Combining an experimental study and ANFIS modeling to predict landfill leachate transport in underlying soil-a case study in north of Iran.

In the contemporary world, urbanization and progressive industrial activities increase the rate of waste material generated in many developed countries. Municipal solid waste landfills (MSWs) are designed to dispose the waste from urban areas. However, discharged landfill leachate, the soluble water mixture that filters through solid waste landfills, can potentially migrate into the soil and affect living organisms by making harmful biological changes in the ecosystem. Due to well-documented landfill problems involving contamination, it is necessary to investigate the long-term influence of discharged leachate on the consistency of the soil beds beneath MSW landfills. To do so, the current study collected vertical deep core samples from different locations in the same unlined landfill. The impacts of effluent leachate on physical and chemical properties of the soil and its propagation depth were studied, and the leachate-transport pattern between successive boreholes was predicted by a developed mathematical model using an adaptive neuro-fuzzy inference system (ANFIS). The decomposition of organic leachate admixtures in the landfill yield is to produce organic acids as well as carbon dioxide, which diminishes the pH level of the landfill soil. The chemical analysis of discharged leachate in the soil samples showed that the concentrations of heavy metals are much lower than those of chloride, COD, BOD5, and bicarbonate. Using linear regression and mean square errors between the measured and predicted data, the accuracy of the proposed ANFIS model has been validated. Results show a high correlation between observed and predicated data.