OXYGEN SAG EQUATION FOR THREE-HALVES ORDER BOD REACTION1

Several published BOD data sets are examined to show that approximately half of them are described best in the least squares sense by treating the BOD equation as being of the three-halves order instead of first order. A dissolved oxygen (DO) sag equation for a stream is developed in which the BOD is described as a three-halves order reaction. The time when the minimum DO concentration occurs is calculated numerically. The DO sag model applied to example problems shows that an increase in the BOD reaction rate constant results in a smaller minimum DO concentration and a decrease in the time to reach the minimum DO.     

POLLUTANT LOADING CAPACITY FOR THE BLACK RWER,CHEHALIS RWER SYSTEM,WASHINGTON1

ABSTRACT: The Black River, a tributary of the Chehalis River in western Washington State, has a history of widespread low dissolved oxygen (DO), anoxia in some locations, and fish kills. As part of a Total Maximum Daily Load (TMDL) study, environmental data were collected during two summer dry seasons and simulations were conducted with the WASP5 model to assess the effect of biochemical oxygen demand ( BOD ), ammonia, and nutrient loads on DO in the Black River. DO levels were below the State water quality regulatory criterion of 8.0 mg/L in almost all locations during the study. The slow middle reach of the river showed stratified conditions, with anoxia in some of the deepest pools. Based on model simulations, DO was found to still fall below the 8.0 mg/L criterion in the entire mainstem under “natural” conditions, and eutrophication was identified as a potential problem in the middle reach. A TMDL was proposed for BOD and ammonia that would prevent significant degradation of DO in the Black River. To prevent eutrophic conditions in the Black River, a TMDL for total phosphorus was proposed that establishes a protective criterion of 0.05 mg/L for the middle river during the dry low-flow season.     

MODELING AND CONTROL OF THE POLLUTION OF WATER RESOURCES SYSTEMS VIA MULTILEVEL APPROACH1

ABSTRACT. The problem of modeling and control of water pollution is considered. A general mathematical model, where the pollution effluent is discharged directly into the river, into the lake, or into a bypass pipe leading to an advanced Waste Water Treatment (AWT) plant, is developed. The Water Resource System (WRS) under consideration is decomposed into N subsystems. The pollution effluent input vector to each subsystem includes the water quantity and different water characteristics such as BOD, DO, pH, conductivity, temperature, algae, phosphates, nitrates, etc. Treatment cost functions and quality transition functions as well as system model constraints are introduced, where all functions can be nonlinear. A system Lagrangian is formed to incorporate the system constraints and coupling. The Lagrangian is decomposed into N independent subsystems, and a two level optimization methodology is introduced. Each subsystem is independently and separately minimized at the first level assuming known Lagrange multipliers. At the second level, the total Lagrangian is maximized with respect to the Lagrange multipliers using optimal values for effluent inputs from all subsystems obtained from the first level. Economic interpretation on the Lagrange multipliers reveals that they are merely prices imposed by the central authority (second level) for the pollution caused by the subsystems. Advantages of the multilevel approach are discussed.     

河流水质模型在双流县流域治理中的应用

研究利用现有的河流水质模型,构建了一个可实时模拟河流水环境质量变化状况的动态模型。模型采用一维稳态单组分水质模型对河流的CODCr、NH3-N的降解进行计算,采用多宾斯-坎普稳态模型对河流的BOD、DO变化情况进行计算。模型引入水文数据、水质监测数据、环境统计数据、社会统计公报数据,以Excel作为数据平台,可以反演出河流不同月份、不同区段的污染物降解系数。研究将该模型应用于双流县的流域治理,以在锦江双流段的应用为例进行了具体说明。根据2008年双流县河流的相关数据,研究使用该模型反演出了锦江双流段的污染物降解系数,并对其反映的流域污染状况进行了分析。随后,研究使用该模型已计算出的岷江中段河流的降解系数,模拟计算了4种情景下锦江双流段出境断面的可能水质变化,以验证拟定的双流县流域治理方案的预期效果。模型具有实用性和进一步扩展的功能。     

SPATIAL AND TEMPORAL WATER QUALITY VARIABILITY IN THE PIRACICABA RIVER BASIN,BRAZIL1

ABSTRACT: The spatial and temporal variability of dissolved oxygen (DO), biochemical oxygen demand (BOD), nitrate concentration and total coliform (TC) were investigated at nine sampling stations distributed along the main rivers of the Piracicaba River Basin, a 12,400 km² catchment located in São Paulo State, one of the most developed regions of Brazil. Spatially, a downstream impoverishment of water quality conditions was observed, as seen by the decrease of DO, and increase of BOD, nitrate, and TC. These changes were probably caused by accumulating downstream discharge of domestic and industrial sewage. Temporal evaluation of 18 years of data showed that DO decreased with time for the majority of the sampling stations, while BOD, nitrate, and TC increased. A law, approved at the end of 1991, proposed a new water tax for river water extraction for industrial and agricultural use. The amount of this tax is determined according to the water quality of the extracted water. Therefore, the evaluation of the water quality status in this basin is a first step to help resources managers to determine the values for this tax.     

WATER QUALITY MANAGEMENT OF SKUDAI RIVER1

ABSTRACT: Urban runoff as well as industrial and agricultural discharges have seriously affected the water quality of the Skudai River, Malaysia. A water quality model is developed for simulating BOD and oxygen relationship. The simulated values agree relatively well with survey data taken during low flow conditions. Survey and simulated values show that a pollution abatement program is needed to prevent further deterioration of the river from organic discharges. A systems approach, involving complete analysis of water quality models and environmental control procedures, considering various water use patterns, water quality criteria, and waste input, is essential for solution.     

STATISTICAL ANALYSIS OF DAILY WATER QUALITY DATA1

ABSTRACT. The stochastic nature of some water quality time series were examined. These time series include nine years of daily observations in: (1) the stream flow (Q), (2) the water temperature (T), (3) the dissolved oxygen (DO), and (4) the biochemical oxygen demand (BOD) of the Passaic River at Little Falls, New Jersey. It was found that the random component contributes more than 60 per cent of the variance in the BOD series, but only 30 per cent or less in the DO series. Autocorrelation analysis suggest that DO and BOD residual series have a persistence of about 30 days. Significant crosscorrelation between DO and temperature T was found when DO lags T for up to 30 days, which indicates that the critical DO probably lags the critical temperature. Also, spectral anlaysis shows multiple peaks in the BOD series, reflecting effects of storm runoff and other non-point source pollution on river water quality.     

PROBABILISTIC METHODS IN STREAM QUALITY MANAGEMENT1

ABSTRACT. Recent advances in water quality modelling have pointed out the need for stochastic models to simulate the probabilistic nature of water quality. However, often all that is needed is an estimate of the uncertainty in predicting water quality variables. First order analysis is a simple method of providing an estimate in the uncertainty in a deterministic model due to uncertain parameters. The method is applied to the simplified Streeter-Phelps equations for DO and BOD; a more complete Monte Carlo simulation is used to check the accuracy of the results. The first order analysis is found to give accurate estimates of means and variances of DO and BOD up to travel times exceeding the critical time. Uncertainty in travel time and the BOD decay constant are found to be most important for small travel times; uncertainty in the reaeration coefficient dominates near the critical time. Uncertainty in temperature was found to be a negligible source of uncertainty in DO for all travel times.     

GM(1.1)模型在水磨河水体污染预测中的应用

以水磨河，搪瓷厂桥，七纺桥，联丰桥，米泉桥4个监测断面，以近6a来的BOD3、DO的环境监测值为依据，应用灰色理论建立GM（1．1）模型，对各断面冬季（10月-3月），夏季（4月-9月），全年的BOD5、DO浓度进行预测，并在此基础上进一步分析了水体污染变化的原因。     

REGIONAL WATER QUALITY MANAGEMENT BY THE GENERALIZED REDUCED GRADIENT METHOD1

ABSTRACT: A river basin-wide water quality management system is considered. The river receives thermal as well as organic wastes. At-source treatment of these pollutants is imposed to control the basin-wide water quality. The related water quality standards are: the minimum DO concentration, the maximum allowable BOD concentration, the maximum allowable stream temperature, and the allowable rise in stream temperature. The general dynamic mathematical model representing water quality in streams and the thermal effects on BOD and DO concentrations is presented. The model is highly nonlinear in nature. The optimal management problem involving the model is solved by a recently developed nonlinear propgramming technique - the generalized reduced gradient (GRG) method. Comparison of results obtained by the GRG method vs. dynamic programming, and of results using a more realistic mathematical model vs. a simple model are presented. The analysis procedure can be applied to designing new and examining existing water quality programs, and to study the influence of alternate policies and constraints.     

An innovative modeling approach using Qual2K and HEC-RAS integration to assess the impact of tidal effect on River Water quality simulation

Water quality modeling has been shown to be a useful tool in strategic water quality management. The present study combines the Qual2K model with the HEC-RAS model to assess the water quality of a tidal river in northern Taiwan. The contaminant loadings of biochemical oxygen demand (BOD), ammonia nitrogen (NH₃-N), total phosphorus (TP), and sediment oxygen demand (SOD) are utilized in the Qual2K simulation. The HEC-RAS model is used to: (i) estimate the hydraulic constants for atmospheric re-aeration constant calculation; and (ii) calculate the water level profile variation to account for concentration changes as a result of tidal effect. The results show that HEC-RAS-assisted Qual2K simulations taking tidal effect into consideration produce water quality indices that, in general, agree with the monitoring data of the river. Comparisons of simulations with different combinations of contaminant loadings demonstrate that BOD is the most import contaminant. Streeter-Phelps simulation (in combination with HEC-RAS) is also performed for comparison, and the results show excellent agreement with the observed data. This paper is the first report of the innovative use of a combination of the HEC-RAS model and the Qual2K model (or Streeter-Phelps equation) to simulate water quality in a tidal river. The combination is shown to provide an alternative for water quality simulation of a tidal river when available dynamic-monitoring data are insufficient to assess the tidal effect of the river.     

A MODEL TO ENHANCE WETLAND DESIGN AND OPTIMIZE NONPOINT SOURCE POLLUTION CONTROL1

ABSTRACT: A dynamic, compartmental, simulation model (WETLAND) was developed for the design and evaluation of constructed wetlands to optimize nonpoint source (NPS) pollution control. The model simulates the hydrologic, nitrogen, carbon, dissolved oxygen (DO), bacteria, vegetative, phosphorous, and sediment cycles of a wetland system. Written in Fortran 77, the WETLAND models both free‐water surface (FWS) and subsurface flow (SSF) wetlands, and is designed in a modular manner that gives the user the flexibility to decide which cycles and processes to model. WETLAND differs from many existing wetland models in that the interactions between the different nutrient cycles are modeled, minimizing the number of assumptions concerning wetland processes. It also directly links microbial growth and death to the consumption and transformations of nutrients in the wetland system. The WETLAND model is intended to be utilized with an existing NPS hydro‐logic simulation model, such as ANSWERS or BASINS, but also may be used in situations where measured input data to the wetland are available. The model was calibrated and validated using limited data from a FWS wetland located at Benton, Kentucky. The WETLAND predictions were not statistically different from measured values for of five‐day biochemical oxygen demand (BOD₅), suspended sediment, nitrogen, and phosphorous. Effluent DO predictions were not always consistent with measured concentrations. A sensitivity analysis indicated the most significant input parameters to the model were those that directly affected bacterial growth and DO uptake and movement. The model was used to design a hypothetical constructed wetland in a subwatershed of the Nomini Creek watershed, located in Virginia. Two‐year simulations were completed for five separate wetland designs. Predicted percent reductions in BOD₅ (4 to 45 percent), total suspended solids (85 to 100 percent), total nitrogen (42 to 56 percent), and total phosphorous (38 to 57 percent) were similar to levels reported by previous research.     

High Sediment Oxygen Demand Within an Instream Swamp in Southern Georgia: Implications for Low Dissolved Oxygen Levels in Coastal Blackwater Streams1

Todd, M. Jason, George Vellidis, R. Richard Lowrance, and Catherine M. Pringle, 2009. High Sediment Oxygen Demand Within an Instream Swamp in Southern Georgia: Implications for Low Dissolved Oxygen Levels in Coastal Blackwater Streams. Journal of the American Water Resources Association (JAWRA) 45(6):1493‐1507. Abstract: Sediment oxygen demand (SOD) is considered a critical and dominant sink for dissolved oxygen (DO) in many river systems including blackwater streams and is often poorly investigated or roughly estimated in oxygen budgets. The purposes of this study are to (1) characterize and document the magnitude and variability of SOD in representative instream swamps found on the Georgia Coastal Plain; (2) predict SOD from more readily measured parameters such as soil, sediment, and litter organic carbon; and (3) obtain an accurate representation of SOD values within this understudied habitat to help improve water quality models and the continued development of DO as an appropriate water quality standard. Results show SOD rates ranging from 0.491 to 14.189 g O₂/m²/day, up to 18 times higher than values reported for southeastern sandy‐bottomed streams and suggest that instream swamps are repositories of large amounts of organic matter and are thus areas of intense oxygen demand and a major factor in determining the oxygen balance of the watershed as a whole. These areas of intense oxygen demand in relatively unimpacted areas indicate that low DO concentrations may be a natural phenomenon. SOD rates were significantly correlated (alpha = 0.05) with a number of sediment parameters, with organic carbon and total organic carbon being the best predictors of SOD rate. When developing water quality models, managers should pay closer attention to the influence of SOD as it plays a critical role in determining DO levels within instream swamps and the river system.     

A MODELLING METHOD FOR EVALUATING WATER QUALITY POLICIES IN NONSERIAL RIVER SYSTEMS1

ABSTRACT: This paper describes a modelling method which simplifies the evaluation of water quality policies for nonserial (branching) river systems. The method introduces dummy facilities at the junctions of the major tributary branches with the mainstream as replacements for the facilities and activities on the tributaries. The cost functions for the dummy facilities and the DO and BOD concentrations at the junctions as determined for each tributary are introduced into the mainstream serial system model which is then solved for the optimal values of the mainstream treatment plant efficiencies, the dummy facility effeciencies, and the tributary system DO and BOD concentrations using nonlinear programming. Given the optimum values for the dummy facility efficiencies and the values for the tributary system DO and BOD concentrations, the optimum values for the tributary treatment plant efficiencies are found using nonlinear programming. The method is applied to a river system with a mainstream and one major tributary which contain industrial and municipal organic and thermal polluters and their associated wastewater treatment plants.     

Review of Urban Stormwater Quality Models: Deterministic,Stochastic, and Hybrid Approaches1

Abstract: The growing impact of urban stormwater on surface‐water quality has illuminated the need for more accurate modeling of stormwater pollution. Water quality based regulation and the movement towards integrated urban water management place a similar demand for improved stormwater quality model predictions. The physical, chemical, and biological processes that affect stormwater quality need to be better understood and simulated, while acknowledging the costs and benefits that such complex modeling entails. This paper reviews three approaches to stormwater quality modeling: deterministic, stochastic, and hybrid. Six deterministic, three stochastic, and three hybrid models are reviewed in detail. Hybrid approaches show strong potential for reducing stormwater quality model prediction error and uncertainty. Improved stormwater quality models will have wide ranging benefits for combined sewer overflow management, total maximum daily load development, best management practice design, land use change impact assessment, water quality trading, and integrated modeling.     

DISPERSION MODEL FOR A STREAM WITH SEVERAL WASTE INPUTS AND WATER INTAKES1

An analytical solution is developed to predict the BOD and DO profiles in a stream having several outfalls of waste and intakes of water. The model also incorporates continuous addition and removal of BOD and DO along the stream. A steady state one dimensional dispersion model is used to describe the transport of BOD and DO in a stream. Changes in stream properties along the length are considered by dividing the stream into several segments and changing the parameters of the BOD and DO equations as needed in each segment. By applying continuity equations at the boundaries of these segments and equilibrium conditions at either ends of the infinitely long stream, the arbitrary constants in the solutions to the differential equations for BOD and DO can be determined. Some applications of the results in studying water pollution problems are illustrated.     

Analysis of pollution status of River Illo,Ota, Nigeria

An assessment of the pollution status of River Illo, located within River Owo catchments area in Ota, Ogun State, Nigeria, was carried out. The River’s response to deoxygenation due to BOD loading from an abattoir and its dissolved oxygen (DO) level was predicted using the modified Streeter-Phelps model. The average concentrations of measured parameters at the sampling stations include: 2.24 mg/l of DO, 312.85 mg/l of BOD, 782.86 mg/l of chemical oxygen demand, and 620.76 g/l of total solids. The DO model for River Illo showed a positive correlation between measured and calculated DO, while the dissolved oxygen curve gave a double spoon shape of two major segments with distinct zones of degradation, decomposition, and recovery. The self-purification factor (f) for both segments ranged between 0.8 and 1.1 depicting River Illo as a slow moving or sluggish river. The above results revealed slow reaeration of the water body while full recovery from pollution was difficult. The treatment of River Illo before usage is very essential to ensure public health safety of users from waterborne diseases.     

Dissolved oxygen sag analysis for a settling fields overlapping type multi-wastewater-outfall

The classical Streeter–Phelps models for Dissolved oxygen (DO) sag do not account for a significantly settleable portion (about 10% in treated to about 60% in the untreated wastewater discharged) of the total biochemical oxygen demand (BOD) inputs into rivers through wastewater outfalls, and therefore, they can not be used to predict the DO sag to any accuracy and rationality. The author’s rationally composited model for an accurate prediction of stream BOD, accounting for near linear removal of settleable BOD as well as simultaneous exponential decay of the non-settleable BOD, is used to predict the DO sag resulting from a multi-wastewater-outfall system, wherein the settling fields of some of the outfalls interfere and overlap. An illustrative case example has been presented to demonstrate use of the models evolved under varying locations of the multi-wastewater-outfalls. A universal and integrated PC based computer program can also be evolved for the computation of the overall resultant DO sag to confirm the manually computed DO sag.     

VIRGINIA USA WATER QUALITY, 1978 TO 1995: REGIONAL INTERPRETATION1

ABSTRACT: Nine surface water‐quality variables were analyzed for trend at 180 Virginia locations over the 1978 to 1995 period. Median values and seasonal Kendall's tau, a trend indicator statistic, were generated for dissolved oxygen saturation (DO), biochemical oxygen demand (BOD), pH (PH), total residue (TR), nonfilterable residue (NFR), nitrate‐nitrite nitrogen (NN), total Kjeldahl nitrogen (TKN), total phosphorus (TP), and fecal coliform (FC) at each location. Each location was assigned to one of four physiographic regions, and mean state and regional medians and taus were calculated. Widespread BOD and NFR improvements were detected and FC improvements occurred in the state's western regions. TR and TKN exhibited predominantly increasing trends at locations throughout the state. BOD, TKN, NFR, and TR medians were higher at coastal locations than in other regions. NN, TKN, and TR exhibited predominantly increasing trends in regions with high median concentrations, while declining trends predominated in regions with relatively high BOD, FC, and NFR medians. Appalachian locations exhibited the greatest regional water‐quality improvements for BOD, FC, NFR, and TKN. Factors responsible for regional differences appear to include geology, land use, and landscape features; these factors vary regionally.     

Modeling biological oxygen demand of the Melen River in Turkey using an artificial neural network technique

Artificial neural networks (ANNs) are being used increasingly to predict and forecast water resources' variables. The feed-forward neural network modeling technique is the most widely used ANN type in water resources applications. The main purpose of the study is to investigate the abilities of an artificial neural networks' (ANNs) model to improve the accuracy of the biological oxygen demand (BOD) estimation. Many of the water quality variables (chemical oxygen demand, temperature, dissolved oxygen, water flow, chlorophyll a and nutrients, ammonia, nitrite, nitrate) that affect biological oxygen demand concentrations were collected at 11 sampling sites in the Melen River Basin during 2001-2002. To develop an ANN model for estimating BOD, the available data set was partitioned into a training set and a test set according to station. In order to reach an optimum amount of hidden layer nodes, nodes 2, 3, 5, 10 were tested. Within this range, the ANN architecture having 8 inputs and 1 hidden layer with 3 nodes gives the best choice. Comparison of results reveals that the ANN model gives reasonable estimates for the BOD prediction.