method and SOM for 17 WQMNs, it was largely divided into 6 groups according to water quality characteristics.Conclusions : It is important to manage pollution sources to systematically manage river water quality as a water resource. It is therefore expected that by converting from the complicated and various water quality information such as is found in this study into a simple water quality index and grouping, the river water quality can be easily understood and can be utilized in the future as basic data for water quality management in Seoul.

scholarly journals Modelling the hydrology and water quality of 3S river system (Sekong, Sesan and Srepok)

2016 ◽  
Vol 19 (2) ◽  
pp. 107-117
Author(s):  
Trang Thi Thuy Nguyen ◽  
Khoi Nguyen Dao
Keyword(s):  
Water Quality ◽  
Swat Model ◽  
Model Performance ◽  
River System ◽  
Water Quality Assessment ◽  
River Basin Management ◽  
Analysis Tool ◽  
Nitrogen And Phosphorus ◽  
Model Soil

The objective of this study was to simulate the hydrologic characteristic and water quality of 3S rivers system (Sekong, Sesan and Srepok) using SWAT model (Soil and Water Analysis Tool). Agriculture and forest are the main land use types in this basin accounting for more than 80 % of the total area. Therfore, nitrogen and phosphorus were selected to be parameters for water quality assessment. SWAT-CUP model was applied to calibrate the model for stream flow and water quality based on SUFI-2 (Sequential Uncertainty Fitting version 2) method. The model performance has been assessed by three statistical indices, including coefficient corellation (R2), Nash-Sutcliffe efficient coefficience (NSE) and percentage Bias (PBIAS). The results showed that SWAT model was well calibrated for simulating the streamflow and water quality with the values of R2 greater than 0.5 except for the Attapeu and Kontum stations, and of PBIAS less than 10 % and 35 % for streamflow and water quality, respectively. The well-calibrated SWAT model can be applied in predicting the hydrology and water quality for other application. Furthermore, it is a tool supporting the policy makers to offer a suitable decisions regarding the sustainable river basin management.

scholarly journals Fuzzy waste load allocation model: a multiobjective approach

2009 ◽  
Vol 12 (1) ◽  
pp. 83-96 ◽  
Author(s):  
Subimal Ghosh ◽  
P. P. Mujumdar
Keyword(s):  
Water Quality ◽  
Goal Programming ◽  
Optimization Model ◽  
River System ◽  
Base Flow ◽  
Risk Minimization ◽  
Waste Load Allocation ◽  
Allocation Model ◽  
Waste Load ◽  
Input Variables

Fuzzy Waste Load Allocation Model (FWLAM), developed in an earlier study, derives the optimal fractional levels, for the base flow conditions, considering the goals of the Pollution Control Agency (PCA) and dischargers. The Modified Fuzzy Waste Load Allocation Model (MFWLAM) developed subsequently is a stochastic model and considers the moments (mean, variance and skewness) of water quality indicators, incorporating uncertainty due to randomness of input variables along with uncertainty due to imprecision. The risk of low water quality is reduced significantly by using this modified model, but inclusion of new constraints leads to a low value of acceptability level, λ, interpreted as the maximized minimum satisfaction in the system. To improve this value, a new model, which is a combination of FWLAM and MFWLAM, is presented, allowing for some violations in the constraints of MFWLAM. This combined model is a multiobjective optimization model having the objectives, maximization of acceptability level and minimization of violation of constraints. Fuzzy multiobjective programming, goal programming and fuzzy goal programming are used to find the solutions. For the optimization model, Probabilistic Global Search Lausanne (PGSL) is used as a nonlinear optimization tool. The methodology is applied to a case study of the Tunga–Bhadra river system in south India. The model results in a compromised solution of a higher value of acceptability level as compared to MFWLAM, with a satisfactory value of risk. Thus the goal of risk minimization is achieved with a comparatively better value of acceptability level.

Sign in / Sign up

Export Citation Format

Share Document