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Development of an intelligent system based on ANFIS model for predicting soil erosion

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Abstract

This study explores capability of adaptive neuro-fuzzy interface system (ANFIS) model for soil erosion assessment of which various parameters are involved and the parameters interaction is highly nonlinear. Soft computing technique has been applied widely in various fields, but its application in soil science is limited. A number of models have been established in predicting soil erosion such as a revised universal soil loss equation (RUSLE) model whereby parameters of the RUSLE model are employed in testing the ANFIS model in this study. Besides, a new parameter of biomass microbe (Mf) is introduced and its effectiveness in controlling erosion is demonstrated. A hilly area near the Guthrie Corridor Expressway, Malaysia, is chosen as a study area whereby five experimental plots size of 8 × 8 m and 5 × 5 m are developed. These five plots are characterized by either natural or planted vegetation or either with or without microbe bio-fertilizer. Input parameters of RUSLE, i.e. rainfall erosivity, soil erodibility, slope length and steepness, vegetation and support practice, are measured, and observed erosion is monitored for 1 year. The microbe factor presented as Mf is examined by pairing the plot with and without microbe while keeping other similar characteristic for those plots. Result shows a satisfactory achievement between observed and predicted model by ANFIS with R2, RMSE and MAE being 0.8275, 1.4276 and − 0.0165, respectively. In terms of a relationship between the Mf factor and soil erosion, it is noticed that the soil erosion is inversely proportional to the Mf when the entire erosion conservation practices are unchanged for a given period. Therefore, the application of microbes could be an alternative or additional erosion conservation technique in soil conservation works.

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Acknowledgements

The authors would like to acknowledge the University of Malaya for overall financial support and the PROLINTAS Expressway Sdn. Bhd., Malaysia, for allowing this study to use their Guthrie Corridor Expressway (GCE) slopes as experimental site. This research was carried out by the University of Malaya Research Grant (UMRG) under the project “Investigate Soil Hydrological Aspects and Vegetation Cover for Slope Erosion” Project No. PR005B-13SUS and the Ministry of Higher Education Grant of FRGS Project No. FP039-2014B.

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Authors and Affiliations

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

    Md. Rabiul Islam, Wan Zurina Wan Jaafar, Lai Sai Hin & Nuruol Syuhadaa Mohd

  2. Institute of Biological Sciences, University of Malaya, Kuala Lumpur, Malaysia

    Normaniza Osman

  3. Department of Mechanical Engineering, University of Malaya, Kuala Lumpur, Malaysia

    Anamul Hossain

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  1. Md. Rabiul Islam
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  2. Wan Zurina Wan Jaafar
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Correspondence to Wan Zurina Wan Jaafar.

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Islam, M.R., Jaafar, W.Z.W., Hin, L.S. et al. Development of an intelligent system based on ANFIS model for predicting soil erosion. Environ Earth Sci 77, 186 (2018). https://doi.org/10.1007/s12665-018-7348-z

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