Risk Assessment of Using Urban Treated Wastewater for Agricultural and Industrial Application with Bayesian Networks Model

Document Type : Research Paper


1 MSc. Student of Water Resources Engineering, Dept. of Water Engineering, College of Aburaihan, University of Tehran, Pakdasht, Tehran, Iran

2 Assoc. Prof., Dept. of Water Engineering, College of Aburaihan, University of Tehran, Pakdasht, Tehran, Iran

3 Assist. Prof., Dept. of Water Engineering, College of Aburaihan, Pakdasht, University of Tehran, Tehran, Iran


Urban treated wastewater is a useful resource for allocation to various non-potable reuses because its quantity and quality can be controlled and managed by humans, but it has its limitations. Improper use of these resources without treatment can lead to environmental and health risks and, as a result, can cause social dissatisfaction and sometimes economic problems. This paper examines the risks of limitations associated with the use of treated wastewater. Qualitative information of 26 wastewater treatment plants in the country was collected to create a proper database for risk assessment of using treated wastewater for agricultural and industrial application by taking into account the major factors such as environmental, socio-cultural, economic, and technical. For risks calculation, multiple risks associated with the use of treated wastewater were identified by reviewing various available publications and categorizing them according to the above four risk factors. Hierarchical networks were prepared to calculate the main and the overall risk. Bayesian networks were used to model risk-based structures. Bayesian relationships are causal and helpful in expressing the links of the nodes in a probabilistic way. Research results show that the risk of using treated urban wastewater in agricultural sector is generally higher than its application in industrial use, and hence it will make it more suitable and more acceptable for industrial use under current treatment. Bayesian risk-based agricultural and industrial structures were suitably modeled according to R2, RMSE, and MAPE indicators. The average values of the above indicators for the calibration of Bayesian model using treated wastewater in agricultural and industrial risked-based structure were 0.993, 0.202 and 0.637; 0.988, 0.980 and 2.731, respectively. From this study it can be concluded that Bayesian networks have a modeling capability in assessing the risk associated with the use of treated wastewater in agricultural and industrial sectors. The method presented in this paper can be used by the wastewater treatment plant managers and end users when assessing the potential risk of using treated effluent for agricultural and industrial applications.


Abebe, Y., Kabir, G. & Tesfamariam, S. 2018. Assessing urban areas vulnerability to pluvial flooding using GIS applications and bayesian belief network model. Journal of Cleaner Production, 174, 1629-1641.
Anbari, M. J., Tabesh, M. & Roozbahani, A. 2017. Risk assessment model to prioritize sewer pipes inspection in wastewater collection networks. Journal of Environmental Management, 190, 91-101.
Asgarian, M., Tabesh, M. & Roozbahani, A. 2013. Risk assessment of wastewater collection performance using the fuzzy decision-making approach. Journal of Water and Wastewater, 26(4), 74-87. (In Persian)
Aven, T. 2011. On some recent definitions and analysis frameworks for risk, vulnerability, and resilience. Risk Analysis, 31, 515-522.
Cockburn, G. & Tesfamariam, S. 2012. Earthquake disaster risk index for Canadian cities using bayesian belief networks. Georisk: Assessment and Management of Risk for Engineered Systems and Geohazards, 6, 128-140.
Ghorbani Mooselu, M., Nikoo, M. R., Latifi, M., Sadegh, M., Al-Wardy, M. & Al-Rawas, G. A. 2020. A multi-objective optimal allocation of treated wastewater in urban areas using leader-follower game. Journal of Cleaner Production, 267, 122189.
Haimes, Y. 2009. On the complex definition of risk: a systems-based approach. Risk Analysis: An Official Publication of the Society for Risk Analysis, 29, 1647-1654.
Hashemi, S. H., Porasghar, F., Nasrabadi, T., Ramezani, S. & Khoshro Gh. 2011. Guidance of Iran's water resources quality index calculation. Iran’s Department of Environment in Cooperation with Shahid Beheshti University. Pub. Tehran, Iran. (In Persian)
Kalavrouziotis, I., Filintas, A., Koukoulakis, P. H. & Hatzopoulos, J. 2011. Application of multicriteria analysis in the management and planning of treated municipal wastewater and sludge reuse in agriculture and land development: the case of Sparti's wastewater treatment plant, Greece. Fresenius Environmental Bulletin, 20, 287-295.
Kayhanian, M. & Tchobanoglous, G.  2018a. Potential application of reclaimed water for potable reuse: part 1-introduction to potable water reuse. Journal of Water and Wastewater, 116(4), 3-22. (In Persian)
Kayhanian, M. & Tchobanoglous, G.  2018b. Potential application of reclaimed water for potable reuse: part II-technical and regulatory issues. Journal of Water and Wastewater, 116(4), 23-60. (In Persian)
Kayhanian, M. & Tchobanoglous, G.  2018c. Potential application of reclaimed water for potable reuse: part III-the path forward and implementation challenges. Journal of Water and Wastewater, 116(4), 61-74. (In Persian)
Khakzad, N., Khan, F. & Amyotte, P. 2011. Safety analysis in process facilities: comparison of fault tree and Bayesian network approaches. Reliability Engineering and System Safety, 96, 925-932.
Pan, Q., Chhipi-Shrestha, G., Zhou, D., Zhang, K., Hewage, K. & Sadiq, R. 2018. Evaluating water reuse applications under uncertainty: generalized intuitionistic fuzzy-based approach. Stochastic Environmental Research and Risk Assessment, 32, 1099-1111.
Pearl, J. 1988. Probabilistic reasoning in intelligent systems: networks of plausible inference, Morgan Kaufmann Publishers Inc. Massachusetts, USA.
Sari, M. D. K., Kristensen, G. H., Andersen, M., Ducheyne, A. A. M. & Lee, W. A. 2017. Water-reuse risk assessment program (WRAP): a refinery case study. Journal of Water Reuse and Desalination, 7, 162-174.
Shakeri, H. & Nazif, S. 2018. Development of an algorithm for risk-based management of wastewater reuse alternatives. Journal of Water Reuse and Desalination, 8, 38-57.
Shariat, R., Roozbahani, A. & Ebrahimian, A. 2018. Risk assessment of the urban runoff collection networks using spatial multi criteria decision-making (case study: district 11 of Tehran). Journal of Water and Wastewater, 30(1), 1-17. (In Persian)
Tabesh, M., Roozbahani, A. & Hadigol, F. 2018a. Risk assessment of water treatment plants using fuzzy fault tree analysis (case study: Jalaliyeh water treatment plant). Journal of Water and Wastewater, 29(4), 132-144. (In Persian)
Tabesh, M., Roozbahani, A., Roghani, B., Faghihi, N. R. & Heydarzadeh, R. 2018b. Risk assessment of factors influencing non-revenue water using Bayesian networks and fuzzy logic. Water Resources Management, 32, 3647-3670.
Taheriyoun, M., Alavi, V. & Ahmadi, A. 2016. Risk analysis of wastewater reuse in agriculture using Baysian network. Amirkabir Journal of Civil Engineering (Amirkabir), 48, 101-109. (In Persian)
Wang, X., Ma, F., Li, C. & Zhu, J. 2015. A Bayesian method for water resources vulnerability assessment: a case study of the Zhangjiakou region, North China. Mathematical Problems in Engineering, 120873.
Yargholi, B., Azimi, M, M. & M. Pormoghadam, M. 2018. Successful experience in using wastewater in eucalyptus cultivation in saline lands of Bushehr province. 2nd National Festival of Water Technologies, Unconventional Waters (Saline and Wastewater), Mashhad, Ferdowsi University of Mashhad, Iran.
(In Persian)