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Predicting sanitary landfill leachate generation in humid regions using ANFIS modeling

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Abstract

Landfill leachate is one of the sources of surface water pollution in Selangor State (SS), Malaysia. Leachate volume prediction is essential for sustainable waste management and leachate treatment processes. The accurate estimation of leachate generation rates is often considered a challenge, especially in developing countries, due to the lack of reliable data and high measurement costs. Leachate generation is related to several variable factors, including meteorological data, waste generation rates, and landfill design conditions. Large variations in these factors lead to complicated leachate modeling processes. The aims of this study are to determine the key elements contributing to leachate production and then develop an adaptive neural fuzzy inference system (ANFIS) model to predict leachate generation rates. Accuracy of the final model performance was tested and evaluated using the root mean square error (RMSE), the mean absolute error (MAE), and the correlation coefficient (R). The study results defined dumped waste quantity, rainfall level, and emanated gases as the most significant contributing factors in leachate generation. The best model structure consisted of two triangular fuzzy membership functions and a hybrid training algorithm with eight fuzzy rules. The proposed ANFIS model showed a good performance with an overall correlation coefficient of 0.952.

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Acknowledgments

The authors would like to acknowledge the University of Malaya Research Grant (FL001-13SUS, RP017C-15SUS) and the Ministry of Higher Education Fundamental Research Grant (FP016-2014A) for the financial support. We would also like to thank the Malaysian Meteorological Department and other related authorities and companies, as well as the UM Water Research Center, for the support rendered. We are most grateful and would like to thank the reviewers for their valuable suggestions, which have led to substantial improvements of the article.

Funding

Financial support was provided by the University of Malaya Research Grant (FL001-13SUS, RP017C-15SUS) and the Ministry of Higher Education Fundamental Research Grant (FP016-2014A).

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Authors and Affiliations

  1. Department of Civil Engineering, University of Malaya, 50603, Kuala Lumpur, Malaysia

    Taher Abunama & Faridah Othman

  2. Department of Civil Engineering, Philadelphia University, Amman, 19392, Jordan

    Mohammad K. Younes

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  1. Taher Abunama
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  3. Mohammad K. Younes
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Correspondence to Faridah Othman.

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Abunama, T., Othman, F. & Younes, M.K. Predicting sanitary landfill leachate generation in humid regions using ANFIS modeling. Environ Monit Assess 190, 597 (2018). https://doi.org/10.1007/s10661-018-6966-y

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