Guest Column | January 25, 2017

A Comprehensive Software Tool For Assessing Risk At Wastewater Treatment Plants


By Lingfeng Wang

Understanding risk is the first step to combating system failure and protecting the public and the environment from unsafe water.

With climate change and increasing occurrences of extreme weather, water resources are becoming critically important to support human lives and societal development. Water recycling and reclamation is an essential way to sustain our water resources. Wastewater treatment plants (WWTPs) are among the most critical infrastructures that play a key role in reclaiming water resources. Thus, the reliable operation of WWTPs is of critical importance. It is a pressing task to assess the reliability of WWTPs in an objective manner for making judicious decisions in budget allocation, maintenance planning, and staff projections. For this purpose, a probabilistic reliability evaluation software tool is developed to comprehensively quantify the reliability of WWTPs. By hedging against uncertainties, the tool is designed to enable informed decision making in asset management for massive WWTPs with aging facilities and limited budgets. The major novelties of this software tool are twofold: (1) the holistic modeling of WWTP reliability and resiliency considering a variety of random uncertainties; and (2) the quantitative analysis of the effluent water quality risk. Specifically, the reliability and resiliency evaluation method considers the long-term WWTP influent profile, the mechanical failures of the WWTP components, and the influence of the electric power supply. Sequential Monte Carlo simulation and fault tree analysis are applied to sample the long-term system states and calculate the available wastewater treatment capacity related to the sampled system states. Additionally, the effluent quality risk in the WWTP is quantified by considering various kinds of factors, such as mechanical failures and test sensor failures related to effluent quality.

Probabilistic Reliability/Resiliency Evaluation Of WWTPs
The reliability of a WWTP indicates its capability to perform wastewater treatment of the required amount and quality. Reliability analysis of a WWTP is beneficial to objectively quantifying the WWTP’s capacity to treat wastewater and providing valuable information about the adequacy of wastewater treatment facilities. The reliability of WWTPs is influenced by various factors, including the time-varying influent to WWTP, random failures of mechanical components, availability of its electricity supply system, and human errors. Considering the aging wastewater reclamation facilities in the U.S., it is highly necessary to develop a comprehensive method to quantitatively assess the reliability of WWTPs by accounting for all these variables and uncertainties, but performing an objective reliability evaluation for such complex systems is quite a challenging task. Conventionally, deterministic reliability criteria were used to indicate the overall system reliability of critical infrastructures. However, the reliability characteristics of system components, such as the widely used availability parameters, mean time to failure (MTTF) and mean time to repair (MTTR) are, in fact, stochastic in nature. Deterministic criteria fail to account for these stochastic characteristics, and therefore probabilistic reliability evaluation methodologies are preferred in order to more comprehensively evaluate the reliability performance of critical systems or infrastructures with uncertainties. In light of these considerations, this decision tool deploys a probabilistic methodology to perform reliability evaluation for WWTPs. A diverse set of probabilistic reliability indices is defined and calculated to quantify the WWTP reliability from different perspectives, including the Expected Wastewater Treatment Capacity, Percentage of Untreated Wastewater, Failure Probability of Wastewater Treatment, Expected Wastewater Not Treated, Probability of Insufficient Capacity Margin, Loss of Load Frequency, Loss of Load Duration, and Probability of Insufficient Capacity Margin.

Additionally, quantifying the ability of the WWTP to recover from the failure state to the normal state is also much needed for WWTP designers and operators. In this project, the WWTP’s capability of transitioning from the failure state to the normal state is quantified in the resiliency analysis. The term of resiliency measures how quickly the WWTP could bounce back to the normal state after a major failure occurs. There are various definitions of resiliency in different contexts, as it is an evolving concept. In this software tool, the resiliency of a WWTP is characterized by the average recovery rate (ARR), which is the probability that the WWTP being in a failure state recovers to a success state within a specified time period.

Effluent Quality Risk Analysis
The development of modern industry, expansion of populations, and the increasing coverage of the domestic water supply have resulted in a substantial increase in wastewater production. In some countries, the WWTP effluent is the water source for the drinking water system and sometimes is directly used for agriculture. There is an increasing need for good quality water; therefore, the wastewater should be adequately treated and the effluent quality must comply with the discharge standard. Insufficiently treated wastewater may lead to environmental and public health issues.

The main purpose of this function of the software tool is to perform an effluent quality risk assessment considering the reliability of WWTPs. Based on the main fault tree built for effluent quality risk assessment, the probability that a WWTP may have a water quality problem can be calculated. The emphasis in wastewater treatment is placed on guaranteeing that the possible pollutants that could be contained in the wastewater are removed or inactivated to a safe level. The overall removal or inactivation efficiency of the biological hazards is determined based on the fault tree model built for the WWTP. The fault tree analysis (FTA) considers possible causes of the effluent quality problem, including mechanical failures, electrical failures, and other possible causes (e.g., human errors, insufficient contact time, etc.).

Based on the treatment plant procedure, the removal or inactivation efficiency of the biological hazards during each process in the WWTP can be studied. Typical pollutants are defined for treated discharge quality assessment, including biochemical oxygen demand (BOD), chemical oxygen demand (COD), nitrogen, phosphorus, oil and grease, suspended solids, and coliform bacteria. The overall treatment procedure of a WWTP is divided into three different types: physical treatment (primary treatment), biological treatment (secondary treatment), and chemical treatment (tertiary treatment or disinfection). Based on the function of each treatment process, the pollutants are linked to one or several treatment processes for removal or inactivation. In the fault tree analysis, the quality risk assessment of each pollutant is analyzed separately, and the overall quality risk assessment of the WWTP is determined based on the results of each part.

For the quality risk assessment of each pollutant, three main conditions are considered: the treatment process failure, the facility monitoring system failure, and the effluent quality test sensor failure. The treatment process failure mainly considers the mechanical failure of the treatment equipment and other causes (e.g., insufficient or excessive chlorine, insufficient contact time). The monitoring system failure indicates the failure of the monitoring equipment that is used for fault detection and diagnosis in each treatment process (e.g., the supervisory control and data acquisition [SCADA] system). Effluent quality test sensor failure means the failure of sensors that are used for effluent water quality tests.

A set of effluent water quality risk metrics can be defined and calculated by the software tool, including the Probability of Excessive Suspended Solids; Probability of Excessive Oil and Grease; Probability of Excessive BOD, Nitrogen, Phosphorus; Probability of Excessive COD and Coliform Bacteria; Failure Probability of WWTP Effluent Quality Test Sensor; and Probability of Unsatisfied Effluent Quality.

More planners and regulators rely on risk-based decision making. This unique, versatile software tool is believed to be a useful addition to the existing asset management tools in the current market for facilitating informed decisions on risk reduction in the evolving wastewater sector.

This project was supported by National Science Foundation Industry/ University Cooperative Research Center on Water Equipment & Policy located at University of Wisconsin-Milwaukee and Marquette University.

About The Author
Dr. Lingfeng Wang, Ph.D., is an associate professor in the Department of Electrical Engineering and Computer Science at the University of Wisconsin-Milwaukee, where he directs the Research Laboratory of Trustworthy Cyber-Physical Systems and Infrastructures. His research is focused on addressing challenging issues on reliability, cybersecurity, and resiliency for contemporary critical infrastructures (e.g., drinking water distribution networks and wastewater reclamation facilities) from the perspectives of cyber-physical systems and waterenergy nexus. Email: