Large amounts of degradable wastes including sewage water and agricultural waste or nutrients that stimulate growth of organic matter are discharged into the Caspian Sea. As a result, average Dissolved Oxygen concentration in deeper layers is decreasing. This paper presents distribution and seasonal variations of the concentration of Dissolved Oxygen over the southern shelf of the Caspian Sea adjacent to Iran. The Dissolved Oxygen data were collected down to 200 m depth in two areas in east (off Babolsar in Mazandaran) and west (off Kiyashahr in Gilan) of the southern coast of the Caspian Sea. Surface Dissolved Oxygen concentration varied between 7.1 and 10.9 mg/l. Distribution of Dissolved Oxygen across the depth was in accordance with the temperature structure. The presence of the seasonal thermocline during spring to mid winter significantly affected the concentration of Dissolved Oxygen across the depth. In autumn, in late October, the Dissolved Oxygen concentration ranged between 7.6 mg/l below thermocline at 40 m level to less than 5 mg/l at 160 m level and 4.2 mg/l at 200 m level. In winter in late February, in the upper 100 m mixed layer the Dissolved Oxygen concentration was more than 11 mg/l. The data indicates the possibility of significant decline in Dissolved Oxygen concentration and serious damage to marine life if algal bloom occurs during the strong seasonal thermocline. The results highlight the necessity of certain measures for an effective decrease in the inputs of degradable wastes and plant nutrients into the Caspian Sea.

Water quality aspect with regard to Dissolved Oxygen was studied for a 24 kilometer stretch of Malaprabha River in Karnataka State, India. Main objective of the research was to simulate the predicted Dissolved Oxygen depletion due to the waste load allocation in the river with the ambient observed values of Dissolved Oxygen, and to ascertain the application of mathematical modeling for predicting the Dissolved Oxygen in a mixing zone. The entire river stretch selected for the study was divided in to four stations and water samples were collected from each station, and analyzed for different parameters. Station S1 was purely the upstream of the sewage discharge point and hence reflected the water quality of the river without pollution. Station S2 and downstream stations were the part of mixing zone where the discharged sewage at S2 kept spreading. Dissolved Oxygen levels at these four stations were calculated through mathematical modeling, considering all variables that affect Dissolved Oxygen variation. Further, this predicted Dissolved Oxygen found with the application of mathematical modeling was then simulated with the actual observed values of Dissolved Oxygen in these four stations. The results were highly encouraging, with the predicted values almost agreeing with the observed values. Thus the application of such mathematical modeling may be useful for a river stretch where water pollution due to the discharge of effluents is expected, and will help the engineers in arriving at a proper waste-load allocation for the river.

A mathematical model was developed to predict the effects of wind speed, light, pH, Temperature, Dissolved carbon dioxide and chemical Oxygen demand (COD) on Dissolved Oxygen (DO) in fish ponds. The effects of organic feeds, aeration and fish activity were added to the model developed by Kayombo et al. for Waste Stabilization Ponds (Ecological Modeling 127(2000): 21-31) to reflect the situation in fish ponds. Model calibration and validation was done by use of average DO, pH, temperature, COD, CO2 and algae biomass data measured from RETCO fish ponds in Dar es Salaam; and light intensity data were adopted from Kayombo et al. (2000). Model results showed a linear relationship between simulated DO and measured DO in fish pond (r2 = 0. 87) for model calibration and (r2= 0.88) for model validation. Simulation results also showed a general decrease of DO with time in 13 days by 28% and 38% for first and second batch, respectively. Thus, the model developed in this study could be used to predict the DO dynamics in fish ponds. Based on the model results, successful cultivation of healthy fish may require that retention time for water in the fish pond be 10 days.

Water is one of the most essential elements in nature that forms the basis of human life and contributes to the economic growth and development of societies. Safe water is closely related to environmental health and activities. The lives of all the animals on our planet depend on water and Oxygen. Moreover, sufficient Dissolved Oxygen (DO) is crucial for the survival of aquatic animals. In the present research, temperature (T) and flow (Q) variables were used to predict DO. The time series were monthly and data were related to the Cumberland River in the southern United States from 2012 to 2022. Support Vector Regression (SVR) was employed for prediction of the model in both standalone and hybrid forms. The employed hybrid models consisted in SVR combined with metaheuristic algorithms of Chicken Swarm Optimization (CSO), Social Ski-Driver (SSD) optimization, and the Algorithm of the Innovative Gunner (AIG). Pearson Correlation Coefficient (PCC) was utilized to select the best input combination. Box plots and Taylor diagrams were employed in the interpretation of the results. It was observed that all the four hybrid models achieved better results. Also, according to the evaluation criteria, among the models used, the following were found: SVR-AIG with the coefficient of determination (R2 = 0.963), the root mean square error (RMSE =0.644 mg/l), the mean absolute value of error (MAE = 0.568 mg/l), the Nash-Sutcliffe coefficient (NS = 0.864), and bias percentage (BIAS = 0.001).

Water pollution is a major global problem that requires constant evaluation and revision of water resources policy at all levels. Dissolved Oxygen (DO) is one of the most important indicators of water quality. In the present study, the water quality parameter of Dissolved Oxygen using intelligent Long Short-Term Memory (LSTM) method based on discrete wavelet transform (DWT) and Complementary Ensemble Empirical Mode Decomposition (CEEMD) pre-processor methods in both temporal and spatial modes. It was investigated in five consecutive stations on the Savannah River. The results of analysis of models showed the ability and high efficiency of the method used in estimating the amount of Dissolved Oxygen in water. On the other hand, pre-processor methods improved the results. It was also observed in the investigations that the results of analysis based on wavelet transformation in spatial modeling reduced the RMSE error by two percent and also the empirical mode decomposition in temporal modeling by 15 percent. The best evaluation for test data was obtained using the empirical mode decomposition in temporal modeling corresponding to the previous day with values ​​of DC=0.977, R=0.988 and RMSE=0.017. Also, in the spatial modeling to estimate Dissolved Oxygen in the third station, it was found that the results obtained from the inputs of the Dissolved Oxygen parameter one day before the second station and two days before the first station have the best results.

Background: Zayandeh-Rood River is the only perennial river in the central basin of Iran that has fresh water. Water from this source is used for drinking, industrial and agricultural purposes. Drinking water is extracted from upstream portion (upstream of Chamaseman Dam) of Zayandeh-Rood River and therefore its quality is very important. Due to growth of population, industry and other factors, its management needs powerful tools such as MIKE model 11 to be able to simulate water quality and quantity.Methods: In this research MIKE model 11 was used to simulate water quality and quantity in Zayandeh-Rood River from Tanzimi Dam to Kalleh Bridge (120 Km distance). For this purpose samples were taken at four hydrometery stations along the river during five months. At each sampling location DO, pH, EC, BOD1, 3, 5, 7, NH4, NO3, PO43-, COD and temperature were measured. Then the model was calibrated and its accuracy was investigated. The model results and measurements were statistically compared and their correlation was determined using Pearson correlation test. Also water quality in Zayandeh-Rood River was simulated under two scenarios for the next 25 years. Pearson correlation indicated an appropriate correlation (approximately r=0.9) between the model results and the field measurements.Findings: The findings of this research revealed that the concentration of PO43-, BOD, COD, and NH4.NO3 from Tanzimi Dam to Kalleh Bridge station exceeds surface water standards. The findings for the next 25 years scenarios indicated that due to the population and industries growth, some parameters’ concentration will be increased. This will affect both Zayandeh-Rood ecosystem and purifying drinking water by Baba Shekhali Water Treatment Plant.Conclusion: Also the findings indicated that although DO is within the standard level but it may affects some type of fish production and migration.

Urban and industrial wastewaters are considered as the most contaminant of surface water. Entrance of these pollutants to the river reduces the concentration of Dissolved Oxygen and aquatic life will be threatened. So, one of the main qualitative characteristics of water resources management is the concentration of Dissolved Oxygen. The base of the developed model in this investigation is the convection-diffusion equation in soil. Terms of production and decay of Dissolved Oxygen were added to this equation. The final equation was discretized using the finite difference method with the implicit scheme. With applying the initial and boundary conditions, the equation set was solved by the Thomas algorithm. The calculations were done by programming in the MATLAB software. For the calibration and validation of the model, data obtained from two reaches of Zayanderoud River, including steel melt and Mobarakeh Steel factories, were used. The temporal and spatial variations of the Dissolved Oxygen were plotted and compared with the real data and the results of the MSP and CSP models. The results showed that the concentration of the Dissolved Oxygen could be well predicted through solving convection-diffusion equation with introducing two terms for the decay and production of Oxygen. The comparison between the results of the model and two other models showed that the model led to better results in comparison to the MSP and CSP models.

Chitgar artificial lake, located in urban District 22 of Tehran Municipality, northwest of Tehran, has a volume of 10 million m3, an average depth of 10m and an area of 224 hectares and is Irans largest man-made lake. The most important water resources of the district, which can support the lake, are the Kan River, the districts runoff, the middle part watersheds runoff, and the treated wastewater of the urban region. In this study, the way to take water from each resource individually or together are discussed, and twelve different choices of resources to maintain the lake water are considered. In this research, WQRRS model has been run to each of the 12 aforementioned choices individually to predict phosphorus concentration as a nutrient in the lake for each one. This simulation has been done during a five-year period, which is assumed to be a typical period of time. In this way, it would be possible to predict the throphic level of the needed input data to run the model: quality factors, meteorological data, and geometrical characteristics of the reservoir, the characteristics of inflow and also the needed coefficients for the model. These data have been collected from hydrometric and meteorological stations of the region and also from the results of other studies. After running the model, the simulation results show that choices 2 and 4 are the best resources to support the lake water and have the fewest difficulties in regard the eutrification problem. The results also show that DO concentration in Kan River is at an acceptable level.