Quality Assessment of Municipal Effluent for Agriculture Using Fuzzy Inference System (Case Study: Sahebgharanieh Wastewater Treatment Plant)

Expanded Abstract
Introduction
There is an increasing global trend in using effluent as a non-conventional water resource for a wide range of applications. effluent can be used in a number of applications, including Makeup water in cooling towers and boilers, Equipment cleaning, Vehicle washing, Agricultural irrigation, Landscaping and lawn maintenance, Urban reuse (air conditioning, toilet flushing, etc.), and Fire protection. The scarcity of freshwater resources is a serious problem in arid and semi-arid regions, such as Iran. Effluent can have different advantages including being a constant, reliable water resource and reduces the amount of water extracted from the environment. Wastewater can be a vast resource if reclaimed properly to become effluent. The right on-site treatment system can transform treated wastewater into a reliable alternative water resource. In a case of inappropriate treatment, wastewater is discharged untreated into rivers, lakes and oceans which is a global problem. Today, around 80% of all wastewater is discharged untreated into rivers, lakes and oceans. It poses health and environmental problems. Recovering water, energy, nutrients and other precious materials embedded in wastewater is an opportunity to cover water demand and contribute to improved water security. To handle increased water demand, effluent is offered to be used for agricultural irrigation. The use of effluent for agricultural irrigation is viewed as a positive means of recycling water due to the potential large volumes of water that can be reused. The availability of nutrients such as N, P or K is a necessity for plant growth. One of the advantages of using effluent for irrigation is supplying nutrients and reducing use of synthetic fertilizers. Effluent can provide the soils with micronutrients and organic matter. There are concerns, however, about the impact of the quality of the effluent, both on the crop itself and on the consumers of the crops. Quality issues of the effluent can cause problems in agriculture incluing nutrient concentrations, heavy metals, and the presence of contaminants such as human and animal pathogens, pharmaceuticals and etc. There are international guidelines and national regulatory standards for quality control of effluent in agriculture. Department of environment in Iran issued the standard for effluent quality used in agricultural irrigation. EPA and WHO have also guidelines for the safe use of effluent. Using effluent for various applications including agriculture irrigation has been examined in many studies. These studies focus on comparing quality parameters of the effluent with the standards without concerning uncertainty in a framework for overall suitability of the effluent quality. This study aims to present a framework of effluent quality assessment for using in agriculture. We perform such an assessment by considering related uncertainty via Fuzzy Inference System and integrating it with Delphi method. The proposed framework can be used for wide range of applications in which effluent can be reused as a source of water.
Material & Methods
Tehran city involves 7 operating wastewater treatment plants. Sahebgharanieh wastewater treatment plant is the oldest wastewater treatment plant in Iran which is located in Pasdaran Street (North Tehran). Its executive operations started in 1960 which was designed with the capacity of 2000 people as the covered population. The material of collecting network with the length of 5.3km is asbestos cement. Its average input flow is 25m3/h and the network’s diameters are 150 to 200 mm.
In the first step, the most effective quality parameters of municipal effluent were identified through questionnaires. The questionnaires were given to the expert panel to be answered. The members were drawn from the university professors and industry sector research organizations. After aggregation of expert's opinion, 28 parameters were identified to assess municipal quality for reusing in agricultural irrigation. Delphi method was used to select the most important parameters from the total of 28 identified parameters. The Delphi method is a structured communication technique or method, originally developed as a systematic, interactive forecasting method which relies on a panel of experts. The experts were selected based on their educational level and work experience. The experts answered questionnaires in two or more rounds. Each member of the panel was sent a questionnaire with instructions to comment on each parameter by considering their importance in overall quality of the effluent for reusing in agricultural irrigation based on Likert scale (1= least important to 5=most important). In the second round, experts were asked to revise their earlier answers in light of the replies of other members of their panel. Finally, the process was stopped since there was low difference between scores of the first and second round. A predefined stop criterion and the mean scores of the final rounds determine the 8 parameters (i.e. Fecal Coliform, pH, TDS, TSS, COD, BOD5, NO3).
In the second step, Mamdani fuzzy inference system was used to assess the overall quality of the effluent. The most commonly used fuzzy inference technique is Mamdani method. It is performed in four steps of: 1- Fuzzification of the input variables. 2- Rule evaluation. 3- Aggregation of the rule outputs. 4- Defuzzification. After fuzzification, 99 rules were used. After defuzzification, the results were compared with the results of crisp method.

Results
Based on fuzzy results, 39 samples were categorized as "excellent, 20 samples as "good", and 1 sample as "poor". According to crisp method, pH, BOD5, COD, TSS, and NO3 in the first sample were categorized as "low", Fecal Coliform and TDS were categorized as "medium" and "high" respectively. Based on fuzzy results, the sample was categorized as "excellent". The fifth sample was categorized as "poor" according to fuzzy results. In this sample pH and NO3 were categorized as "low". BOD5, COD, and fecal coliform were categorized as "medium" and Nematodes, TDS, TSS were categorized as "high". The ninth sample was categorized as "good". Fecal Coliform, nematodes, BOD5, COD, pH, and NO3 were categorized as "low". TSS and TDS were categorized as "medium" and "high" respectively. The last sample was categorized as "excellent" and all the parameters were "low". Fuzzy method results showed that samples No. 58, 59, and 60 were categorized as good and according to crisp method all the parameters except nematodes and TDS categorized as "high".
Discussion & Conclusion
Uncertainty as a result of data unavailability and incompleteness is a challenge in effluent quality assessment. In the present study, Mamdani fuzzy inference system was used to deal with uncertainty. Its ability to reflect the human thoughts and expertise in the assessment make it possible to deal with non-linear, uncertain, ambiguous and subjective information. In order to select the most important quality parameters considering agricultural irrigation, Delphi method was combined with Mamdani fuzzy inference system. Expert knowledge and standards were simultaneously used to determine membership functions. 8 parameters including Fecal Coliform, nematodes, pH, TDS, TSS, COD, BOD5, and NO3 were selected to assess the overall effluent quality for reusing in agricultural irrigation. The results showed the suitability of the selected 8 parameters in effluent quality assessment. Reviewing other studies showed that they just make a comparison between calculated quality parameters and standards. But, the present study presented a framework for overall effluent quality assessment. The proposed framework was demonstrated via the case study of a Sahebgharanieh wastewater treatment plant in Tehran. In order to indicate the model validity, the results of fuzzy model were compared with the results of crisp method. The comparison showed the same results. It can be concluded that Fuzzy model capability in considering thresholds in input and output values enables dealing with uncertainty. The proposed framework can be further used for other applications of effluent reuse such as industrial, aquaculture, environment, etc .



Key words: Municipal effluent, Fuzzy inference system, Reuse, Agricultural uses.