Dissolved Oxygen Balance Research Articles

Siting and evaluation of offshore suspended mussel farms through nutritional restriction approach

An individual-based model based on mussel feeding on algae was developed for the first time, and the model was introduced to a three-dimensional water quality model based on nitrogen, phosphorus, phytoplankton cycling and dissolved oxygen balance, describing the ecological influence of mussel feeding. The drag of aquaculture facilities on suspended farms was introduced to a three-dimensional hydrodynamic model. The water quality model was coupled with the three-dimensional hydrodynamic model to simulate the hydrodynamic environment field of a large offshore suspended mussel farm in Gouqi Island throughout a year. The simulation results agree well with observations. Based on the nutritional restriction approach, the cause of mussel mortality in Gouqi Island is insufficient algal concentration and insufficient filtration rate. Accordingly, an optimized site selection of the suspended mussel farms was proposed, and its feasibility was validated in hydrology and water quality by using the model. Furthermore, hydrodynamic and ecological effects of aquaculture facilities and site selection were quantified. Aquaculture facilities in Gouqi Island reduces surface current speed by 86% and increases half-time of water exchange by 64%. P is the limiting nutrient in the suspended mussel farms of Gouqi Island. The siting of offshore suspended mussel farms only changes the local distribution of nutrients, causing minimal changes in nutrient concentrations and having limited ecological influence.

Implication of dissolved nitrogen dynamics of urban rivers using multivariate regression and structural equation modeling

AbstractThe river's functional balance varies according to flow regimes and nutrient distribution. Watercourses can receive water from different point and nonpoint sources, which discharge high nitrogen load in rivers generated from domestic and industrial effluents and agricultural runoff. The excessive concentration of nitrogen load affects the riverine ecosystem by attenuating dissolved oxygen balance and disturbing the water quality. A study has been conducted to determine the nitrogen dynamics and their impact on the water quality of the Delhi stretch of Yamuna River, India, which is highly influenced by anthropogenic activities. Multivariate linear regression (MLR) was performed to gain insight into nitrogen dynamics, and structural equation modeling was applied to determine the direct (primary) and indirect (secondary) relation between the water quality parameters and the subsequent impact on water quality. Dissolved inorganic nitrogen (DIN) was measured using ammonia, nitrate, and nitrite, and total Kjeldahl nitrogen was estimated to reflect the dissolved organic nitrogen (DON). The variation in dissolved nitrogen (organic and inorganic) signifies high negative flux on the river's organic content, causing further degradation of river water quality. MLR predicted a high correlation between predicted and observed DIN at the Income Tax Office (ITO) (92.5%) and Nizamuddin (94.37%) and DON at ITO (93.49%) and Nizamuddin (95.28%). The high concentration during the lean period deteriorates the water quality tremendously and suggests that the variation in dissolved nitrogen content should be monitored carefully to maintain the river's water quality dominated by the organic load.

Sediment oxygen demand rate in a flow regulated lagoon (Venice, Italy)

From October 2020, the MOSE system went into operation in the three inlets to protect Venice and its lagoon from flooding caused by high tide events in the Adriatic Sea. While the MOSE increases the prospect of physical defense, how will the new status of a regulated lagoon affect the functioning of the waterbody? In particular, the dissolved oxygen balance in the water column can be affected by the expected increase in water residence times. Sediments play an important role in oxygen consumption in the water column and for this reason sediment oxygen demand (SOD) was studied in situ for the first time, in 16 sites at four lagoon areas. SOD rate, measured throughout 2021 with specially made benthic chambers, varied in the different areas and with seasons (from 0.63 to 24.00 g m−2 d−1), with higher values at the more confined sites and significantly lower values in those belonging to the open lagoon. Based on SOD rate, consumption times of dissolved oxygen in the water column were estimated at the MOSE closures, from saturation values to hypoxia and in the temperature range of 11.7–33.3°C. Especially in the confined sites, sediments can exert an important depleting action on dissolved oxygen already at water temperatures above 20°C, which are not particularly high for the lagoon.

Detection method of dissolved oxygen saturation in ecological water in coastal cities

In order to monitor the dissolved oxygen saturation in the ecological water environment of coastal cities in real time, it provides a basis for the control of ecological water pollution in coastal cities. Therefore, the detection method of ecological water pollution saturation in coastal cities is studied. First, the process and principle of dissolved oxygen in the water body are solved, and the equilibrium equation of dissolved oxygen is obtained. The Mutual Information-Particle Swarm Optimization-Radial Basis Function (MI-PSO-RBF) saturation detection method is used to detect the dissolved oxygen saturation in the ecological water of coastal cities. This method preprocesses the sampling data of ecological water in coastal cities, uses mutual information theory and dissolved oxygen balance equation, and detects the saturation of ecological water pollution through particle swarm optimization RBF neural network. Experimental results show that this method can effectively detect the saturation of ecological water pollution in coastal cities. The detection accuracy of dissolved oxygen saturation in a research area in Shandong is as high as 99%, and the detection time is less than 40 ms.

Application of Qual2e Model for River Water Quality Modelling

QUAL2E is modeling software which simulates up to 15 water quality parameters in branching stream system. The model uses mathematical equations like finite-difference solution of the adjective- dispersive mass transport and reaction equations. The program computes a series of steady- state water surface profiles and simulates changes in flow conditions along the stream. The model is applicable only to dendritic streams that are well mixed and it assumes that the major transport mechanism, advection and dispersion are significant only along the main direction of flow of the stream. QUAL2E can operate as either a steady state or a dynamic model and it simulates dynamic dial heat budget and water quality kinetics for a one dimensional and steady flow system. QUAL2E program performs dissolved oxygen balance by including source and sink terms in mass balance equation and is used to quantify the non point sources loading rate, determine the pollutants, calculate the phosphorus and estimate the natural conditions. It accommodates four types of hydraulic and mass load functions in addition to local climate factors: headwater-inputs, point sources, inflow/outflow and downstream boundary conditions.

Numerical modeling of the Xiangxi River algal bloom and sediment-related process in China

A three-dimensional unstructured mesh eco-dynamic model was developed to simulate temporal and spatial variations in water quality with respect to phytoplankton, nutrients, dissolved oxygen, and suspended sediment, based on the ELcirc model. Four major interacting systems were simulated, including phytoplankton dynamics, nutrient cycles, dissolved oxygen balance, and suspended sediment. The effects of suspended and bed sediment on water quality processes were also considered. The model was applied to simulate algal bloom processes in the Xiangxi River (XXR), a tributary of the Yangtze River that was affected by the impounding of the Three Gorges Project. The model was calibrated and verified by field data during the XXR algal blooms. The simulated time serial concentrations of phytoplankton (chlorophyll) and nutrients were generally consistent with field observations. Sensitivity studies were then conducted to assess the impacts of varying inlet discharges, suspended sediment loads, and nutrient loading on the chlorophyll concentration of algae.

An Eulerian–Lagrangian method for the simulation of the oxygen concentration dissolved by a two-phase turbulent jet system

Multiphase jet systems are used in environmental engineering to mix and provide oxygen in activated sludge plants for the aerobic digestion of degradable substrates.Here a laboratory experiment, based on a lab-scale model where mixing is obtained by a turbulent multiphase jet of tap water and pure oxygen, is used to validate a multiscale numerical model of the oxygen concentration evolution based on a “one-way coupling” approach.The velocity field inside the lab-model, measured by means of a 3D Acoustic Doppler Velocimeter, allows to check the data provided by a finite-volume RANS numerical model of the flow, where turbulent effects are taken into account by a RNG k–ε turbulence model. The obtained numerical velocity field is then used as input for an Eulerian–Lagrangian numerical model for the dissolved oxygen balance equation, where diffusion effects are computed by a random walk model based on the turbulent kinetic energy field. The bubble size distribution of the jet, determined by a photographic technique, is taken into account in the numerical model in order to calculate the mass transfer from the bubbles to the liquid. Several mass transfer models are implemented and tested in order to perform a sensitivity analysis. The obtained numerical results are compared with experimental measurements of dissolved oxygen concentration inside the lab-scale model during a transient. Results show that the developed numerical technique yields an accurate reproduction of the measured oxygen concentration in time and can be applied to analyse the behaviour of jet systems for oxygenation and mixing in activated sludge plants.

Behavior comparison for biomass observers in batch processes

ABSTRACTOn‐line estimation of biomass concentration in batch biotechnological processes is an active area of research because normally, the biomass is the desired process product output, and also because it is necessary for control purposes to replace the unavailable biomass concentration measurements with reliable and robust on‐line estimations. This work presents five different alternatives to face the problem of biomass estimation in a particular batch bioprocess (δ‐endotoxins production of Bacillus thuringiensis), namely: a phenomenological estimator based on dissolved oxygen balance, an extended Kalman filter estimator, a Gaussian process regression‐based estimator, an artificial neural networks‐based estimator, and finally, an estimator based on information fusion by a decentralized Kalman filter. Each proposed biomass estimation method has its own advantages and drawbacks according to their ability to take into account the model uncertainties and the measurement errors. First, the design techniques of these five biomass estimators are exposed, and finally, the behavior of each estimation method is compared. The availability of efficient biomass estimators is of great importance for engineers because, on the one hand, it allows developing new control strategies for other bioprocess variables such as for instance: the growth rate of the microorganism, the dissolved oxygen concentration, and so on. On the other hand, it is also important to improve the performance of the bioprocess optimization procedure. This work also aims to show the evolution on biomass estimation techniques from classical to more contemporary approaches, such as the design based on neural networks and Gaussian processes regression. © 2013 Curtin University of Technology and John Wiley & Sons, Ltd.

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.

Water quality modelling for ephemeral rivers: Model development and parameter assessment

Summary River water quality models can be valuable tools for the assessment and management of receiving water body quality. However, such water quality models require accurate model calibration in order to specify model parameters. Reliable model calibration requires an extensive array of water quality data that are generally rare and resource-intensive, both economically and in terms of human resources, to collect. In the case of small rivers, such data are scarce due to the fact that these rivers are generally considered too insignificant, from a practical and economic viewpoint, to justify the investment of such considerable time and resources. As a consequence, the literature contains very few studies on the water quality modelling for small rivers, and such studies as have been published are fairly limited in scope. In this paper, a simplified river water quality model is presented. The model is an extension of the Streeter–Phelps model and takes into account the physico-chemical and biological processes most relevant to modelling the quality of receiving water bodies (i.e., degradation of dissolved carbonaceous substances, ammonium oxidation, algal uptake and denitrification, dissolved oxygen balance, including depletion by degradation processes and supply by physical reaeration and photosynthetic production). The model has been applied to an Italian case study, the Oreto river (IT), which has been the object of an Italian research project aimed at assessing the river’s water quality. For this reason, several monitoring campaigns have been previously carried out in order to collect water quantity and quality data on this river system. In particular, twelve river cross sections were monitored, and both flow and water quality data were collected for each cross section. The results of the calibrated model show satisfactory agreement with the measured data and results reveal important differences between the parameters used to model small rivers as compared to those for large rivers. Additionally, these results appear related to the different roles played by physical–chemical–biological processes in small rivers as compared to larger systems.

A hydrodynamic water quality model for propagation of pollutants in rivers

Numerical modelling can be a useful tool to assess a receiving water body's quality state. Indeed, the use of mathematical models in river water quality management has become a common practice to show the cause-effect relationship between emissions and water body quality and to design as well as assess the effectiveness of mitigation measures. In the present study, a hydrodynamic river water quality model is presented. The model consists of a quantity and a quality sub-model. The quantity sub-model is based on the Saint Venant equations. The solution of the Saint Venant equations is obtained by means of an explicit scheme based on space-time conservation. The method considers the unification of space and time and the enforcement of flux conservation in both space and time. On the other hand, the quality sub-model is based on the advection dispersion equation. Particularly, the principle of upstream weighting applied to finite difference methods is employed. This method enable us to reduce the numerical dispersion avoiding oscillation phenomena. The optimal weighting coefficient was calculated on the basis of the mesh Peclet number. Regarding the quality processes, the model takes into account the main physical/chemical processes; these are degradation of dissolved carbonaceous substances, ammonium oxidation, algal uptake and denitrification, dissolved oxygen balance, including depletion by degradation processes and supply by physical reaeration and photosynthetic production. To properly simulate the river water quality, four state variables were considered: DO, BOD, NH4, and NO. The model was applied to the Savena River (Italy), which is the focus of a European-financed project for which quantity and quality data were gathered. A sensitivity analysis of the model output compared to the model input or parameters was carried out.

Water Quality Modeling and Dissolved Oxygen Balance in Streams: A Point Source Streeter‐Phelps Application in the Case of the Harsit Stream

AbstractThe Harsit Stream flowing into the Black Sea is an important watershed in the northeastern part of Turkey. The monthly averages of dissolved oxygen, carbonaceous biochemical oxygen demand, temperature, pH, total suspended solids, total phosphorus and total nitrogen were obtained for the water samples taken from the Tekke, Akcakale and Haciemin sites of the Harsit Stream. Water quality parameters were analyzed and evaluated according to the WHO standards and the Turkish Water Pollution Control Regulation. Initially, the variations in the dissolved oxygen profile were determined from dissolved oxygen, temperature and carbonaceous biochemical oxygen demand measurements by using the point source Streeter‐Phelps equation. Critical dissolved oxygen deficit values were calculated for the monthly average from January–December 2005, which are below the limit value (4 mg L–1) excluding April (7.26 mg L–1) and May (5.98 mg L–1) in the Harsit Stream, resulting in it having second class water quality in terms of dissolved oxygen concentration, temperature, pH and biochemical oxygen demand. It is also seen that the minimum dissolved oxygen limit value (8 mg L–1), which is a desired quantity for drinking water, is under the limit value for all months in the case of the water mixture. In particular, during the summer months, the consumption speed of oxygen is greater than the production speed of oxygen with increasing temperature and decreasing discharge, and negative values (anoxia) of dissolved oxygen sag are seen. These situations call for significant precautions and treatment criteria.

Numerical modeling of water quality and sediment related processes

A three-dimensional water quality model (CCHE3D_WQ) was developed for simulating temporal and spatial variations of water quality with respect to phytoplankton, nutrients, and dissolved oxygen. Four major interacting systems were simulated, including phytoplankton dynamics, nitrogen cycle, phosphorus cycle, and dissolved oxygen balance. The effects of suspended and bed sediment on the water quality processes were also considered. The model was verified using analytical solutions for the transport of non-conservative substances in open channel flow, and then calibrated and validated by applying it to the study of the water quality of a natural shallow oxbow lake. The simulated time serial concentration of phytoplankton (as chlorophyll) and nutrients were generally in good agreement with field observations. Sensitivity studies were then conducted to demonstrate the impacts on water quality due to varying nutrients and suspended sediment loads to the chlorophyll concentration.

The effect of complexity on parameter sensitivity and model uncertainty in river water quality modelling

Snowling and Kramer [2001. Evaluating modelling uncertainty for model selection. Ecol. Modell. 138(1), 17–30] proposed a hypothesis stating that as a model becomes more complex in terms of increased number of parameters and variable, the error between simulations and measurements decreases and the overall model sensitivity increases. In this paper, the hypothesis is tested using a river water quality model of the lower course of the Saale river, Germany. The eutrophication module of WASP5 (5th version of Water quality Analysis Simulation Program), which was developed by the U.S. EPA, was implemented. The model allows the complexity of the dissolved oxygen balance and dynamics in a water body to be easily varied from a simple Streeter–Phelps approach of dissolved oxygen–biological oxygen demand (DO–BOD) interaction to more complex phytoplankton–nutrient dynamics. Five complexities were modelled and plotted against a normalized root-mean-squared error and a normalized global sensitivity. The results verify the hypothesis. A utility function, which minimizes both error and sensitivity, shows that the most complex model is not necessarily the most “useful”. In the case of the lower Saale river, modelling only the phytoplankton–nutrient cycle has almost as much descriptive power as when the complexity is increased by adding the DO–BOD cycle. The low sensitivity of the parameters linking the two cycles also indicates their weak coupling in the Saale river system. This verifies the observations that the source of the organic loading in the Saale has shifted from primary (point load) to secondary (phytoplankton) origin.

Effects of Ni, Cr, Hg, Cu, Zn, Al on the dissolved oxygen balance of streams

Inorganic metals besides their direct toxic effects, carry the potential of causing serious variations on existing ecosystems in receiving waters. Self purification mechanism is vital for the continuity of the existing micro and macro living organisms in the streams. This mechanism is effected from the existence of metals. In this study, interferences of HgCl 2, HgSO 4, Ni(NO 3) 2, CrCl 3, CuSO 4 · 5H 2O, K 2Cr 2O 7, ZnSO 4 · 7H 2O and Al 2(SO 4) 3 · 18H 2O metal compounds on respirometric BOD and related effects on the self purification, are investigated with the representative formations of DO deficit curves. In the presence of these metals, streamwater BOD parameters and related DO deficit curve formations are significantly effected.

Three-Dimensional Ecological-Eutrophication Model for Singapore

A 3D multilevel eutrophication model has been developed and applied to the tropical coastal waters of Singapore. The model considers the nitrogen, phosphorus, and carbon cycles; phytoplankton and zooplankton dynamics; and dissolved oxygen balance in the water column coupled to benthic processes and is driven by a 3D multi-level hydrodynamic model. The eutrophication model was calibrated with field data obtained from the Southwest Monsoon in August 1998 and subsequently validated using data from the Northeast Monsoon in December 1998. Predictions of nutrient and phytoplankton concentrations from the model simulation agreed well with the observed data. The model results show that the coastal waters of Singapore are relatively well-mixed and differences in concentration with depth for all state variables are generally <20%. In the Singapore Strait, horizontal spatial differences for all the variables are generally <40%. In the Southwest Monsoon, slightly larger values for phytoplankton and dissolved oxygen but smaller nutrient values are found in the eastern region of the Singapore, compared to the west. The reverse trend is found in the Northeast Monsoon.

Dissolved Oxygen Balance Model for Neris

We consider a dissolved oxygen balance model for Neris, which includes biochemical oxygen demand, nitrification, sedimentation, algae respiration and photosynthesis. The load from point sources, tributaries and distributed sources are taken into account. Long-term systematic components such as drift and seasonal components are analysed by applying time series analysis.&#x0D; The model is adapted according to the State Environmental Monitoring, and source data of controlled pollution covering the period 1978-1998.

Refinement of predictive reaeration equations for a typical Indian river

AbstractDissolved oxygen mass balance has been computed for different reaches of River Kali in western Uttar Pradesh (India) to obtain the reaeration coefficient (K2). A total of 270 field data sets have been collected during the period from March 1999 to February 2000. Eleven most popular predictive equations, used for reaeration prediction and utilizing mean stream velocity, bed slope, flow depth, friction velocity and Froude number, have been tested for their applicability in the River Kali using data generated during field survey. The K2 values computed from these predictive equations have been compared with the K2 values observed from dissolved oxygen balance measurements in the field. The performance of predictive equations have been evaluated using error estimation, namely standard error (SE), normal mean error (NME), mean multiplicative error (MME) and correlation statistics. The equations developed by Smoot and by Cadwallader and McDonnell showed comparatively better results. Moreover, a refined predictive equation has been developed using a least‐squares algorithm for the River Kali that minimizes error estimates and improves correlation between observed and computed reaeration coefficients. Copyright © 2001 John Wiley &amp; Sons, Ltd.

Prediction of dissolved oxygen concentration along sanitary sewers

The oxygen balance in wastewater collection systems is important in respect to the degree of biological oxidation that occurs within the stream and in respect to the control of septicity and its effects. In this paper, a simple mathematical model is presented, in order to predict dissolved oxygen concentration profiles along sanitary sewers. The mathematical model was developed based on an analytical solution of the simple differential equation of dissolved oxygen balance in sewers, and includes an empirical expression for prediction of dissolved oxygen transfer to the slime layer on the pipe walls. Because the factors controlling dissolved oxygen balance in sewers are so complex, it would be unrealistic to expect, that with this rather simple model, dissolved oxygen concentrations can be accurately predicted. Nevertheless, it is reasonable to suppose that the predictions may be adequate for some design and operation purposes.

Prediction of dissolved oxygen concentration along sanitary sewers

The oxygen balance in wastewater collection systems is important in respect to the degree of biological oxidation that occurs within the stream and in respect to the control of septicity and its effects. In this paper, a simple mathematical model is presented, in order to predict dissolved oxygen concentration profiles along sanitary sewers.The mathematical model was developed based on an analytical solution of the simple differential equation of dissolved oxygen balance in sewers, and includes an empirical expression for prediction of dissolved oxygen transfer to the slime layer on the pipe walls.Because the factors controlling dissolved oxygen balance in sewers are so complex, it would be unrealistic to expect, that with this rather simple model, dissolved oxygen concentrations can be accurately predicted. Nevertheless, it is reasonable to suppose that the predictions may be adequate for some design and operation purposes.