Study the Effect of Precipitation on the Performance of Wastewater Treatment Plant using KSOM

The main area of concern in water and wastewater engineering is the treatment system that involves the transportation, disposal and purification of water. There is a need for extra care in water treatment as it leads to disease outbreak if it is not being handled properly. Therefore, with so many factors involved in treatment system, it becomes a very complicated process for the engineers where they have to monitor all the aspect of the treatment system in order to avoid any faults. One of these factors is precipitation which contributes a significant input to the wastewater treatment system. Hence, to analyze the effects of precipitation, self-organizing map (SOM), an unsupervised artificial neural network, is used to study the effects of precipitation on the performance of wastewater treatment plant. This paper used data collected from a wastewater treatment plant in San Diego, California for a period of 5 years. The results of the case study showcased a tool which was able to recognize the relationship among different parameters with rain in the wastewater treatment system. The 2D component plane of the SOM showed a positive correlation of rain with nitrates, pH and flow while a negative correlation with the Biochemical chemical demand (BOD), Chemical oxygen demand (COD), Suspended Solids (SS), ammonia and phosphate. Finally, this study shows the merits and disadvantages of monitoring the treatment system with SOM tool.