Development of an algorithm for risk-based management of wastewater reuse alternatives

Due to water resources limitations, special attention has been paid to wastewater reuse in recent years. The risks associated with wastewater reuse alternatives should be considered in decision-making. Even when selecting the alternative with the least risk, risk management issues are of high importance. This study aims to develop an algorithm for risk-based management of wastewater reuse alternatives. This algorithm uses a three-step risk assessment and management approach. Risks are identified, then risks of alternatives are assessed, and, finally, risk management measures are proposed for risk reduction in the selected alternative. In risk identification, economic, social, health, and environmental aspects are taken into account. In risk assessment, its three components of likelihood, severity, and vulnerability are considered through a fuzzy inference system. Alternatives are prioritized based on calculated risks using a fuzzy VIKOR method. A case study is presented in which the proposed algorithm is used to select the best alternative for reuse of treated wastewater from Ekbatan Town, located in the western part Tehran in Iran. The results showed that the proposed approach provides the users with an easier understanding of risks and increases the relative confidence of decision-makers about the selection of the best alternatives for wastewater reuse and their risk control methods.

[1]  Blanca Jiménez,et al.  Water Reuse: An International Survey of current practice, issues and needs , 2015 .

[2]  M. Zarghami,et al.  Risk-based evaluation of wastewater treatment projects: A case study in Niasar city, Iran , 2014 .

[3]  Massoud Tabesh,et al.  Integrated risk assessment of urban water supply systems from source to tap , 2013, Stochastic Environmental Research and Risk Assessment.

[4]  P. Drechsel,et al.  Social and Cultural Dimensions in Wastewater Use , 2015 .

[5]  S. Baas,et al.  Disaster risk management systems analysis : a guide book , 2008 .

[6]  Seth D. Guikema,et al.  Risk classification and uncertainty propagation for virtual water distribution systems , 2009, Reliab. Eng. Syst. Saf..

[7]  Risk Assessment on Population Health , 2007 .

[8]  Jacques Ganoulis,et al.  Risk analysis of wastewater reuse in agriculture , 2012, International Journal Of Recycling of Organic Waste in Agriculture.

[9]  Jamie Bartram,et al.  Assessment of risk and risk management for water-related infectious disease , 2001 .

[10]  Junying Chu,et al.  Wastewater reuse potential analysis: implications for China's water resources management. , 2004, Water research.

[11]  Ziying Tang,et al.  Comparison of Fuzzy Membership Functions for Value of Information Determination , 2014, MAICS.

[12]  Alinezhad Alireza,et al.  Sensitivity Analysis in the QUALIFLEX and VIKOR Methods , 2012 .

[13]  Challenges in defining acceptable risk levels , 2006 .

[14]  Zhe Tian,et al.  Application of a trapezoidal fuzzy AHP method for work safety evaluation and early warning rating of hot and humid environments , 2012 .

[15]  A. Olander,et al.  Risk Assessment for South Africa’s first direct wastewater reclamation system for drinking water production , 2011 .

[16]  Muhammad A. Al-Zahrani,et al.  Fuzzy synthetic evaluation of treated wastewater reuse for agriculture , 2014, Environment, Development and Sustainability.

[17]  B. Tchórzewska-Cieślak,et al.  Fuzzy failure risk analysis in drinking water technical system , 2011 .

[18]  J. Buckley,et al.  Fuzzy hierarchical analysis , 1999, FUZZ-IEEE'99. 1999 IEEE International Fuzzy Systems. Conference Proceedings (Cat. No.99CH36315).

[19]  J. Ganoulis Integrated Risk Analysis for Sustainable Water Resources Management , 2004 .

[20]  S. Chowdhury Decision making with uncertainty: an example of water treatment approach selection , 2012 .

[21]  Takashi Asano,et al.  Milestones in Water Reuse: The Best Success Stories , 2012 .

[22]  Jacques Ganoulis,et al.  Risk Analysis of Water Pollution , 2009 .

[23]  Eun-Sung Chung,et al.  Fuzzy VIKOR approach for assessing the vulnerability of the water supply to climate change and variability in South Korea , 2013 .

[24]  Hisao Ishibuchi,et al.  A simple but powerful heuristic method for generating fuzzy rules from numerical data , 1997, Fuzzy Sets Syst..

[25]  Amit Kumar,et al.  Ranking of Generalized Trapezoidal Fuzzy Numbers Based on Rank, Mode, Divergence and Spread , 2010 .

[26]  A. Mubarak,et al.  Effect of incorporation of some wastes on a wheat-guar rotation system on soil physical and chemical properties , 2012, International Journal Of Recycling of Organic Waste in Agriculture.

[27]  Shyi-Ming Chen NEW METHODS FOR SUBJECTIVE MENTAL WORKLOAD ASSESSMENT AND FUZZY RISK ANALYSIS , 1996 .

[28]  Serafim Opricovic,et al.  Fuzzy VIKOR with an application to water resources planning , 2011, Expert Syst. Appl..

[29]  Yin-Feng Xu,et al.  Consensus models for AHP group decision making under row geometric mean prioritization method , 2010, Decis. Support Syst..

[30]  Nan Liu,et al.  Risk evaluation in failure mode and effects analysis with extended VIKOR method under fuzzy environment , 2012, Expert Syst. Appl..

[31]  Huipeng Li Hierarchical risk assessment of water supply systems , 2007 .

[32]  H. D. Stensel,et al.  Wastewater Engineering: Treatment and Reuse , 2002 .

[33]  Tarek Zayed,et al.  Hierarchical Fuzzy Expert System for Risk of Failure of Water Mains , 2010 .