alternative data driven approach for prediction of thermal discharge initial dilution using tee diffusers

Mixing of heated water discharged from outfalls is an efficient and effective method of waste disposal in coastal areas. Discharging the heated water with large quantities of mass flux generally requires multi-port diffusers. In recent years, using numerical models to predict the plume behavior has received attention from many researchers, who are interested in design of outfalls. This study reports the development and application of an artificial neural network model for prediction of initial dilution of multi-port tee diffusers. Several networks with different structures were trained and tested using error back propagation algorithm. Statistical error measures showed that a three layer network with 9 neurons in the hidden layer is skillful in prediction of initial dilution and the outputs are in good agreement [R=0.97] with experimental results. Furthermore, the sensitivity analyses showed that the width of the equivalent slot of the diffuser is the most important parameter in the estimation of initial dilution

Prediction of tidal excursion length in estuaries due to the environmental changes

Tidal excursion is an important parameter that indicates hydraulic and mixing characteristics of estuarine environments. Prediction of the tidal excursion length provides a proper tool for environmental management of estuaries. In this study, the governing equations of the salinity transport were scaled first to recognize the effective dimensionless parameters of tidal excursion length. Then, a laterally averaged two-dimensional numerical model called CE-QUAL-W2 was used as a virtual laboratory to simulate the salinity intrusion length. Existing field data of Limpopo estuary, as a case study, was used for calibration and verification of the model and reasonable agreement was observed between the model results and the field data. Finally, the verified model was used to assess the influences of the governing parameters. The results showed that simple power functions can be used to describe the effects of dimensionless parameters obtained by scaling of the governing equations. As a result, a new formula in form of a power function was derived to predict the tidal excursion length based on the geometric and hydrodynamic characteristics of alluvial estuaries. Comparison of the computed tidal excursion lengths using the derived formula with the observed measurements in several estuaries showed the robustness of the developed formula

Total dissolved solid modeling; Karkheh reservoir case example

The Karkheh Dam Reservoir with a capacity of more than 5 billion cubic meter is the largest dam in Iran with both agricultural and drinking usages. Its hydrodynamics and water quality were modeled and simulated to analyze the total maximum daily load [TMDL] of Total Dissolved Solids [TDS]. The simulation was supported with measurements of temperature and TDS measurements during two years. A laterally averaged 2D model called CE-QUAL-W2 was used for the simulation and hypothetical low height spillways were implemented in the model to avoid drying of the cells in the river branch. The model was then calibrated successfully with an absolute mean error of 0.71 [degree sign] C. More importantly, vertical stratification of temperature and TDS in the Karkheh Reservoir was reproduced by the model throughout year 2000 to 2003. The calibrated model was then used to simulate water quality response to various TDS reduction scenarios. Model results reveal that a 50% reduction of the TDS load is required for a 40% reduction of TDS in the reservoir outlet. The modeling of a complex combination of a steep and long river-reservoir system was another important achievement of this study