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.

Monitoring and evaluation of the water quality of the Lower Neches River, Texas, USA

Increasing bacteria levels in the Lower Neches River caused by Hurricane Harvey has been of a serious concern.This study is to analyze the historical water sampling measurements and real-time water quality data collected with wireless sensors to monitor and evaluate water quality under different hydrological and hydraulic conditions.The statistical and Pearson correlation analysis on historical water samples determines that alkalinity,chloride,hardness,conductivity,and pH are highly correlated,and they decrease with increasing flow rate due to dilution.The flow rate has positive correlations with Escherichia coli,total suspended solids,and turbidity,which demonstrates that runoff is one of the causes of the elevated bacteria and sediment loadings in the river.The correlation between E.coli and turbidity indicates that turbidity greater than 45 nephelometric turbidity units in the Neches River can serve as a proxy for E.coli to indicate the bacterial outbreak.A series of statistical tools and an innovative two-layer data smoothing filter are developed to detect outliers,fill missing values,and filter spikes of the sensor measurements.The correlation analysis on the sensor data illustrates that the elevated sediment/bacteria/algae in the river is either caused by the first flush rain and heavy rain events in December to March or practices of land use and land cover.Therefore,utilizing sensor measurements along with rainfall and discharge data is recommended to monitor and evaluate water quality,then in turn to provide early alerts on water resources management decisions.

Comparative Study of the Physicochemical Quality of the Waters of the Méné River (Sassandra Watershed, Ivory Coast) in the Dry Season and in the Rainy Season

The study carried out on the waters of the Méné River led to an overall assessment of its water quality during the dry season and the rainy season. The analysis focused on eight (8) water samples taken from the river during a period of dry season (January-February) and a period of rainy season (June and September). The various physicochemical parameters were measured according to Afnor standardized methods. The readings of temperature, turbidity, pH and conductivity made it possible to account for the disturbances occurring in water quality. A temporal variation correlated with the seasons (dry or rainy) is noted. Turbidity depends on the concentration of suspended solids (SS) in the water and drained particles and therefore on the seasons. Just like the temperature, the conductivity changes with the season. The waters of the Méné River are generally acidic. The results obtained show that there is a low level of pollution by chlorides, phosphates, nitrites and nitrates. A slight pollution of the waters of Méné in organic matter (chemical oxygen demand values are less than 25 mg∙L−1 during dry season and 32.33 ± 4.73 mg∙L−1 during rainy season) was observed. The concentrations of metallic trace elements such as iron, manganese and aluminum indicate significant pollution of these waters by these elements. Overall, the waters of the Méné River are of satisfactory quality because all the physicochemical parameters analyzed have values below standards during the dry season as well as during the rainy season with the exception of COD and a few metallic trace elements.

Spatial-temporal Variation Characteristics of Water Quality in the Lower Reaches of the Nenjiang River

As an important river in the western part of Jilin Province,the lower reach of the Nenjiang River is an important wetland water source conservation area in Jilin Province.Within the watershed,it governs the Momoge Wetland,the Xianghai Wetland,and the Danjiang Wetland in Jilin Province.The main problem in the lower reaches of the Nenjiang River is the uneven distribution of water resources in time and space,and the intensification of land salinization.Zhenlai County and Da an City in the Nenjiang River Basin have sufficient surface water resources,with surface water as the drinking water source.Baicheng City and Tongyu County have scarce surface water resources,and both use groundwater as their domestic water source.The main polluted section in the basin is the Xianghai Reservoir,and the annual water quality evaluation is Class V.However,the water quality of the Tao er River,the main stream of the Nenjiang River,is significantly better than that of the Xianghai Reservoir.In order to better study the water environmental pollution situation in the Nenjiang River basin,monitoring data from five sections of non seasonal rivers in the basin from 2012 to 2021 were selected for studying water quality.This in-depth exploration of the water pollution status and river water quality change trends in the Nenjiang River basin is of great significance for future rural development,agricultural pattern transformation,and the promotion of water ecological civilization construction.

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.

Assessment of Point and Nonpoint Sources Pollution in Songhua River Basin,Northeast China by Using Revised Water Quality Model

Individual participation of pollutants in the pollution load should be estimated even if roughly for the appropriate environmental management of a river basin.It is difficult to identify the sources and to quantify the load, especially in modeling nonpoint source.In this study a revised model was established by integrating point and nonpoint sources into one-dimensional Streeter-Phelps(S-P) model on the basis of real-time hydrologic data and surface water quality monitoring data in the Jilin Reach of the Songhua River Basin.Chemical oxygen demand(COD) and ammonia nitrogen(NH 3-N) loads were estimated.Results showed that COD loads of point source and nonpoint source were 134 958 t/yr and 86 209 t/yr, accounting for 61.02% and 38.98% of total loads, respectively.NH 3-N loads of point source and nonpoint source were 16 739 t/yr and 14 272 t/yr, accounting for 53.98% and 46.02%, respectively.Point source pollution was stronger than nonpoint source pollution in the study area at present.The water quality of upstream was better than that of downstream of the rivers and cities.It is indispensable to treat industrial wastewater and municipal sewage out of point sources, to adopt the best management practices to control diffuse pollutants from agricultural land and urban surface runoff in improving water quality of the Songhua River Basin.The revised S-P model can be successfully used to identify pollution source and quantify point source and nonpoint source loads by calibrating and validating.

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 fiver reach of the Liaohe River Estuary. Dissolved oxygen （DO）, biochemical oxygen demand （BODs）, 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 wa- ter 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 fiver.

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.

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-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.

Application of QUAL2K for Water Quality Modeling of River Ghataprabha （India）

River Ghataprabha, during its course through Belgaum district in Karnataka state （India）, receives untreated domestic waste from Gokak town and other neighboring villages situated on the bank of the river. The present study involves the application of water quality model QUAL2K to predict the water quality of this polluted segment of the river. The model was calibrated and validated for biochemical oxygen demand （BOD）, dissolved oxygen （DO） and total nitrogen （TN） in pre-monsoon season. Data for calibration and validation were obtained after the field and laboratory measurements. The performance of the model was evaluated using statistics based on standard errors （SE） and mean multiplicative errors （MME）. The model represented the field data quite well with some exceptions. In spite of some differences between the measured and simulated data sets at some points, the calibration and validation results are acceptable especially for the developing countries where the financial resources are often limited for frequent monitoring campaigns and higher accuracy data analysis.

PARAMETER ESTIMATION OF MULTI-CONSTITUENT WATER QUALITY MODEL FOR THE LIANGXI RIVER BY MARQUARDT METHOD

A multi-constituent water quality model is presented,Which relates carbonaceous biochemical oxygen demand (CBOD),amonia (NH3-N), nitrite(NO2-N), nitrate(NO3-N) and dissolvedoxygen(DO). The parameters are solved by Marquardt Method (i. e.,Dampled Least Square Method) while initial values inoptimization are produced by Monte-Carlo Method. The Potential ofthe method as a parameter estimation aid is demonstrated for theapplication to the Liangyi Rver, JiangSu Province of China and by aspecial comparison with Gauss Method.

Incorporating sorption/desorption of organic pollutants into river water quality model

Preliminary research was conducted about how to incorporate sorption/desorption of organic pollutants with suspended solids and sediments into single-chemical and one-dimensional water quality model of Jinghang Canal. Sedimentation-resuspension coefficient k 3 was deduced; characteristics of organic pollutants, concentrations and components of suspended solids/sediments and hydrological and hydraulic conditions were integrated into k 3 and further into river water quality model; impact of sorption/desorption of organic pollutants with suspended solids and sediments on prediction function of the model was discussed. Results demonstrated that this impact is pronounced for organic pollutants with relatively large K oc and K ow, especially when they are also conservative and f oc of river suspended solids/sediments is high, and that incorporation of sorption/ desorption of organic pollutants into river water quality model can improve its prediction accuracy.

Water level updating model for flow calculation of river networks

Complex water movement and insufficient observation stations are the unfavorable factors in improving the accuracy of flow calculation of river networks. A water level updating model for river networks was set up based on a three-step method at key nodes, and model correction values were collected from gauge stations. To improve the accuracy of water level and discharge forecasts for the entire network, the discrete coefficients of the Saint-Venant equations for river sections were regarded as the media carrying the correction values from observation locations to other cross-sections of the river network system. To examine the applicability, the updating model was applied to flow calculation of an ideal river network and the Chengtong section of the Yangtze River. Comparison of the forecast results with the observed data demonstrates that this updating model can improve the forecast accuracy in both ideal and real river networks.

River Water Quality Model Based on Remote Sensing Information Methods——A Case Study of Lijing River in Guilin City

River water quality models based on remote sensing information models are superior to pure water quality models because they combine the inevitability and risk of geographical phenomena and can take complex geographical characteristics into account. A water quality model for forecasting COD has been established with remote sensing in- formation modeling methods by monitoring and analyzing water quantity and water quality of the Lijing River reach which flows through a complicated Karst mountain area. This model provides a good tool to predict water quality of complex rivers. It is validated by simulating contaminant concentrations of the study area. The results show that remote sensing information models are suitable for complex geography. It is not only a combined model of inevitability and risk of the geographical phenomena, but also a semi-theoretical and semi-empirical formula, providing a good tool to study organic contaminants in complicated rivers. The coefficients and indices obtained have limited value and the model is not suitable for all situations. Some improvements are required.

Application of River Network Hydrodynamic Model in Determining Water Distribution Scale of Haishu Plain

The water distribution network is an important part of the plain water environment improvement system. To make efficient use of the regional water diversion source, scientifically distribute the water diversion flow and improve the water environment carrying capacity of Haishu Plain, the river network hydrodynamic model is used in this paper to simulate the water intake location, reasonable water quantity and influence range of water transfer in Haishu Plain. The simulation results have high accuracy, which can provide a scientific basis for the scale, water transfer mechanism and project layout of water transfer construction in Haishu Plain and show a strong reference value for the study of water diversion and distribution scheme of coastal plain river network.

Simulation of Water Quality of Neijiang River Based on RMA4 Model

Using the RMA4 water quality model to simulate the water quality of Neijiang river in Zhenjiang, the result showed that： in the dry season the ranges of the concentration of various pollutants simulation of Neijiang were BOD5 3.2-5.2 mg/L, CODMn 4.7-6.8 mg/L, NH3-N 0.46-1.8 mg/L, TP 0.23-0.48 mg/L, and in the rainy period, the ranges of the concentration of various pollutants simulation of Neijiang were BOD5 0.69-0.73 mg/L, CODM, 1.9-2.3 mg/L, NH3-N 0.25-0.38 mg/L, TP 0.14-0.17 mg/L.These simulated values were closed to the monitoring values of pollution concentrations of Neijiang, which indicated that RMA4 was certain practical in the river water quality simulation, and simulation results have a certain degree of reliability, and it provides a scientific planning and management method for the river pollution control.

Underground water quality model inversion of genetic algorithm

The underground water quality model with non-linear inversion problem is ill-posed, and boils down to solving the minimum of nonlinear function. Genetic algorithms are adopted in a number of individuals of groups by iterative search to find the optimal solution of the problem, the encoding strings as its operational objective, and achieving the iterative calculations by the genetic operators. It is an effective method of inverse problems of groundwater, with incomparable advantages and practical significances.

Spatial Heterogeneity of Embedded Water Consumption from the Perspective of Virtual Water Surplus and Deficit in the Yellow River Basin,China

Virtual water trade(VWT)provides a new perspective for alleviating water crisis and has thus attracted widespread attention.However,the heterogeneity of virtual water trade inside and outside the river basin and its influencing factors remains further study.In this study,for better investigating the pattern and heterogeneity of virtual water trade inside and outside provincial regions along the Yellow River Basin in 2015 using the input-output model(MRIO),we proposed two new concepts,i.e.,virtual water surplus and virtual water deficit,and then used the Logarithmic Mean Divisia Index(LMDI)model to identify the inherent mechanism of the imbalance of virtual water trade between provincial regions along the Yellow River Basin and the other four regions in China.The results show that:1)in provincial regions along the Yellow River Basin,the less developed the economy was,the larger the contribution of the agricultural sector in virtual water trade,while the smaller the contribution of the industrial sector.2)Due to the large output of agricultural products,the upstream and midstream provincial regions of the Yellow River Basin had a virtual water surplus,with a net outflow of virtual water of 2.7×10^(8) m^(3) and 0.9×10^(8) m^(3),respectively.3)provincial regions along the Yellow River Basin were in a virtual water deficit with the rest of China,and the decisive factor was the active degree of trade with the outside.This study would be beneficial to illuminate the trade-related water use issues in provincial regions along the Yellow River Basin,which has farreaching practical signific-ance for alleviating water scarcity.