Landslide with question marks symbolizing incomplete data.

Unstable Ground? How to Analyze Landslides with Limited Data

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Jordan Keane in Climate & Environment August 2025 • 4 min read.

"Learn practical techniques for landslide analysis when complete information is unavailable, ensuring safer and more reliable geotechnical assessments."


Slope stability analysis is crucial for preventing landslides and ensuring public safety. Ideally, these analyses rely on comprehensive data from detailed site investigations, laboratory testing, and thorough modeling. However, in real-world scenarios, geotechnical engineers often face the challenge of incomplete data. This might be due to budget constraints, unsafe site conditions for drilling, the need for rapid response, or unavailable historical records.

Despite these limitations, it's still imperative to proceed with the analysis to assess risk and inform mitigation strategies. The key is to employ tools and techniques that reduce errors and provide reasonable estimates of stability, even with limited information. This article explores several strategies that help navigate these challenges, ensuring safer and more reliable assessments.

Whether you're a seasoned geotechnical engineer or an environmental scientist, understanding how to work with incomplete landslide data is essential. This guide provides practical approaches and real-world examples to enhance your analytical skills and decision-making in complex geotechnical projects.

Iterative Analysis: A Step-by-Step Approach

Landslide with question marks symbolizing incomplete data.

Iterative analysis is a powerful method for refining slope stability assessments when data is scarce. This technique involves analyzing multiple cross-sections of a potential landslide area and adjusting parameters until the expected factor of safety (FS) aligns with observed conditions. By working through several iterations, engineers can narrow down the range of possible values for unknown parameters.

The factor of safety (FS) is a critical concept in slope stability analysis. It represents the ratio of resisting forces to driving forces on a slope. An FS of 1 indicates a slope is in a state of barely equilibrium, meaning it is on the verge of failure. An FS greater than 1 suggests the slope is stable, while an FS less than 1 indicates instability and a high risk of landslide. The higher the FS value above 1, the more stable the slope is considered to be.

  • Select Multiple Cross-Sections: Choose three to five cross-sections that represent the suspected landslide area. These sections should capture the variability in topography and geology across the site.
  • Establish Reasonable Piezometric Surfaces: Define a range of possible groundwater levels, bracketed by the lowest and highest expected values. Incorporate data from piezometers or surface water observations if available.
  • Define Parameter Ranges: Determine bracketed ranges for key soil parameters like friction angle, cohesion, and density for each geologic unit. Use laboratory tests, field data, literature values, or published data for similar geotechnical materials to inform these ranges.
  • Calculate and Refine: Start with mid-range values for each parameter and calculate the FS for each cross-section. Focus on narrowing the range of piezometric surfaces first, then adjust friction angles for deeper slides or cohesion for shallower slides. The goal is to achieve FS values close to 1 for all cross-sections, indicating a calibrated model.
  • Validate with Smaller Failures: On larger landslides, examine smaller failures at the toe of the slope. These can provide valuable checks on back-calculated material strength and density values, assuming the materials are similar and the failure mechanisms are comparable.
When applying iterative analysis, anticipate discarding some cross-sections due to poor convergence or unusual site conditions. Also, understand that two-dimensional limit equilibrium analysis introduces inherent errors in a three-dimensional system. Landslide margins provide stabilizing effects not accounted for in 2D, potentially leading to underestimation of actual stability. This discrepancy is reduced for large, wide, and shallow landslides where edge effects are minimal.

Embrace Uncertainty, Enhance Accuracy

Dealing with incomplete data in landslide analysis is inevitable. By using methods like iterative analysis, sensitivity studies, and by carefully considering the factors affecting material strength, engineers can make more informed decisions. Recognizing the limitations and expressing results with appropriate confidence enhances the value and reliability of geotechnical assessments, leading to safer and more resilient infrastructure.

About this Article -

This article was crafted using a human-AI hybrid and collaborative approach. AI assisted our team with initial drafting, research insights, identifying key questions, and image generation. Our human editors guided topic selection, defined the angle, structured the content, ensured factual accuracy and relevance, refined the tone, and conducted thorough editing to deliver helpful, high-quality information.See our About page for more information.

This article is based on research published under:

DOI-LINK: 10.1061/9780784481936.002, Alternate LINK

Title: Landslide Analysis With Incomplete Data: Examples From Colorado And Wyoming

Journal: Rocky Mountain Geo-Conference 2018

Publisher: American Society of Civil Engineers

Authors: Paul Santi

Published: 2018-11-01

Everything You Need To Know

1

What is the main challenge in slope stability analysis, and why is it important?

The main challenge is often incomplete data, stemming from budget limitations, unsafe site conditions, the need for rapid response, or unavailable historical records. Despite this, slope stability analysis is crucial for preventing landslides and ensuring public safety. It helps assess risks and inform mitigation strategies, making geotechnical assessments safer and more reliable.

2

Explain the concept of the Factor of Safety (FS) and its significance in slope stability analysis.

The Factor of Safety (FS) is a critical concept in slope stability analysis. It represents the ratio of resisting forces to driving forces on a slope. An FS of 1 indicates the slope is at equilibrium and on the verge of failure. An FS greater than 1 suggests stability, while an FS less than 1 indicates instability and a high landslide risk. The higher the FS value above 1, the more stable the slope is considered.

3

How does iterative analysis help geotechnical engineers deal with incomplete data?

Iterative analysis is a step-by-step approach that helps refine slope stability assessments when data is scarce. Engineers analyze multiple cross-sections of a potential landslide area and adjust parameters until the expected Factor of Safety (FS) aligns with observed conditions. This involves selecting cross-sections, establishing piezometric surfaces, defining parameter ranges for soil properties (friction angle, cohesion, density), calculating the FS, and refining the model. It helps narrow down the range of possible values for unknown parameters.

4

What are the key steps involved in conducting an iterative analysis for landslide assessment?

The key steps include: Selecting multiple cross-sections (3-5) representing the landslide area; Establishing reasonable piezometric surfaces (groundwater levels); Defining parameter ranges for key soil properties like friction angle, cohesion, and density. Then, calculate the Factor of Safety (FS) for each cross-section, refine parameters to achieve FS values close to 1 across all sections, and validate the results using smaller failures. It's crucial to anticipate discarding some cross-sections due to poor convergence and to acknowledge the limitations of 2D analysis in a 3D system.

5

What are the limitations of two-dimensional limit equilibrium analysis, and how does it impact the accuracy of assessing landslide stability?

Two-dimensional limit equilibrium analysis introduces inherent errors in a three-dimensional system. Landslide margins provide stabilizing effects not accounted for in 2D, potentially leading to an underestimation of actual stability. This discrepancy is reduced for large, wide, and shallow landslides where edge effects are minimal. Therefore, engineers should be aware of these limitations and express results with appropriate confidence to enhance the value and reliability of geotechnical assessments.

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