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 effciency.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 coeffcient 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.

Two-dimensional numerical algorithm for water quality modeling in the topographically complicated river

In this paper, a two dimensional numerical calculation algorithm for the water quality modeling in the Hengyang City section of the Xiangjiang River is researched considering the effect of the Dayuandu navigational key project. The research river is winding and has two branches resulted from an isle. The numerical calculation algorithm for the water quality modeling is set up on the basis of applying topographic map of the river course and the finite element method. The calculation result for the water quality modeling includes the concentration fields for various pollutants. The numerical calculation algorithm for the water quality modeling set up in this paper can be applied to shallow river with similar topographically complicated river course.

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

Performance assessment of two-dimensional hydraulic models for generation of flood inundation maps in mountain river basins

Hydraulic models for the generation of flood inundation maps are not commonly applied in mountain river basins because of the difficulty in modeling the hydraulic behavior and the complex topography. This paper presents a comparative analysis of the performance of four twodimensional hydraulic models (HEC-RAS 2D, Iber 2D, Flood Modeller 2D, and PCSWMM 2D) with respect to the generation of flood inundation maps. The study area covers a 5-km reach of the Santa B-arbara River located in the Ecuadorian Andes, at 2330 masl, in Gualaceo. The model's performance was evaluated based on the water surface elevation and flood extent, in terms of the mean absolute difference and measure of fit. The analysis revealed that, for a given case, Iber 2D has the best performance in simulating the water level and inundation for flood events with 20- and 50-year return periods, respectively, followed by Flood Modeller 2D, HEC-RAS 2D, and PCSWMM 2D in terms of their performance. Grid resolution, the way in which hydraulic structures are mimicked, the model code, and the default value of the parameters are considered the main sources of prediction uncertainty.

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.

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

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.

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.

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.

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.

Hyper-spectrum models for monitoring water quality in Dianshan Lake,China

The correlation between water quality parameters and hyper-spectral reflectance is studied with models established for each parameter and applied in Dianshan Lake, in the upstream of the Huangpu River running through Shanghai, China. Models are for dissolved oxygen (DO in mg/L): R720/R680 = 20.362×(R720/R680)2?31.438×(R720/R680)+19.156; for turbidity (NTU): R*714.5 = 206.07× (R*714.5)2?582.5×R*714.5 + 423.24; and for total phosphorus (TP in mg/L): R*509.5 = 16.661× (R*509.5)2?32.646×R*509.5+16.116. The R2 values are 0.770 8, 0.660 4 and 0.738 7, respectively, showing strong positive relationships. The models were then applied to assess water quality of different times. Results are quite satisfactory for some samples.

Water Quality Evaluation in Tidal River Reaches of Liaohe River Estuary, China Using a Revised QUAL2K Model

Rivers in the Liaohe River Estuary area have been seriously polluted by discharges of wastewater containing petroleum pol- lutants and nutrients. In this paper, The Enhanced Stream Water Quality Model (QUAL2K) and its revised model as well as One-dimensional Tide Mean Model (1D model) were applied to predict and assess the water quality of the tidal river reach of the Liaohe River Estuary. Dissolved oxygen (DO), biochemical oxygen demand (BOD5), ammonia nitrogen (NH3-N) and total phosphorus (TP) were chosen as water quality indices in the two model simulations. The modelled results show that the major reasons for degraded rivers remain petroleum and non-point source pollution. Tidal water also has a critical effect on the variation of water quality. The sensitivity analysis identifies that flow rate, point load and diffuse load are the most sensitive parameters for the four water quality indices in the revised QUAL2K simulation. Uncertainty analysis based on a Monte Carlo simulation gives the probability distribution of the four water quality indices at two locations (6.50 km and 44.84 km from the river mouth). The statistical outcomes indicate that the observed data fall within the 90% confidence intervals at all sites measured, and show that the revised QUAL2K gives better results in simulating the water quality of a tidal river.

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>p H. 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 fourparameter model. This work may serve as a reference for monitoring the quality of other marine waters by remote sensing.

Modelling of water quality of Minjiang estuary

In order to establish economic development region at Mawei districtwhich is nearby downstream of Minjiang river and to answer the question of impact of economic development on water quality of Minjiang estuary, the analyses of hydrologic and hydraulic characteristics of Mawei reach of Minjiang tidal river, a two-dimensional mathematical model has been established and simulation of water quality was studied. The results show that the flushing time of a conservative pollutant during dry and raining period are 12 and 7 days respectively from Mawei to Minjiang mouth, the decay rate constants of BOD and NH3-N are 0.1 to 0.4 and 0.18 to 0.45 d-1 respectively. The capacity of dilution and assimilation for pollutants is larger.

A study of groundwater irrigation water quality in south-central Bangladesh: a geo-statistical model approach using GIS and multivariate statistics

Southern Bangladesh's irrigation and drinking water is threatened by saline intrusion. This study aimed to establish an irrigation water quality index(IWQI) using a geostatistical model and multivariate indices in Gopalgan district, south-central Bangladesh. Groundwater samples were taken randomly(different depths) in two seasons(wet-monsoon and dry-monsoon). Hydrochemical analysis revealed groundwater in this area was neutral to slightly alkaline and dominating cations were Na^+, Mg^(2+), and Ca^(2+) along with major anions Cl-and HCO^(3-). Principa component analysis and Gibbs plot helped explain possible geochemical processes in the aquifer. The irrigation wate evaluation indices showed: electrical conductivity(EC)[750 l S/cm, moderate to extreme saline; sodium adsorption ratio(SAR), excellent to doubtful; total hard ness(TH), moderate to very hard; residual sodium bicar bonate, safe to marginal; Kelly's ratio [1; soluble sodiumpercentage(SSP), fair to poor; magnesium adsorption ratio,harmful for soil; and IWQI, moderate to suitable. In addition, the best fitted semivariogram for IWQI, EC, SAR,SSP, and TH confirmed that most parameters had strong spatial dependence and others had moderate to weak spatial dependence. This variation might be due to the different origin/sources of major contributing ions along with the influence of variable river flow and small anthropogenic contributions. Furthermore, the spatial distribution maps for IWQI, EC, SSP, and TH during both seasons confirmed the influence of salinity from the sea; low-flow in the major river system was the driving factor of overall groundwater quality in the study area. These findings may contribute to management of irrigation and/or drinking water in regions with similar groundwater problems.

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.