Modeling short-circuiting index as a critical measure of hydraulic efficiency in waste stabilization pond

The simplest yet economical approach to municipal wastewater treatment is the utilization of Waste Stabilization Ponds (WSP). WSPs are relatively simple earthen basins that can be used to treat wastewater; their effectiveness depends on long detention periods and external elements like wind and sunlight. However, the presence of short-circuiting affects its hydraulic efficiency while minimization of short-circuiting will result in higher hydraulic efficiency. Consequently, in the study of WSP, short-circuiting is one of the most crucial factors that can be utilized as a gauge of its hydraulic efficiency. It is a more direct approach compared to other methods; hence, modeling short-circuiting index offers better assessment of its hydraulic performance. When some wastewater particles arrive at the pond's outlet before the anticipated detention time, this is known as short-circuiting. The model in this study was derived from the principle of conservation of mass, obtained by performing a mass balance analysis and solving the resulting two-dimensional equation numerically by the finite difference computational scheme, a scenario that is similar to the practical operation of a field WSP. The data used in the modeling were obtained from the literature of a lab-scale WSP experiment that incorporates short-circuiting index. The summary of the model results was as follows: for a flow of 58.8 ml/s, an average correlation coefficient of 92% and Root-Mean-Square-Error (RMSE) of 0.11 was recorded when compared with the experimental results. Similarly, an average correlation coefficient of 93.5% and RMSE estimate of 0.10 were obtained when the flow was 91.6 ml/s and for the flow of 120.8 ml/s; an average of 91.8% correlation were obtained with the average error of estimate of 0.13. The accuracy of the model in this study suggests a very good fit. It gave an overall average correlation of 92.4% with just 0.11 RMSE on the average. This result is reliable and the model is therefore recommended