Water Quality Simulation Model Research Articles

Resolving Disputes over Reservoir-River Operation

The main objective of this work is to allocate water with acceptable quality from a reservoir-river system to different water users and to determine the maximum acceptable pollution load that each user discharges to the river. To achieve this, a bargaining model is developed based on a system dynamics approach, and it is compared with an alternative model based on the Nash bargaining theory. The quality of water released from the reservoir is assessed considering selective withdrawal schemes, obtained from schemes based on operating rules derived from an artificial neural network (ANN) and a K-nearest neighborhood (NN) model. A river water-quality simulation model is also linked with the two bargaining models. These models are then applied to the Karkheh reservoir-river system and using a 50-year monthly time series of qualitative and quantitative data of this system. Finally, the performance criteria for the results of the models are determined and compared. This study shows the significant value of the ...

Parameter determination to calculate water environmental capacity in Zhangweinan Canal Sub-basin in China

Zhangweinan canal sub-basin (ZWN) has the most serious water resource shortage and water pollution problems in north of China. To calculate the water environmental capacity in ZWN, determination methods for design flow rates and degradation coeffcients were discussed in this study. Results showed that 90% and 50% hydrological guarantee flow rates were suitable to be the design flow rates for rainy and dry seasons, respectively. Degradation coeffcients of COD Mn and NH 3-N were 0.25 day −1 and 0.15 day −1 for branch streams and 0.5 day −1 and 0.25 day −1 for mainstreams, respectively in ZWN. With one-dimensional water quality simulation model, water environmental capacities were calculated to be 82,139 tons/yr for COD Mn and 2394 tons/yr for NH 3-N in ZWN.

The development of a multi-species algal ecodynamic model for urban surface water systems and its application

An ecodynamic model that can simulate four phytoplankton species has been developed to deal with the unique characteristics of urban river systems which has manmade river profile, flow controlled by gates, severe eutrophication status, and fragile aquatic ecosystem. The ecodynamic model was developed referencing two typical models: the water quality simulation model WASP and ecological model CAEDYM. The model can simulate 11 state variables: dissolved oxygen, carbonaceous biochemical oxygen demand, ammonia nitrogen, nitrate nitrogen, organic nitrogen, inorganic phosphorus, organic phosphorus and four phytoplankton species with zooplankton as a boundary condition. The ecodynamic model was applied to Sihai section of the Beijing urban river system, where serious algal blooms broke out in recent years. The dominant phytoplankton species are Cyanophyta, Chlorophyta, Bacillariophyta, and Cryptophyta. Site-specific data on geometry, meteorology, pollution sources, and existing ecosystem parameters were collected and used for model calibration and verification The model results mimic observed trends of water quality and phytoplankton species succession and can be used for forecasting algal blooms as well as assessment of river management measures.

Estimation of water quality model parameters

A modified Gauss-Newton method was utilized to estimate water quality model parameters, which is important in the modeling of water quality transport process. This method served the unknown parameters of three engineering problems exceptionally well. We applied this method to obtain a set of water quality parameters by solving the kinetic equations for dissolved and particulate water quality species during episodic events in the Indian River Lagoon, FL. The method was successful in producing water quality model parameters, and the relative errors between measurements and model predictions are below 46.4% and 39.4% for all dissolved and particulate water quality state variables, respectively. In this study we evaluated a good capability of suggested parameter estimation method by comparing a couple of water quality model simulations: (1) water quality model simulation using model parameters produced by the modified Gauss-Newton method and (2) water quality model simulation employing model parameters obtained by the trial-and-error method. The average relative error and ROC score between observed data and water quality model results using model parameters calculated by the modified Gauss-Newton method are 58.3% and 0.565, respectively. In the case of water quality model simulation using model parameters obtained by the trial-and-error method, the average relative error and ROC score are 60.5% and 0.555, respectively. This suggests that the modified Gauss-Newton method efficiently yields water quality model parameters resulting in better or similar model prediction errors when compared to the trial-and-error method.

Developing operating rules for reservoirs considering the water quality issues: Application of ANFIS-based surrogate models

In this study, a methodology combining a water quality simulation model and a hybrid genetic algorithm (HGA) is developed for determining optimal operating policies for different reservoir outlets. The water quality simulation model is based on an adaptive neural fuzzy inference system (ANFIS), which is trained using the results of a numerical water quality simulated model. This ANFIS-based simulation model has an acceptable run-time and can be easily linked to the HGA-based optimization model. To further reduce the model run-time, the main problem is decomposed to a long-term and some annual optimization models. ANFIS is also utilized to develop monthly operating rules for reservoir outlets. To evaluate the efficiency of the proposed methodology, it is applied to the 15-Khordad dam located in the central part of Iran. The results show that this ANFIS-based model can significantly reduce the run-time of the previously developed models while it dose not reduce the accuracy of the reservoir operation policies. The ANFIS-based operating rules can be effectively used for real-time reservoir operation.

총량규제에 따른 주암호의 장래 수질 예측

When the Juam multipurpose dam which is connected with existing large water supply facilities is finished, water environment is changed from stream to lake. The changed quality of water should be examined. In this study, the result of water quality forecasting is analysed and an effective management plan of water quality is presented. Tn this study, the WASPS model that is a dynamic water quality simulation model was selected to forecast the water quality. This model forecasts movement of change of pollutants. For an application of the model, the subject areas were divided into seventeen sub-areas by considering change temperature depending measuring points and on depth of water. Meteorological data collected by the meteorological observatory and data about quality measured by the Korea Water Resources Development Corporation were used for an operation of the model. As a result of quality examination through quality data and estimated pollutant loading, the water quality environment criterion was grade II and the nutritive condition was measured as meso-graphic grade. In this study, an effective management was planned to improve water quality by reducing pollution load. According to the result of examination, when more than 30% of BOD was reduced it was recorded that the environment standard of water quality was improved to the second grade.

Evaluation of the intrusion generated by a submerged contact chamber of hypolimnetic oxygenator in a reservoir

Physical characteristics of a hypolimnetic oxygenator known as a Water Environmental Preservation System (WEP), were investigated through field tests carried out in Sanbe Reservoir, Japan. Field data showed that the oxygen‐rich intrusion traveled at nearly the same height as the outflow opening of the device. The thickness of the intrusion, travel time and other important values were derived from the field data. The results showed the flow to be similar to that of an intrusion emanating from a bubble plume after the plunging point and was controlled by an inertia‐buoyancy force balance. The intrusion from the oxygenator was successfully simulated with a three‐dimensional hydrodynamic and water quality simulation model (ELCOM‐CAEYDM) including a simple integral model for the oxygenator.

SWAT 및 KoRiv1 모형을 활용한 하류하천 탁도관리 시스템구축

High turbid water in the River has been one of the major concerns to the downstream residence. Especially in the Nakdong River basin severe turbid water problem occurred in year 2002 and 2003 due to the typhoon Rusa and Maemi consecutively. The main objective of this study is to develop turbid water management system in reservoir downstream of the Nakdong River combining physically based semi-distributed hydrologic simulation model SWAT with 1-dimensional dynamic water quality simulation model. SWAT model covers the area from the upstream of the Imha and Andong reservoir to the Gumi gage station for the purpose of estimating flow rates and suspended sediment of the tributaries. From year 1999 to 2007 runoff simulation for 8 years <TEX>$R_{eff}$</TEX> and <TEX>$R^2$</TEX> ranges <TEX>$0.46{\sim}0.9$</TEX>, <TEX>$0.54{\sim}0.99$</TEX> respectively. Through the linkage of models, outputs of SWAT model such as suspended sediment and flow rates of the tributaries can be incorporated into the 1-dimensional dynamic water quality simulation model, KoRiv1 to support joint reservoir operation considering the turbidity released from Imha and Andong reservoir. The applicability of model simulation has been tested for year 2006 and compared with measured data.

Water quality parameter estimation for water distribution systems

Wall decay coefficients vary between pipes and must be determined indirectly from field measured concentration data. A general calibration model for identifying these parameters is formulated here. The problem is solved using the shuffled frog leaping algorithm optimisation algorithm that is coupled with hydraulic and water quality simulation models using the EPANET Toolkit. The methodology is applied to two application networks to examine the robustness of the parameter estimation algorithm and to study the effects of the network flow conditions, data availability, model simplification, and measurement errors. To that end, different field conditions are considered, including a network with or without tanks, altering disinfectant injection policies, changing measurement locations, and varying the number of wall decay coefficients. Results from conditions with exact data show that the solution approach is robust and consistently finds the true parameter values. However, when the number of decay coefficients is increased, results suggest that the distribution and number of meter locations affects model parameter identifiability. It is also noted that the parameter sensitivity is relatively small and related to the velocities in the network. Finally, isolated tracer data can supplement information from normal operating conditions to improve decay coefficient calibration but, if sufficient data is available, the incremental improvement may not be significant. To confirm this result, model calibration must be extended to parameter and model prediction uncertainty.

Probabilistic reservoir operation using Bayesian stochastic model and support vector machine

Available water resources are often not sufficient or too polluted to satisfy the needs of all water users. Therefore, allocating water to meet water demands with better quality is a major challenge in reservoir operation. In this paper, a methodology to develop operating strategies for water release from a reservoir with acceptable quality and quantity is presented. The proposed model includes a genetic algorithm (GA)-based optimization model linked with a reservoir water quality simulation model. The objective function of the optimization model is based on the Nash bargaining theory to maximize the reliability of supplying the downstream demands with acceptable quality, maintaining a high reservoir storage level, and preventing quality degradation of the reservoir. In order to reduce the run time of the GA-based optimization model, the main optimization model is divided into a stochastic and a deterministic optimization model for reservoir operation considering water quality issues. The operating policies resulted from the reservoir operation model with the water quantity objective are used to determine the released water ranges (permissible lower and upper bounds of release policies) during the planning horizon. Then, certain values of release and the optimal releases from each reservoir outlet are determined utilizing the optimization model with water quality objectives. The support vector machine (SVM) model is used to generate the operating rules for the selective withdrawal from the reservoir for real-time operation. The results show that the SVM model can be effectively used in determining water release from the reservoir. Finally, the copula function was used to estimate the joint probability of supplying the water demand with desirable quality as an evaluation index of the system reliability. The proposed method was applied to the Satarkhan reservoir in the north-western part of Iran. The results of the proposed models are compared with the alternative models. The results show that the proposed models could be used as effective tools in reservoir operation.

A game theoretic approach for interbasin water resources allocation considering the water quality issues

In this paper, a new game theoretic methodology is developed for interbasin water transfer management with regard to economic, equity, and environmental criteria. The main objective is to supply the competing users in a fair way, while the efficiency and environmental sustainability criteria are satisfied and the utilities of water users are incorporated. Firstly, an optimization model is developed to proportionally allocate water to the competing users in water donor and receiving basins based on their water demands. Secondly, for different coalitions of water users, the water shares of the coalitions are determined using an optimization model with economic objectives regarding the physical and environmental constraints of the system. In order to satisfy water-quality requirements, the impacts of decreasing the instream flow in donor basin are estimated using a water-quality simulation model, and the required treatment levels for effluents discharged into the river, downstream of the water transfer point are determined. Finally, to achieve equity and to provide sufficient incentives for water users to participate in the cooperation, some cooperative game theoretic approaches are utilized for reallocation of net benefits to water users. This model is applied to a large-scale interbasin water allocation problem including two different basins struggling with water scarcity in Iran. The results show that this model can be utilized as an effective tool for optimal interbasin water allocation management involving stakeholders with conflicting objectives subject to physical and environmental constraints.

Interbasin Water Transfer: Economic Water Quality-Based Model

The interbasin water transfer project is an alternative to balance the nonuniform temporal and spatial distribution of water resources and water demands, especially in arid and semi arid regions. A water transfer project can be executed if it is environmentally and economically justified. In this study, the feasibility of two interbasin water transfer projects from Karoon River in the western part of Iran to the central part of the country is investigated. An optimization model with an economic objective function to maximize the net benefit of the interbasin water transfer projects is developed. The planning horizon of the model is 23 years (the length of historical data); and it is solved using genetic algorithm. In order to consider environmental impacts of water transfer projects, a water quality simulation model has been used. Then, an Artificial Neural Network model is trained based on the simulation results of a river water quality model in order to be coupled with the optimization model. The outputs of the optimization model are the value of economic gain of the sending (Karoon) basin to offset the loss of agricultural income and environmental costs. The optimal polices for water transfer during the planning horizon has been generated using the coupled simulation-optimization model. Then, operating rules are developed using a K Nearest Neighborhood model for the real time water transfer operation. The results show the significant value of using the proposed algorithm and economic evaluation for water transfer projects.

Soil Nitrogen Balance under Wastewater Management: Field Measurements and Simulation Results

The use of treated wastewater for irrigation of crops could result in high nitrate-nitrogen (NO(3)-N) concentrations in the vadose zone and ground water. The goal of this 2-yr field-monitoring study in the deep silty clay loam soils south of Dodge City, Kansas, was to assess how and under what circumstances N from the secondary-treated, wastewater-irrigated corn reached the deep (20-45 m) water table of the underlying High Plains aquifer and what could be done to minimize this problem. We collected 15.2-m-deep soil cores for characterization of physical and chemical properties; installed neutron probe access tubes to measure soil-water content and suction lysimeters to sample soil water periodically; sampled monitoring, irrigation, and domestic wells in the area; and obtained climatic, crop, irrigation, and N application rate records for two wastewater-irrigated study sites. These data and additional information were used to run the Root Zone Water Quality Model to identify key parameters and processes that influence N losses in the study area. We demonstrated that NO(3)-N transport processes result in significant accumulations of N in the vadose zone and that NO(3)-N in the underlying ground water is increasing with time. Root Zone Water Quality Model simulations for two wastewater-irrigated study sites indicated that reducing levels of corn N fertilization by more than half to 170 kg ha(-1) substantially increases N-use efficiency and achieves near-maximum crop yield. Combining such measures with a crop rotation that includes alfalfa should further reduce the accumulation and downward movement of NO(3)-N in the soil profile.

Water quality monitoring of Maong River, Malaysia

A water quality simulation model for Maong River, which flows through Kuching City, in Malaysia was explored with a focus on predicting the dissolved oxygen (DO) parameter. The model simulated the DO levels using the hourly data collected in December 2006. The water quality model was developed to simulate the inflow water conditions and estimate the DO levels at various locations along the river reaches as it flows through the highly populated Maong River catchments. The model adopted a hydrodynamic flow simulation to capture advection and diffusion due to different flow conditions. From the results, it is clear that DO concentrations are clearly affected as the river flows downstream. The correlation of the observed and simulated DO concentration was 0·82.

Evaluating long-term hydrological impacts of regional urbanisation in Hanyang, China, using a GIS model and remote sensing

China has experienced a rapid urbanisation, especially since the 1980s; however, the environmental impacts of this process are not fully investigated. Hanyang (Hubei Province, south China) was selected as a typical case to investigate runoff and non-point source (NPS) pollution impacts of urbanisation. A water quality simulation model (L-THIA) was applied to determine the long-term implications of different degrees of regional urbanisation impacts on NPS pollutants. Land-use patterns in 1987, 1998 and 2003 were analysed to evaluate the temporal variation of urbanisation, and the precipitation dataset from 1975 to 2003 was used to estimate the mean annual runoff and NPS pollutants. The contributions of different land-use categories to average annual runoff and NPS pollutant production were assessed by the means of a regression model. Results show that urban/impervious lands increased by 30.4% between 1987 and 2003, with the most increase occurring in 1998–2003. Industrial and forestlands have the most and least impact, respectively, on mean annual runoff and NPS pollutants. A combination of L-THIA and the regression model was found to be useful as a decision support tool for regional and urban planning from the perspectives of water quality control.

Developing real time operating rules for trading discharge permits in rivers: Application of Bayesian Networks

Transferable discharge permit (TDP) programs show potential cost-effective methods of pollution control in river systems. Nevertheless, there remain uncertainties that, if not adequately addressed, might impair their success. Trading Ratio System (TRS) suggested by Hung and Shaw [2005. A trading-ratio system for trading water pollution discharge permits. Journal of Environmental Economics and Management 49, 83–102] is a cost-effective tool for water quality management in river systems, which provides the optimum trading pattern among dischargers. TRS has been designed for a single conservative water quality variable and the existing uncertainties are not incorporated. In this study, TRS is extended to be applicable to Biochemical Oxygen Demand (BOD) and Dissolved Oxygen (DO) management in river systems and uncertainties in input variables of river water quality simulation model are also considered. In the proposed methodology, low water quality is also quantified as a fuzzy event and fuzzy risk of violating the water quality standards is estimated at each checkpoint along the river. The Extended Trading Ratio System (ETRS) is used in a Monte Carlo Analysis to provide the required data for training and validating a Bayesian Network (BN). The trained BN can be used for real time river water quality management and provides the probability density functions of treatment levels and trading discharge permit policies. The methodology is successfully applied to the Zarjub River in the northern part of Iran to show its usefulness as a cost-effective and risk-informed decision-making tool in real time river water quality management.

Design of on-line river water quality monitoring systems using the entropy theory: a case study

The design of a water quality monitoring network is considered as the main component of water quality management including selection of the water quality variables, location of sampling stations and determination of sampling frequencies. In this study, an entropy-based approach is presented for design of an on-line water quality monitoring network for the Karoon River, which is the largest and the most important river in Iran. In the proposed algorithm of design, the number and location of sampling sites and sampling frequencies are determined by minimizing the redundant information, which is quantified using the entropy theory. A water quality simulation model is also used to generate the time series of the concentration of water quality variables at some potential sites along the river. As several water quality variables are usually considered in the design of water quality monitoring networks, the pair-wise comparison is used to combine the spatial and temporal frequencies calculated for each water quality variable. After selecting the sampling frequencies, different components of a comprehensive monitoring system such as data acquisition, transmission and processing are designed for the study area, and technical characteristics of the on-line and off-line monitoring equipment are presented. Finally, the assessment for the human resources needs, as well as training and quality assurance programs are presented considering the existing resources in the study area. The results show that the proposed approach can be effectively used for the optimal design of the river monitoring systems.

A Benefit‐Cost Analysis of Total Maximum Daily Load Implementation1

Abstract: Total Maximum Daily Load (TMDL) implementation generates benefits and costs from water quality improvements, which are rarely quantified. This analysis examines a TMDL written to address bacteria and aquatic‐life‐use impairments on Abrams and Opequon Creeks in Virginia. Benefits were estimated using a contingent valuation survey of local residents. Costs were based on the number and type of best management practices (BMPs) necessary to achieve TMDL pollution reduction goals. BMPs were quantified using watershed‐scale water quality simulation models (Generalized Watershed Loading Function and Hydrological Simulation Program‐FORTRAN). Based on our projections, the costs to achieve TMDL induced pollution reduction goals outweigh the estimated benefits. Benefit‐cost ratios ranged between 0.1 and 0.3.

An Inexact Chance-constrained Quadratic Programming Model for Stream Water Quality Management

Water quality management is complicated with a variety of uncertainties and nonlinearities. This leads to difficulties in formulating and solving the resulting inexact nonlinear optimization problems. In this study, an inexact chance-constrained quadratic programming (ICCQP) model was developed for stream water quality management. A multi-segment stream water quality (MSWQ) simulation model was provided for establishing the relationship between environmental responses and pollution-control actions. The relationship was described by transformation matrices and vectors that could be used directly in a multi-point-source waste reduction (MWR) optimization model as water-quality constraints. The interval quadratic polynomials were employed to reflect the nonlinearities and uncertainties associated with wastewater treatment costs. Uncertainties associated with the water-quality parameters were projected into the transformation matrices and vectors through Monte Carlo simulation. Uncertainties derived from water quality standards were characterized as random variables with normal probability distributions. The proposed ICCQP model was applied to a water quality management problem in the Changsha section of the Xiangjiang River in China. The results demonstrated that the proposed optimization model could effectively communicate uncertainties into the optimization process, and generate inexact solutions containing a spectrum of wastewater treatment options. Decision alternatives could then be obtained by adjusting different combinations of the decision variables within their solution intervals. Solutions from the ICCQP model could be used to analyze tradeoffs between the wastewater treatment cost and system-failure risk due to inherent uncertainties. The results are valuable for supporting decision makers in seeking cost-effective water management strategies.

A simplified model for reservoir operation considering the water quality issues: Application of the Young conflict resolution theory

In this study, an algorithm combining a multi-objective genetic algorithm (GA)-based optimization model and a water quality simulation model is developed for determining a trade-off curve between objectives related to the allocated water quantity and quality. To reduce the run-time of the GA-based optimization model, the main problem is decomposed to long-term and annual optimization models. The reliability of water supply is considered to be the objective function in the long-term stochastic optimization model, but the objective functions of the annual models are related to both the allocated water quantity and quality. The operating policies obtained using this long-term model provide the time series of the optimum reservoir water storages at the beginning and the end of each water year. In the next step, these optimal reservoir storage values are considered as constraints for water storage in the annual reservoir operation optimization models. The epsilon-constraint method is then used to develop a trade-off curve between the reliability of water supply and the average allocated water quality. The Young conflict resolution theory, which incorporates the existing conflicts among decision-makers and stakeholders, is used for selecting the best solution on the trade-off curve. The monthly reservoir operating rules are then calculated using an Adaptive Neuro-Fuzzy Inference System, which is trained using the optimal operating policies. The proposed model is applied to the 15-Khordad Reservoir in the central part of Iran. The results show that this simplified procedure does not reduce the accuracy of the reservoir operating policies and it can effectively reduce the computational burden of the previously developed models.