Real-Time Dynamic Hazard Maps for Shallow Colluvial Landslides in Eastern Kentucky

Researcher ORCID Identifier

https://orcid.org/0000-0003-2350-2241

https://orcid.org/0009-0006-8610-5605

Files

Download

Download Full Text (3 KB)

Download Jupiter Notebook Code for LHM Automation (130 KB)

Download Landslide Susceptibility Readme File (7 KB)

Download Breathitt County Rasters gdb Files (16.6 MB)

Download VWC and Rainfall Spreadsheets (806 KB)

Download LSM and LHM Data Files (27.2 MB)

Dataset Creation Date

2024

Release Date

Fall 8-21-2025

Publisher

University of Kentucky Libraries

Description

Landslide hazards pose a persistent threat to communities and infrastructure in Eastern Kentucky, where steep slopes, shallow colluvial soils, and variable hydrological conditions drive frequent slope failures. This work advances landslide hazard mapping (LHM) through the development of dynamic, spatiotemporal models for shallow colluvial landslides. Two studies refine the use of a limit equilibrium framework to enhance predictive capability. The first study establishes a novel LHM workflow that integrates Hydrus-1D simulations of soil moisture dynamics, driven by precipitation and evapotranspiration data, into slope stability analysis. Factor of Safety (FS) parameters are applied to statistics-based landslide susceptibility maps (LSM), producing accurate, predictive hazard maps validated against documented landslides in Pike and Breathitt Counties. This approach demonstrates the feasibility of generating robust LHMs using publicly accessible datasets. The second study extends this workflow by improving slope stability assessments through refinement of the depth-to-bedrock parameter and incorporation of soil root cohesion into FS calculations. By automating data extraction and map generation in a Python environment, this study enables efficient, near-real-time forecast capabilities, including 72-hour landslide hazard predictions. Results underscore the critical role of vegetation and root cohesion in slope stability while highlighting the potential for proactive hazard mitigation. Together, these studies establish a comprehensive, adaptable methodology that leverages both physical process modeling and machine learning, providing a pathway toward accurate, operational landslide hazard forecasting in data-limited regions.

Digital Object Identifier (DOI)

https://doi.org/10.13023/cedata8.25

Rights

This dataset is distributed under the terms of the Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided that the dataset creators and source are credited and that changes (if any) are clearly indicated.

Supporting Information

Please see the Readme files.

File Format

Landslide Mapping Readme file: Text document (.txt)

Landslide Susceptibility Readme file: Text document (.txt)

Microsoft Excel file (.xlsx)

VWC and Rainfall Spreadsheets: zip format

LSM and LHM Data Files: zip format

Breathitt County Rasters.gdb: .zip format

Python code: Jupyter notebook (.ipynb)

File Size

Landslide Mapping Readme file: 3.95 KB

Landslide Susceptibility Readme file: 7.26 KB

VWC and Rainfall Spreadsheets: 806 KB

LSM and LHM Data Files: 27.2 MB

Breathitt County Rasters.gdb: 16.5 MB

LHM Automation Continuous: 130 KB

Spatial Coverage

Pike County, Kentucky

Breathitt County, Kentucky

Temporal Coverage

2013 to 2023

Language

English

Related Content

O'Leary, Nathaniel, "Visualizing and Automating Past and Real-Time Dynamic Hazard Maps for Shallow Colluvial Landslides in Eastern Kentucky" (2024). Theses and Dissertations--Earth and Environmental Sciences. 110. https://doi.org/10.13023/etd.2024.430

Francis, D.M., and Bryson, L.S. (2025). “Rainfall-Induced Landslide Hazard Analyses using Spatiotemporal Retrievals of Soil Moisture and Geomorphologic Data,” Environmental Earth Sciences, Springer, 84(8), 201. https://doi.org/10.1007/s12665-025-12209-0.

Francis, D.M.., and Bryson, L.S. (2025). “Coupled Landslide Analyses Through Dynamic Susceptibility and Forecastable Hazard Analysis,” Natural Hazards Journal, Springer, 121(3), 2971–2999. https://doi.org/10.1007/s11069-024-06908-3.

Real-Time Dynamic Hazard Maps for Shallow Colluvial Landslides in Eastern Kentucky

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