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Neural network modeling applications in active slope stability problems

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Abstract

A back propagation artificial neural network approach is applied to three common challenges in engineering geology: (1) characterization of subsurface geometry/position of the slip (or failure surface) of active landslides, (2) assessment of slope displacements based on ground water elevation and climate, and (3) assessment of groundwater elevations based on climate data. Series of neural network models are trained, validated, and applied to a landslide study along Lake Michigan and cases from the literature. The subsurface characterization results are also compared to a limit equilibrium circular failure surface search with specific adopted boundary conditions. It is determined that the neural network models predict slip surfaces better than the limit equilibrium slip surface search using the most conservative criteria. Displacements and groundwater elevations are also predicted fairly well, in real time. The models’ ability to predict displacements and groundwater elevations provides a foundational framework for building future warning systems with additional inputs.

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Acknowledgments

We wish to acknowledge funding for the field studies from the US Army Corps of Engineers Engineering Research and Development Center (ERDC), and the Detroit District USACE. Western Michigan University provided both financial and logistical support. We are grateful to the property owners in Allegan County, MI, Allegan County Road Commission, and State of Michigan for granting access to the study site. Three anonymous reviewers provided helpful comments and suggestions. We also thank Dr. William Sauck, Department of Geosciences for reviewing the manuscript.

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Authors and Affiliations

  1. Department of Geosciences, Western Michigan University, Kalamazoo, MI, 49008, USA

    Rennie B. Kaunda, Ronald B. Chase & Alan E. Kehew

  2. Department of Computer Science, Western Michigan University, Kalamazoo, MI, 49008, USA

    Karlis Kaugars

  3. Great Lakes Hydraulics and Hydrology Office, U.S. Army Corps of Engineers, Detroit District, Detroit, MI, 48226, USA

    James P. Selegean

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  1. Rennie B. Kaunda
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  2. Ronald B. Chase
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  3. Alan E. Kehew
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  4. Karlis Kaugars
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  5. James P. Selegean
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Correspondence to Rennie B. Kaunda.

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Kaunda, R.B., Chase, R.B., Kehew, A.E. et al. Neural network modeling applications in active slope stability problems. Environ Earth Sci 60, 1545–1558 (2010). https://doi.org/10.1007/s12665-009-0290-3

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  • DOI: https://doi.org/10.1007/s12665-009-0290-3

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