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Potential effects of the soluble formation of Gachsaran on reservoir water quality of Persian Dam reservoir
Published in Jean-Pierre Tournier, Tony Bennett, Johanne Bibeau, Sustainable and Safe Dams Around the World, 2019
N. Tavoosi, A. Farokhnia, F. Hooshyaripor
Water quality modeling consists of the use of mathematical equations to simulate the fate and transport processes of pollutants spilled into water bodies. Currently, there are several models for water quality simulation. They are usually applied for water resources planning, industrial and urban wastewater control and evaluation of ecological issues (Fernando Mainardi Fan, 2015). In the current study, the CE-QUAL-W2 model which could be used to perform both hydrodynamic and water quality simulation was selected as the simulating model. The CE-QUAL-W2 model is a 2D laterally-averaged water quality model over 40 years in development. The US Army Corps of Engineers launched the model in 1975. Developments have continued in order to make the model simpler and more practical. In this research the CE-QUAL-W2 model was used to simulate TDS. The model produces detailed output files useful for visual calibration. (Sadeghian and et al, 2017).
Machine learning models with potential application to predict source water quality for treatment purposes: a critical review
Published in Environmental Technology Reviews, 2022
Christian Ortiz-Lopez, Christian Bouchard, Manuel Rodriguez
Finally, we aimed to review the most recent advances in water quality modelling using artificial intelligence and machine learning tools. Although few of the reviewed models were used specifically to forecast raw water quality parameters at DWTPs, we discovered several techniques, methodologies and approaches that can be adapted and applied in order to model raw water quality for treatment purposes. Moreover, because rapidly progressing technologies bring new advances in water quality modelling (monitoring capacities and modelling tools), we can expect that the number of applications will quickly increase in the near future. Also, we hope this work could inspire future research in modelling and forecasting water source quality.
Overview of water quality modeling
Published in Cogent Engineering, 2021
Water quality modeling applies in the estimation and prediction of water pollution using mathematical simulation techniques. An illustrative water quality model consists of a collection of formulations, representing physical mechanisms that determine the position and movement of pollutants in a waterbody (Victoria, 2012). Mathematical water quality modeling is considered as one of the best approaches to estimate the existing pollutant load, pollutant transfer, and upcoming cause–effect relation between pollutant sources and water quality (Nair & Bhatia, 2017). Water quality modeling allows decision and policy makers to choose better, more technically strong solutions among alternative possibilities for water quality management. The models are required to determine better alternatives for solving sustainable water quality problems in the long term. In addition, models are essential to provide a basis for economic analysis, and then decision-makers can use the output to assess the environmental implications of a project and the cost–benefit ratio. The quality of water has been evaluated and modeled with its physical, chemical, and biological characteristics. The relations between the processes related to these characteristics are necessarily multifaceted, and water system managers must pursue to develop a worthy understanding of the main factors and processes that affect the water quality of each local water resource they are responsible for if they are to make correct or improved management decisions (Liu, 2018). The concentrations and distribution of contaminants are influenced by the inactivation of contaminants and some dynamic processes, including diffusion, dispersion, and advection. These processes are closely related to the water flow characteristics, influent and effluent entering and leaving, respectively, the waterbody, wind stress, and temperature stratification (Liu, 2018). Hence, for a better understanding of how the environment and water systems are polluted and to make fruitful decisions and directions, concrete knowledge derived from water quality modeling is significant.