A Three-Dimensional Water Quality Model and Its Application to Jiaozhou Bay, China

A three-dimensional coupled physical and water quality model was developed and applied to the Jiaozhou Bay to study water quality involving nutrients, biochemical oxygen demand, dissolved oxygen, and phytoplankton that are closely related to eutrophication process. The physical model is a modified ECOM-si version with inclusion of flooding/draining processes over the intertidal zone. The water quality model is based on WASP5 which quantifies processes governing internal nutrients cycling, dissolved oxygen balance and phytoplankton growth. The model was used to simulate the spatial distribution and the temporal variation of water quality in the Jiaozhou Bay for the period of May 2005 to May 2006. In addition, the effect of reduction of riverine nutrients load was simulated and evaluated. The simulated results show that under the influence of nutrients discharged from river, the concentrations of nutrients and phytoplankton were higher in the northwest and northeast of the bay, and decreased from the inner bay to the outer. Affected by strong tidal mixing, the concentrations of all state variables were vertically homogeneous except in the deeper regions where a small gradient was found. Obvious seasonal variation of phytoplankton biomass was found, which exhibited two peaks in March and July, respectively. The variation of riverine waste loads had remarkable impact on nutrients concentration in coastal areas, but slightly altered the distribution in the center of the bay.

Three-Dimensional Water Quality Model Based on FVCOM for Total Load Control Management in Guan River Estuary,Northern Jiangsu Province

Guan River Estuary and adjacent coastal area(GREC) suffer from serious pollution and eutrophicational problems over the recent years.Thus,reducing the land-based load through the national pollutant total load control program and developing hydrodynamic and water quality models that can simulate the complex circulation and water quality kinetics within the system,including longitudinal and lateral variations in nutrient and COD concentrations,is a matter of urgency.In this study,a three-dimensional,hydrodynamic,water quality model was developed in GREC,Northern Jiangsu Province.The complex three-dimensional hydrodynamics of GREC were modeled using the unstructured-grid,finite-volume,free-surface,primitive equation coastal ocean circulation model(FVCOM).The water quality model was adapted from the mesocosm nutrients dynamic model in the south Yellow Sea and considers eight compartments:dissolved inorganic nitrogen,soluble reactive phosphorus(SRP),phytoplankton,zooplankton,detritus,dissolved organic nitrogen(DON),dissolved organic phosphorus(DOP),and chemical oxygen demand.The hydrodynamic and water quality models were calibrated and confirmed for 2012 and 2013.A comparison of the model simulations with extensive dataset shows that the models accurately simulate the longitudinal distribution of the hydrodynamics and water quality.The model can be used for total load control management to improve water quality in this area.

Three-Dimensional Tidal Model and Its Application to Numerical Simulation of Water Quality in Coastal Waters

The turbulence mechanism plays an important part in the mixing process and momentum transfer of turbulence. A three-dimensional Prandtl mixing length tidal model has been developed to simulate tidal flows and water quality. The eddy viscosities and diffusivities are computed from the Prandtl mixing length model. In order to model the water quality of an estuary or coastal area many interdependent processes need to be simulated. These may be conveniently separated into three main groups: transport and mixing processes, biochemical interaction of water quality variables and the utilization and re-cycling of nutrients by living matter. The model simulates full oxygen and nutrient balance, primary productivity and the transport, reaction mechanism and fate of pollutants over tidal time-scales. The model is applied to numerical simulation of tidal flows and water quality in Dalian Bay. The model has been calibrated against a limited data set of historical water quality observations and in general demonstrates excellent agreement with all available data.

Three-dimensional refined modeling of water quality in Victoria Harbour

Ｔｈｒｅｅ－ｄｉｍｅｎｓｉｏｎａｌｒｅｆｉｎｅｄｍｏｄｅｌｉｎｇｏｆｗａｔｅｒｑｕａｌｉｔｙｉｎＶｉｃｔｏｒｉａＨａｒｂｏｕｒＳｈｅｎＹｏｎｇｍｉｎｇ，ＱｉｕＤａｈｏｎｇ，Ａ．Ｔ．Ｃｈｗａｎｇ（ＲｅｃｅｉｖｅｄＳｅｐｔｅｍｂｅｒ１２，１９９６；ａｃｃ...

A three-dimensional prediction system for water quality polluction in coastal waters

The hydrodynamics and water quality in Hakata Bay, Japan are strongly affected by the seasonal variations in both the gravitational circulation and the stratification in the bay. The three\|dimensional hydrodynamics and water quality model has been developed to simulate the long\|term transport and fate of pollutants in the system. The model is unique in that it completely integrates the refined modelling of the hydrodynamics, biochemical reactions and the ecosystem in the coastal waters. It is a 3\|dimensional segmented model which is capable of resolving mean daily variations in all the parameters relevant to pollution control. It predicts daily fluctuations in the oxygen content at different depths in water throughout the year. It takes into account transport and settling of pollutant particles. It predicts light penetration from computed turbidity variations. It includes interactions between the ecosystem and water quality through nutrient cycling and photosynthesis. The model has been calibrated well against the data set of historical water quality observations in Hakata Bay.

Three-Dimensional Water-Quality Simulation for River Based on VOF Method

In the present study, considering the transport and transformation processes of variables, a threedimensional water quality model for the river system was established, which coupled the volume of fluid(VOF) method with the k-ε turbulence mathematical model. Then, the water hydrodynamic characteristics and transport processes for BOD_5, NH_(3^-)N and TP were analyzed. The results showed that the water surface of convex bank was a little lower than that of concave bank due to the centrifugal force near the bend, and most concentrations were inferior to the type Ⅴ standard indexes of surface water environmental quality. The model validation indicated that the errors between the simulated and monitored values were comparatively small, satisfying the application demands and providing scientific basis and decision support for the restoration and protection of water quality.

Projection pursuit cluster model and its application in water quality assessment

One of the difficulties frequently encountered in water quality assessment is that there are many factors and they cannot be assessed according to one factor, all the effect factors associated with water quality must be used. In order to overcome this issues the projection pursuit principle is introduced into water quality assessment, and projection pursuit cluster(PPC) model is developed in this study. The PPC model makes the transition from high dimension to one-dimension. In other words, based on the PPC model, multifactor problem can be converted to one factor problem. The application of PPC model can be divided into four parts: (1) to estimate projection index function Q(); (2) to find the right projection direction ; (3) to calculate projection characteristic value of the i th sample z-i, and (4) to draw comprehensive analysis on the basis of z-i. On the other hand, the empirical formula of cutoff radius R is developed, which is benefit for the model to be used in practice. Finally, a case study of water quality assessment is proposed in this paper. The results showed that the PPC model is reasonable, and it is more objective and less subjective in water quality assessment. It is a new method for multivariate problem comprehensive analysis.

Development and application of a two-dimensional water quality model for the Daqinghe River Mouth of the Dianchi Lake

Water quality models are important tools to support the optimization of aquatic ecosystem rehabilitation programs and assess their efficiency. Basing on the flow conditions of the Daqinghe River Mouth of the Dianchi Lake, China, a two-dimensional water quality model was developed in the research. The hydrodynamics module was numerically solved by the alternating direction iteration （ADI） method. The parameters of the water quality module were obtained through the in situ experiments and the laboratory analyses that were conducted from 2006 to 2007. The model was calibrated and verified by the observation data in 2007. Among the four modelled key variables, i.e., water level, COD （in CODcr）, NH4＋-N and PO43-P the minimum value of the coefficient of determination （COD） was 0.69, indicating the model performed reasonably well. The developed model was then applied to simulate the water quality changes at a downstream cross-section assuming that the designed restoration programs were implemented. According to the simulated results, the restoration programs could cut down the loads of COD and PO43-P about 15%. Such a load reduction, unfortunately, would have very little effect on the NH4^＋-N removal. Moreover, the water quality at the outlet cross-section would be still in class V （3838-02）, indicating more measures should be taken to further reduce the loads. The study demonstrated the capability of water quality models to support aquatic ecosystem restorations.

Application of a water quality model for determining instream aeration station location and operational rules:A case study

Instream aeration has been used as a supplement to secondary treatment or a substitute for tertiary treatment for meeting dissolved oxygen （DO） standards in rivers. Many studies have used water quality models to determine the number, location, and capacity of instream aeration stations （IASs） needed to meet DO standards in combination with other pollution control measures. DO concentrations have been improved in the North Shore Channel and North Branch Chicago River by the Devon Avenue IAS for more than 35 years. A study was initiated to determine whether it was better to rehabilitate or relocate this station and to determine appropriate operational guidance for the IAS at the selected location. A water quality model capable of simulating DO concentrations during unsteady flow was used to evaluate the proper location for an IAS and operational guidance for this IAS. Three test years, a dry year, a wet year, and an extreme year, were considered in the evaluation. The study found that the Devon Avenue IAS should be rehabilitated as this location performed as well as or better than any of 10 alternative locations. According to the new operational guidance for this IAS, the amount of time with blowers operating could be substantially reduced compared to traditional operations while at the same time the attainment of the DO standards could be increased. This study shows that a carefully designed modeling study is key to effective selection, location, and operation of IASs such that attainment of DO standards can be maximized while operation hours of blowers can be minimized.

Three-dimensional physical simulation and optimization of water injection of a multi-well fractured-vuggy unit

With complex fractured-vuggy heterogeneous structures, water has to be injected to facilitate oil pro- duction. However, the effect of different water injection modes on oil recovery varies. The limitation of existing numerical simulation methods in representing fractured- vuggy carbonate reservoirs makes numerical simulation difficult to characterize the fluid flow in these reservoirs. In this paper, based on a geological example unit in the Tahe Oilfield, a three-dimensional physical model was designed and constructed to simulate fluid flow in a fractured-vuggy reservoir according to similarity criteria. The model was validated by simulating a bottom water drive reservoir, and then subsequent water injection modes were optimized. These were continuous （constant rate）, intermittent, and pulsed injection of water. Experimental results reveal that due to the unbalanced formation pressure caused by pulsed water injection, the swept volume was expanded and consequently the highest oil recovery increment was achieved. Similar to continuous water injection, intermit- tent injection was influenced by factors including the connectivity of the fractured-vuggy reservoir, well depth, and the injection-production relationship, which led to a relative low oil recovery. This study may provide a constructive guide to field production and for the devel- opment of the commercial numerical models specialized for fractured-vuggy carbonate reservoirs.

Parameter selection and model research on remote sensing evaluation for nearshore water quality

Using remote sensing technology for water quality evaluation is an inevitable trend in marine environmental monitoring. However, fewer categories of water quality parameters can be monitored by remote sensing technology than the 35 specified in GB3097-1997 Marine Water Quality Standard. Therefore, we considered which parameters must be selected by remote sensing and how to model for water quality evaluation using the finite parameters. In this paper, focused on Leizhou Peninsula nearshore waters, we found N, P, COD, PH and DO to be the dominant parameters of water quality by analyzing measured data. Then, mathematical statistics was used to determine that the relationship among the five parameters was COD〉DO〉P〉N〉pH. Finally, five-parameter, fourparameter and three-parameter water quality evaluation models were established and compared. The results showed that COD, DO, P and N were the necessary parameters for remote sensing evaluation of the Leizhou Peninsula nearshore water quality, and the optimal comprehensive water quality evaluation model was the four- parameter model. This work may serve as a reference for monitoring the quality of other marine waters by remote sensing.

Inversion of dispersion coeffcient in water quality model using optimal perturbation algorithm

As a primary parameter in the water quality model for shallow bays, the dispersion coefficient is traditionally determined with a trial-and-error method, which is time-consuming and requires much experience. In this paper, based on the measured data of chemical oxygen demand （COD）, the dispersion coefficient is calculated using an inversion method. In the process, the regularization method is applied to treat the ill-posedness, and an operator identity perturbation method is used to obtain the solu- tion. Using the model with an inverted dispersion coefficient, the distributions of COD, inorganic nitrogen （IN）, and inorganic phosphorus （IP） in Bohai Bay are predicted and compared with the measured data. The results indicate that the method is feasible and the inverted dispersion coefficient can be used to predict other pollutant distribution. This method may also be further extended to the inversion of other parameters in the water quality model.

An integrated measurement and modeling methodology for estuarine water quality management

This paper describes research undertaken by the authors to develop an integrated measurement and modeling methodology for water quality management of estuaries. The approach developed utilizes modeling and measurement results in a synergistic manner. Modeling results were initially used to inform the field campaign of appropriate sampling locations and times, and field data were used to develop accurate models. Remote sensing techniques were used to capture data for both model development and model validation. Field surveys were undertaken to provide model initial conditions through data assimilation and determine nutrient fluxes into the model domain. From field data, salinity re- lationships were developed with various water quality parameters, and relationships between chlorophyll a concentrations, transparency, and light attenuation were also developed. These relationships proved to be invaluable in model development, particularly in modeling the growth and decay of chlorophyll a. Cork Harbour, an estuary that regularly experiences summer algal blooms due to anthropogenic sources of nutrients, was used as a case study to develop the methodology. The integration of remote sensing, conventional fieldwork, and modeling is one of the novel aspects of this research and the approach developed has widespread applicability.

Sensitivity Analysis of Parameters in Water Quality Models and Water Environment Management

The impacts of changes of various parameters and stochastic factors on water quality models were studied. The impact of deviation of the degradation coefficient on the model results was investigated. The degradation coefficient was decomposed into the exact part and the deviation part, and the relationship between the errors of the water quality model results and the deviation of the degradation coefficient was derived. The impact of changes in the initial concentration on the model results was discussed. A linear relationship between the initial concentration changes and errors in the model results was obtained, and relevant recommendations to the water quality management were made based on the results. The impacts of stochastic factors in the water environment on the water quality model were analyzed. A variety of random factors which may affect the water quality conditions were attributed to one stochastic factor and it was further assumed to be the white noise. The solutions to the water quality model including the stochastic process were obtained by solving the stochastic differential equation. Simulation results showed that the decay trend of the concentration of the solute would not be changed, and that the results would fluctuate around the expectation centered at each corresponding displacement

Discharge Water Quality Models of Storm Runoff in a Catchment

The relationships between the water qualities of nitrogen and phosphorous contents in the discharge water and the discharge of storm runoff of an experimental catchment including terraced paddy field are analyzed based on experiment results of the catchment. By summarizing the currently related research on water quality models, the water quality models of different components of storm runoff of the catchment are presented and verified with the experiment data of water quality analyses and the corresponding discharge of the storm runoffs during 3 storms. Through estimating the specific discharge of storm runoff, the specific load of different components of nitrogen and phosphorus in the discharge water of the catchment can be forecasted by the models. It is found that the mathematical methods of linear regression are very useful for analysis of the relationship between the concentrations of nitrogen and phosphorus and the water discharge of storm runoff. It is also found that the most content of the nitrogen (75%) in the discharge water is organic, while half of the content (49%) of phosphorus in the discharge water is inorganic.

Application of Water Quality Model QUAL2K to Model the Dispersion of Pollutants in River Ndarugu, Kenya

Ndarugu River, Kenya, during its course through the different agricultural and industrial areas of Gatundu, Gachororo and Juja farms, receives untreated industrial, domestic and agricultural waste of point source discharges from coffee and tea factories. During wet season the water is also polluted by non-point (diffuse) sources created by runoff carrying soil, fertilizer and pesticide residues from the catchment area. This study involved the calibration of water quality model QUAL2K to predict the water quality of this segment of the river. The model was calibrated and validated for flow discharge (Q), temperature (T&deg), flow velocity (V), biochemical oxygen demand (BOD5), dissolved oxygen (DO) and nitrate (NO3-N), using data collected and analyzed during field and laboratory measurements done in July and November-December 2013. The model was then used in simulation and its performance was evaluated using statistical criteria based on correlation coefficient (R2) and standard errors (SE) between the observed and simulated data. The model reflected the field data quite well with minor exceptions. In spite of these minor differences between the measured and simulated data set at some points, the calibration and validation results are acceptable especially for developing countries where the financial resources for frequent monitoring works and higher accuracy data analysis are very limited. The water is being polluted by the human activities in the catchment. There is need for proper control of wastewater by various techniques, and preliminary treatment of waste discharges prior to effluent disposal. Management of the watershed is necessary so as to protect the river from the adverse impacts of agricultural activities and save it from further deterioration.

Comprehensive Evaluation of Water Quality of Rivers in Binzhou Based on RAGA-PPCE Model

The water quality of main rivers in Binzhou City,Shandong Province was comprehensively evaluated based on RAGA-PPCE model. Six main factors such as ammonia nitrogen(NH_3-N),total phosphorus(TP),total nitrogen(TN),chemical oxygen demand(COD),dissolved oxygen(DO) and p H were used to establish the evaluation and classification standards of water quality. The results show that the evaluation results of water quality by RAGA-PPCE model and the fuzzy comprehensive evaluation method are basically the same. The evaluation results of RAGA-PPCE model are objective and reasonable and can be applied to the comprehensive evaluation of water quality.

Water Quality Model Establishment for Middle and Lower Reaches of Hanshui River,China

With the development of industry and agriculture,nitrogen,phosphorus and other nutrients in the Hanshui River greatly increase and eutrophication has become an important threat to the water quality of the Hanshui River,especially in the middle and lower reaches.The primary objective of this study was to establish the water quality model for the middle and lower reaches of the Hanshui River based on the model of MIKE 11.The main pollutants migration and transformation process could be simulated using the water quality model.The rainfall-runoff model,hy-drodynamic model and water quality model were established using MIKE 11.The pollutants,such as chemical oxygen demand(COD),biochemical oxygen demand(BOD),ammonia nitrogen,nitrate nitrogen,phosphorus,dissolved oxy-gen(DO),were simulated and predicted using the above three models.A set of methods computing non-point source pollution load of the Hanshui River Basin was proposed in this study.The simulated and observed values of COD,BOD5,ammonia,nitrate,DO,and total phosphorus were compared after the parameter calibration of the water quality model.The simulated and observed results match better,thus the model can be used to predict water quality in the fu-ture for the Hanshui River.The pollution trend could be predicted using the water quality model according pollution load generation.It is helpful for government to take effective measures to prevent the water bloom and protect water quality in the river.

Artificial neural network modeling of water quality of the Yangtze River system:a case study in reaches crossing the city of Chongqing

An effective approach for describing complicated water quality processes is very important for river water quality management. We built two artificial neural network(ANN) models,a feed-forward back-propagation(BP) model and a radial basis function(RBF) model,to simulate the water quality of the Yangtze and Jialing Rivers in reaches crossing the city of Chongqing,P. R. China. Our models used the historical monitoring data of biological oxygen demand,dissolved oxygen,ammonia,oil and volatile phenolic compounds. Comparison with the one-dimensional traditional water quality model suggest that both BP and RBF models are superior; their higher accuracy and better goodness-of-fit indicate that the ANN calculation of water quality agrees better with measurement. It is demonstrated that ANN modeling can be a tool for estimating the water quality of the Yangtze River. Of the two ANN models,the RBF model calculates with a smaller mean error,but a larger root mean square error. More effort to identify out the causes of these differences would help optimize the structures of neural network water-quality models.

An attribute recognition model based on entropy weight for evaluating the quality of groundwater sources

In our study, entropy weight coefficients, based on Shannon entropy, were determined for an attribute recognition model to model the quality of groundwater sources. The model follows the theory previously proposed by Chen Q S. In the model, firstly, the author establishes the attribute space matrix and determines the weight based on Shannon entropy theory; secondly, calculates attribute measure; thirdly, evaluates that with confidence criterion and score criterion; finally, an application example is given. The results show that the water quality of the groundwater sources for the city comes up to the grade II or III standard. There is no pollution that obviously exceeds the standard and the water can meet people’s needs .The results from an evaluation of this model are in basic agreement with the observed situation and with a set pair analysis (SPA) model.