Instream water quality management encompasses field monitoring and utilisation of mathematical models. These models can be coupled with optimisation techniques to determine more efficient water quality management alternatives. Among these activities, wastewater treatment plays a crucial role. In this work, a Streeter-Phelps dissolved oxygen model (DO) is implemented in a semi-hypothetical Upper Olifants River system to forecast instream dissolved oxygen profiles in response to different wastewater discharge scenarios. A mixed integer programming (MIP) numerical approach was used in the simulation and determination of the best treatment regimen to meet the instream DO standard at the minimum cost for the chosen river catchment. The Olifants River catchment modelled in this study features 9 wastewater treatment plants. Three treatment levels were evaluated for biochemical oxygen demand (BOD) and the impact was evaluated at specific measuring points (checkpoints) within the river system. Using this model, it was demonstrated that water quality standards can be met at all monitoring points at a minimum cost by simultaneously optimising treatment levels at each treatment plant.
In this study, basic interpolation and machine learning data augmentation were applied to scarce data used in Water Quality Analysis Simulation Programme (WASP) and Continuous Stirred Tank Reactor (CSTR) that were applied to nitrogenous compound degradation modelling in a river reach. Model outputs were assessed for statistically significant differences. Furthermore, artificial data gaps were introduced into the input data to study the limitations of each augmentation method. The Python Data Analysis Library (Pandas) was used to perform the deterministic interpolation. In addition, the effect of missing data at local maxima was investigated. The results showed little statistical difference between deterministic interpolation methods for data augmentation but larger differences when the input data were infilled specifically at locations where extrema occurred.
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