Wastewater management is an important approach to protect water resources and it is defined as the collection, treatment, and reuse of wastewater. In wastewater collection network as one of important infrastructures, undesirable performance can lead to different problems. Also, wastewater treatment is a process that depends on different physical and chemical issues and therefore the prediction of factors in wastewater treatment plants is so essential.
On the other hand, urban treated wastewater is a proper resource for allocating to various uses such as agriculture and industry, but it has its limitations. Improper use of these resources can lead to environmental and health risks and as a result, social dissatisfaction and sometimes economic problems. To manage various aspects of wastewater such as those mentioned earlier, the appropriate risk-based modeling approaches as well as prediction tools are required. Recently, using of Bayesian networks (BNs) because of its advantages has rapidly increased in water and environment modeling and management with considering different sources of uncertainty.
Wastewater and environmental engineers and decision makers can effectively use this model as a soft computing skill in prediction and risk assessment applications. In this chapter the fundamentals of BNs modeling, its applications in wastewater systems management, and some practical conclusions are presented and discussed, respectively.
This chapter can be helpful as a guideline for academics, professional engineers, operators, and decision makers to enhance the different wastewater management aspects by applying BN modeling.